Adam J. Zolotor, MD, MPH

Evidence summary

One RCT that compared the levonorgestrel IUD (Mirena) with oral contraceptives in 200 nulliparous women 18 to 25 years of age found the IUD to have equivalent safety and efficacy to OCPs.¹ Moreover, the IUD group experienced a significant decrease in bleeding, with a number needed to treat of 4 (P=.001).

Neither group reported any pregnancies or pelvic inflammatory disease at one year. The overall discontinuation rate at one year was 20% for IUDs and 27% for OCPs (P=not significant [NS]).¹ Multiple studies show no unintended pregnancies with the IUD.^1-3

Study of adolescents finds low complication rate
A prospective cohort study of 179 adolescents 10 to 19 years of age found that the overall incidence of complications with the levonorgestrel IUD was relatively low, with removal rates of 8/179 (4.5%) each for pain and abnormal vaginal bleeding. The cumulative incidence of expulsion was estimated at 8.3% (95% confidence interval [CI], 4.2%-14.3%). No cases of uterine perforation were identified, and the one-year continuation rate was 85% (95% CI, 77%-90%).² Other studies haven’t evaluated adolescents as a separate group.

IUDs are also well tolerated in an older cohort
A cohort study of 113 nulliparous women 16 to 30 years of age found insertion of a copper or levonorgestrel IUD to be well tolerated; no perforations were observed. At one year, 65 women (58%) still had their original IUD, 15 (13%) had had it removed, 6 (5%) had experienced expulsion, and 27 (24%) were lost to follow-up.³

Abdominal and back pain can be a problem
An RCT of 200 nulliparous women 18 to 25 years of age found that levonorgestrel IUDs were associated with more abdominal and back pain at 12 months than OCPs (54.7% of women with IUDs had pain vs 40% of women with OCPs; number needed to harm=7; P=.007). Pain was the leading cause of discontinuation in the IUD group (6 women with IUDs stopped using them vs no OCP users; P=.012).¹

No difference in IUD complications in nulliparous vs parous women
A retrospective cohort study compared 129 nulliparous women with 332 parous women 17 to 52 years of age who had either copper or levonorgestrel IUDs. The researchers found no differences between the 2 groups in rates of perforation, pelvic inflammatory disease, ectopic pregnancy, or expulsion.⁴

Fertility after IUD removal: An encouraging picture
No studies have evaluated fertility after IUD use exclusively in adolescents. A prospective cohort study of 558 nulliparous women ages 18 to 40 years who stopped using a barrier method, copper IUD, or OCP in order to conceive found the quickest return to fertility among women who used the barrier method. The main outcome, percent of women who delivered within 12 months of discontinuation, was highest in the barrier method cohort and lowest in the OCP cohort (54% vs 32%; P=.002). The difference in delivery rates between the IUD and OCP groups at 12 months wasn’t statistically significant (39% vs 32%). By 18 months after cessation of contraception, the delivery rates in all 3 groups were similar (76%, 67%, and 70% for barrier, OCP, and IUD use, respectively).⁵

A retrospective cohort study that compared 36 nulliparous women with 83 parous women 18 to 41 years of age who were trying to conceive after removal of the GyneFix (copper) IUD found no statistical difference in pregnancy rates for age or duration of IUD use. Among women younger than 30 years, nulliparous women conceived earlier than parous women; cumulative pregnancy rates after 12 months were 100% for nulliparous and 80% for parous women (P=.007). No ectopic pregnancies were observed.⁶

Recommendations

The United Kingdom’s National Institute for Health and Clinical Excellence states that IUD use isn’t contraindicated in nulliparous women of any age, and that women of all ages may use IUDs. The Institute also states that no specific restrictions limit the use of copper or levonorgestrel IUDs by adolescents.

All women at risk for sexually transmitted infections may need to be tested before insertion. No evidence exists for a delay in return to fertility after removal or expulsion of an IUD.⁷

Evidence summary

One RCT that compared the levonorgestrel IUD (Mirena) with oral contraceptives in 200 nulliparous women 18 to 25 years of age found the IUD to have equivalent safety and efficacy to OCPs.¹ Moreover, the IUD group experienced a significant decrease in bleeding, with a number needed to treat of 4 (P=.001).

Neither group reported any pregnancies or pelvic inflammatory disease at one year. The overall discontinuation rate at one year was 20% for IUDs and 27% for OCPs (P=not significant [NS]).¹ Multiple studies show no unintended pregnancies with the IUD.^1-3

Study of adolescents finds low complication rate
A prospective cohort study of 179 adolescents 10 to 19 years of age found that the overall incidence of complications with the levonorgestrel IUD was relatively low, with removal rates of 8/179 (4.5%) each for pain and abnormal vaginal bleeding. The cumulative incidence of expulsion was estimated at 8.3% (95% confidence interval [CI], 4.2%-14.3%). No cases of uterine perforation were identified, and the one-year continuation rate was 85% (95% CI, 77%-90%).² Other studies haven’t evaluated adolescents as a separate group.

IUDs are also well tolerated in an older cohort
A cohort study of 113 nulliparous women 16 to 30 years of age found insertion of a copper or levonorgestrel IUD to be well tolerated; no perforations were observed. At one year, 65 women (58%) still had their original IUD, 15 (13%) had had it removed, 6 (5%) had experienced expulsion, and 27 (24%) were lost to follow-up.³

Abdominal and back pain can be a problem
An RCT of 200 nulliparous women 18 to 25 years of age found that levonorgestrel IUDs were associated with more abdominal and back pain at 12 months than OCPs (54.7% of women with IUDs had pain vs 40% of women with OCPs; number needed to harm=7; P=.007). Pain was the leading cause of discontinuation in the IUD group (6 women with IUDs stopped using them vs no OCP users; P=.012).¹

No difference in IUD complications in nulliparous vs parous women
A retrospective cohort study compared 129 nulliparous women with 332 parous women 17 to 52 years of age who had either copper or levonorgestrel IUDs. The researchers found no differences between the 2 groups in rates of perforation, pelvic inflammatory disease, ectopic pregnancy, or expulsion.⁴

Fertility after IUD removal: An encouraging picture
No studies have evaluated fertility after IUD use exclusively in adolescents. A prospective cohort study of 558 nulliparous women ages 18 to 40 years who stopped using a barrier method, copper IUD, or OCP in order to conceive found the quickest return to fertility among women who used the barrier method. The main outcome, percent of women who delivered within 12 months of discontinuation, was highest in the barrier method cohort and lowest in the OCP cohort (54% vs 32%; P=.002). The difference in delivery rates between the IUD and OCP groups at 12 months wasn’t statistically significant (39% vs 32%). By 18 months after cessation of contraception, the delivery rates in all 3 groups were similar (76%, 67%, and 70% for barrier, OCP, and IUD use, respectively).⁵

A retrospective cohort study that compared 36 nulliparous women with 83 parous women 18 to 41 years of age who were trying to conceive after removal of the GyneFix (copper) IUD found no statistical difference in pregnancy rates for age or duration of IUD use. Among women younger than 30 years, nulliparous women conceived earlier than parous women; cumulative pregnancy rates after 12 months were 100% for nulliparous and 80% for parous women (P=.007). No ectopic pregnancies were observed.⁶

Recommendations

The United Kingdom’s National Institute for Health and Clinical Excellence states that IUD use isn’t contraindicated in nulliparous women of any age, and that women of all ages may use IUDs. The Institute also states that no specific restrictions limit the use of copper or levonorgestrel IUDs by adolescents.

All women at risk for sexually transmitted infections may need to be tested before insertion. No evidence exists for a delay in return to fertility after removal or expulsion of an IUD.⁷

Evidence summary

One RCT that compared the levonorgestrel IUD (Mirena) with oral contraceptives in 200 nulliparous women 18 to 25 years of age found the IUD to have equivalent safety and efficacy to OCPs.¹ Moreover, the IUD group experienced a significant decrease in bleeding, with a number needed to treat of 4 (P=.001).

Neither group reported any pregnancies or pelvic inflammatory disease at one year. The overall discontinuation rate at one year was 20% for IUDs and 27% for OCPs (P=not significant [NS]).¹ Multiple studies show no unintended pregnancies with the IUD.^1-3

Study of adolescents finds low complication rate
A prospective cohort study of 179 adolescents 10 to 19 years of age found that the overall incidence of complications with the levonorgestrel IUD was relatively low, with removal rates of 8/179 (4.5%) each for pain and abnormal vaginal bleeding. The cumulative incidence of expulsion was estimated at 8.3% (95% confidence interval [CI], 4.2%-14.3%). No cases of uterine perforation were identified, and the one-year continuation rate was 85% (95% CI, 77%-90%).² Other studies haven’t evaluated adolescents as a separate group.

IUDs are also well tolerated in an older cohort
A cohort study of 113 nulliparous women 16 to 30 years of age found insertion of a copper or levonorgestrel IUD to be well tolerated; no perforations were observed. At one year, 65 women (58%) still had their original IUD, 15 (13%) had had it removed, 6 (5%) had experienced expulsion, and 27 (24%) were lost to follow-up.³

Abdominal and back pain can be a problem
An RCT of 200 nulliparous women 18 to 25 years of age found that levonorgestrel IUDs were associated with more abdominal and back pain at 12 months than OCPs (54.7% of women with IUDs had pain vs 40% of women with OCPs; number needed to harm=7; P=.007). Pain was the leading cause of discontinuation in the IUD group (6 women with IUDs stopped using them vs no OCP users; P=.012).¹

No difference in IUD complications in nulliparous vs parous women
A retrospective cohort study compared 129 nulliparous women with 332 parous women 17 to 52 years of age who had either copper or levonorgestrel IUDs. The researchers found no differences between the 2 groups in rates of perforation, pelvic inflammatory disease, ectopic pregnancy, or expulsion.⁴

Fertility after IUD removal: An encouraging picture
No studies have evaluated fertility after IUD use exclusively in adolescents. A prospective cohort study of 558 nulliparous women ages 18 to 40 years who stopped using a barrier method, copper IUD, or OCP in order to conceive found the quickest return to fertility among women who used the barrier method. The main outcome, percent of women who delivered within 12 months of discontinuation, was highest in the barrier method cohort and lowest in the OCP cohort (54% vs 32%; P=.002). The difference in delivery rates between the IUD and OCP groups at 12 months wasn’t statistically significant (39% vs 32%). By 18 months after cessation of contraception, the delivery rates in all 3 groups were similar (76%, 67%, and 70% for barrier, OCP, and IUD use, respectively).⁵

A retrospective cohort study that compared 36 nulliparous women with 83 parous women 18 to 41 years of age who were trying to conceive after removal of the GyneFix (copper) IUD found no statistical difference in pregnancy rates for age or duration of IUD use. Among women younger than 30 years, nulliparous women conceived earlier than parous women; cumulative pregnancy rates after 12 months were 100% for nulliparous and 80% for parous women (P=.007). No ectopic pregnancies were observed.⁶

Recommendations

The United Kingdom’s National Institute for Health and Clinical Excellence states that IUD use isn’t contraindicated in nulliparous women of any age, and that women of all ages may use IUDs. The Institute also states that no specific restrictions limit the use of copper or levonorgestrel IUDs by adolescents.

All women at risk for sexually transmitted infections may need to be tested before insertion. No evidence exists for a delay in return to fertility after removal or expulsion of an IUD.⁷

Evidence summary

No RCTs have evaluated the risks, benefits, and clinical outcomes of screening for GDM. A review of universal screening compared with risk factor screening included 2 retrospective studies, 1 observational cohort study, and 1 nonconcurrent cohort study.^1-4

Risk factor screening misses women with GDM
All 4 studies clearly show that risk factor screening would miss patients with GDM.^1-4 Two studies found that the detection rate of GDM increases when universal screening is performed.^1,4

One observational study in a multiethnic cohort concluded that risk factor screening missed 30% of patients with GDM and that universal screening increased the detection rate from 8.3% to 12.6% (P=.001) compared with risk factor screening.¹ Similarly, a retrospective study of 147 pregnant women with GDM found that risk factor screening would have missed 23%.²

Universal screening diagnoses GDM earlier than risk factor screening
One prospective randomized study that compared universal screening (using a 50-g 1-hour glucose challenge test) in 1853 women with risk factor screening in 1299 women demonstrated that nearly half of those with GDM had no historical risk factors and would have been missed by risk factor screening in a low-prevalence, mostly Caucasian sample. The prevalence was 2.7% in the universal screening group vs 1.45% in the risk factor screening group (P<.03). Universal screening diagnosed GDM earlier than risk factor screening (mean gestation 30 ± 2.6 weeks vs 33 ± 3.7 weeks; P<.05).³

Need for insulin is similar, with and without GDM risk factors
A retrospective cohort study demonstrated that risk factor screening misses 43% of women with GDM. The study also showed that women with GDM who had identifiable risk factors and women without identifiable risk factors were equally likely to require insulin to control their GDM. Adverse birth outcomes such as macrosomia and shoulder dystocia or cesarean section were similar in patients with and without risk factors for GDM.⁴

Macrosomia and primary C-section increase along with glucose intolerance
The prospective cohort Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study of 23,316 women at 15 centers in 9 countries used the 2-hour 75-g oral glucose tolerance test at 24 to 32 weeks’ gestation to clarify the risks of adverse outcomes associated with varying degrees of maternal glucose intolerance. The study found a linear increase in the risk of macrosomia and primary cesarean section as glucose intolerance levels increased from normal to the gestational diabetes range.⁵

Recommendations

The US Preventive Services Task Force states that evidence is insufficient to advise for or against routine screening for GDM.⁶

The American College of Obstetricians and Gynecologists considers universal glucose challenge screening for GDM to be the most sensitive approach, but notes that some pregnant women at low risk may be less likely to benefit from testing.⁷

The Cochrane review protocol states that universally accepted screening is controversial because of a lack of clearly defined, universally accepted screening criteria and uncertainty about the severity of glucose intolerance at which treatment is beneficial.⁸

Evidence summary

No RCTs have evaluated the risks, benefits, and clinical outcomes of screening for GDM. A review of universal screening compared with risk factor screening included 2 retrospective studies, 1 observational cohort study, and 1 nonconcurrent cohort study.^1-4

Risk factor screening misses women with GDM
All 4 studies clearly show that risk factor screening would miss patients with GDM.^1-4 Two studies found that the detection rate of GDM increases when universal screening is performed.^1,4

One observational study in a multiethnic cohort concluded that risk factor screening missed 30% of patients with GDM and that universal screening increased the detection rate from 8.3% to 12.6% (P=.001) compared with risk factor screening.¹ Similarly, a retrospective study of 147 pregnant women with GDM found that risk factor screening would have missed 23%.²

Universal screening diagnoses GDM earlier than risk factor screening
One prospective randomized study that compared universal screening (using a 50-g 1-hour glucose challenge test) in 1853 women with risk factor screening in 1299 women demonstrated that nearly half of those with GDM had no historical risk factors and would have been missed by risk factor screening in a low-prevalence, mostly Caucasian sample. The prevalence was 2.7% in the universal screening group vs 1.45% in the risk factor screening group (P<.03). Universal screening diagnosed GDM earlier than risk factor screening (mean gestation 30 ± 2.6 weeks vs 33 ± 3.7 weeks; P<.05).³

Need for insulin is similar, with and without GDM risk factors
A retrospective cohort study demonstrated that risk factor screening misses 43% of women with GDM. The study also showed that women with GDM who had identifiable risk factors and women without identifiable risk factors were equally likely to require insulin to control their GDM. Adverse birth outcomes such as macrosomia and shoulder dystocia or cesarean section were similar in patients with and without risk factors for GDM.⁴

Macrosomia and primary C-section increase along with glucose intolerance
The prospective cohort Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study of 23,316 women at 15 centers in 9 countries used the 2-hour 75-g oral glucose tolerance test at 24 to 32 weeks’ gestation to clarify the risks of adverse outcomes associated with varying degrees of maternal glucose intolerance. The study found a linear increase in the risk of macrosomia and primary cesarean section as glucose intolerance levels increased from normal to the gestational diabetes range.⁵

Recommendations

The US Preventive Services Task Force states that evidence is insufficient to advise for or against routine screening for GDM.⁶

The American College of Obstetricians and Gynecologists considers universal glucose challenge screening for GDM to be the most sensitive approach, but notes that some pregnant women at low risk may be less likely to benefit from testing.⁷

The Cochrane review protocol states that universally accepted screening is controversial because of a lack of clearly defined, universally accepted screening criteria and uncertainty about the severity of glucose intolerance at which treatment is beneficial.⁸

Evidence summary

No RCTs have evaluated the risks, benefits, and clinical outcomes of screening for GDM. A review of universal screening compared with risk factor screening included 2 retrospective studies, 1 observational cohort study, and 1 nonconcurrent cohort study.^1-4

Risk factor screening misses women with GDM
All 4 studies clearly show that risk factor screening would miss patients with GDM.^1-4 Two studies found that the detection rate of GDM increases when universal screening is performed.^1,4

One observational study in a multiethnic cohort concluded that risk factor screening missed 30% of patients with GDM and that universal screening increased the detection rate from 8.3% to 12.6% (P=.001) compared with risk factor screening.¹ Similarly, a retrospective study of 147 pregnant women with GDM found that risk factor screening would have missed 23%.²

Universal screening diagnoses GDM earlier than risk factor screening
One prospective randomized study that compared universal screening (using a 50-g 1-hour glucose challenge test) in 1853 women with risk factor screening in 1299 women demonstrated that nearly half of those with GDM had no historical risk factors and would have been missed by risk factor screening in a low-prevalence, mostly Caucasian sample. The prevalence was 2.7% in the universal screening group vs 1.45% in the risk factor screening group (P<.03). Universal screening diagnosed GDM earlier than risk factor screening (mean gestation 30 ± 2.6 weeks vs 33 ± 3.7 weeks; P<.05).³

Need for insulin is similar, with and without GDM risk factors
A retrospective cohort study demonstrated that risk factor screening misses 43% of women with GDM. The study also showed that women with GDM who had identifiable risk factors and women without identifiable risk factors were equally likely to require insulin to control their GDM. Adverse birth outcomes such as macrosomia and shoulder dystocia or cesarean section were similar in patients with and without risk factors for GDM.⁴

Macrosomia and primary C-section increase along with glucose intolerance
The prospective cohort Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study of 23,316 women at 15 centers in 9 countries used the 2-hour 75-g oral glucose tolerance test at 24 to 32 weeks’ gestation to clarify the risks of adverse outcomes associated with varying degrees of maternal glucose intolerance. The study found a linear increase in the risk of macrosomia and primary cesarean section as glucose intolerance levels increased from normal to the gestational diabetes range.⁵

Recommendations

The US Preventive Services Task Force states that evidence is insufficient to advise for or against routine screening for GDM.⁶

The American College of Obstetricians and Gynecologists considers universal glucose challenge screening for GDM to be the most sensitive approach, but notes that some pregnant women at low risk may be less likely to benefit from testing.⁷

The Cochrane review protocol states that universally accepted screening is controversial because of a lack of clearly defined, universally accepted screening criteria and uncertainty about the severity of glucose intolerance at which treatment is beneficial.⁸

Illustrative case

A 10-year-old boy comes in with his mother for a well-child check-up. His BMI is 40 kg/m²—above the 99th percentile for his age and up from 37 a year ago. His blood pressure is 120/84 mm Hg. What treatment, if any, should you offer for his obesity?

Childhood obesity is a global epidemic. In the United States, 19.6% of children ages 6 through 11 and 18.1% of 12- to 19-year-olds are obese, a 3-fold increase in the last 30 years.³ Without intervention, most obese adolescents will become obese adults, threatening to reverse the progress in slowing cardiovascular morbidity and mortality that has occurred over the past few decades.³

Obese kids get adult diseases
Obesity is a risk factor for a variety of chronic conditions, including cardiovascular disease, cerebrovascular disease, and arthritis. Severe obesity is also associated with higher mortality rates.⁴ Unfortunately, these comorbidities are not limited to adulthood.

“Adult” diseases, such as obstructive sleep apnea, dyslipidemia, and type 2 diabetes, are increasingly seen in children and adolescents.¹ Nutritional deficits such as vitamin D and iron deficiency are often seen in obese children, as well.⁵ There are also psychological ramifications of childhood obesity, including social isolation and depression.⁶

The USPSTF recently upgraded its recommendation regarding obesity screening in children ages 6 and older from I (insufficient evidence) to B (a positive grade based on high or moderate certainty of the benefit of the intervention), citing new evidence in favor of screening and treating or referring children when appropriate.² The systematic review we report on here, which formed the basis for the USPSTF’s upgrade, focused on management options for children identified as overweight or obese.

STUDY SUMMARY: Intense, comprehensive efforts pay off

This systematic review¹ included studies of children ages 4 to 18 years who were overweight (defined as a body mass index [BMI] in the 85th to 94th percentile for age and sex) or obese (either a BMI at or above the 95th percentile for age and sex or a BMI >30 kg/m²). The researchers found 25 trials—15 of behavioral interventions alone and 10 that combined behavioral and pharmacologic interventions—that met their criteria: The studies focused on weight loss and/or maintenance, reported outcomes ≥6 months from baseline, and were conducted (or feasible) in a primary care setting.

Behavioral interventions were categorized by treatment intensity (as measured by hours of contact, which ranged from <10 hours to >75) and comprehensiveness (including nutritional counseling, physical activity counseling or participation, and counseling on behavioral management techniques). Weight outcomes were categorized as short-term (6-12 months since treatment initiation) or maintenance (≥12 months after the end of active treatment).

The 15 behavioral intervention trials included 1258 children ages 4 to 18 years, most of whom were obese. Most trials were small and reported high retention rates. All had beneficial effects on weight in the intervention group compared with the controls, but not all changes were statistically significant. Higher intensity and more comprehensive programs had better outcomes.

The largest effects were in 3 moderate- to high-intensity, comprehensive weight management programs with ≥26 hours of contact. These 3 trials demonstrated a difference in BMI of 1.9 to 3.3 in the intervention groups at 12 months compared with the controls. (A 3.3 difference in BMI is equal to approximately 13 lb in an 8-year-old and 17 lb in a 12-year-old.)

Four behavioral intervention studies reported outcomes ≥12 months after completing the intervention (range 15-48 months). Three of the 4 reported continued beneficial effects on weight after the active treatment period, but the effects were markedly attenuated.

The only adverse effect reported in the trials of behavioral interventions was the injury rate among children in an exercise program, but it was minimal: One fracture was reported, vs no injuries for the controls. No differences were reported in height, eating disorders, or depression. However, fewer than half of the behavioral intervention trials reported on adverse effects.

Weight loss drugs have modest effects
Ten trials combining pharmacologic and behavioral interventions involved a total of 1294 obese adolescents ages 12 to 19. All evaluated short-term weight loss effects of either sibutramine (10-15 mg/d) or orlistat (120 mg tid). Trials ranged from 3 to 12 months. Participants in both the control and intervention groups received behavioral counseling.

The trials all favored the treatment groups, although not all of the results were statistically significant. Trials of longer duration (12 months) had more favorable results than those lasting 6 months.

The largest sibutramine trial (n=498) reported a mean BMI reduction of 2.9 in the treatment group, compared with a reduction of 0.3 in the control group (P<.001). This corresponds to an average weight loss of 14 lb in the intervention group, vs 4.2 lb in the control group, after 12 months.

The largest orlistat trial (n=539) reported a mean BMI reduction in the treatment group of 0.6, vs 0.3 in the control group (P<.001)—an average weight loss of 4.2 lb in the intervention group, compared with 2.1 lb among the controls after 12 months. None of the trials evaluated weight change after cessation of the study drug, and none compared orlistat with sibutramine.

Adverse effects in the sibutramine-treated patients were primarily cardiovascular and gastrointestinal. Cardiovascular effects included tachycardia and increases in systolic and diastolic blood pressure. The differences between the intervention and control groups were small, and no differences were observed in discontinuation rates caused by adverse events. Nor were differences reported in growth and maturation between the intervention and control groups.

Adverse effects in the orlistat-treated patients were also low and similar in the intervention and control groups. Gastrointestinal effects were common. The number needed to harm (NNH) for fatty or oily stools was 2,⁴ and the NNH for fecal incontinence was 12.⁵

WHAT'S NEW: Clinicians treating obese kids have cause for optimism

Although the trials included in this review were heterogeneous and many were small, this systematic review provides evidence that intensive, comprehensive behavioral weight loss interventions for obese children can be effective up to 12 months after the conclusion of the program. Family physicians should consider referring obese children and adolescents to such programs—or finding ways to provide supportive strategies themselves.

Sibutramine and orlistat may be helpful in the context of comprehensive, intensive behavioral interventions, although there is no follow-up data to demonstrate long-term safety and weight maintenance after the medication is stopped.

CAVEATS: Little is known about long-term safety of the drugs

There have been few randomized trials of pharmacologic interventions in adolescents and none evaluating weight maintenance after 12 months (or discontinuation of treatment), or assessing long-term safety of the medication.

Sibutramine is not approved by the US Food and Drug Administration (FDA) for use in children or adolescents.⁷ Orlistat is currently approved only for individuals over the age of 12.⁸

In January 2010, an additional contraindication was added to the sibutramine drug label, stating that it is not to be used in patients with a history of cardiovascular disease.⁹ And the FDA is currently investigating a rare association between orlistat and liver injury, although no conclusions have been released.¹⁰ Children and adolescents are particularly vulnerable to long-term side effects, given their relatively young age at the time of drug initiation, so we urge caution with the use of these drugs in this patient population.

CHALLENGES TO IMPLEMENTATION: Intensive approach may be hard to reproduce

Implementation of high-intensity comprehensive interventions for obese children faces a number of roadblocks, including limited availability of programs, cost, and reimbursement. Most of the intensive interventions in these trials took place in specialty centers rather than in primary care offices. Replicating them could require a referral—or significant resources within the primary care setting itself. Yet many, if not most, insurance policies still do not cover such extensive lifestyle interventions. (For information on weight loss interventions for adults, see “Weight loss strategies that really work”).

None of these trials reported on cost or cost effectiveness. Despite the considerable cost of a comprehensive obesity management program, however, a successful weight-maintenance model could be a worthwhile investment in long-term health.

Lastly, the results of this trial should not negate the importance of obesity prevention efforts by parents, who are in the best position to reverse the childhood obesity epidemic.¹¹

Acknowledgement
The PURLs Surveillance System is supported in part by Grant Number UL1RR024999; awarded by the National Center for Research Resources; the grant is a Clinical Translational Science Award to the University of Chicago. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center for Research Resources or the National Institutes of Health.

Click here to view PURL METHODOLOGY

Illustrative case

A 10-year-old boy comes in with his mother for a well-child check-up. His BMI is 40 kg/m²—above the 99th percentile for his age and up from 37 a year ago. His blood pressure is 120/84 mm Hg. What treatment, if any, should you offer for his obesity?

Childhood obesity is a global epidemic. In the United States, 19.6% of children ages 6 through 11 and 18.1% of 12- to 19-year-olds are obese, a 3-fold increase in the last 30 years.³ Without intervention, most obese adolescents will become obese adults, threatening to reverse the progress in slowing cardiovascular morbidity and mortality that has occurred over the past few decades.³

Obese kids get adult diseases
Obesity is a risk factor for a variety of chronic conditions, including cardiovascular disease, cerebrovascular disease, and arthritis. Severe obesity is also associated with higher mortality rates.⁴ Unfortunately, these comorbidities are not limited to adulthood.

“Adult” diseases, such as obstructive sleep apnea, dyslipidemia, and type 2 diabetes, are increasingly seen in children and adolescents.¹ Nutritional deficits such as vitamin D and iron deficiency are often seen in obese children, as well.⁵ There are also psychological ramifications of childhood obesity, including social isolation and depression.⁶

The USPSTF recently upgraded its recommendation regarding obesity screening in children ages 6 and older from I (insufficient evidence) to B (a positive grade based on high or moderate certainty of the benefit of the intervention), citing new evidence in favor of screening and treating or referring children when appropriate.² The systematic review we report on here, which formed the basis for the USPSTF’s upgrade, focused on management options for children identified as overweight or obese.

STUDY SUMMARY: Intense, comprehensive efforts pay off

This systematic review¹ included studies of children ages 4 to 18 years who were overweight (defined as a body mass index [BMI] in the 85th to 94th percentile for age and sex) or obese (either a BMI at or above the 95th percentile for age and sex or a BMI >30 kg/m²). The researchers found 25 trials—15 of behavioral interventions alone and 10 that combined behavioral and pharmacologic interventions—that met their criteria: The studies focused on weight loss and/or maintenance, reported outcomes ≥6 months from baseline, and were conducted (or feasible) in a primary care setting.

Behavioral interventions were categorized by treatment intensity (as measured by hours of contact, which ranged from <10 hours to >75) and comprehensiveness (including nutritional counseling, physical activity counseling or participation, and counseling on behavioral management techniques). Weight outcomes were categorized as short-term (6-12 months since treatment initiation) or maintenance (≥12 months after the end of active treatment).

The 15 behavioral intervention trials included 1258 children ages 4 to 18 years, most of whom were obese. Most trials were small and reported high retention rates. All had beneficial effects on weight in the intervention group compared with the controls, but not all changes were statistically significant. Higher intensity and more comprehensive programs had better outcomes.

The largest effects were in 3 moderate- to high-intensity, comprehensive weight management programs with ≥26 hours of contact. These 3 trials demonstrated a difference in BMI of 1.9 to 3.3 in the intervention groups at 12 months compared with the controls. (A 3.3 difference in BMI is equal to approximately 13 lb in an 8-year-old and 17 lb in a 12-year-old.)

Four behavioral intervention studies reported outcomes ≥12 months after completing the intervention (range 15-48 months). Three of the 4 reported continued beneficial effects on weight after the active treatment period, but the effects were markedly attenuated.

The only adverse effect reported in the trials of behavioral interventions was the injury rate among children in an exercise program, but it was minimal: One fracture was reported, vs no injuries for the controls. No differences were reported in height, eating disorders, or depression. However, fewer than half of the behavioral intervention trials reported on adverse effects.

Weight loss drugs have modest effects
Ten trials combining pharmacologic and behavioral interventions involved a total of 1294 obese adolescents ages 12 to 19. All evaluated short-term weight loss effects of either sibutramine (10-15 mg/d) or orlistat (120 mg tid). Trials ranged from 3 to 12 months. Participants in both the control and intervention groups received behavioral counseling.

The trials all favored the treatment groups, although not all of the results were statistically significant. Trials of longer duration (12 months) had more favorable results than those lasting 6 months.

The largest sibutramine trial (n=498) reported a mean BMI reduction of 2.9 in the treatment group, compared with a reduction of 0.3 in the control group (P<.001). This corresponds to an average weight loss of 14 lb in the intervention group, vs 4.2 lb in the control group, after 12 months.

The largest orlistat trial (n=539) reported a mean BMI reduction in the treatment group of 0.6, vs 0.3 in the control group (P<.001)—an average weight loss of 4.2 lb in the intervention group, compared with 2.1 lb among the controls after 12 months. None of the trials evaluated weight change after cessation of the study drug, and none compared orlistat with sibutramine.

Adverse effects in the sibutramine-treated patients were primarily cardiovascular and gastrointestinal. Cardiovascular effects included tachycardia and increases in systolic and diastolic blood pressure. The differences between the intervention and control groups were small, and no differences were observed in discontinuation rates caused by adverse events. Nor were differences reported in growth and maturation between the intervention and control groups.

Adverse effects in the orlistat-treated patients were also low and similar in the intervention and control groups. Gastrointestinal effects were common. The number needed to harm (NNH) for fatty or oily stools was 2,⁴ and the NNH for fecal incontinence was 12.⁵

WHAT'S NEW: Clinicians treating obese kids have cause for optimism

Although the trials included in this review were heterogeneous and many were small, this systematic review provides evidence that intensive, comprehensive behavioral weight loss interventions for obese children can be effective up to 12 months after the conclusion of the program. Family physicians should consider referring obese children and adolescents to such programs—or finding ways to provide supportive strategies themselves.

Sibutramine and orlistat may be helpful in the context of comprehensive, intensive behavioral interventions, although there is no follow-up data to demonstrate long-term safety and weight maintenance after the medication is stopped.

CAVEATS: Little is known about long-term safety of the drugs

There have been few randomized trials of pharmacologic interventions in adolescents and none evaluating weight maintenance after 12 months (or discontinuation of treatment), or assessing long-term safety of the medication.

Sibutramine is not approved by the US Food and Drug Administration (FDA) for use in children or adolescents.⁷ Orlistat is currently approved only for individuals over the age of 12.⁸

In January 2010, an additional contraindication was added to the sibutramine drug label, stating that it is not to be used in patients with a history of cardiovascular disease.⁹ And the FDA is currently investigating a rare association between orlistat and liver injury, although no conclusions have been released.¹⁰ Children and adolescents are particularly vulnerable to long-term side effects, given their relatively young age at the time of drug initiation, so we urge caution with the use of these drugs in this patient population.

CHALLENGES TO IMPLEMENTATION: Intensive approach may be hard to reproduce

Implementation of high-intensity comprehensive interventions for obese children faces a number of roadblocks, including limited availability of programs, cost, and reimbursement. Most of the intensive interventions in these trials took place in specialty centers rather than in primary care offices. Replicating them could require a referral—or significant resources within the primary care setting itself. Yet many, if not most, insurance policies still do not cover such extensive lifestyle interventions. (For information on weight loss interventions for adults, see “Weight loss strategies that really work”).

None of these trials reported on cost or cost effectiveness. Despite the considerable cost of a comprehensive obesity management program, however, a successful weight-maintenance model could be a worthwhile investment in long-term health.

Lastly, the results of this trial should not negate the importance of obesity prevention efforts by parents, who are in the best position to reverse the childhood obesity epidemic.¹¹

Acknowledgement
The PURLs Surveillance System is supported in part by Grant Number UL1RR024999; awarded by the National Center for Research Resources; the grant is a Clinical Translational Science Award to the University of Chicago. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center for Research Resources or the National Institutes of Health.

Click here to view PURL METHODOLOGY

Illustrative case

A 10-year-old boy comes in with his mother for a well-child check-up. His BMI is 40 kg/m²—above the 99th percentile for his age and up from 37 a year ago. His blood pressure is 120/84 mm Hg. What treatment, if any, should you offer for his obesity?

Childhood obesity is a global epidemic. In the United States, 19.6% of children ages 6 through 11 and 18.1% of 12- to 19-year-olds are obese, a 3-fold increase in the last 30 years.³ Without intervention, most obese adolescents will become obese adults, threatening to reverse the progress in slowing cardiovascular morbidity and mortality that has occurred over the past few decades.³

Obese kids get adult diseases
Obesity is a risk factor for a variety of chronic conditions, including cardiovascular disease, cerebrovascular disease, and arthritis. Severe obesity is also associated with higher mortality rates.⁴ Unfortunately, these comorbidities are not limited to adulthood.

“Adult” diseases, such as obstructive sleep apnea, dyslipidemia, and type 2 diabetes, are increasingly seen in children and adolescents.¹ Nutritional deficits such as vitamin D and iron deficiency are often seen in obese children, as well.⁵ There are also psychological ramifications of childhood obesity, including social isolation and depression.⁶

The USPSTF recently upgraded its recommendation regarding obesity screening in children ages 6 and older from I (insufficient evidence) to B (a positive grade based on high or moderate certainty of the benefit of the intervention), citing new evidence in favor of screening and treating or referring children when appropriate.² The systematic review we report on here, which formed the basis for the USPSTF’s upgrade, focused on management options for children identified as overweight or obese.

STUDY SUMMARY: Intense, comprehensive efforts pay off

This systematic review¹ included studies of children ages 4 to 18 years who were overweight (defined as a body mass index [BMI] in the 85th to 94th percentile for age and sex) or obese (either a BMI at or above the 95th percentile for age and sex or a BMI >30 kg/m²). The researchers found 25 trials—15 of behavioral interventions alone and 10 that combined behavioral and pharmacologic interventions—that met their criteria: The studies focused on weight loss and/or maintenance, reported outcomes ≥6 months from baseline, and were conducted (or feasible) in a primary care setting.

Behavioral interventions were categorized by treatment intensity (as measured by hours of contact, which ranged from <10 hours to >75) and comprehensiveness (including nutritional counseling, physical activity counseling or participation, and counseling on behavioral management techniques). Weight outcomes were categorized as short-term (6-12 months since treatment initiation) or maintenance (≥12 months after the end of active treatment).

The 15 behavioral intervention trials included 1258 children ages 4 to 18 years, most of whom were obese. Most trials were small and reported high retention rates. All had beneficial effects on weight in the intervention group compared with the controls, but not all changes were statistically significant. Higher intensity and more comprehensive programs had better outcomes.

The largest effects were in 3 moderate- to high-intensity, comprehensive weight management programs with ≥26 hours of contact. These 3 trials demonstrated a difference in BMI of 1.9 to 3.3 in the intervention groups at 12 months compared with the controls. (A 3.3 difference in BMI is equal to approximately 13 lb in an 8-year-old and 17 lb in a 12-year-old.)

Four behavioral intervention studies reported outcomes ≥12 months after completing the intervention (range 15-48 months). Three of the 4 reported continued beneficial effects on weight after the active treatment period, but the effects were markedly attenuated.

The only adverse effect reported in the trials of behavioral interventions was the injury rate among children in an exercise program, but it was minimal: One fracture was reported, vs no injuries for the controls. No differences were reported in height, eating disorders, or depression. However, fewer than half of the behavioral intervention trials reported on adverse effects.

Weight loss drugs have modest effects
Ten trials combining pharmacologic and behavioral interventions involved a total of 1294 obese adolescents ages 12 to 19. All evaluated short-term weight loss effects of either sibutramine (10-15 mg/d) or orlistat (120 mg tid). Trials ranged from 3 to 12 months. Participants in both the control and intervention groups received behavioral counseling.

The trials all favored the treatment groups, although not all of the results were statistically significant. Trials of longer duration (12 months) had more favorable results than those lasting 6 months.

The largest sibutramine trial (n=498) reported a mean BMI reduction of 2.9 in the treatment group, compared with a reduction of 0.3 in the control group (P<.001). This corresponds to an average weight loss of 14 lb in the intervention group, vs 4.2 lb in the control group, after 12 months.

The largest orlistat trial (n=539) reported a mean BMI reduction in the treatment group of 0.6, vs 0.3 in the control group (P<.001)—an average weight loss of 4.2 lb in the intervention group, compared with 2.1 lb among the controls after 12 months. None of the trials evaluated weight change after cessation of the study drug, and none compared orlistat with sibutramine.

Adverse effects in the sibutramine-treated patients were primarily cardiovascular and gastrointestinal. Cardiovascular effects included tachycardia and increases in systolic and diastolic blood pressure. The differences between the intervention and control groups were small, and no differences were observed in discontinuation rates caused by adverse events. Nor were differences reported in growth and maturation between the intervention and control groups.

Adverse effects in the orlistat-treated patients were also low and similar in the intervention and control groups. Gastrointestinal effects were common. The number needed to harm (NNH) for fatty or oily stools was 2,⁴ and the NNH for fecal incontinence was 12.⁵

WHAT'S NEW: Clinicians treating obese kids have cause for optimism

Although the trials included in this review were heterogeneous and many were small, this systematic review provides evidence that intensive, comprehensive behavioral weight loss interventions for obese children can be effective up to 12 months after the conclusion of the program. Family physicians should consider referring obese children and adolescents to such programs—or finding ways to provide supportive strategies themselves.

Sibutramine and orlistat may be helpful in the context of comprehensive, intensive behavioral interventions, although there is no follow-up data to demonstrate long-term safety and weight maintenance after the medication is stopped.

CAVEATS: Little is known about long-term safety of the drugs

There have been few randomized trials of pharmacologic interventions in adolescents and none evaluating weight maintenance after 12 months (or discontinuation of treatment), or assessing long-term safety of the medication.

Sibutramine is not approved by the US Food and Drug Administration (FDA) for use in children or adolescents.⁷ Orlistat is currently approved only for individuals over the age of 12.⁸

In January 2010, an additional contraindication was added to the sibutramine drug label, stating that it is not to be used in patients with a history of cardiovascular disease.⁹ And the FDA is currently investigating a rare association between orlistat and liver injury, although no conclusions have been released.¹⁰ Children and adolescents are particularly vulnerable to long-term side effects, given their relatively young age at the time of drug initiation, so we urge caution with the use of these drugs in this patient population.

CHALLENGES TO IMPLEMENTATION: Intensive approach may be hard to reproduce

Implementation of high-intensity comprehensive interventions for obese children faces a number of roadblocks, including limited availability of programs, cost, and reimbursement. Most of the intensive interventions in these trials took place in specialty centers rather than in primary care offices. Replicating them could require a referral—or significant resources within the primary care setting itself. Yet many, if not most, insurance policies still do not cover such extensive lifestyle interventions. (For information on weight loss interventions for adults, see “Weight loss strategies that really work”).

None of these trials reported on cost or cost effectiveness. Despite the considerable cost of a comprehensive obesity management program, however, a successful weight-maintenance model could be a worthwhile investment in long-term health.

Lastly, the results of this trial should not negate the importance of obesity prevention efforts by parents, who are in the best position to reverse the childhood obesity epidemic.¹¹

Acknowledgement
The PURLs Surveillance System is supported in part by Grant Number UL1RR024999; awarded by the National Center for Research Resources; the grant is a Clinical Translational Science Award to the University of Chicago. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center for Research Resources or the National Institutes of Health.

Click here to view PURL METHODOLOGY

Evidence summary

Multiple cohort studies demonstrate that the expected events of normal labor form a bell-shaped curve. The range of labor experiences makes predicting when a particular woman will enter active labor difficult.

When does latent labor become active labor?

The first stage of labor includes latent and active phases. The latent phase is defined as the period between onset of labor and cervical dilatation of 3 to 4 cm or the time between onset of regular contractions and escalation in the rate of cervical dilation. Regular contractions must be intense, last 60 seconds, and occur in a predictable pattern. Escalating cervical dilation is marked by a change in the cervical examination over a short period of time (usually 2 hours).¹

The World Health Organization defines active labor as cervical dilation between 4 and 9 cm, with dilation usually occurring at 1 cm per hour or faster and accompanied by the beginning of fetal descent.²

Latent labor was initially described in a large prospective cohort of 10,293 term gravidas (including 4175 nulliparas and 5599 multiparas) followed from presentation to delivery.¹ Cervical dilation was assessed by examination every 30 to 120 minutes, almost always performed by the same examiner throughout labor. In primigravidas, latent labor averaged 6.4 hours, with 95% of women completing the latent phase in 20.6 hours. In multigravidas, the mean duration of latent labor was 4.8 hours, with 95% of women transitioning to active labor in 13.6 hours.

Shorter intercontraction interval linked to active labor

A recently published cohort study of women presenting to labor and delivery found that a relative decrease in the intercontraction interval was associated with a diagnosis of labor (odds ratio=1.42; 95% confidence interval, 1.06-1.90). The study failed to define either active labor or decrease in the intercontraction interval.³

Earlier admission leads to more interventions and poorer outcomes

Many studies have suggested that admitting women to the hospital during the latent phase of labor is associated with more interventions and poorer outcomes. Two large retrospective cohort studies (N=2697 and 3220) found increased rates of cesarean section in women admitted during the latent phase.^4,5 They also reported increased use of oxytocin, epidural analgesia, intrauterine pressure catheters, and fetal scalp electrodes, and increased rates of chorioamnionitis, postpartum infection, and neonatal intubation.^4,5 See the TABLE for a summary of the effects of latent-phase admission.

TABLE
Consequences of hospital admission during latent vs active labor

Labor assessment program reduced time in the labor ward

Labor assessment programs attempt to delay admission during early active labor. One randomized clinical trial (N=209) among low-risk women with reassuring maternal and fetal assessments in early labor divided the women into 2 groups when they presented for labor and delivery. One group received advice, encouragement, and support along with instructions to walk or return home and come back when labor became more active (defined as regular, painful contractions and dilation of at least 3 cm). The other group was admitted directly to the labor and delivery ward. The study found that early labor assessment decreased use of analgesics and oxytocin and reduced time spent in the labor ward.⁶

Recommendations

The American College of Obstetricians and Gynecologists (ACOG) acknowledges in patient education literature that distinguishing true from false labor is difficult. ACOG lists characteristics of each and recommend that a woman monitor the frequency of contractions for an hour and call the doctor’s office or hospital if she thinks she’s in labor.⁷

Similarly, a patient handout from the American College of Nurse-Midwives recommends calling the health care provider if contractions are ≤5 minutes apart for more than 1 hour, several contractions are so painful that the woman cannot walk or talk, or her water breaks.⁸

A standard textbook describes normal uterine contractions during active labor as occurring every 2 to 5 minutes, and as often as every 2 to 3 minutes.⁹

Evidence summary

Multiple cohort studies demonstrate that the expected events of normal labor form a bell-shaped curve. The range of labor experiences makes predicting when a particular woman will enter active labor difficult.

When does latent labor become active labor?

The first stage of labor includes latent and active phases. The latent phase is defined as the period between onset of labor and cervical dilatation of 3 to 4 cm or the time between onset of regular contractions and escalation in the rate of cervical dilation. Regular contractions must be intense, last 60 seconds, and occur in a predictable pattern. Escalating cervical dilation is marked by a change in the cervical examination over a short period of time (usually 2 hours).¹

The World Health Organization defines active labor as cervical dilation between 4 and 9 cm, with dilation usually occurring at 1 cm per hour or faster and accompanied by the beginning of fetal descent.²

Latent labor was initially described in a large prospective cohort of 10,293 term gravidas (including 4175 nulliparas and 5599 multiparas) followed from presentation to delivery.¹ Cervical dilation was assessed by examination every 30 to 120 minutes, almost always performed by the same examiner throughout labor. In primigravidas, latent labor averaged 6.4 hours, with 95% of women completing the latent phase in 20.6 hours. In multigravidas, the mean duration of latent labor was 4.8 hours, with 95% of women transitioning to active labor in 13.6 hours.

Shorter intercontraction interval linked to active labor

A recently published cohort study of women presenting to labor and delivery found that a relative decrease in the intercontraction interval was associated with a diagnosis of labor (odds ratio=1.42; 95% confidence interval, 1.06-1.90). The study failed to define either active labor or decrease in the intercontraction interval.³

Earlier admission leads to more interventions and poorer outcomes

Many studies have suggested that admitting women to the hospital during the latent phase of labor is associated with more interventions and poorer outcomes. Two large retrospective cohort studies (N=2697 and 3220) found increased rates of cesarean section in women admitted during the latent phase.^4,5 They also reported increased use of oxytocin, epidural analgesia, intrauterine pressure catheters, and fetal scalp electrodes, and increased rates of chorioamnionitis, postpartum infection, and neonatal intubation.^4,5 See the TABLE for a summary of the effects of latent-phase admission.

TABLE
Consequences of hospital admission during latent vs active labor

Labor assessment program reduced time in the labor ward

Labor assessment programs attempt to delay admission during early active labor. One randomized clinical trial (N=209) among low-risk women with reassuring maternal and fetal assessments in early labor divided the women into 2 groups when they presented for labor and delivery. One group received advice, encouragement, and support along with instructions to walk or return home and come back when labor became more active (defined as regular, painful contractions and dilation of at least 3 cm). The other group was admitted directly to the labor and delivery ward. The study found that early labor assessment decreased use of analgesics and oxytocin and reduced time spent in the labor ward.⁶

Recommendations

The American College of Obstetricians and Gynecologists (ACOG) acknowledges in patient education literature that distinguishing true from false labor is difficult. ACOG lists characteristics of each and recommend that a woman monitor the frequency of contractions for an hour and call the doctor’s office or hospital if she thinks she’s in labor.⁷

Similarly, a patient handout from the American College of Nurse-Midwives recommends calling the health care provider if contractions are ≤5 minutes apart for more than 1 hour, several contractions are so painful that the woman cannot walk or talk, or her water breaks.⁸

A standard textbook describes normal uterine contractions during active labor as occurring every 2 to 5 minutes, and as often as every 2 to 3 minutes.⁹

Evidence summary

Multiple cohort studies demonstrate that the expected events of normal labor form a bell-shaped curve. The range of labor experiences makes predicting when a particular woman will enter active labor difficult.

When does latent labor become active labor?

The first stage of labor includes latent and active phases. The latent phase is defined as the period between onset of labor and cervical dilatation of 3 to 4 cm or the time between onset of regular contractions and escalation in the rate of cervical dilation. Regular contractions must be intense, last 60 seconds, and occur in a predictable pattern. Escalating cervical dilation is marked by a change in the cervical examination over a short period of time (usually 2 hours).¹

The World Health Organization defines active labor as cervical dilation between 4 and 9 cm, with dilation usually occurring at 1 cm per hour or faster and accompanied by the beginning of fetal descent.²

Latent labor was initially described in a large prospective cohort of 10,293 term gravidas (including 4175 nulliparas and 5599 multiparas) followed from presentation to delivery.¹ Cervical dilation was assessed by examination every 30 to 120 minutes, almost always performed by the same examiner throughout labor. In primigravidas, latent labor averaged 6.4 hours, with 95% of women completing the latent phase in 20.6 hours. In multigravidas, the mean duration of latent labor was 4.8 hours, with 95% of women transitioning to active labor in 13.6 hours.

Shorter intercontraction interval linked to active labor

A recently published cohort study of women presenting to labor and delivery found that a relative decrease in the intercontraction interval was associated with a diagnosis of labor (odds ratio=1.42; 95% confidence interval, 1.06-1.90). The study failed to define either active labor or decrease in the intercontraction interval.³

Earlier admission leads to more interventions and poorer outcomes

Many studies have suggested that admitting women to the hospital during the latent phase of labor is associated with more interventions and poorer outcomes. Two large retrospective cohort studies (N=2697 and 3220) found increased rates of cesarean section in women admitted during the latent phase.^4,5 They also reported increased use of oxytocin, epidural analgesia, intrauterine pressure catheters, and fetal scalp electrodes, and increased rates of chorioamnionitis, postpartum infection, and neonatal intubation.^4,5 See the TABLE for a summary of the effects of latent-phase admission.

TABLE
Consequences of hospital admission during latent vs active labor

Labor assessment program reduced time in the labor ward

Labor assessment programs attempt to delay admission during early active labor. One randomized clinical trial (N=209) among low-risk women with reassuring maternal and fetal assessments in early labor divided the women into 2 groups when they presented for labor and delivery. One group received advice, encouragement, and support along with instructions to walk or return home and come back when labor became more active (defined as regular, painful contractions and dilation of at least 3 cm). The other group was admitted directly to the labor and delivery ward. The study found that early labor assessment decreased use of analgesics and oxytocin and reduced time spent in the labor ward.⁶

Recommendations

The American College of Obstetricians and Gynecologists (ACOG) acknowledges in patient education literature that distinguishing true from false labor is difficult. ACOG lists characteristics of each and recommend that a woman monitor the frequency of contractions for an hour and call the doctor’s office or hospital if she thinks she’s in labor.⁷

Similarly, a patient handout from the American College of Nurse-Midwives recommends calling the health care provider if contractions are ≤5 minutes apart for more than 1 hour, several contractions are so painful that the woman cannot walk or talk, or her water breaks.⁸

A standard textbook describes normal uterine contractions during active labor as occurring every 2 to 5 minutes, and as often as every 2 to 3 minutes.⁹

ILLUSTRATIVE CASE

A 71-year-old woman with diabetes and coronary artery disease has just been admitted to the ICU, where she’ll receive treatment for sepsis, multilobar pneumonia, and respiratory failure requiring mechanical ventilation. Her blood sugar is 253 mg/dL. In writing her admission orders, you contemplate targets for glycemic control. How low should you go?

Hyperglycemia is common in patients admitted to intensive care, whether or not they have diabetes. Elevated blood sugar is associated with stress and trauma and affects both postoperative and critically ill medical patients. A wealth of evidence has demonstrated that hyperglycemia is associated with poorer outcomes and increased mortality in this patient population, including those with myocardial infarction, stroke, trauma, and other medical conditions.^2-5 Thus, intensive glucose control is the standard of care in the ICU, based on consensus guidelines from such groups as the American Diabetes Association (ADA) and the Surviving Sepsis Campaign—an initiative developed by 3 critical care organizations and endorsed by 16 specialty groups.^6-8

Is intense therapy better? Study results differ
The association between hyperglycemia and an increased risk of death led investigators to study the effectiveness of aggressive treatment with insulin in decreasing morbidity and mortality. A 2004 meta-analysis of 35 trials comparing insulin vs no insulin in critically ill hospitalized patients demonstrated a 15% reduction in short-term mortality among patients treated with insulin.⁹ A 2008 meta-analysis of 29 randomized trials, including data from 8432 adult ICU patients, compared intensive insulin therapy with conventional therapy—and found that intensive therapy did not lower hospital mortality rates compared with conventional therapy. In addition, this meta-analysis revealed a marked increase in severe hypoglycemia (blood sugar ≤40 mg/dL) in the intensive therapy group.¹⁰ (The intensive therapy group included studies with glucose goals of ≤110 mg/dL and <150 mg/dL in about equal numbers; conventional therapy goals were generally between 180 and 200 mg/dL.)

The studies included in both the meta-analyses, however, were mostly small, single-center trials, and of low-to-medium quality. In addition, methods for achieving glycemic control varied. Nonetheless, current consensus guidelines set a goal for glucose levels of 80 to 110 mg/dL for all critically ill hospitalized patients.^6-8 But because of the lack of sufficient high-quality evidence from a single large RCT, Finfer et al conducted the large study described here to clearly establish that intensive glycemic control decreases all-cause mortality. Given their hypothesis, the results were surprising.

STUDY SUMMARY: Intensive therapy does more harm than help

NICE-SUGAR (Normoglycaemia in Intensive Care Evaluation-Survival Using Glucose Algorithm Regulation) was a large-scale, multicenter, multinational trial comparing aggressive blood sugar control (goal 81-108 mg/dL) with conventional therapy (goal ≤180 mg/dL) in 6104 critically ill hospitalized patients with hyperglycemia. Patients were followed for 90 days. The primary end point was death from any cause 90 days after randomization. Secondary outcomes included survival time during the first 90 days, specific cause of death, duration of mechanical ventilation, renal replacement therapy, and length of stays in the ICU and in the hospital. Other outcomes included death from any cause within 28 days, place of death, new organ failure, positive blood culture, blood transfusion, and units of blood transfused.

The study was conducted in 42 hospitals in Canada, Australia, and New Zealand. Patients had to have an anticipated ICU admission of 3 days or more and randomization had to occur within 24 hours of admission. The study protocol was discontinued when patients began eating or were discharged from the ICU; if they were readmitted to the ICU within 90 days of randomization, the study protocol was resumed.

Treatment assignment was revealed to clinical staff after randomization, and was determined by a specific algorithm ( https://studies.thegeorgeinstitute.org/nice/ ). Blood sugar levels were managed with insulin infusions.

In the conventional group, insulin was started at 1 unit/h for glucose levels >180 mg/dL, and decreased or stopped when levels were <144 mg/dL, depending on previous glucose value and current rate of drip. In the intensive therapy group, insulin was initiated for lower levels (blood sugar >109 mg/dL) and at a higher rate (2 units/h). The insulin rate was decreased or maintained for glucose levels from 64 to 80 mg/dL, depending on previous glucose value and current rate of drip. Insulin was withheld for blood sugar levels of <64 mg/dL.

Contrary to the hypothesis, intensive therapy spelled trouble. Patients with intensive glycemic control had an all-cause mortality rate of 27.5%, compared with a rate of 24.9% for patients in the conventional therapy group (P=.04, number needed to harm [NNH]=38). Severe hypoglycemia (glucose ≤40 mg/dL) occurred in 6.8% of those in the intensive therapy group, compared with 0.5% in the conventional therapy group (P=.03, NNH=16).

Most of the deaths in both groups occurred in the ICU or in the hospital. Deaths from cardiovascular causes were more common among those in the intensive therapy group. There were no significant differences in any other outcomes. The mean glucose level in the intensive therapy group was 118, vs 145 mg/dL in the conventional therapy group.

For multivariate and subgroup analyses, the patients were assigned strata (Canada or Australia/New Zealand; operative vs nonoperative admission) or classified into groups (traumatic vs atraumatic; diabetes vs no diabetes; corticosteroids in previous 72 hours or not; high vs low critical illness symptom severity) based on predefined characteristics. No subgroups had significantly improved outcomes with intensive therapy.¹

WHAT’S NEW: Now we know: Don’t go too low

This study, in contrast to a number of smaller studies of lower quality, demonstrates a higher all-cause mortality rate at 90 days for critically ill patients receiving intensive glucose therapy. It is now clear that, among critically ill hospitalized patients, aiming for intensive glucose control (81-108 mg/dL) is associated with an increased rate of severe hypoglycemic events and all-cause mortality at 90 days. The previously used goal of conventional therapy (≤180 mg/dL) is safer.

CAVEATS: Study population may not reflect primary care

There are 2 caveats to this study. The first is that because of the nature of the research, it was impossible to maintain blinding of the clinical staff to patient assignments. The second important caveat pertains to the severity of illness among participants in this multicenter study: Most of these patients were in ICUs at tertiary care medical centers and had an expected ICU length of stay of 3 or more days. Although many family physicians manage patients in ICUs, the patients randomized in this study may represent a sicker than average patient population for some hospitals.

CHALLENGES TO IMPLEMENTATION: Some may doubt validity of this outcome

Less aggressive glycemic control for critically ill patients should be easier to achieve, not more difficult. However, a change in glucose targets may require new admission order sets and, notably, reeducation of physicians and nurses who have been convinced by earlier studies that more intensive glucose control is superior.

Acknowledgments

The PURLs Surveillance System is supported in part by Grant Number UL1RR024999 from the National Center for Research Resources, a Clinical Translational Science Award to the University of Chicago. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center for Research Resources or the National Institutes of Health.

PURLs methodology

This study was selected and evaluated using FPIN’s Priority Updates from the Research Literature (PURL) Surveillance System methodology. The criteria and findings leading to the selection of this study as a PURL can be accessed at www.jfponline.com/purls.

ILLUSTRATIVE CASE

A 71-year-old woman with diabetes and coronary artery disease has just been admitted to the ICU, where she’ll receive treatment for sepsis, multilobar pneumonia, and respiratory failure requiring mechanical ventilation. Her blood sugar is 253 mg/dL. In writing her admission orders, you contemplate targets for glycemic control. How low should you go?

Hyperglycemia is common in patients admitted to intensive care, whether or not they have diabetes. Elevated blood sugar is associated with stress and trauma and affects both postoperative and critically ill medical patients. A wealth of evidence has demonstrated that hyperglycemia is associated with poorer outcomes and increased mortality in this patient population, including those with myocardial infarction, stroke, trauma, and other medical conditions.^2-5 Thus, intensive glucose control is the standard of care in the ICU, based on consensus guidelines from such groups as the American Diabetes Association (ADA) and the Surviving Sepsis Campaign—an initiative developed by 3 critical care organizations and endorsed by 16 specialty groups.^6-8

Is intense therapy better? Study results differ
The association between hyperglycemia and an increased risk of death led investigators to study the effectiveness of aggressive treatment with insulin in decreasing morbidity and mortality. A 2004 meta-analysis of 35 trials comparing insulin vs no insulin in critically ill hospitalized patients demonstrated a 15% reduction in short-term mortality among patients treated with insulin.⁹ A 2008 meta-analysis of 29 randomized trials, including data from 8432 adult ICU patients, compared intensive insulin therapy with conventional therapy—and found that intensive therapy did not lower hospital mortality rates compared with conventional therapy. In addition, this meta-analysis revealed a marked increase in severe hypoglycemia (blood sugar ≤40 mg/dL) in the intensive therapy group.¹⁰ (The intensive therapy group included studies with glucose goals of ≤110 mg/dL and <150 mg/dL in about equal numbers; conventional therapy goals were generally between 180 and 200 mg/dL.)

The studies included in both the meta-analyses, however, were mostly small, single-center trials, and of low-to-medium quality. In addition, methods for achieving glycemic control varied. Nonetheless, current consensus guidelines set a goal for glucose levels of 80 to 110 mg/dL for all critically ill hospitalized patients.^6-8 But because of the lack of sufficient high-quality evidence from a single large RCT, Finfer et al conducted the large study described here to clearly establish that intensive glycemic control decreases all-cause mortality. Given their hypothesis, the results were surprising.

STUDY SUMMARY: Intensive therapy does more harm than help

NICE-SUGAR (Normoglycaemia in Intensive Care Evaluation-Survival Using Glucose Algorithm Regulation) was a large-scale, multicenter, multinational trial comparing aggressive blood sugar control (goal 81-108 mg/dL) with conventional therapy (goal ≤180 mg/dL) in 6104 critically ill hospitalized patients with hyperglycemia. Patients were followed for 90 days. The primary end point was death from any cause 90 days after randomization. Secondary outcomes included survival time during the first 90 days, specific cause of death, duration of mechanical ventilation, renal replacement therapy, and length of stays in the ICU and in the hospital. Other outcomes included death from any cause within 28 days, place of death, new organ failure, positive blood culture, blood transfusion, and units of blood transfused.

The study was conducted in 42 hospitals in Canada, Australia, and New Zealand. Patients had to have an anticipated ICU admission of 3 days or more and randomization had to occur within 24 hours of admission. The study protocol was discontinued when patients began eating or were discharged from the ICU; if they were readmitted to the ICU within 90 days of randomization, the study protocol was resumed.

Treatment assignment was revealed to clinical staff after randomization, and was determined by a specific algorithm ( https://studies.thegeorgeinstitute.org/nice/ ). Blood sugar levels were managed with insulin infusions.

In the conventional group, insulin was started at 1 unit/h for glucose levels >180 mg/dL, and decreased or stopped when levels were <144 mg/dL, depending on previous glucose value and current rate of drip. In the intensive therapy group, insulin was initiated for lower levels (blood sugar >109 mg/dL) and at a higher rate (2 units/h). The insulin rate was decreased or maintained for glucose levels from 64 to 80 mg/dL, depending on previous glucose value and current rate of drip. Insulin was withheld for blood sugar levels of <64 mg/dL.

Contrary to the hypothesis, intensive therapy spelled trouble. Patients with intensive glycemic control had an all-cause mortality rate of 27.5%, compared with a rate of 24.9% for patients in the conventional therapy group (P=.04, number needed to harm [NNH]=38). Severe hypoglycemia (glucose ≤40 mg/dL) occurred in 6.8% of those in the intensive therapy group, compared with 0.5% in the conventional therapy group (P=.03, NNH=16).

Most of the deaths in both groups occurred in the ICU or in the hospital. Deaths from cardiovascular causes were more common among those in the intensive therapy group. There were no significant differences in any other outcomes. The mean glucose level in the intensive therapy group was 118, vs 145 mg/dL in the conventional therapy group.

For multivariate and subgroup analyses, the patients were assigned strata (Canada or Australia/New Zealand; operative vs nonoperative admission) or classified into groups (traumatic vs atraumatic; diabetes vs no diabetes; corticosteroids in previous 72 hours or not; high vs low critical illness symptom severity) based on predefined characteristics. No subgroups had significantly improved outcomes with intensive therapy.¹

WHAT’S NEW: Now we know: Don’t go too low

This study, in contrast to a number of smaller studies of lower quality, demonstrates a higher all-cause mortality rate at 90 days for critically ill patients receiving intensive glucose therapy. It is now clear that, among critically ill hospitalized patients, aiming for intensive glucose control (81-108 mg/dL) is associated with an increased rate of severe hypoglycemic events and all-cause mortality at 90 days. The previously used goal of conventional therapy (≤180 mg/dL) is safer.

CAVEATS: Study population may not reflect primary care

There are 2 caveats to this study. The first is that because of the nature of the research, it was impossible to maintain blinding of the clinical staff to patient assignments. The second important caveat pertains to the severity of illness among participants in this multicenter study: Most of these patients were in ICUs at tertiary care medical centers and had an expected ICU length of stay of 3 or more days. Although many family physicians manage patients in ICUs, the patients randomized in this study may represent a sicker than average patient population for some hospitals.

CHALLENGES TO IMPLEMENTATION: Some may doubt validity of this outcome

Less aggressive glycemic control for critically ill patients should be easier to achieve, not more difficult. However, a change in glucose targets may require new admission order sets and, notably, reeducation of physicians and nurses who have been convinced by earlier studies that more intensive glucose control is superior.

Acknowledgments

The PURLs Surveillance System is supported in part by Grant Number UL1RR024999 from the National Center for Research Resources, a Clinical Translational Science Award to the University of Chicago. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center for Research Resources or the National Institutes of Health.

PURLs methodology

This study was selected and evaluated using FPIN’s Priority Updates from the Research Literature (PURL) Surveillance System methodology. The criteria and findings leading to the selection of this study as a PURL can be accessed at www.jfponline.com/purls.

ILLUSTRATIVE CASE

A 71-year-old woman with diabetes and coronary artery disease has just been admitted to the ICU, where she’ll receive treatment for sepsis, multilobar pneumonia, and respiratory failure requiring mechanical ventilation. Her blood sugar is 253 mg/dL. In writing her admission orders, you contemplate targets for glycemic control. How low should you go?

Hyperglycemia is common in patients admitted to intensive care, whether or not they have diabetes. Elevated blood sugar is associated with stress and trauma and affects both postoperative and critically ill medical patients. A wealth of evidence has demonstrated that hyperglycemia is associated with poorer outcomes and increased mortality in this patient population, including those with myocardial infarction, stroke, trauma, and other medical conditions.^2-5 Thus, intensive glucose control is the standard of care in the ICU, based on consensus guidelines from such groups as the American Diabetes Association (ADA) and the Surviving Sepsis Campaign—an initiative developed by 3 critical care organizations and endorsed by 16 specialty groups.^6-8

Is intense therapy better? Study results differ
The association between hyperglycemia and an increased risk of death led investigators to study the effectiveness of aggressive treatment with insulin in decreasing morbidity and mortality. A 2004 meta-analysis of 35 trials comparing insulin vs no insulin in critically ill hospitalized patients demonstrated a 15% reduction in short-term mortality among patients treated with insulin.⁹ A 2008 meta-analysis of 29 randomized trials, including data from 8432 adult ICU patients, compared intensive insulin therapy with conventional therapy—and found that intensive therapy did not lower hospital mortality rates compared with conventional therapy. In addition, this meta-analysis revealed a marked increase in severe hypoglycemia (blood sugar ≤40 mg/dL) in the intensive therapy group.¹⁰ (The intensive therapy group included studies with glucose goals of ≤110 mg/dL and <150 mg/dL in about equal numbers; conventional therapy goals were generally between 180 and 200 mg/dL.)

The studies included in both the meta-analyses, however, were mostly small, single-center trials, and of low-to-medium quality. In addition, methods for achieving glycemic control varied. Nonetheless, current consensus guidelines set a goal for glucose levels of 80 to 110 mg/dL for all critically ill hospitalized patients.^6-8 But because of the lack of sufficient high-quality evidence from a single large RCT, Finfer et al conducted the large study described here to clearly establish that intensive glycemic control decreases all-cause mortality. Given their hypothesis, the results were surprising.

STUDY SUMMARY: Intensive therapy does more harm than help

NICE-SUGAR (Normoglycaemia in Intensive Care Evaluation-Survival Using Glucose Algorithm Regulation) was a large-scale, multicenter, multinational trial comparing aggressive blood sugar control (goal 81-108 mg/dL) with conventional therapy (goal ≤180 mg/dL) in 6104 critically ill hospitalized patients with hyperglycemia. Patients were followed for 90 days. The primary end point was death from any cause 90 days after randomization. Secondary outcomes included survival time during the first 90 days, specific cause of death, duration of mechanical ventilation, renal replacement therapy, and length of stays in the ICU and in the hospital. Other outcomes included death from any cause within 28 days, place of death, new organ failure, positive blood culture, blood transfusion, and units of blood transfused.

The study was conducted in 42 hospitals in Canada, Australia, and New Zealand. Patients had to have an anticipated ICU admission of 3 days or more and randomization had to occur within 24 hours of admission. The study protocol was discontinued when patients began eating or were discharged from the ICU; if they were readmitted to the ICU within 90 days of randomization, the study protocol was resumed.

Treatment assignment was revealed to clinical staff after randomization, and was determined by a specific algorithm ( https://studies.thegeorgeinstitute.org/nice/ ). Blood sugar levels were managed with insulin infusions.

In the conventional group, insulin was started at 1 unit/h for glucose levels >180 mg/dL, and decreased or stopped when levels were <144 mg/dL, depending on previous glucose value and current rate of drip. In the intensive therapy group, insulin was initiated for lower levels (blood sugar >109 mg/dL) and at a higher rate (2 units/h). The insulin rate was decreased or maintained for glucose levels from 64 to 80 mg/dL, depending on previous glucose value and current rate of drip. Insulin was withheld for blood sugar levels of <64 mg/dL.

Contrary to the hypothesis, intensive therapy spelled trouble. Patients with intensive glycemic control had an all-cause mortality rate of 27.5%, compared with a rate of 24.9% for patients in the conventional therapy group (P=.04, number needed to harm [NNH]=38). Severe hypoglycemia (glucose ≤40 mg/dL) occurred in 6.8% of those in the intensive therapy group, compared with 0.5% in the conventional therapy group (P=.03, NNH=16).

Most of the deaths in both groups occurred in the ICU or in the hospital. Deaths from cardiovascular causes were more common among those in the intensive therapy group. There were no significant differences in any other outcomes. The mean glucose level in the intensive therapy group was 118, vs 145 mg/dL in the conventional therapy group.

For multivariate and subgroup analyses, the patients were assigned strata (Canada or Australia/New Zealand; operative vs nonoperative admission) or classified into groups (traumatic vs atraumatic; diabetes vs no diabetes; corticosteroids in previous 72 hours or not; high vs low critical illness symptom severity) based on predefined characteristics. No subgroups had significantly improved outcomes with intensive therapy.¹

WHAT’S NEW: Now we know: Don’t go too low

This study, in contrast to a number of smaller studies of lower quality, demonstrates a higher all-cause mortality rate at 90 days for critically ill patients receiving intensive glucose therapy. It is now clear that, among critically ill hospitalized patients, aiming for intensive glucose control (81-108 mg/dL) is associated with an increased rate of severe hypoglycemic events and all-cause mortality at 90 days. The previously used goal of conventional therapy (≤180 mg/dL) is safer.

CAVEATS: Study population may not reflect primary care

There are 2 caveats to this study. The first is that because of the nature of the research, it was impossible to maintain blinding of the clinical staff to patient assignments. The second important caveat pertains to the severity of illness among participants in this multicenter study: Most of these patients were in ICUs at tertiary care medical centers and had an expected ICU length of stay of 3 or more days. Although many family physicians manage patients in ICUs, the patients randomized in this study may represent a sicker than average patient population for some hospitals.

CHALLENGES TO IMPLEMENTATION: Some may doubt validity of this outcome

Less aggressive glycemic control for critically ill patients should be easier to achieve, not more difficult. However, a change in glucose targets may require new admission order sets and, notably, reeducation of physicians and nurses who have been convinced by earlier studies that more intensive glucose control is superior.

Acknowledgments

The PURLs Surveillance System is supported in part by Grant Number UL1RR024999 from the National Center for Research Resources, a Clinical Translational Science Award to the University of Chicago. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center for Research Resources or the National Institutes of Health.

PURLs methodology

This study was selected and evaluated using FPIN’s Priority Updates from the Research Literature (PURL) Surveillance System methodology. The criteria and findings leading to the selection of this study as a PURL can be accessed at www.jfponline.com/purls.

Evidence summary

A variety of brief ADHD-specific rating scales are used for both parent and teacher assessment of child behavior. Rating scales are generally evaluated to establish mean scores for affected and unaffected children. Many scales publish such normative data in commercially available manuals. Some scales have been evaluated by 1 or more independent studies to compare children with and without ADHD. Rating scales have not been evaluated as a sole tool for the diagnosis of ADHD.

The test characteristics of a particular scale depend on the cut points for a positive or negative test. The usefulness of psychological tests in discriminating normal from abnormal behavior is often reported as “effect size.” The effect size is the difference in mean scores between 2 populations divided by an estimate of the individual standard deviation.¹ An effect size of 4.0 means that abnormal subjects and normal controls are separated 4 standard deviations and thus almost completely separated. An effect size of 1.0 shows significant overlap between the 2 populations. An effect size of 4.0 is roughly equivalent to a sensitivity and specificity of 97%. An effect size of 1.0 is roughly equal to a sensitivity and specificity of 71%.

Table 1 outlines the characteristics and effect size of several available brief ADHD-specific checklists.^2-4,6,11-13 Typically, the gold standard was a clinical diagnostic interview, usually conducted by a clinical psychologist, as well as supporting data from schools and parents.

TABLE
Descriptive characteristics of abbreviated symptom checklists for ADHD

Recommendations from others

The American Academy of Pediatrics states that the use of ADHD-specific checklists is a clinical option when evaluating children for ADHD. They caution that the ADHD scales may function less well in clinicians’ offices than suggested by reported effect size and, in addition, rating scales are subject to bias and may convey a false sense of validity. They also state that it is not known if these scales provide additional information beyond a careful clinical assessment.⁷

The Institute for Clinical Systems Improvement recommends use of at least 1 ADHD-specific rating scale to be administered to parents and teachers. This information should be used as part of the overall historical database for the child and should not be used as the sole criteria for diagnosis of ADHD.⁸

Many sources agree that ADHD-specific rating scales allow a rapid and consistent collection of information from multiple sources. However, the information they provide is necessary, but not sufficient, to make a definitive diagnosis of ADHD. In addition to assisting in diagnosis, checklists can be helpful in monitoring treatment changes once a diagnosis has been established.

Evidence summary

A variety of brief ADHD-specific rating scales are used for both parent and teacher assessment of child behavior. Rating scales are generally evaluated to establish mean scores for affected and unaffected children. Many scales publish such normative data in commercially available manuals. Some scales have been evaluated by 1 or more independent studies to compare children with and without ADHD. Rating scales have not been evaluated as a sole tool for the diagnosis of ADHD.

The test characteristics of a particular scale depend on the cut points for a positive or negative test. The usefulness of psychological tests in discriminating normal from abnormal behavior is often reported as “effect size.” The effect size is the difference in mean scores between 2 populations divided by an estimate of the individual standard deviation.¹ An effect size of 4.0 means that abnormal subjects and normal controls are separated 4 standard deviations and thus almost completely separated. An effect size of 1.0 shows significant overlap between the 2 populations. An effect size of 4.0 is roughly equivalent to a sensitivity and specificity of 97%. An effect size of 1.0 is roughly equal to a sensitivity and specificity of 71%.

Table 1 outlines the characteristics and effect size of several available brief ADHD-specific checklists.^2-4,6,11-13 Typically, the gold standard was a clinical diagnostic interview, usually conducted by a clinical psychologist, as well as supporting data from schools and parents.

TABLE
Descriptive characteristics of abbreviated symptom checklists for ADHD

Recommendations from others

The American Academy of Pediatrics states that the use of ADHD-specific checklists is a clinical option when evaluating children for ADHD. They caution that the ADHD scales may function less well in clinicians’ offices than suggested by reported effect size and, in addition, rating scales are subject to bias and may convey a false sense of validity. They also state that it is not known if these scales provide additional information beyond a careful clinical assessment.⁷

The Institute for Clinical Systems Improvement recommends use of at least 1 ADHD-specific rating scale to be administered to parents and teachers. This information should be used as part of the overall historical database for the child and should not be used as the sole criteria for diagnosis of ADHD.⁸

Many sources agree that ADHD-specific rating scales allow a rapid and consistent collection of information from multiple sources. However, the information they provide is necessary, but not sufficient, to make a definitive diagnosis of ADHD. In addition to assisting in diagnosis, checklists can be helpful in monitoring treatment changes once a diagnosis has been established.

Evidence summary

A variety of brief ADHD-specific rating scales are used for both parent and teacher assessment of child behavior. Rating scales are generally evaluated to establish mean scores for affected and unaffected children. Many scales publish such normative data in commercially available manuals. Some scales have been evaluated by 1 or more independent studies to compare children with and without ADHD. Rating scales have not been evaluated as a sole tool for the diagnosis of ADHD.

The test characteristics of a particular scale depend on the cut points for a positive or negative test. The usefulness of psychological tests in discriminating normal from abnormal behavior is often reported as “effect size.” The effect size is the difference in mean scores between 2 populations divided by an estimate of the individual standard deviation.¹ An effect size of 4.0 means that abnormal subjects and normal controls are separated 4 standard deviations and thus almost completely separated. An effect size of 1.0 shows significant overlap between the 2 populations. An effect size of 4.0 is roughly equivalent to a sensitivity and specificity of 97%. An effect size of 1.0 is roughly equal to a sensitivity and specificity of 71%.

Table 1 outlines the characteristics and effect size of several available brief ADHD-specific checklists.^2-4,6,11-13 Typically, the gold standard was a clinical diagnostic interview, usually conducted by a clinical psychologist, as well as supporting data from schools and parents.

TABLE
Descriptive characteristics of abbreviated symptom checklists for ADHD

Recommendations from others

The American Academy of Pediatrics states that the use of ADHD-specific checklists is a clinical option when evaluating children for ADHD. They caution that the ADHD scales may function less well in clinicians’ offices than suggested by reported effect size and, in addition, rating scales are subject to bias and may convey a false sense of validity. They also state that it is not known if these scales provide additional information beyond a careful clinical assessment.⁷

The Institute for Clinical Systems Improvement recommends use of at least 1 ADHD-specific rating scale to be administered to parents and teachers. This information should be used as part of the overall historical database for the child and should not be used as the sole criteria for diagnosis of ADHD.⁸

Many sources agree that ADHD-specific rating scales allow a rapid and consistent collection of information from multiple sources. However, the information they provide is necessary, but not sufficient, to make a definitive diagnosis of ADHD. In addition to assisting in diagnosis, checklists can be helpful in monitoring treatment changes once a diagnosis has been established.