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Lora T. McGlade is editor of GI & Hepatology News and The New Gastroenterologist; she joined the company in 2013. Before that she worked for the company as a freelancer for several years; did bacterial genetic and murine oncogenetic research at NIH; and was a technical editor at the American Journal of Clinical Nutrition. She earned a BS in biological sciences from Cornell University, Ithaca, N.Y., and an MS in journalism from Syracuse (N.Y.) University.
Hyperandrogenic PCOS Linked to Lower Pregnancy and Live Birth Rates
TOPLINE:
Women with hyperandrogenic polycystic ovary syndrome (PCOS) have lower pregnancy (29.9%) and live birth rates (20.1%) than those with nonhyperandrogenic PCOS (40.2% and 33.1%, respectively).
METHODOLOGY:
- Researchers conducted a retrospective cohort study of 1376 participants from the PPCOS I and II trials, all meeting National Institutes of Health diagnostic criteria for PCOS.
- Participants were categorized into hyperandrogenic (A and B) and nonhyperandrogenic (D) PCOS phenotypes on the basis of medical interviews, demographics, physical examinations, and laboratory data.
- Outcomes of interest included clinical pregnancy, pregnancy loss, live birth, obstetric complications, and neonatal outcomes.
- Fasting blood samples were analyzed for hormonal assays, and Homeostatic Model Assessment for Insulin Resistance scores were calculated using fasting glucose and insulin values.
TAKEAWAY:
- Participants with hyperandrogenic PCOS had higher body mass index (35.5 ± 8.9 vs 31.9 ± 9.3; P < .001) and fasting insulin levels (21.6 ± 27.7 vs 14.7 ± 15.0 μIU/mL; P < .001) than those with nonhyperandrogenic PCOS.
- Participants with hyperandrogenic PCOS had lower odds of achieving pregnancy (odds ratio [OR], 0.63; 95% CI, 0.44-0.92) and live birth (OR, 0.51; 95% CI, 0.34-0.76) than those with nonhyperandrogenic PCOS.
- No significant differences were found in pregnancy loss rates (23.9% vs 32.3%, P = .06) or neonatal outcomes between the two groups.
- The study lacked the power to detect differences in neonatal outcomes because of the low prevalence of these outcomes.
IN PRACTICE:
“Patients with nonhyperandrogenic PCOS may represent a different disease process with unique morbidities and outcomes and could be counseled differently than hyperandrogenic PCOS,” wrote the authors of the study.
SOURCE:
The study was led by Jessica L. Chan, MD, MSCE, Cedars-Sinai Medical Center in Los Angeles, California. It was published online in Obstetrics & Gynecology.
LIMITATIONS:
The primary limitation of this study was that it is a secondary analysis of previously collected randomized controlled trial data, which may affect the availability of certain information. Additionally, the lower number of participants in the nonhyperandrogenic PCOS group could affect the power of the results. The study was underpowered to detect statistically significant differences in neonatal outcomes because of their low prevalence.
DISCLOSURES:
The study was supported by a grant from the ASRM/NICHD/Duke Clinical Research/Reproductive Scientist Training Program. One coauthor disclosed receiving payments from Celmatix, Ferring Pharmaceuticals, Exeltis, Organon, and Monsanto; another disclosed receiving payments from Ferring Pharmaceuticals. Additional disclosures are noted in the original article.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
TOPLINE:
Women with hyperandrogenic polycystic ovary syndrome (PCOS) have lower pregnancy (29.9%) and live birth rates (20.1%) than those with nonhyperandrogenic PCOS (40.2% and 33.1%, respectively).
METHODOLOGY:
- Researchers conducted a retrospective cohort study of 1376 participants from the PPCOS I and II trials, all meeting National Institutes of Health diagnostic criteria for PCOS.
- Participants were categorized into hyperandrogenic (A and B) and nonhyperandrogenic (D) PCOS phenotypes on the basis of medical interviews, demographics, physical examinations, and laboratory data.
- Outcomes of interest included clinical pregnancy, pregnancy loss, live birth, obstetric complications, and neonatal outcomes.
- Fasting blood samples were analyzed for hormonal assays, and Homeostatic Model Assessment for Insulin Resistance scores were calculated using fasting glucose and insulin values.
TAKEAWAY:
- Participants with hyperandrogenic PCOS had higher body mass index (35.5 ± 8.9 vs 31.9 ± 9.3; P < .001) and fasting insulin levels (21.6 ± 27.7 vs 14.7 ± 15.0 μIU/mL; P < .001) than those with nonhyperandrogenic PCOS.
- Participants with hyperandrogenic PCOS had lower odds of achieving pregnancy (odds ratio [OR], 0.63; 95% CI, 0.44-0.92) and live birth (OR, 0.51; 95% CI, 0.34-0.76) than those with nonhyperandrogenic PCOS.
- No significant differences were found in pregnancy loss rates (23.9% vs 32.3%, P = .06) or neonatal outcomes between the two groups.
- The study lacked the power to detect differences in neonatal outcomes because of the low prevalence of these outcomes.
IN PRACTICE:
“Patients with nonhyperandrogenic PCOS may represent a different disease process with unique morbidities and outcomes and could be counseled differently than hyperandrogenic PCOS,” wrote the authors of the study.
SOURCE:
The study was led by Jessica L. Chan, MD, MSCE, Cedars-Sinai Medical Center in Los Angeles, California. It was published online in Obstetrics & Gynecology.
LIMITATIONS:
The primary limitation of this study was that it is a secondary analysis of previously collected randomized controlled trial data, which may affect the availability of certain information. Additionally, the lower number of participants in the nonhyperandrogenic PCOS group could affect the power of the results. The study was underpowered to detect statistically significant differences in neonatal outcomes because of their low prevalence.
DISCLOSURES:
The study was supported by a grant from the ASRM/NICHD/Duke Clinical Research/Reproductive Scientist Training Program. One coauthor disclosed receiving payments from Celmatix, Ferring Pharmaceuticals, Exeltis, Organon, and Monsanto; another disclosed receiving payments from Ferring Pharmaceuticals. Additional disclosures are noted in the original article.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
TOPLINE:
Women with hyperandrogenic polycystic ovary syndrome (PCOS) have lower pregnancy (29.9%) and live birth rates (20.1%) than those with nonhyperandrogenic PCOS (40.2% and 33.1%, respectively).
METHODOLOGY:
- Researchers conducted a retrospective cohort study of 1376 participants from the PPCOS I and II trials, all meeting National Institutes of Health diagnostic criteria for PCOS.
- Participants were categorized into hyperandrogenic (A and B) and nonhyperandrogenic (D) PCOS phenotypes on the basis of medical interviews, demographics, physical examinations, and laboratory data.
- Outcomes of interest included clinical pregnancy, pregnancy loss, live birth, obstetric complications, and neonatal outcomes.
- Fasting blood samples were analyzed for hormonal assays, and Homeostatic Model Assessment for Insulin Resistance scores were calculated using fasting glucose and insulin values.
TAKEAWAY:
- Participants with hyperandrogenic PCOS had higher body mass index (35.5 ± 8.9 vs 31.9 ± 9.3; P < .001) and fasting insulin levels (21.6 ± 27.7 vs 14.7 ± 15.0 μIU/mL; P < .001) than those with nonhyperandrogenic PCOS.
- Participants with hyperandrogenic PCOS had lower odds of achieving pregnancy (odds ratio [OR], 0.63; 95% CI, 0.44-0.92) and live birth (OR, 0.51; 95% CI, 0.34-0.76) than those with nonhyperandrogenic PCOS.
- No significant differences were found in pregnancy loss rates (23.9% vs 32.3%, P = .06) or neonatal outcomes between the two groups.
- The study lacked the power to detect differences in neonatal outcomes because of the low prevalence of these outcomes.
IN PRACTICE:
“Patients with nonhyperandrogenic PCOS may represent a different disease process with unique morbidities and outcomes and could be counseled differently than hyperandrogenic PCOS,” wrote the authors of the study.
SOURCE:
The study was led by Jessica L. Chan, MD, MSCE, Cedars-Sinai Medical Center in Los Angeles, California. It was published online in Obstetrics & Gynecology.
LIMITATIONS:
The primary limitation of this study was that it is a secondary analysis of previously collected randomized controlled trial data, which may affect the availability of certain information. Additionally, the lower number of participants in the nonhyperandrogenic PCOS group could affect the power of the results. The study was underpowered to detect statistically significant differences in neonatal outcomes because of their low prevalence.
DISCLOSURES:
The study was supported by a grant from the ASRM/NICHD/Duke Clinical Research/Reproductive Scientist Training Program. One coauthor disclosed receiving payments from Celmatix, Ferring Pharmaceuticals, Exeltis, Organon, and Monsanto; another disclosed receiving payments from Ferring Pharmaceuticals. Additional disclosures are noted in the original article.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
Does Preconception BMI Affect Time to Pregnancy and Miscarriage Risk?
TOPLINE:
Higher body mass index (BMI) in both partners is linked to lower fecundability and increased subfertility. Overweight and obesity in women are associated with higher odds of miscarriage.
METHODOLOGY:
- Researchers conducted a population-based prospective cohort study in Rotterdam, the Netherlands, from August 9, 2017, to July 1, 2021.
- A total of 3604 women and their partners were included, with follow-up until birth.
- BMI was measured in preconception or early pregnancy, and outcomes included fecundability, subfertility, and miscarriage.
- Fecundability was defined as the probability of conceiving within 1 month and subfertility as time to pregnancy or duration of actively pursuing pregnancy of more than 12 months or use of assisted reproductive technology.
- Miscarriage was defined as pregnancy loss before 22 weeks of gestation.
TAKEAWAY:
- Higher BMI in women and men was associated with lower fecundability: For every unit increase in BMI, fecundability decreased (women, 0.98; 95% CI, 0.97-0.99; men, 0.99; 95% CI, 0.98-1.00).
- Women with overweight (0.88; 95% CI, 0.80-0.98) and obesity (0.72; 95% CI, 0.63-0.82) had lower fecundability than women with normal weight.
- Overweight (1.35; 95% CI, 1.11-1.63) and obesity (1.67; 95% CI, 1.30-2.13) in women were associated with increased odds of subfertility.
- Obesity in men was associated with increased odds of subfertility (1.69; 95% CI, 1.24-2.31).
IN PRACTICE:
“We observed in this cohort study that BMI outside of the normal category in women and men was associated with lower fecundability, subfertility, and increased odds of miscarriage. Optimizing BMI from the preconception period onward in women and men might be an important strategy to improve fertility and pregnancy outcomes,” wrote the authors of the study.
SOURCE:
The study was led by Aline J. Boxem, MD, and Vincent W. V. Jaddoe, MD, PhD, The Generation R Study Group, Erasmus University Medical Centre in Rotterdam, the Netherlands. It was published online in JAMA Network Open.
LIMITATIONS:
The study’s generalizability may be affected by differences between included and excluded participants, who were younger and had a higher BMI. The accuracy of time-to-pregnancy duration may have been impacted by retrospectively answered questionnaires. Residual confounding might still be an issue due to the observational nature of the study.
DISCLOSURES:
Dr. Boxem and Dr. Jaddoe disclosed receiving grants from the Erasmus University Medical Centre, the Erasmus University Rotterdam, and the Netherlands Organisation for Health Research and Development. Additional disclosures are noted in the original article.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
TOPLINE:
Higher body mass index (BMI) in both partners is linked to lower fecundability and increased subfertility. Overweight and obesity in women are associated with higher odds of miscarriage.
METHODOLOGY:
- Researchers conducted a population-based prospective cohort study in Rotterdam, the Netherlands, from August 9, 2017, to July 1, 2021.
- A total of 3604 women and their partners were included, with follow-up until birth.
- BMI was measured in preconception or early pregnancy, and outcomes included fecundability, subfertility, and miscarriage.
- Fecundability was defined as the probability of conceiving within 1 month and subfertility as time to pregnancy or duration of actively pursuing pregnancy of more than 12 months or use of assisted reproductive technology.
- Miscarriage was defined as pregnancy loss before 22 weeks of gestation.
TAKEAWAY:
- Higher BMI in women and men was associated with lower fecundability: For every unit increase in BMI, fecundability decreased (women, 0.98; 95% CI, 0.97-0.99; men, 0.99; 95% CI, 0.98-1.00).
- Women with overweight (0.88; 95% CI, 0.80-0.98) and obesity (0.72; 95% CI, 0.63-0.82) had lower fecundability than women with normal weight.
- Overweight (1.35; 95% CI, 1.11-1.63) and obesity (1.67; 95% CI, 1.30-2.13) in women were associated with increased odds of subfertility.
- Obesity in men was associated with increased odds of subfertility (1.69; 95% CI, 1.24-2.31).
IN PRACTICE:
“We observed in this cohort study that BMI outside of the normal category in women and men was associated with lower fecundability, subfertility, and increased odds of miscarriage. Optimizing BMI from the preconception period onward in women and men might be an important strategy to improve fertility and pregnancy outcomes,” wrote the authors of the study.
SOURCE:
The study was led by Aline J. Boxem, MD, and Vincent W. V. Jaddoe, MD, PhD, The Generation R Study Group, Erasmus University Medical Centre in Rotterdam, the Netherlands. It was published online in JAMA Network Open.
LIMITATIONS:
The study’s generalizability may be affected by differences between included and excluded participants, who were younger and had a higher BMI. The accuracy of time-to-pregnancy duration may have been impacted by retrospectively answered questionnaires. Residual confounding might still be an issue due to the observational nature of the study.
DISCLOSURES:
Dr. Boxem and Dr. Jaddoe disclosed receiving grants from the Erasmus University Medical Centre, the Erasmus University Rotterdam, and the Netherlands Organisation for Health Research and Development. Additional disclosures are noted in the original article.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
TOPLINE:
Higher body mass index (BMI) in both partners is linked to lower fecundability and increased subfertility. Overweight and obesity in women are associated with higher odds of miscarriage.
METHODOLOGY:
- Researchers conducted a population-based prospective cohort study in Rotterdam, the Netherlands, from August 9, 2017, to July 1, 2021.
- A total of 3604 women and their partners were included, with follow-up until birth.
- BMI was measured in preconception or early pregnancy, and outcomes included fecundability, subfertility, and miscarriage.
- Fecundability was defined as the probability of conceiving within 1 month and subfertility as time to pregnancy or duration of actively pursuing pregnancy of more than 12 months or use of assisted reproductive technology.
- Miscarriage was defined as pregnancy loss before 22 weeks of gestation.
TAKEAWAY:
- Higher BMI in women and men was associated with lower fecundability: For every unit increase in BMI, fecundability decreased (women, 0.98; 95% CI, 0.97-0.99; men, 0.99; 95% CI, 0.98-1.00).
- Women with overweight (0.88; 95% CI, 0.80-0.98) and obesity (0.72; 95% CI, 0.63-0.82) had lower fecundability than women with normal weight.
- Overweight (1.35; 95% CI, 1.11-1.63) and obesity (1.67; 95% CI, 1.30-2.13) in women were associated with increased odds of subfertility.
- Obesity in men was associated with increased odds of subfertility (1.69; 95% CI, 1.24-2.31).
IN PRACTICE:
“We observed in this cohort study that BMI outside of the normal category in women and men was associated with lower fecundability, subfertility, and increased odds of miscarriage. Optimizing BMI from the preconception period onward in women and men might be an important strategy to improve fertility and pregnancy outcomes,” wrote the authors of the study.
SOURCE:
The study was led by Aline J. Boxem, MD, and Vincent W. V. Jaddoe, MD, PhD, The Generation R Study Group, Erasmus University Medical Centre in Rotterdam, the Netherlands. It was published online in JAMA Network Open.
LIMITATIONS:
The study’s generalizability may be affected by differences between included and excluded participants, who were younger and had a higher BMI. The accuracy of time-to-pregnancy duration may have been impacted by retrospectively answered questionnaires. Residual confounding might still be an issue due to the observational nature of the study.
DISCLOSURES:
Dr. Boxem and Dr. Jaddoe disclosed receiving grants from the Erasmus University Medical Centre, the Erasmus University Rotterdam, and the Netherlands Organisation for Health Research and Development. Additional disclosures are noted in the original article.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
Is Intravenous Iron More Effective Than Oral Iron for Anemia During Pregnancy?
TOPLINE:
Intravenous iron reduced iron deficiency more effectively than oral iron, which is often distasteful, among pregnant women in Nigeria. However, no significant difference was found in the prevalence of anemia or preterm birth between the two groups.
METHODOLOGY:
- A total of 1056 pregnant women aged 15-49 years with hemoglobin concentrations 10 g/dL at 20-32 weeks’ gestation were included in the trial.
- Participants were randomly assigned to receive either a single dose of intravenous ferric carboxymaltose (20 mg/kg to a maximum of 1000 mg) or oral ferrous sulphate (200 mg; 65 mg elemental iron) three times daily until 6 weeks postpartum.
- Primary outcomes were maternal anemia (hemoglobin, < 11 g/dL) at 36 weeks’ gestation and preterm birth before 37 weeks’ gestation.
- Secondary outcomes were iron deficiency, iron deficiency anemia, maternal depression, infections, immunization, and breastfeeding practices.
- The trial was conducted in 11 health facilities in Lagos and Kano, Nigeria, with follow-up visits at 2 weeks and 6 weeks postpartum.
TAKEAWAY:
- No significant difference was found in the prevalence of anemia at 36 weeks’ gestation between the intravenous and oral iron groups (58% vs 61%; P = .36).
- Intravenous iron was more effective at reducing iron deficiency (5% vs 16%; P = .0001) and iron deficiency anemia (2% vs 10%; P = .0001) at 36 weeks’ gestation.
- The incidence of preterm birth did not significantly differ between the intravenous and oral iron groups (14% vs 15%; P = .66).
- Intravenous iron led to a higher mean hemoglobin concentration from baseline to 4 weeks in both iron-deficient and non–iron-deficient subgroups.
IN PRACTICE:
“Although the effect on overall anaemia did not differ, intravenous iron reduced the prevalence of iron deficiency to a greater extent than oral iron and was considered to be safe. We recommend that intravenous iron be considered for anaemic pregnant women in Nigeria and similar settings,” wrote the authors of the study.
SOURCE:
This study was led by Bosede B. Afolabi, Department of Obstetrics and Gynaecology, Faculty of Clinical Sciences, College of Medicine, University of Lagos, Nigeria. It was published online in The Lancet Global Health.
LIMITATIONS:
The study’s sample size estimation assumed a 25% rate of preterm births, but the actual rate was only 14.5%, which potentially underpowered the study to measure this outcome. Most participants were enrolled after 20 weeks’ gestation, which limited the ability to explore the effect of treatment duration. The interpretation of postpartum hemorrhage was limited by the use of visual assessment to determine blood loss, which is subjective.
DISCLOSURES:
A coathor, Kristi S. Annerstedt, PhD, reported participation on the ALERT project Data Safety Monitoring Board. Additional disclosures are noted in the original article. The study was supported by grants from the Bill & Melinda Gates Foundation.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
TOPLINE:
Intravenous iron reduced iron deficiency more effectively than oral iron, which is often distasteful, among pregnant women in Nigeria. However, no significant difference was found in the prevalence of anemia or preterm birth between the two groups.
METHODOLOGY:
- A total of 1056 pregnant women aged 15-49 years with hemoglobin concentrations 10 g/dL at 20-32 weeks’ gestation were included in the trial.
- Participants were randomly assigned to receive either a single dose of intravenous ferric carboxymaltose (20 mg/kg to a maximum of 1000 mg) or oral ferrous sulphate (200 mg; 65 mg elemental iron) three times daily until 6 weeks postpartum.
- Primary outcomes were maternal anemia (hemoglobin, < 11 g/dL) at 36 weeks’ gestation and preterm birth before 37 weeks’ gestation.
- Secondary outcomes were iron deficiency, iron deficiency anemia, maternal depression, infections, immunization, and breastfeeding practices.
- The trial was conducted in 11 health facilities in Lagos and Kano, Nigeria, with follow-up visits at 2 weeks and 6 weeks postpartum.
TAKEAWAY:
- No significant difference was found in the prevalence of anemia at 36 weeks’ gestation between the intravenous and oral iron groups (58% vs 61%; P = .36).
- Intravenous iron was more effective at reducing iron deficiency (5% vs 16%; P = .0001) and iron deficiency anemia (2% vs 10%; P = .0001) at 36 weeks’ gestation.
- The incidence of preterm birth did not significantly differ between the intravenous and oral iron groups (14% vs 15%; P = .66).
- Intravenous iron led to a higher mean hemoglobin concentration from baseline to 4 weeks in both iron-deficient and non–iron-deficient subgroups.
IN PRACTICE:
“Although the effect on overall anaemia did not differ, intravenous iron reduced the prevalence of iron deficiency to a greater extent than oral iron and was considered to be safe. We recommend that intravenous iron be considered for anaemic pregnant women in Nigeria and similar settings,” wrote the authors of the study.
SOURCE:
This study was led by Bosede B. Afolabi, Department of Obstetrics and Gynaecology, Faculty of Clinical Sciences, College of Medicine, University of Lagos, Nigeria. It was published online in The Lancet Global Health.
LIMITATIONS:
The study’s sample size estimation assumed a 25% rate of preterm births, but the actual rate was only 14.5%, which potentially underpowered the study to measure this outcome. Most participants were enrolled after 20 weeks’ gestation, which limited the ability to explore the effect of treatment duration. The interpretation of postpartum hemorrhage was limited by the use of visual assessment to determine blood loss, which is subjective.
DISCLOSURES:
A coathor, Kristi S. Annerstedt, PhD, reported participation on the ALERT project Data Safety Monitoring Board. Additional disclosures are noted in the original article. The study was supported by grants from the Bill & Melinda Gates Foundation.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
TOPLINE:
Intravenous iron reduced iron deficiency more effectively than oral iron, which is often distasteful, among pregnant women in Nigeria. However, no significant difference was found in the prevalence of anemia or preterm birth between the two groups.
METHODOLOGY:
- A total of 1056 pregnant women aged 15-49 years with hemoglobin concentrations 10 g/dL at 20-32 weeks’ gestation were included in the trial.
- Participants were randomly assigned to receive either a single dose of intravenous ferric carboxymaltose (20 mg/kg to a maximum of 1000 mg) or oral ferrous sulphate (200 mg; 65 mg elemental iron) three times daily until 6 weeks postpartum.
- Primary outcomes were maternal anemia (hemoglobin, < 11 g/dL) at 36 weeks’ gestation and preterm birth before 37 weeks’ gestation.
- Secondary outcomes were iron deficiency, iron deficiency anemia, maternal depression, infections, immunization, and breastfeeding practices.
- The trial was conducted in 11 health facilities in Lagos and Kano, Nigeria, with follow-up visits at 2 weeks and 6 weeks postpartum.
TAKEAWAY:
- No significant difference was found in the prevalence of anemia at 36 weeks’ gestation between the intravenous and oral iron groups (58% vs 61%; P = .36).
- Intravenous iron was more effective at reducing iron deficiency (5% vs 16%; P = .0001) and iron deficiency anemia (2% vs 10%; P = .0001) at 36 weeks’ gestation.
- The incidence of preterm birth did not significantly differ between the intravenous and oral iron groups (14% vs 15%; P = .66).
- Intravenous iron led to a higher mean hemoglobin concentration from baseline to 4 weeks in both iron-deficient and non–iron-deficient subgroups.
IN PRACTICE:
“Although the effect on overall anaemia did not differ, intravenous iron reduced the prevalence of iron deficiency to a greater extent than oral iron and was considered to be safe. We recommend that intravenous iron be considered for anaemic pregnant women in Nigeria and similar settings,” wrote the authors of the study.
SOURCE:
This study was led by Bosede B. Afolabi, Department of Obstetrics and Gynaecology, Faculty of Clinical Sciences, College of Medicine, University of Lagos, Nigeria. It was published online in The Lancet Global Health.
LIMITATIONS:
The study’s sample size estimation assumed a 25% rate of preterm births, but the actual rate was only 14.5%, which potentially underpowered the study to measure this outcome. Most participants were enrolled after 20 weeks’ gestation, which limited the ability to explore the effect of treatment duration. The interpretation of postpartum hemorrhage was limited by the use of visual assessment to determine blood loss, which is subjective.
DISCLOSURES:
A coathor, Kristi S. Annerstedt, PhD, reported participation on the ALERT project Data Safety Monitoring Board. Additional disclosures are noted in the original article. The study was supported by grants from the Bill & Melinda Gates Foundation.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
Can AI Improve Cardiomyopathy Detection in Pregnant Women?
TOPLINE:
Artificial intelligence (AI)–guided screening using digital stethoscopes doubled the detection of left ventricular systolic dysfunction (LVSD) in pregnant and postpartum women in Nigeria. Cardiomyopathy during pregnancy and post partum is challenging to diagnose because of symptom overlap with normal pregnancy changes. AI-guided screening showed a significant improvement in diagnosis rates, compared with usual care.
METHODOLOGY:
- Researchers conducted an open-label, randomized clinical trial involving 1232 pregnant and postpartum women in Nigeria.
- Participants were randomized to either AI-guided screening using digital stethoscopes and 12-lead ECGs or usual care.
- The primary outcome was the identification of LVSD confirmed by echocardiography.
- Secondary outcomes were AI model performance across subgroups and the effectiveness of AI in identifying various levels of LVSD.
TAKEAWAY:
- AI-guided screening using digital stethoscopes detected LVSD in 4.1% of participants, compared with 2.0% of controls (P = .032).
- The 12-lead AI-ECG model detected LVSD in 3.4% of participants in the intervention arm, compared with 2.0% of those in the control arm (P = .125).
- No serious adverse events related to study participation were reported.
- The study highlighted the potential of AI-guided screening to improve the diagnosis of pregnancy-related cardiomyopathy.
IN PRACTICE:
“Delays in the diagnosis of cardiomyopathy during the peripartum period is associated with poorer outcomes as such, it is imperative that we are able to identify cardiac dysfunction early so that appropriate care can be initiated to reduce associated adverse maternal and infant outcomes,” wrote the authors of the study.
SOURCE:
This study was led by Demilade A. Adedinsewo, MBchB, Mayo Clinic in Jacksonville, Florida. It was published online in Nature Medicine.
LIMITATIONS:
The study’s pragmatic design and enrollment at teaching hospitals with echocardiography capabilities limited generalizability. Two thirds of participants were in the third trimester or postpartum at study entry, which limited follow-up visits. The study did not require completion of all seven visits, which led to potential attrition bias. The selected cutoff for LVSD (left ventricular ejection fraction < 50%) did not match the original model specifications, which potentially affected results.
DISCLOSURES:
Dr. Adedinsewo disclosed receiving grants from the Mayo Clinic BIRCWH program funded by the National Institutes of Health. Two coauthors reported holding patents for AI algorithms licensed to Anumana, AliveCor, and Eko Health. Additional disclosures are noted in the original article.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
TOPLINE:
Artificial intelligence (AI)–guided screening using digital stethoscopes doubled the detection of left ventricular systolic dysfunction (LVSD) in pregnant and postpartum women in Nigeria. Cardiomyopathy during pregnancy and post partum is challenging to diagnose because of symptom overlap with normal pregnancy changes. AI-guided screening showed a significant improvement in diagnosis rates, compared with usual care.
METHODOLOGY:
- Researchers conducted an open-label, randomized clinical trial involving 1232 pregnant and postpartum women in Nigeria.
- Participants were randomized to either AI-guided screening using digital stethoscopes and 12-lead ECGs or usual care.
- The primary outcome was the identification of LVSD confirmed by echocardiography.
- Secondary outcomes were AI model performance across subgroups and the effectiveness of AI in identifying various levels of LVSD.
TAKEAWAY:
- AI-guided screening using digital stethoscopes detected LVSD in 4.1% of participants, compared with 2.0% of controls (P = .032).
- The 12-lead AI-ECG model detected LVSD in 3.4% of participants in the intervention arm, compared with 2.0% of those in the control arm (P = .125).
- No serious adverse events related to study participation were reported.
- The study highlighted the potential of AI-guided screening to improve the diagnosis of pregnancy-related cardiomyopathy.
IN PRACTICE:
“Delays in the diagnosis of cardiomyopathy during the peripartum period is associated with poorer outcomes as such, it is imperative that we are able to identify cardiac dysfunction early so that appropriate care can be initiated to reduce associated adverse maternal and infant outcomes,” wrote the authors of the study.
SOURCE:
This study was led by Demilade A. Adedinsewo, MBchB, Mayo Clinic in Jacksonville, Florida. It was published online in Nature Medicine.
LIMITATIONS:
The study’s pragmatic design and enrollment at teaching hospitals with echocardiography capabilities limited generalizability. Two thirds of participants were in the third trimester or postpartum at study entry, which limited follow-up visits. The study did not require completion of all seven visits, which led to potential attrition bias. The selected cutoff for LVSD (left ventricular ejection fraction < 50%) did not match the original model specifications, which potentially affected results.
DISCLOSURES:
Dr. Adedinsewo disclosed receiving grants from the Mayo Clinic BIRCWH program funded by the National Institutes of Health. Two coauthors reported holding patents for AI algorithms licensed to Anumana, AliveCor, and Eko Health. Additional disclosures are noted in the original article.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
TOPLINE:
Artificial intelligence (AI)–guided screening using digital stethoscopes doubled the detection of left ventricular systolic dysfunction (LVSD) in pregnant and postpartum women in Nigeria. Cardiomyopathy during pregnancy and post partum is challenging to diagnose because of symptom overlap with normal pregnancy changes. AI-guided screening showed a significant improvement in diagnosis rates, compared with usual care.
METHODOLOGY:
- Researchers conducted an open-label, randomized clinical trial involving 1232 pregnant and postpartum women in Nigeria.
- Participants were randomized to either AI-guided screening using digital stethoscopes and 12-lead ECGs or usual care.
- The primary outcome was the identification of LVSD confirmed by echocardiography.
- Secondary outcomes were AI model performance across subgroups and the effectiveness of AI in identifying various levels of LVSD.
TAKEAWAY:
- AI-guided screening using digital stethoscopes detected LVSD in 4.1% of participants, compared with 2.0% of controls (P = .032).
- The 12-lead AI-ECG model detected LVSD in 3.4% of participants in the intervention arm, compared with 2.0% of those in the control arm (P = .125).
- No serious adverse events related to study participation were reported.
- The study highlighted the potential of AI-guided screening to improve the diagnosis of pregnancy-related cardiomyopathy.
IN PRACTICE:
“Delays in the diagnosis of cardiomyopathy during the peripartum period is associated with poorer outcomes as such, it is imperative that we are able to identify cardiac dysfunction early so that appropriate care can be initiated to reduce associated adverse maternal and infant outcomes,” wrote the authors of the study.
SOURCE:
This study was led by Demilade A. Adedinsewo, MBchB, Mayo Clinic in Jacksonville, Florida. It was published online in Nature Medicine.
LIMITATIONS:
The study’s pragmatic design and enrollment at teaching hospitals with echocardiography capabilities limited generalizability. Two thirds of participants were in the third trimester or postpartum at study entry, which limited follow-up visits. The study did not require completion of all seven visits, which led to potential attrition bias. The selected cutoff for LVSD (left ventricular ejection fraction < 50%) did not match the original model specifications, which potentially affected results.
DISCLOSURES:
Dr. Adedinsewo disclosed receiving grants from the Mayo Clinic BIRCWH program funded by the National Institutes of Health. Two coauthors reported holding patents for AI algorithms licensed to Anumana, AliveCor, and Eko Health. Additional disclosures are noted in the original article.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
Are Pharmacy Deserts Worsening Health Disparities?
TOPLINE:
Pharmacy closures in the United States are creating “pharmacy deserts,” disproportionately affecting socially vulnerable communities. High social vulnerability and low primary care practitioner (PCP) density are linked to increased pharmacy desert density.
METHODOLOGY:
- Data through 2020 on communities located 10 or more miles from the nearest retail pharmacy were sourced from TelePharm Map.
- Counties were stratified as having a high pharmacy desert density if the number of pharmacy deserts per 1000 inhabitants was in the 80th percentile or higher.
- Social vulnerability index and healthcare practitioner data were obtained from the Agency for Toxic Substances and Disease Registry and the Area Health Resources Files.
- PCP density was calculated as the number of PCPs per 10,000 inhabitants.
- A total of 3143 counties were analyzed, with 1447 (46%) having at least one pharmacy desert.
TAKEAWAY:
- Counties with a high pharmacy desert density had a higher social vulnerability index than those with a low pharmacy desert density (P = .006).
- Areas with a high pharmacy desert density had lower median PCP density than those with low or no pharmacy desert density (P < .001).
- High social vulnerability index (odds ratio [OR], 1.35; 95% CI, 1.07-1.70; P = .01) and low PCP density (OR, 2.27; 95% CI, 1.80-2.86; P < .001) were associated with a higher likelihood for a county to have a high pharmacy desert density.
- Pharmacy closures are leaving more individuals without easy access to medications, with disproportionate consequences for certain communities.
IN PRACTICE:
“As high pharmacy desert density counties also have a lower PCP density, patients residing in these regions face increased barriers to accessing primary healthcare needs,” wrote the authors of the study.
SOURCE:
The study was led by Giovanni Catalano, MD, Muhammad Muntazir Mehdi Khan, MBBS, and Timothy M. Pawlik, MD, PhD, MPH, MTS, MBA, Department of Surgery, The Ohio State University Wexner Medical Center in Columbus, Ohio. It was published online in JAMA Network Open.
LIMITATIONS:
The cross-sectional design of the study limited the ability to draw causal inferences. The study relied on public county-level data, which may not have captured all relevant variables. The use of the social vulnerability index and PCP density as proxies did not fully represent the complexity of pharmacy access issues. The study’s findings were not generalizable to regions outside the United States.
DISCLOSURES:
No relevant conflicts of interest were disclosed by the authors. Additional disclosures are noted in the original article.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
TOPLINE:
Pharmacy closures in the United States are creating “pharmacy deserts,” disproportionately affecting socially vulnerable communities. High social vulnerability and low primary care practitioner (PCP) density are linked to increased pharmacy desert density.
METHODOLOGY:
- Data through 2020 on communities located 10 or more miles from the nearest retail pharmacy were sourced from TelePharm Map.
- Counties were stratified as having a high pharmacy desert density if the number of pharmacy deserts per 1000 inhabitants was in the 80th percentile or higher.
- Social vulnerability index and healthcare practitioner data were obtained from the Agency for Toxic Substances and Disease Registry and the Area Health Resources Files.
- PCP density was calculated as the number of PCPs per 10,000 inhabitants.
- A total of 3143 counties were analyzed, with 1447 (46%) having at least one pharmacy desert.
TAKEAWAY:
- Counties with a high pharmacy desert density had a higher social vulnerability index than those with a low pharmacy desert density (P = .006).
- Areas with a high pharmacy desert density had lower median PCP density than those with low or no pharmacy desert density (P < .001).
- High social vulnerability index (odds ratio [OR], 1.35; 95% CI, 1.07-1.70; P = .01) and low PCP density (OR, 2.27; 95% CI, 1.80-2.86; P < .001) were associated with a higher likelihood for a county to have a high pharmacy desert density.
- Pharmacy closures are leaving more individuals without easy access to medications, with disproportionate consequences for certain communities.
IN PRACTICE:
“As high pharmacy desert density counties also have a lower PCP density, patients residing in these regions face increased barriers to accessing primary healthcare needs,” wrote the authors of the study.
SOURCE:
The study was led by Giovanni Catalano, MD, Muhammad Muntazir Mehdi Khan, MBBS, and Timothy M. Pawlik, MD, PhD, MPH, MTS, MBA, Department of Surgery, The Ohio State University Wexner Medical Center in Columbus, Ohio. It was published online in JAMA Network Open.
LIMITATIONS:
The cross-sectional design of the study limited the ability to draw causal inferences. The study relied on public county-level data, which may not have captured all relevant variables. The use of the social vulnerability index and PCP density as proxies did not fully represent the complexity of pharmacy access issues. The study’s findings were not generalizable to regions outside the United States.
DISCLOSURES:
No relevant conflicts of interest were disclosed by the authors. Additional disclosures are noted in the original article.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
TOPLINE:
Pharmacy closures in the United States are creating “pharmacy deserts,” disproportionately affecting socially vulnerable communities. High social vulnerability and low primary care practitioner (PCP) density are linked to increased pharmacy desert density.
METHODOLOGY:
- Data through 2020 on communities located 10 or more miles from the nearest retail pharmacy were sourced from TelePharm Map.
- Counties were stratified as having a high pharmacy desert density if the number of pharmacy deserts per 1000 inhabitants was in the 80th percentile or higher.
- Social vulnerability index and healthcare practitioner data were obtained from the Agency for Toxic Substances and Disease Registry and the Area Health Resources Files.
- PCP density was calculated as the number of PCPs per 10,000 inhabitants.
- A total of 3143 counties were analyzed, with 1447 (46%) having at least one pharmacy desert.
TAKEAWAY:
- Counties with a high pharmacy desert density had a higher social vulnerability index than those with a low pharmacy desert density (P = .006).
- Areas with a high pharmacy desert density had lower median PCP density than those with low or no pharmacy desert density (P < .001).
- High social vulnerability index (odds ratio [OR], 1.35; 95% CI, 1.07-1.70; P = .01) and low PCP density (OR, 2.27; 95% CI, 1.80-2.86; P < .001) were associated with a higher likelihood for a county to have a high pharmacy desert density.
- Pharmacy closures are leaving more individuals without easy access to medications, with disproportionate consequences for certain communities.
IN PRACTICE:
“As high pharmacy desert density counties also have a lower PCP density, patients residing in these regions face increased barriers to accessing primary healthcare needs,” wrote the authors of the study.
SOURCE:
The study was led by Giovanni Catalano, MD, Muhammad Muntazir Mehdi Khan, MBBS, and Timothy M. Pawlik, MD, PhD, MPH, MTS, MBA, Department of Surgery, The Ohio State University Wexner Medical Center in Columbus, Ohio. It was published online in JAMA Network Open.
LIMITATIONS:
The cross-sectional design of the study limited the ability to draw causal inferences. The study relied on public county-level data, which may not have captured all relevant variables. The use of the social vulnerability index and PCP density as proxies did not fully represent the complexity of pharmacy access issues. The study’s findings were not generalizable to regions outside the United States.
DISCLOSURES:
No relevant conflicts of interest were disclosed by the authors. Additional disclosures are noted in the original article.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
MRI-Derived Abdominal Adipose Tissue Linked to Chronic Musculoskeletal Pain
TOPLINE:
MRI-derived abdominal adipose tissue is linked to chronic musculoskeletal pain in multiple sites. The association is stronger in women, suggesting sex differences in fat distribution and hormones.
METHODOLOGY:
- Researchers used data from the UK Biobank, a large population-based cohort study, to investigate the associations between MRI-measured abdominal adipose tissue and chronic musculoskeletal pain.
- A total of 32,409 participants (50.8% women; mean age, 55.0 ± 7.4 years) were included in the analysis, with abdominal MRI scans performed at two imaging visits.
- Pain in the neck/shoulder, back, hip, knee, or “all over the body” was assessed, and participants were categorized based on the number of chronic pain sites.
- Mixed-effects ordinal, multinomial, and logistic regression models were used to analyze the associations between visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and their ratio with chronic pain.
TAKEAWAY:
- According to the authors, there was a dose-response association between VAT, SAT, and their ratio with the number of chronic pain sites in both women and men.
- Higher levels of abdominal adipose tissue were associated with greater odds of reporting chronic pain in both sexes, with effect estimates being relatively larger in women.
- The researchers found that the VAT/SAT ratio was associated with the number of chronic pain sites and chronic pain in both sexes, reflecting differences in fat distribution and hormones.
- The study suggested that excessive abdominal adipose tissue may be involved in the pathogenesis of multisite and widespread chronic musculoskeletal pain.
IN PRACTICE:
“Abdominal adipose tissue was associated with chronic musculoskeletal pain, suggesting that excessive and ectopic fat depositions may be involved in the pathogenesis of multisite and widespread chronic musculoskeletal pain,” wrote the authors of the study.
SOURCE:
This study was led by Zemene Demelash Kifle, University of Tasmania Menzies Institute for Medical Research in Hobart, Australia. It was published online in Regional Anesthesia & Pain Medicine.
LIMITATIONS:
The study’s limitations included the use of a pain questionnaire that did not assess pain severity, which limited the ability to examine the relationship between fat measures and pain severity. Additionally, MRI was conducted on only two occasions, which may have not captured patterns and fluctuations in chronic pain sites. The relatively small size of the imaging sample, compared with the original baseline sample limited the generalizability of the findings. The predominant White ethnicity of participants also limited the generalizability to diverse populations.
DISCLOSURES:
The study was supported by grants from the Australian National Health and Medical Research Council (NHMRC). Mr. Kifle disclosed receiving grants from the Australian NHMRC. Additional disclosures are noted in the original article.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
TOPLINE:
MRI-derived abdominal adipose tissue is linked to chronic musculoskeletal pain in multiple sites. The association is stronger in women, suggesting sex differences in fat distribution and hormones.
METHODOLOGY:
- Researchers used data from the UK Biobank, a large population-based cohort study, to investigate the associations between MRI-measured abdominal adipose tissue and chronic musculoskeletal pain.
- A total of 32,409 participants (50.8% women; mean age, 55.0 ± 7.4 years) were included in the analysis, with abdominal MRI scans performed at two imaging visits.
- Pain in the neck/shoulder, back, hip, knee, or “all over the body” was assessed, and participants were categorized based on the number of chronic pain sites.
- Mixed-effects ordinal, multinomial, and logistic regression models were used to analyze the associations between visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and their ratio with chronic pain.
TAKEAWAY:
- According to the authors, there was a dose-response association between VAT, SAT, and their ratio with the number of chronic pain sites in both women and men.
- Higher levels of abdominal adipose tissue were associated with greater odds of reporting chronic pain in both sexes, with effect estimates being relatively larger in women.
- The researchers found that the VAT/SAT ratio was associated with the number of chronic pain sites and chronic pain in both sexes, reflecting differences in fat distribution and hormones.
- The study suggested that excessive abdominal adipose tissue may be involved in the pathogenesis of multisite and widespread chronic musculoskeletal pain.
IN PRACTICE:
“Abdominal adipose tissue was associated with chronic musculoskeletal pain, suggesting that excessive and ectopic fat depositions may be involved in the pathogenesis of multisite and widespread chronic musculoskeletal pain,” wrote the authors of the study.
SOURCE:
This study was led by Zemene Demelash Kifle, University of Tasmania Menzies Institute for Medical Research in Hobart, Australia. It was published online in Regional Anesthesia & Pain Medicine.
LIMITATIONS:
The study’s limitations included the use of a pain questionnaire that did not assess pain severity, which limited the ability to examine the relationship between fat measures and pain severity. Additionally, MRI was conducted on only two occasions, which may have not captured patterns and fluctuations in chronic pain sites. The relatively small size of the imaging sample, compared with the original baseline sample limited the generalizability of the findings. The predominant White ethnicity of participants also limited the generalizability to diverse populations.
DISCLOSURES:
The study was supported by grants from the Australian National Health and Medical Research Council (NHMRC). Mr. Kifle disclosed receiving grants from the Australian NHMRC. Additional disclosures are noted in the original article.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
TOPLINE:
MRI-derived abdominal adipose tissue is linked to chronic musculoskeletal pain in multiple sites. The association is stronger in women, suggesting sex differences in fat distribution and hormones.
METHODOLOGY:
- Researchers used data from the UK Biobank, a large population-based cohort study, to investigate the associations between MRI-measured abdominal adipose tissue and chronic musculoskeletal pain.
- A total of 32,409 participants (50.8% women; mean age, 55.0 ± 7.4 years) were included in the analysis, with abdominal MRI scans performed at two imaging visits.
- Pain in the neck/shoulder, back, hip, knee, or “all over the body” was assessed, and participants were categorized based on the number of chronic pain sites.
- Mixed-effects ordinal, multinomial, and logistic regression models were used to analyze the associations between visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and their ratio with chronic pain.
TAKEAWAY:
- According to the authors, there was a dose-response association between VAT, SAT, and their ratio with the number of chronic pain sites in both women and men.
- Higher levels of abdominal adipose tissue were associated with greater odds of reporting chronic pain in both sexes, with effect estimates being relatively larger in women.
- The researchers found that the VAT/SAT ratio was associated with the number of chronic pain sites and chronic pain in both sexes, reflecting differences in fat distribution and hormones.
- The study suggested that excessive abdominal adipose tissue may be involved in the pathogenesis of multisite and widespread chronic musculoskeletal pain.
IN PRACTICE:
“Abdominal adipose tissue was associated with chronic musculoskeletal pain, suggesting that excessive and ectopic fat depositions may be involved in the pathogenesis of multisite and widespread chronic musculoskeletal pain,” wrote the authors of the study.
SOURCE:
This study was led by Zemene Demelash Kifle, University of Tasmania Menzies Institute for Medical Research in Hobart, Australia. It was published online in Regional Anesthesia & Pain Medicine.
LIMITATIONS:
The study’s limitations included the use of a pain questionnaire that did not assess pain severity, which limited the ability to examine the relationship between fat measures and pain severity. Additionally, MRI was conducted on only two occasions, which may have not captured patterns and fluctuations in chronic pain sites. The relatively small size of the imaging sample, compared with the original baseline sample limited the generalizability of the findings. The predominant White ethnicity of participants also limited the generalizability to diverse populations.
DISCLOSURES:
The study was supported by grants from the Australian National Health and Medical Research Council (NHMRC). Mr. Kifle disclosed receiving grants from the Australian NHMRC. Additional disclosures are noted in the original article.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.