News

Race, Sex Affect Congenital Heart Surgery Outcomes


 

References

FT. LAUDERDALE, FLA. – Sex and race appear to play a role in outcomes following congenital heart surgery in children and adolescents, according to a new analysis of data from almost 21,000 patients.

Black patients had significantly greater rates of mortality and complications and a significantly longer length of postoperative stay than other races, while female patients had a significantly shorter length of stay than males, Dr. Daniel J. DiBardino reported at the annual meeting of the Society of Thoracic Surgeons.

"The analysis of demographic and clinical data from nearly 21,000 patients in the congenital heart surgery database revealed important associations between gender, race, and outcome," said Dr. DiBardino, who is a cardiac surgeon at the Blair E. Batson Children’s Hospital in Jackson, Miss.

Dr. DiBardino’s study was chosen as a 2011 Richard E. Clark Paper by the Society of Thoracic Surgeons.

The researchers used data from the Society of Thoracic Surgeons Congenital Heart Surgery Database (STS-CHSD). Patients were included in the analysis if they were less than 18 years of age and had undergone cardiac surgery between 2007 and 2009.

Exclusion criteria included centers with more than 15% of data missing for key variables and centers with very small samples (less than five cases).

Data collection included demographics (age, sex, weight, and race) and preoperative data (noncardiac/genetic abnormalities and STS-defined risk factors). Race was classified as white, black, Hispanic, and other.

Operations were classified by STAT Mortality category, which is "a complexity stratification tool based on empiric data from 80,000 cases in STS and EACTS (European Association for Cardio-Thoracic Surgery) databases," said Dr. DiBardino.

The researchers looked at hospital mortality, postoperative length of stay, and complications. Multivariable analyses included dichotomous variables (mortality, complications) and a continuous variable (postoperative length of stay). Models were adjusted for age, weight, noncardiac/genetic abnormalities, any other STS preoperative risk factor, and STAT Mortality category.

In all, 20,399 patients were included from 49 centers. Of these, 54% were male. In terms of race, 55% were white, 17% were black, 16% were Hispanic, and 12% were other.

Based on unadjusted outcomes, there were no differences between the sexes for in-hospital mortality or complications. However, females had significantly shorter postoperative stays. In terms of race, white patients had significantly lower mortality, shorter length of stay, and fewer complications than any of the other racial groups.

In the adjusted multivariate analysis, there was no difference for mortality between the sexes. However, black patients had a significantly greater mortality risk with an odds ratio of 1.67.

Females did have a significantly shorter mean length of stay – 0.8 fewer days. In terms of race, black patients had a significantly longer mean length of stay by 2.4 hospital days, compared with white patients. Hispanic patients also had a significantly longer mean length of stay by almost 1 hospital day.

There was no difference between the sexes in terms of the occurrence of complications. In terms of race, "black patients experienced significantly more complications than other races with an odds ratio of 1.15," according to Dr. DiBardino.

The study is unique with the respect to the use of multivariable models. The researchers measured the association of sex and race with outcomes within each center and then combined the results, in order to mitigate the potential center effects.

"Our results cannot be explained by the possibility that patients of certain races might be disproportionately treated at centers with poorer outcomes in general."

The evaluation of complex relationships between clinical variables and socioeconomic and other factors affecting health care remains a significant challenge.

Since some pertinent socioeconomic data are not collected in the STS-CHSD, an analysis of a linked data set, which capitalizes on the strengths of both the CHSD and those of an administrative claims data set may be the next logical step, said Dr. DiBardino.

Dr. DiBardino and his coinvestigators reported that they have no relevant disclosures.