Association of Race/Ethnicity With Very Preterm Neonatal Morbidities
Bibliographic record
Abstract
Importance: Severe morbidity in very preterm infants is associated with profound clinical implications on development and life-course health. However, studies of racial/ethnic disparities in severe neonatal morbidities are scant and suggest that these disparities are modest or null, which may be an underestimation resulting from the analytic approach used. Objective: To estimate racial/ethnic differences in severe morbidities among very preterm infants. Design, Setting, and Participants: This population-based retrospective cohort study was conducted in New York City, New York, using linked birth certificate, mortality data, and hospital discharge data from January 1, 2010, through December 31, 2014. Infants born before 24 weeks' gestation, with congenital anomalies, and with missing data were excluded. Racial/ethnic disparities in very preterm birth morbidities were estimated through 2 approaches, conventional analysis and fetuses-at-risk analysis. The conventional analysis used log-binomial regression to estimate the relative risk of 4 severe neonatal morbidities for the racial/ethnic groups. For the fetuses-at-risk analysis, Cox proportional hazards regression with death as competing risk was used to estimate subhazard ratios associating race/ethnicity with each outcome. Estimates were adjusted for sociodemographic factors and maternal morbidities. Data were analyzed from September 5, 2017, to May 21, 2018. Main Outcomes and Measures: Four morbidity outcomes were defined using International Classification of Diseases, Ninth Revision, diagnosis and procedure codes: necrotizing enterocolitis, intraventricular hemorrhage, bronchopulmonary dysplasia, and retinopathy of prematurity. Results: In total, 582 297 infants were included in this study. Of these infants, 285 006 were female (48.9%) and 297 291 were male (51.0%). Using the conventional approach in the very preterm birth subcohort, black compared with white infants had an increased risk of only bronchopulmonary dysplasia (adjusted risk ratio [aRR], 1.34; 95% CI, 1.09-1.64) and a borderline increased risk of necrotizing enterocolitis (aRR, 1.39; 95% CI, 1.00-1.93). Hispanic infants had a borderline increased risk of necrotizing enterocolitis (aRR, 1.39; 95% CI, 0.98-1.96), and Asian infants had an increased risk of retinopathy of prematurity (aRR, 1.85; 95% CI, 1.15-2.97). In the fetuses-at-risk analysis, black infants had a 4.40 times higher rate of necrotizing enterocolitis (95% CI, 2.98-6.51), a 2.73 times higher rate of intraventricular hemorrhage (95% CI, 1.63-4.57), a 4.43 times higher rate of bronchopulmonary dysplasia (95% CI, 2.88-6.81), and a 2.98 times higher rate of retinopathy of prematurity (95% CI, 2.01-4.40). Hispanic infants had an approximately 2 times higher rate for all outcomes, and Asian infants had increased risk only for retinopathy of prematurity (adjusted hazard ratio, 2.43; 95% CI, 1.43-4.11). Conclusions and Relevance: In this study, racial/ethnic disparities in neonatal morbidities among very preterm infants appear to be sizable, but may have been underestimated in previous studies, and may have implications for the future. Understanding these racial/ethnic disparities is important, as they may contribute to inequalities in health and development later in the child's life.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".