Newborn Apgar Score and Prediction of Maternal Death
Bibliographic record
Abstract
To the Editor: The Apgar score efficiently evaluates a newborn’s condition at birth.1,2 Compared to a 5-minute Apgar score of 7–10, the risk of neonatal death rises substantially at a score of 0–6.1,2 A low newborn Apgar score reflects a higher risk of maternal admission to intensive care unit (ICU).3 Moreover, early maternal mortality is highest when a mother is admitted to ICU.4 Because the 5-minute newborn Apgar score is routinely collected, we assessed whether it is associated with early and late maternal death. We included 587,002 first obstetric livebirths in Ontario, Canada, April 1, 2006, to March 31, 2012. All care is provided under a universal healthcare system, with standardized collection of data on births, including Apgar scores, as well as maternal mortality by hour and day. For twins, we used the Apgar score of the first-born twin. The Sunnybrook Health Sciences Centre research ethics board approved the study. We used Cox proportional hazard regression to generate hazard ratios (HR) and 95% confidence intervals (CI) for maternal death in relation to the newborn 5-minute Apgar score of 0–6 versus 7–10 (the referent). Maternal death was assessed at (1) 0–24 hours, (2) 0–42 days, (3) 43–365 days, and (4) 366 days to 5 years after the index delivery. HRs were adjusted (aHR) for maternal age at delivery. Model 4 was censored at the end of the study period of March 31, 2016. Mothers of newborns with an Apgar score of 0–6 tended to smoke more and to have more health problems and obstetric complications than mothers of newborn with an Apgar score of score of 7–10 (eTable 1; https://links.lww.com/EDE/B352). More newborns with an Apgar of 0–6 were male, a twin, born earlier, and required resuscitation, in contrast to those with an Apgar score of 7–10. The rate of maternal death within 24 hours of delivery was 8.4 versus 0.12 per 10,000 women, comparing those whose 5-minute newborn Apgar score was 0–6 versus 7–10—an aHR of 71 (95% CI = 25, 203; Figure). For maternal death from 0 to 42 days, the aHR was 19 (95% CI = 9.9, 38). For late maternal death from 43 to 365 days (aHR 6.9, 95% CI = 3.5, 14) and death 366 days to 5 years (aHR 1.6, 95% CI = 1.0, 2.7), the risk remained higher in women whose infant had a lower Apgar score, albeit less pronounced (Figure). At both under 24 hours and 0–42 days, no deaths occurred in mothers of infants with an Apgar score of 10.Figure.: Early and late maternal death, among all 587,002 pregnancies, in association with newborn Apgar score at 5 minutes. Relative to an Apgar score of 7–10 is the age-adjusted hazard ratio for maternal death within 24 hours, within 42 days, from 43 to 365 days, and from 366 days to 5 years, after birth of a newborn with an Apgar score of 0–6.Upon restricting to 386,313 term births otherwise unaffected by an anomaly or obstetrical complication, the rate of maternal death within 24 hours was 3.0 versus 0.08 per 10,000 women, comparing Apgar scores of 0–6 versus 7–10—an aHR of 42 (4.3, 400; eFigure 1; https://links.lww.com/EDE/B352). The aHRs for the other outcomes did not meaningfully differ from the null (eFigure 1; https://links.lww.com/EDE/B352). A 5-minute Apgar score of 0–6 is associated with a higher risk of early and late maternal death, especially death within the first 24 hours of delivery. This observation reflects a previous finding of a higher risk of maternal ICU admission if her newborn’s Apgar score is low.3 It is of interest that a newborn Apgar score also reflects a higher risk of late maternal death, at least among more complicated pregnancies. While the causes of early maternal mortality are generally understood,5 the same is not so for late maternal mortality.6 The current findings highlight the potential use of the newborn 5-minute Apgar score as a reflection of not only newborn health but also the health of the mother. Among women with a lower newborn Apgar score, it remains to be determined whether increased surveillance is warranted, short term or long term. ACKNOWLEDGMENTS J.G.R. was involved with conception of the study, interpretation of the results, writing and editing of the article, as well as approval of the final version. A.L.P. was involved with conception of the study, data analysis, interpretation of results, editing of the article, and approval of final version. A.F.K. was involved in interpretation of results as well as writing and editing of the article. Alyssa F. KahaneUndergraduate Medical Education,Faculty of MedicineUniversity of OttawaOttawa, Ontario Alison L. ParkKeenan Research Centre, Li Ka ShingKnowledge InstituteSt. Michael’s HospitalToronto, OntarioInstitute for Clinical Evaluative SciencesToronto, Ontario Joel G. RayDepartments of Medicine and Obstetrics and GynecologyKeenan Research Centre, Li Ka ShingKnowledge InstituteSt. Michael’s HospitalToronto, OntarioInstitute for Clinical Evaluative SciencesUniversity of TorontoToronto, Ontario[email protected]
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".