MétaCan
Menu
Back to cohort
Record W4408718749 · doi:10.1111/ppe.70015

Surviving Severe Bleeding After Childbirth: Consequences Along the Life Course?

2025· article· en· W4408718749 on OpenAlexaffabout
Ugochinyere Vivian Ukah, Cande V. Ananth

Bibliographic record

VenuePaediatric and Perinatal Epidemiology · 2025
Typearticle
Languageen
FieldMedicine
TopicMaternal and fetal healthcare
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersNational Institute of Environmental Health SciencesNational Heart, Lung, and Blood Institute
KeywordsMedicineChildbirthCourse (navigation)Life course approachObstetricsPregnancyGeneral surgeryDevelopmental psychology

Abstract

fetched live from OpenAlex

Postpartum haemorrhage (PPH), which refers to severe bleeding or excessive blood loss after childbirth, is one of the chief causes of maternal mortality and morbidity worldwide [1]. PPH is usually associated with significant placental physiology, and approximately 70% of PPH cases are caused by uterine atony [1, 2]. Other causes of PPH include retained placenta, trauma during delivery (obstetric trauma), and coagulation disorders. Given that up to 60% of PPH patients have at least one identifiable risk factor, such as advanced maternal age, history of PPH, nulliparity, and grand multiparity [1], counselling and timely obstetrical management could mitigate the risk of PPH. PPH can be classified as primary (i.e., occurring within 24 h postpartum) or secondary (between 24 h and 6 weeks postpartum) [3]. Although different definitions for PPH exist [1, 3], the American College of Obstetricians and Gynaecologists defines PPH as cumulative blood loss of ≥1000 mL or more, or blood loss accompanied by signs or symptoms of hypovolemia within 24 h after the birthing process [2]. The global incidence of PPH varies depending on the location and definition used, but estimates suggest that 3% of all births in the US encounter PPH. The rate of PPH is rising [4], which may partly be due to improved reporting. PPH is also associated with adverse immediate, short-term effects, including severe maternal morbidity, anaemia, hysterectomy, and recurrence in subsequent pregnancies [1, 4], thereby posing a substantial public health concern. However, there is limited data on associations between PPH and adverse long-term health. In this issue of Paediatric and Perinatal Epidemiology, Elser and colleagues [5] report the risk of long-term mortality after PPH using data from the Collaborative Perinatal Project (CPP) Mortality Linkage Study in the US. The study included 43,583 participants who had at least one singleton pregnancy across 12 states in the US between 1959 and 1966. PPH was defined based on obstetrical records documented within 24 h after delivery or between 24 h and 6 weeks postpartum. Pregnancy records of participants were linked with the National Death Index and Social Security Death Master File to obtain their mortality follow-up status up to 2016. The observed frequency of PPH in this study population was 3.5%. The initial increased risk of all-cause mortality associated with PPH occurring in the last pregnancy (hazard ratio 1.13, 95% confidence interval 1.04, 1.22) disappeared following adjustments for several confounding factors. Further investigation of specific causes of mortality revealed that PPH was not associated with any mortality except arrhythmia. In secondary analyses of various subgroups, including race and health characteristics, the authors reported no association between PPH and mortality except for a slight increase in risk when participants with pre-pregnancy conditions, such as cardiovascular disease (CVD), respiratory disease, diabetes, cancer, and blood disorders, were included. This study [5] presents novel findings with potentially important clinical implications. Apart from one study [6] reporting an increased risk for long-term mortality after severe haemorrhage (combined PPH with antepartum and intrapartum haemorrhage, requiring blood transfusion and interventions), there are no other studies on long-term mortality after PPH. Previous studies examining long-term maternal health after PPH have focused on the risk of CVD [6, 7]. Findings from these two studies are conflicting, with a Scottish study [8] (n = 70,904) documenting an increased risk of CVD after PPH, whereas one Canadian study [6] (n = 1,224,975) and a Korean study [8] (n = 150,381) did not find any association. Nonetheless, PPH, which resulted in red blood transfusion, was associated with an increased risk of CVD [6, 8], suggesting that cardiovascular risks may increase with the severity of haemorrhage. The study by Elser and colleagues [5] has several strengths that add to the merit of their findings. A key strength is the long follow-up period (median follow-up time of 52 years) in the study. Given that the median maternal age at delivery in the study was 23 years old, a long follow-up of patients is essential to capture mortality. The well-curated analyses, with careful consideration of potential confounders, also add rigour to the findings. However, the study has some major weaknesses, including a lack of information in the data on the severity of PPH (defined by the amount of blood loss or need for transfusion) and the risk of potential exposure misclassification due to changes in PPH definition over time. In particular, there has been increasing attention regarding quantitative measurement of blood rather than estimated blood loss to define PPH [1, 9]. These weaknesses call for caution with study interpretation and generalisability. While PPH was generally not associated with long-term mortality in the study by Elser and colleagues, further inquiry is needed regarding whether the observed risk of arrhythmia-related mortality is consistent over time and across successive pregnancies. Furthermore, studying specific causes of death, rather than all-cause mortality, would be a more meaningful public health assessment to better understand disease aetiologies with PPH. For example, is the risk of dying from arrhythmia after PPH higher within the first 5 years following delivery than in 10 years or later? As Elser and colleagues did not state what ‘long-term’ mortality means, it is not clear whether they began to measure mortality immediately after delivery hospitalisation discharge or several years later. Also, do people who encounter PPH in more than one pregnancy (i.e., recurrent PPH) have the same risk of all-cause or cause-specific mortality compared with those who have only one pregnancy complicated by PPH? Understanding how timing after delivery and cumulative exposure to PPH are associated with the risk of cause-specific mortality would require a much larger sample size with consistent measurement of PPH over time. Isolating these subgroups of PPH persistence might improve our comprehension of the potential role PPH plays in CVD-related mortality or risk, particularly with regard to arrhythmia, and could provide essential clues for optimal management of high-risk patients. Nonetheless, these findings provide much-needed information on the long-term mortality risk, which may have policy-based implications, including recommendations from national guidelines. For example, the American Heart Association suggests that persons who had hypertension during pregnancy should be flagged for subsequent clinical follow-up for cardiovascular screening [10]. However, it is unclear where PPH fits in the recommendations for clinical postpartum surveillance and whether increased surveillance in this group can reduce CVD or CVD-related death. Lastly, with the growing recognition of pregnancy complications as predictors of future adverse health, future studies can explore whether PPH should be considered a potential predictor of CVD. Although more research is needed to fully understand the relationship of PPH and cause-specific mortality, especially CVD-related, it appears that women who experienced PPH are not at increased risk of all-cause mortality. Ugochinyere Vivian Ukah drafted the commentary, and Cande V. Ananth critically reviewed for important intellectual content. Both authors approved the final version of the manuscript and take responsibility for the integrity of the work as a whole, from inception to published article. The authors declare no conflicts of interest. Only information from published sources were used for this commentary.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.027
GPT teacher head0.324
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venuePaediatric and Perinatal EpidemiologySame topicMaternal and fetal healthcareFrench-language works237,207