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Record W1999279188 · doi:10.1016/s1526-9523(00)00096-9

HIDDEN FROM VIEW: VIOLENT DEATHS AMONG PREGNANT WOMEN IN THE DISTRICT OF COLUMBIA, 1988–1996

2001· article· en· W1999279188 on OpenAlexaff
Cara J. Krulewitch, Marie Pierre-Louis, Regina de Leon‐Gomez, Richard Guy, Richard Green

Bibliographic record

VenueJournal of Midwifery & Women s Health · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsOffice of the Chief Medical Examiner
Fundersnot available
KeywordsMedicinePregnancyHomicideMedical examinerDemographyCause of deathMaternal deathObstetricsInjury preventionPoison controlPopulationMedical emergencyEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVE: Maternal mortality is underreported in the United States in part because traumatic deaths are not included in nationally reported maternal mortality ratios. The overall study goal was to compare women whose deaths had been reported to and investigated by a medical examiner and who had evidence of pregnancy to women without evidence of pregnancy in terms of socio-demographic information, toxicology results, and manner and cause of death. A secondary goal was to compare the pregnancy status and gestational age of women with evidence of pregnancy at the time of death in relation to the manner of death, with particular focus on women who died as a result of violent death. METHODOLOGY: Autopsy charts from 1988-1996 for 651 women aged 15 to 50 from the District of Columbia Office of the Chief Medical Examiner whose autopsies included examination of the uterus were reviewed. Medical examiners' classification of manner and specific causes of death were used as the main outcome measures. Overall, the sample reflected demographic characteristics of women of childbearing age in the District of Columbia, with 82% black, 74.6% unmarried, and 46.5% aged 20 to 34. RESULTS: Among the 651 autopsy charts evaluated, 30 (4.6%) documented evidence of pregnancy; 43.3% of the women who died due to homicide with evidence of pregnancy were not included in the 21 pregnancy-related deaths officially reported by the District of Columbia State Center for Health Statistics during the study period, and therefore, were also not included in national maternal mortality ratios. Although not statistically significant, 11% more homicides occurred among women with evidence of pregnancy as compared to non-pregnant women. Pregnant women who died a violent death were significantly more likely than non-pregnant women to have died due to gunshot trauma. A significant proportion of pregnant women were < 21 weeks gestation at the time of their death. Additionally, women in this sample with evidence of pregnancy were over 3 times more likely to have been teenagers compared to non-pregnant women. CONCLUSION: Medical examiner autopsy records identify violent pregnancy-associated deaths, many of which occur early in pregnancy and are missed by other enhanced case-finding techniques that require a record of a birth or fetal death. These deaths are usually excluded from reported maternal mortality ratios. Few studies have evaluated the prevalence of homicide in women of childbearing age, yet understanding the extent of less commonly associated causes of death during pregnancy such as homicide, may lead to improved identification of preventable problems that contribute to maternal morbidity and mortality. This study, which sheds new light on the identifying and reporting of maternal mortality, and specifically on homicide as a form of violence toward pregnant women, should be of particular interest for all women's health providers, as well as public health professionals, researchers, and advocates who are interested in the design, development, and evaluation of prevention programs, especially those directed toward preventable problems such as domestic violence.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.760
Threshold uncertainty score0.483

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.314
Teacher spread0.291 · 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 source (direct Gemma or distilled Codex), 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

Citations79
Published2001
Admission routes1
Has abstractyes

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