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Record W2986397216 · doi:10.1371/journal.pmed.1002976

Amniotic fluid embolism: A puzzling and dangerous obstetric problem

2019· letter· en· W2986397216 on OpenAlexaff
Sarka Lisonkova, Michael S. Kramer

Bibliographic record

VenuePLoS Medicine · 2019
Typeletter
Languageen
FieldMedicine
TopicMaternal and fetal healthcare
Canadian institutionsMcGill UniversityUniversity of British Columbia
Fundersnot available
KeywordsAmniotic fluid embolismMedicinePerspective (graphical)Amniotic fluidIntensive care medicineObstetricsPregnancyComputer scienceBiology

Abstract

fetched live from OpenAlex

Owing to its uncertain etiology, varying symptoms, rapid onset, and high fatality rate, amniotic fluid embolism (AFE) is one of the most challenging obstetric emergencies.In a new international study published in PLOS Medicine, Kathryn Fitzpatrick and colleagues [1] provide valuable clinical information about this rare complication, which occurs in 2-8 of 100,000 pregnancies [2].The clinical signs and symptoms of AFE include a rapid deterioration of maternal condition, cardiac arrest or arrhythmia, hypotension, respiratory distress, coagulopathy and massive hemorrhage, and acute fetal compromise.Premonitory symptoms such as tingling, shortness of breath, and agitation may occur before the signs and symptoms of cardiovascular collapse.Consumptive coagulopathy without cardiorespiratory symptoms is sometimes recognized as a forme fruste of AFE, but it is important to exclude other possible diagnoses, such as septic shock or coagulopathy caused by, rather than the cause of, excessive bleeding.Myocardial infarction and other conditions can also resemble AFE.Given the acuity and complexity of AFE signs and symptoms, an immediate response by a multidisciplinary team including experienced specialists in obstetrics, maternal-fetal medicine, anesthesia, intensive care, and hematology is probably key for survival, as observed by Fitzpatrick and colleagues [1].Because AFE is a diagnosis of exclusion, a precise case definition is difficult to establish.For these reasons, Fitzpatrick and coauthors examined risk factors, prognosis, and clinical management of AFE using three different definitions: the most liberal definition proposed by the United Kingdom Obstetric Surveillance System (UKOSS) [3], a consensus-driven definition developed by the International Network of Obstetric Survey Systems (INOSS) [4], and the most restrictive definition developed by Clark and colleagues and used by the Amniotic Fluid Embolism Registry in the United States [5].The latter two definitions were modified to harmonize the data collected across international sites.Interestingly, the main risk factors identified in this study were consistent across all three case definitions.Prenatal risk factors included advanced maternal age, multiple pregnancy, gestational diabetes, polyhydramnios, placenta previa, and placental abruption.Several risk factors were related to common obstetric interventions: induction of labor, operative vaginal delivery, and cesarean delivery.This new evidence corroborates the results of previous studies [2,[6][7][8][9] and should spawn further etiologic research.Knowledge of these risk factors has little utility for clinical prediction of AFE, however, because the vast majority of women with these risk factors will have a normal pregnancy and delivery.In previous studies, the case fatality of AFE varied between 11% and 48%, depending on the study design (population versus hospital based) and case definition [2,6].Using the UKOSS

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)0.003
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.050
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0040.006
Open science0.0010.002
Research integrity0.0500.039
Insufficient payload (model declined to judge)0.0050.004

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 head0.041
GPT teacher head0.273
Teacher spread0.232 · 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 designCase report
Domainnot available
GenreEditorial

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

Citations15
Published2019
Admission routes1
Has abstractyes

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