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Record W2979463017 · doi:10.1055/s-0039-1697668

The Contribution of an Infectious Workup in Understanding Stillbirth

2019· article· en· W2979463017 on OpenAlexaff
Yuval Fouks, Ariel Many, Yael Shulman, Stella Bak, Shiri Shinar

Bibliographic record

VenueAmerican Journal of Perinatology · 2019
Typearticle
Languageen
FieldMedicine
TopicMaternal and fetal healthcare
Canadian institutionsMount Sinai Hospital
Fundersnot available
KeywordsMedicineChorioamnionitisEtiologyObstetricsGestationFetusPregnancyAutopsyGestational ageRetrospective cohort studySerologyPathologyImmunologyAntibody

Abstract

fetched live from OpenAlex

Abstract Objective This study was aimed to assess the utility of diagnostic tests of maternal and fetal infection in the evaluation of stillbirth. Study Design A single-center retrospective study from January 2011 to December 2016 of all women presenting to the hospital with intrauterine fetal death at or after 20 weeks of gestation. Standard evaluation included review of medical records, clinical and laboratory inflammatory workup, maternal serologies, fetal autopsy, placental pathology, and fetal and placental cultures. A suspected infectious etiology was defined as meeting at least two diagnostic criteria, and only after exclusion of any other identifiable stillbirth cause. Results During the 7-year study period, 228 cases of stillbirth were diagnosed at our center. An infectious etiology was the suspected cause of stillbirth in 35 cases (15.3%). The mean gestational age of infection-related stillbirth was 28 1/7 (range: 22–37) weeks, while for a noninfectious etiology, it was 34 0/7 (range: 25–38) weeks (p = 0.005). Placental histological findings diagnostic of overt chorioamnionitis and funisitis were observed in 31 (88.5%) cases. In 16 (45.7%) cases the placental and fetal cultures were positive for the same pathogen. Serology of acute infection was positive in three (8.5%) of the cases. Conclusion Maternal and fetal infectious workup is valuable in the investigation of stillbirth, particularly before 30 weeks of gestation and should be considered a part of standard evaluation.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.075
Threshold uncertainty score0.146

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.012
GPT teacher head0.301
Teacher spread0.290 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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