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Record W2043447890 · doi:10.1016/s0029-7844(00)00971-6

Prelabor rupture of the membranes at term: expectant management at home or in hospital?

2000· article· en· W2043447890 on OpenAlexaff
Mary Hannah

Bibliographic record

VenueObstetrics and Gynecology · 2000
Typearticle
Languageen
FieldMedicine
TopicPreterm Birth and Chorioamnionitis
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicinePromOdds ratioHome managementConfidence intervalLogistic regressionObstetricsPremature rupture of membranesPediatricsRupture of membranesAdverse effectPregnancyGestationInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine whether adverse effects of expectant management for premature rupture of membranes (PROM) at term and patient satisfaction were greater if women were managed at home rather than in a hospital. METHODS: We undertook a secondary analysis of data from the International TermPROM Study for women managed expectantly at home or in a hospital. Using multiple logistic regression analyses, we determined the effect of home and hospital management and controlled for differences in baseline characteristics, in measures of maternal and neonatal infections and rates of cesarean. RESULTS: Six hundred fifty-three women (39.1%) were managed at home, and 1017 (60.9%) in a hospital. Management at home, compared with in a hospital, increased risk of nulliparas needing antibiotics before delivery (odds ratio [OR] 1.52 95% confidence interval [CI] 1.04, 2.24, P =.03), those not colonized with group B streptococcus having cesareans (OR 1.48 95% CI 1.03, 2. 14, P =.04), and neonatal infections (OR 1.97 95% CI 1.00, 3.90, P =. 05). More multiparas managed at home said they would participate in the study again (OR 1.80 95% CI 1.27, 2.54, P <.001). CONCLUSION: Expectant management at home, rather than in a hospital, might increase the likelihood of some adverse outcomes.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.221
Threshold uncertainty score1.000

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)0.0010.000

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 head0.006
GPT teacher head0.219
Teacher spread0.212 · 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.

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

Citations44
Published2000
Admission routes1
Has abstractyes

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