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Record W3174547412 · doi:10.21203/rs.3.rs-579316/v1

Outcomes of Induction Versus Spontaneous Onset of Labour at 40 and 41 Gw: Findings From A Prospective Database, Sri Lanka

2021· preprint· en· W3174547412 on OpenAlexfundno aff
Hemantha Senanayake, Ilaria Mariani, Emanuelle Pessa Valente, Monica Piccoli, Benedetta Armocida, Caterina Businelli, Mohamed Rishard, Benedetta Covi, Marzia Lazzerini

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsMedicineSri lankaLogistic regressionPregnancyProspective cohort studyGestational ageObstetricsPreterm labourPediatricsGynecologyDemographyGestationSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Abstract Objectives The World Health Organization recommends induction of labour (IOL) for low risk pregnancy from 41 + 0 gestational weeks (GW). Nevertheless, in Sri Lanka IOL at 40 GW is common practice. This study compares maternal/newborn outcomes after IOL versus spontaneous onset of labour (SOL) at 40 GW (IOL40) and 41 GW (IOL41). Methods Data were extracted from the routine prospective individual patient database of the Soysa Teaching Hospital for Women, Colombo. IOL and SOL groups were compared using logistic regression. Results Of 13670 deliveries, 2359 (17.4%) were singleton and low risk at 40 or 41 GW. Of these, 456 (19.3%) women underwent IOL40, 318 (13.5%) IOL41, and 1585 (67.2%) SOL. Both IOL40 and IOL41 were associated with an increased risk of any maternal/newborn negative outcomes (OR = 2.21, 95%CI = 1.75–2.77, p < 0.001 and OR = 1.91, 95%CI = 1.47–2.48, p < 0.001 respectively), maternal complications (OR = 2.18, 95%CI = 1.71–2.77, p < 0.001 and OR = 2.34, 95%CI = 1.78–3.07, p < 0.001 respectively) and CS (OR = 2.75, 95%CI = 2.07–3.65, p < 0.001 and OR = 3.01, 95%CI = 2.21–4.12, p < 0.001 respectively). Results did not change in secondary and sensitivity analyses. Conclusions Both IOL groups were associated with higher risk of negative outcomes compared to SOL. Findings, potentially explained by selection bias, local IOL protocols and CS practices, are valuable for Sri Lanka, particularly given contradictory findings from other settings.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.111
GPT teacher head0.450
Teacher spread0.339 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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