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Record W1999440905 · doi:10.1515/jpm.2007.079

Incidence and correlates of cesarean section in a capital city of a middle-income country

2007· article· en· W1999440905 on OpenAlexaff
Hala Tamim, Souheil El‐Chemaly, Anwar H. Nassar, Ghina R. Mumtaz, A. Kaddour, Tamar Kabakian‐Khasholian, Hassan Fakhoury, Khalid Yunis

Bibliographic record

VenueJournal of Perinatal Medicine · 2007
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsYork University
Fundersnot available
KeywordsMedicineIncidence (geometry)Section (typography)Middle incomeCapital (architecture)Low and middle income countriesObstetricsDemographic economicsDemographySocioeconomicsEconomic growthDeveloping countryAncient historyAdvertisingEconomics

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the prevalence and correlates of cesarean deliveries (CS) in Beirut. METHODS: A cross-sectional study conducted on 18,837 consecutive infants born at nine hospitals from the National Collaborative Perinatal Neonatal Network (NCPNN). Stepwise Logistic Regression was performed to determine CS correlates. RESULTS: The rate of CS was 26.4% and correlated with socio-demographic, obstetrical and provider-related variables. Regression analysis identified age, paternal occupation, mode of payment, parity, birth weight, gestational age, multiple pregnancies, adequate prenatal care, complications during pregnancy, body mass index at delivery, hospital teaching status, day of the week and year of delivery to be significant correlates of CS. CONCLUSION: This study shows an increased CS rate in a middle-income country, and identifies the correlates of women delivering by the abdominal route. These correlates may be used for effective reduction policies in the future.

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)0.001
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 score0.005
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.024
GPT teacher head0.329
Teacher spread0.305 · 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

Citations10
Published2007
Admission routes1
Has abstractyes

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