Risk Factors for Preterm Birth in Morocco, 2017
Bibliographic record
Abstract
Background: Preterm birth (PTB) is a delivery that occurs before 37 weeks of gestation. It is the leading cause of newborn deaths in Morocco and worldwide. Objective: The aims of our study were to identify the main risk factors of PTB and to propose measures to prevent and improve its management in our context. Methods: We conducted case-control study in intensive care unit of neonatal medical service in Rabat university hospital considered as the inter-regional hospital. We included 87 preterm births before 37 gestations weeks and 174 term-controls. Data about the women’s obstetrical and gynecological history, pregnancy complications and behavior during pregnancy was obtained using a structured questionnaire and medical records. The data was analyzed using SPSS version 20. The logistic regression was employed to identify risk factors of preterm birth. Results: The PTB incidence was 10.92%,The major factors leading to preterm labor were: herbal medicine use during pregnancy (OR adjusted 20.23, CI 5.39-75.8); Short interpregnancy intervals (OR adjusted 14.62, CI 2.75-77.5), history of preterm delivery (OR adjusted 9.51, CI 1.54-58.6 ); taking medicine during pregnancy (OR adjusted 2.40, CI 0.98-5.91), history of uterine curettage (OR adjusted 7.97, CI 1.63-38.8), having a twin pregnancy (OR adjusted 8.57, CI 1.95-37.7), maternal age less than 20 years old (OR adjusted 8.32, CI 1.59-43.5); primiparity (OR adjusted 7.31, CI 1.26-42.3); urogenital tract infection(OR adjusted 6.63, CI 2.37-18.4) and insufficient monitoring of pregnancy (OR adjusted 2.78, CI 1.04-7.40). Conclusions: Mortality rates of newborn could be reduced if the incidence of prematurity decreases. Therefore, we should improve the prenatal care, the screening and early detection of pregnancies at risk for preterm birth, the screening of urogenital infections. Young women should be aware of risk behaviors during pregnancy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".