The Challenges of Cesarean Delivery at Teaching Hospital Gabriel Toure, Bamako Mali
Bibliographic record
Abstract
Introduction: Cesarean permits to treat difficulties related to vaginal delivery and risk situations of fetal asphyxia. It also permits to save the mother and fetus. However, in developing countries as ours, complications related to this cesarean are not to be neglected. It constitutes an important cause of maternal and fetal morbidity and mortality. Here, the experience of the structure of complications of cesarean is reported. Objectives: The objectives of this study were to study the complications of cesarean section at the teaching hospital Gabriel TOURE, Bamako, Mali. Materials and Methods: A cross-sectional analytic study from January 1st 2003 to December 31st 2013 was carried out. All the patients who gave birth by cesarean operation in the gynecology-obstetric service of the teaching hospital Gabriel TOURE were included during this period of study. Descriptive statistics were used, Chi-square test, Pearson, and Cochran Armitage test have been used to calculate the P-value of trend. A multivariate analyses with a high alpha threshold of 10%, and then logistic regression multivariate was performed. It has been applied to appreciate the effect of maternal characteristics, obstetric practice, systemic factors, on the cesarean delivery rate and the complications. Results: We have registered 28,376 deliveries with 9509 cases of cesarean (33.5%) and a complication cesarean rate of 32% (3049/9509). The main risk factors for cesarean operation completions were adolescence, primiparity, obesity, the non-realization of antenatal care, evacuations and co-morbidities. Intraoperative complications were dominated by hemorrhage 8.3% and bladder lesion 1.1%, whereas anemia (58.8%) and parietal infection (21.1%) dominated the postoperative complications table. The evacuation (Odds Ratio adjusted (ORa) = 1.96) as well as pre-eclampsia/eclampsia (ORa = 2.34) and the sickle cell disease (ORa = 9.99) were the main influencing factors of maternal death. Praevia placenta (ORa = 1.75) abruption placenta (ORa = 11.08) and fetal malformation (ORa = 2.21) dominated the influencing factors of perinatal death. Conclusion: The cesarean complications rates were high in our improvement of the quality of antenatal care. The reorganization and revitalization of the reference and against reference system will permit the program some cesarean operations to reduce the morbidity related to cesarean.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".