Indications for Caesarean Sections in Rundu State Hospital in Kavango East Region, Namibia
Bibliographic record
Abstract
BACKGROUND: A caesarean section is a life saving procedure for both the mother and the baby. However, the fact that caesarean section rates are increasing worldwide, in both the developed and developing countries is becoming an issue of increasing concern, which raised a concern. The purpose of this study was to evaluate the indications for a caesarean section in the Rundu State Hospital. METHODS: A cross sectional retrospective study was conducted.The study population comprised the records of women who had undergone caesarean section between 1 January 2017 to 31 March 2017. After conducting a sample size calculation the delivery, records of 149 women who had undergone a caesarean section during the study period were reviewed. The required data was collected using individual data collection sheets and then analysed using SPSS version 24. RESULTS: The age of participants ranged between 20 and 50 years. The mean age for the study group was 25.1 years. The overall leading indications for a caesarean section included foetal distress (25.6%), previous uterine scar (18.1%) and Cephalopelvic disproportion (16.1%) while other major contributing indications were eclampsia (16.1%), mal-presentation (8.1%), prolonged labour (6.7%, ante partum haemorrhage (3.4%), failed vaginal birth after caesarean section (2.0%), cord prolapse (1.3%) and severe vaginal warts (0.6%). In addition, the study found that a primary caesarean section was more common at 81.9% as compared to previous uterine scar at 18.1 % while maternal indications contributed to 61% of caesarean sections while foetal indications constituted 39%. CONCLUSION: Overall, the study found that the leading indications for caesarean section were foetal distress and previous uterine scar. It was recommended that foetal distress, as the main indicator for a primary caesarean section, should be further confirmed with a printed cardiotocograph. Training health workers on the interpretation of cardiotocograph and the importance of the use of other methods, such as the fetoscope and doptone, may help to reduce the incidence of unnecessary primary caesarean section due to foetal distress. In addition, previous uterine scar cases should be embark on labour before a decision is made.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".