Responsive Audit of Lower Segment Caesarean Section in a Private Hospital in Kuwait
Bibliographic record
Abstract
Objective: To evaluate current practice and audit against international standards for various parameters relating to elective lower segment caesarean section in our institution. Design: Retrospective cohort study for all elective caesarean sections in a 6 months period. Methods Medical records of 163 elective caesarean sections done from October 2018 till April 2019 were reviewed after taking approval from the office of the Medical Director as per local policy for such an audit. The audit standards used as gold standards were from RCOG guidelines, NICE guidelines and from the Kuwait Ministry of Health. The audit criteria were antiemetic and antacid prophylaxis, antibiotic prophylaxis, type of antibiotic used and time of administration, thromboprophylaxis, documented consent and grade of lower segment caesarean section” and “type of anaesthesia and cord blood PH”. Results We achieved the standard of 100% compliance for consent & grade of lower segment caesarean section, cord blood PH, antacid prophylaxis and antiemetic prophylaxis. For the type of antibiotic, Cephalosporin was used in 73.6% of cases, timing of administration before skin incision was 44%, within 60 minutes of incision was 52% , and thromboprophylaxis was given in 78% of cases .For all these criteria the recommended standard was 100%. Regional anaesthesia was given in 53% against the recommended 95%, while general anaesthesia was given in 47% against the recommended 5%. Conclusion We are a large private hospital in Kuwait accredited by Joint Commission International and Accreditation Canada International with around 2000 deliveries per year. In order to maintain standards of care as per the established guidelines, audit of key interventions like elective lower segment caesarean section is done as part of our regular review cycle through New Mowasat Hospital Quality Systems Management Department. These results are encouraging in many areas yet highlight the need for improvement in others. Improving the quality of obstetric and perinatal care is an urgent priority worldwide and criteria-based clinical audits can play a key role in this process by critical analysis of current medical practice and identification of substandard care factors. Keeping medical records is the safe, economic and simple way to analyze cesarean sections. A re-audit to be undertaken after 1 year is planned. A multidisplinary approach with involvement of all stakeholders including the consumers, local audit department and obstetrics and gynecology department will be the way forward to achieve the change.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".