Cesarean Delivery at Maternal Request in a Rural Medical College Hospital
Bibliographic record
Abstract
Background: The aim of the study was to find out the reasons behind women preferring cesarean section (CS) in the absence of obstetric and medical indications. Methods: This was a prospective study among women who came for delivery at R.L. Jalappa Hospital and Research Center, Kolar, a tertiary level teaching hospital. All women who underwent cesarean delivery for maternal request were included in this study. Results: The total number of deliveries during the study period (1.5 years) was 3,639. There were 1,877 (52%) vaginal deliveries and 1,762 (48%) CSs. Among 1,762 cesarean deliveries, 44 (2.5%) had maternal request as their indication. Majority (54.5%) of them were in the age group of 20 - 25 years. Multigravida opted for CS more than primigravida (30 versus 14). Most (61.3%) of them have finished their primary school. Majority of them (56.8%) were in class IV socioeconomic status of Kuppuswamy’s scale. The various reasons for women requesting cesarean delivery were refusal of vagina birth after cesarean section (VBAC), simultaneous tubectomy, painless delivery, prolonged infertility, afraid of neonatal outcome and astrological concerns. Conclusion: Many of the women opted for cesarean delivery in our study for preventable reasons like painless labor and simultaneous tubectomy which would have been avoided by prior counseling starting from antenatal period and by providing labor analgesia. Proper education of the patient and personal involvement of the treating obstetrician in counseling the patient and her supporters can reduce cesarean delivery for maternal request. J Clin Gynecol Obstet. 2016;5(2):64-67 doi: http://dx.doi.org/10.14740/jcgo290w
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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 | 0.000 | 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".