The Effect of Coffee Consumption on Post Dural Puncture Headache due to Spinal Anesthesia in Cesarean Section: A Randomized Clinical Trial
Bibliographic record
Abstract
Background and Objectives: Post dural puncture headache (PDPH) is a Common problem in pregnant women, but there is still uncertainty about clinical effectiveness, especially in terms of drug therapy. The aim of this study was to determine the effect of coffee consumption on PDPH in cesarean section. Methods: This study was performed as a clinical trial on all women candidate for cesarean section referred to Razi hospital in Torbat Heydariye city, in 2015, and 140 cases were selected based on random allocation (Balanced Blocking method). In the intervention group, the patients were given instant coffee 8 hours after operation two times with one hour interval, in each of which two cups were given. In the control group, the same routine care was performed. The incidence and severity of headache in both groups were monitored by McGill Pain Questionnaire up to 24 hours after the operation. Data were analyzed using Chi-square and independent t- statistical tests. The significance level was considered to be p<0.05. Results: The incidence of PDPH was seen in 15.7% of patients in the intervention group and 37.1% of patients in the control group, which was significantly different (p=0.004). The mean severity of PDPH was 22.2±4.6 in the control group and 13.5±5.8 in the intervention group, which was statically significant (p=0.001). Conclusion: This study revealed that coffee consumption in patients who underwent cesarean section under spinal anesthesia canprevent PDPH and reduce the severity of headache.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".