Response to question: Is intranasal oxytocin useful in preventing post-dural puncture headache in caesarean section? A randomised clinical trial
Bibliographic record
Abstract
search, G -Funds CollectionBackground.Post-dural puncture headache (PDPH) as an annoying complication after spinal anaesthesia and is of great importance in patients undergoing caesarean section.Objectives.This study aimed to evaluate the effect of nasal oxytocin on the incidence and severity of PDPH after caesarean section.Material and methods.This double-blinded randomised clinical trial was carried out on 170 patients undergoing elective caesarean section in Kamali Hospital, Karaj, Iran, from May 2021 to September 2021.Participants were randomly assigned to receive three puffs of intranasal oxytocin (30 IU) (intervention group) or intranasal normal saline (0.3 ml of 0.09% saline solution) (control group) as a placebo right after delivery.The occurrence of PDPH was the primary outcome, and participants were also asked about the use of analgesics and associated symptoms. Results.The results showed that the rate of PDPH was not significantly different between the two groups at 12 (p = 0.108) and 72 (p = 0.245) hours after surgery, but it significantly reduced the incidence of PDPH at 24 (p = 0.022) and 48 hours (p = 0.042).Oxytocin did not reduce the analgesic requirement compared to the control group (p > 0.05).Oxytocin did not significantly mitigate PDPH associated symptoms, including tinnitus, vertigo, nausea and double vision (p > 0.05).Conclusions.Administration of intranasal oxytocin in combination with routine analgesic for post-dural puncture headache after caesarean section is beneficial and reduces the incidence of headache after 24 and 48 hours of surgery.Use of nasal oxytocin has no effect on the need for sedation and reduction of associated symptoms (dizziness, diplopia, nausea, tinnitus).
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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 | 0.021 | 0.172 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.030 | 0.013 |
| Insufficient payload (model declined to judge) | 0.061 | 0.018 |
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".