Surgical sensation during caesarean section: a qualitative analysis
Bibliographic record
Abstract
BACKGROUND: Caesarean section (CS) is a major abdominal surgery performed usually on a young and healthy population under neuraxial anesthesia with little to no sedation. This creates a distinct surgical experience whereby patients are aware of the surgical process, physical sensations, and their environment. This study aimed to provide an in-depth descriptive assessment of subjective surgical experience during CS under regional anaesthesia. We expected the information gained would enhance our current understanding and better alleviate patient anxiety through informed counselling. METHODS: This qualitative descriptive study was conducted at a Canadian academic centre. Twenty patients participated in semi-structured interviews within a week of CS, using an interview guide developed for this study. Patient medical records were reviewed to collect demographic and surgical information. Thematic analysis was conducted using an inductive approach to determine common themes. RESULTS: Nine themes were identified. Five themes were identified in the category of surgical sensation and four themes were identified in the category of peri-operative education. CONCLUSIONS: Patients commonly experienced pressure and movement sensations at varying intensity, and most did not experience pain. Environmental factors, including sounds and distraction by the newborn, affected perception of surgical sensation. Patients wish to receive pre-operative counselling regarding potential surgical sensations, as well as ongoing communication from their anaesthesiologist. These results can be used to guide informed discussions with patients and direct further investigation in this area.
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".