Effets préliminaires d’une consultation préopératoire infirmière auprès des patients devant subir une arthroplastie de la hanche ou du genou : une étude préexpérimentale
Bibliographic record
Abstract
Introduction: A large proportion of patients undergoing hip or knee replacement surgery experience preoperative anxiety, a predictor of postoperative pain. Objective: To evaluate the preliminary effects of a preoperative nursing consultation incorporating therapeutic education with relaxation on pre- and postoperative anxiety and postoperative pain in patients undergoing hip or knee replacement surgery. Method: Pre-experimental study conducted with a single group and several measurement times: before and after the consultation with a nurse; the day before surgery; and during the hospital stay. Results: A total of 92 people participated in the study. There was a significant and progressive decrease in levels of pain and anxiety. The reduction in anxiety levels before/after the consultation (T0-T1) correlated with anxiety levels the day before surgery (T2), anxiety levels during the hospital stay (T3), and postoperative pain. Discussion: This preoperative nursing consultation appears to have been effective in reducing levels of pre- and postoperative anxiety, as well as postoperative pain, in the patients studied. Conclusion: This randomized clinical trial demonstrates the relevance of continuing to study this combined therapeutic approach in the management of pre- and postoperative anxiety and pain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".