Application of multi-mode analgesia in the treatment of aged femoral intertrochanteric fracture under the enhanced recovery after surgery (ERAS)
Bibliographic record
Abstract
Objective To explore the application of perioperative multimodal analgesia in the treatment of intertrochanteric fractures in the elderly under the guidance of the concept of accelerated rehabilitation surgery. Methods A retrospective study of 45 elderly (≥80 years old) femoral intertrochanteric fractures who underwent PFNA surgery in our department from June 2016 to June 2017.There were 19 males (42.2%) and 26 females (57.8%) with an average age of (81.3±1.0) years. All patients underwent closed reduction PFNA within 48 h after fracture. Internal fixation was performed and a multimodal analgesia protocol was used to intervene. The Jane McGill pain questionnaire and the Harris hip function score were used to observe pain relief and hip function recovery. Results All patients were evaluated by the simple McGill Pain Questionnaire and the Harris Hip Function Score. Patients were followed up for 3-14 months with an average of (9.0±2.0) months. The final follow-up showed 39 cases of painless of the simple McGill pain questionnaire, 6 cases of mild pain, 0 case of moderate, 0 case of severe, the rate of painlessness was about 86.67%. Harris hip function score were excellent in 25 cases, 13 cases were good, 7 cases were fair, and 0 case were poor. The excellent and good rate was about 84.44%. Conclusion Perioperative multi-mode analgesia applied to the elderly patients with intertrochanteric fractures is beneficial to reduce the negative effects of traumatic stress caused by post-fracture pain and accelerate the postoperative recovery process. Key words: Perioperative period; Analgesis; Aged; Hip fractures; Enhanced recovery after surgery
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".