Analysis of ralated factors of chronic post surgical pain of video assisted thoracic surgery
Bibliographic record
Abstract
Objective To explore the incidence of chronic postsurgical pain (CPSP) of video assisted thoracic surgery (VATS) and its influencing factors. Methods Totally 216 patients who received elective VATS in a class Ⅲ grade A hospital between January and June 2016 were selected by convenience sampling. Their pain level was assessed with Visual Analogue Scale (VAS) in 1 to 3 days after surgery. The patients were then investigated with Simplified McGill Pain Questionnaire (SF-MPQ) in 1 to 3 months after surgery, with the features of CPSP analyzed and 11 related risk factors statistically analyzed. Results The incidence of CPSP in 3 months after surgery in the 199 patients who received follow-up visits was 49.20%, of which 18.37% suffered moderate pain, and 32.65% felt constant pain. Age (OR=2.16) and pain level in 1-3 days after surgery (OR=2.25) were independent risk factors to CPSP (P<0.05) . Conclusions CPSP occurred in a certain proportion of patients who received VATS. Actively and effectively controlling acute post surgical pain in especially young patients may help to reduce the incidenc of CPSP. Key words: Pain, postsurgerical; Thoracic surgery; Thoracoscope; Risk factors
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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) | 0.002 | 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".