Influence of obstructive sleep apnea on postoperative cognitive dysfunction in elderly patients undergoing joint replacement.
Bibliographic record
Abstract
OBJECTIVE: To clarify the influence of obstructive sleep apnea (OSA) on postoperative cognitive dysfunction (POCD) in elderly patients undergoing joint replacement. METHODS: This study retrospectively enrolled130 patients who underwent joint replacement in the Department of Orthopaedics of Taizhou Municipal Hospital between January 2019 and March 2021 for analysis. According to polysomnography (PSG) results, 80 patients without OSA were included in group A and 50 with OSA were assigned to group B. The two groups were compared with respect to the following items: surgical indications (length of stay (LOS), intraoperative blood loss (IBL) and operation time (OT), incidence of postoperative delirium (POD), postoperative cognitive function (Mini-mental State Examination, MMSE), neurological function recovery (National Institutes of Health Stroke Scale, NIHSS) and (Scandinavian Stroke Scale, SSS)), mental health (Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS)), compliance, overall response rate (ORR), complications and patient satisfaction. RESULTS: The LOS and OT were shorter, and the IBL was less in group A compared with those in group B. Group A also showed reduced NIHSS and SSS scores as well as SAS and SDS scores when compared with group B. In addition, lower incidence of POD, and higher compliance, ORR and satisfaction were observed in group A than in group B. In terms of cognitive function, although the MMSE score in both groups decreased after surgery, patients in group B had a lower MMSE score and a milder form of POCD. CONCLUSIONS: OSA may affect the postoperative cognitive function and adversely influence the treatment outcome of elderly patients undergoing joint replacement.
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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 | 0.002 |
| 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".