Incidence and associated factors of delirium after primary total joint arthroplasty in elderly patients: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: A total of 1.5% to 20.2% of total joint arthroplasty patients experience delirium. Until now, no formal systematic review or meta-analysis was performed to summarize the risk factors of delirium after primary total joint arthroplasty (TJA). METHODS: A comprehensive search encompassing Medline, Embase, and the Cochrane central database was conducted, incorporating studies available up to June 2023. We systematically reviewed research on the risk factors contributing to delirium following TJA in elderly patients, without language restrictions. The methodological quality of the included studies was evaluated using the Newcastle-Ottawa Scale. Data synthesis through pooling and a meta-analysis were performed to analyze the findings. RESULTS: A total of 23 studies altogether included 71,095 patients with primary TJA, 2142 cases of delirium occurred after surgery, suggesting the accumulated incidence of 3.0%. The results indicated that age, current smoker, heavy drinker, mini-mental state examination score, hypertension, diabetes mellitus, chronic kidney disease, history of stroke, coronary arterial disease, dementia, history of psychiatric illness, American Society of Anesthesiologists physical status III-IV, general anesthesia, anesthesia time, operative time, intraoperative blood loss, blood transfusion, β-blockers, ACEI drugs, use of psychotropic drugs, preoperative C-reactive protein level, and preoperative albumin level were significantly associated with postoperative delirium after primary TJA. CONCLUSIONS: Related prophylaxis strategies should be implemented in the elderly involved with above-mentioned risk factors to prevent delirium after primary TJA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.014 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".