Prevalence of postoperative neurocognitive disorders in older non-cardiac surgical patients: A systematic review and meta-analysis
Bibliographic record
Abstract
STUDY OBJECTIVE: The growing number of older persons undergoing surgery are at a higher risk of neurocognitive disorder due to multimorbidity and age-related changes. Previous reviews estimated postoperative neurocognitive disorder or cognitive dysfunction (POCD) prevalence without accounting for the sample size or study quality. The prevalence of POCD in this population requires further investigation. This systematic review and meta-analysis applies systematic weighting to estimate the pooled prevalence of POCD in older non-cardiac surgical patients. DESIGN: Systematic review and meta-analysis. SETTING: MEDLINE, MEDLINE ePub, Embase, Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Reviews for relevant articles. PATIENTS: Non-cardiac surgical patients aged ≥60 years old. INTERVENTIONS: Perioperative cognitive assessments. MEASUREMENT: The primary outcome was the prevalence of POCD. MAIN RESULTS: Thirty-nine studies (n = 12,921) were included with mean age of 70.0 ± 8.9 years and 44.3 % women. The overall prevalence of POCD was 23 % (95 % CI: 20 %, 27 %) at day 7, 16 % (95 % CI: 7 %, 25 %) at 1 month, 10 % (95 % CI: 8 %, 13 %) at 3 months and 3 % (95 % CI: 2 %, 4 %) at 1 year. Our meta-regression showed a higher prevalence of POCD in abdominal surgeries at day 7 (β = 0.13, 95 % CI: 0.03-0.22, P = 0.01) and 3 months (β = 0.49, 95 % CI: 0.40-0.58, P < 0.001), versus orthopedic surgeries. CONCLUSIONS: The overall prevalence of POCD in older non-cardiac surgical populations was 23 %, 16 %, 10 %, and 3 % at day 7, 1 month, 3 months, and 1 year, respectively. Abdominal surgery had a higher prevalence of POCD than orthopedic surgery. The substantial risk of POCD calls for cognitive screening, risk mitigation and interventions to improve surgical outcomes. Through routine preoperative cognitive screening and addressing modifiable risk factors, the incidence and impact of POCD can be markedly reduced, enhancing patient outcomes and recovery.
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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 | 0.013 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.046 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".