Systematic review and meta-analysis of risk factors for postoperative delirium among older patients undergoing gastrointestinal surgery
Bibliographic record
Abstract
BACKGROUND: Postoperative delirium (POD) is common after surgery. As age is a known risk factor, the increased ageing of the population undergoing surgery emphasizes the importance of the subject. Knowledge of other potential risk factors in older patients with surgical gastrointestinal diseases is lacking. The aim here was to collate and synthesize the published literature on risk factors for delirium in this group. METHODS: Five databases were searched (MEDLINE, Web of Science, Embase, CINAHL(®) and PSYCinfo(®) ) between January 1987 and November 2014. The Newcastle-Ottawa Scale was used to rate study quality. Pooled odds ratios or mean differences for individual risk factors were estimated using the Mantel-Haenszel and inverse-variance methods. RESULTS: Eleven studies met the inclusion criteria; they provided a total of 1427 patients (318 with delirium and 1109 without), and predominantly included patients undergoing elective colorectal surgery. The incidence of POD ranged from 8·2 to 54·4 per cent. A total of 95 risk factors were investigated, illustrating wide heterogeneity in study design. Seven statistically significant risk factors were identified in pooled analysis: old age, American Society of Anesthesiologists (ASA) physical status grade at least III, body mass index, lower serum level of albumin, intraoperative hypotension, perioperative blood transfusion and history of alcohol excess. Patients with POD had a significantly increased duration of hospital stay and a higher mortality rate compared with those without delirium. CONCLUSION: Delirium is common in older patients undergoing gastrointestinal surgery. Several risk factors were consistently associated with POD.
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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 | 0.012 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.028 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".