The impact of preoperative malnutrition on postoperative delirium: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Postoperative delirium (POD) is a common postoperative complication, characterized by disturbance of attention, perception, and consciousness within 1 week after surgery, and linked to cognitive decline, increased mortality, and other serious surgical outcomes. Early identification and treatment of risk factors for POD could reduce the occurrence of delirium and the related poor outcomes. Malnutrition as a possible precipitating factor, defined as the poor anthropometric, functional, and clinical outcomes of nutrient deficiency, has been investigated. However, the evidence is controversial. The goal of this systematic review and meta-analysis was to comprehensively assess the correlation between preoperative malnutrition and POD. Methods PubMed, Embase, Cochrane Library, and Web of Science were used to search prospective cohort articles that explored the correlation between preoperative malnutrition and POD from inception until September 30, 2022. Two researchers independently conducted the literature selection and data extraction. The quality of the literature was evaluated according to the Newcastle–Ottawa scale (NOS). Odds ratios (ORs) and 95% confidence intervals (CIs) for POD associated with malnutrition relative to normal nutritional status were calculated. Results Seven prospective cohort studies qualified for the meta-analysis, which included 2701 patients. The pooled prevalence of preoperative malnutrition was 15.1% (408/2701), and POD occurred in 428 patients (15.8%). The NOS score was above 7 points in all 7 studies. Our results demonstrated that the pooled OR for malnutrition and POD was 2.32 (95% CI 1.62–3.32) based on a random-effects model. Our subgroup analysis suggested that the relationship between malnutrition and POD was significant in adults following noncardiac surgery (OR = 3.04, 95% CI, 1.99–4.62, P < 0.001), while there was no statistical significance in adults following cardiac surgery (OR = 1.76, 95% CI, 0.96–3.22, P = 0.07). Additionally, in the subgroup analysis based on different malnutrition assessment tools (MNA-SF versus others), a significant association was found in the MNA-SF group (OR = 3.04, 95% CI, 1.99–4.62, P < 0.001), but not in the others group (OR = 1.76, 95% CI, 0.96–3.22, P = 0.07). Other subgroup analyses showed that this association was not significantly affected by evaluation instruments for POD, location of the study, or quality of the article (all P < 0.05). Conclusions Based on the currently available evidence, our results suggested that preoperative malnutrition was independently associated with POD in adult surgical patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.137 | 0.001 |
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".