ArticleClinical and experimental gastroenterology2026
Development and Validation of a Postoperative Delirium Prediction Model for Patients Undergoing Gastrointestinal Surgery.
Article in Clinical and experimental gastroenterology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Postoperative delirium (POD) is a critical and prevalent postoperative complication challenging to major surgeries, associated with the increased morbidity and mortality rate, prolonged hospitalization, and higher healthcare expenditure. Despite the availability of POD prediction tools, none of the models deals particularly with the unique preoperative risks of gastrointestinal surgery patients, which is the critical gap in the present clinical practice. Thus, the objectives of the study were the development and validation of an easy-to-use preoperative prediction model for POD specifically for patients undergoing gastrointestinal surgery, to narrow this gap by a specific population tool. Methods: A total of 369 patients undergoing gastrointestinal surgery were analyzed retrospectively. Univariate analysis was used to identify candidate variables, and a multivariate logistic regression model was built using with statistically significant predictors (P<0.05). The area under the receiver operating characteristic curve (AUC) was used as a measure of model performance. Internal validation was done though 20 times 5-fold cross-validation of the models as a measure of robustness. Results: Univariate analysis identified four statistically significant factors for POD: advanced age (OR = 4.19, 95% CI: 1.68-11.91), lower educational level (OR = 0.25, 95% CI: 0.10-0.60), history of cerebrovascular disease (OR = 6.59, 95% CI: 2.55-16.47), and elevated preoperative serum glucose level (OR = 2.68, 95% CI: 1.03-6.54). All these factors were included in the final POD prediction model, which proved to have strong discriminative power (AUC = 0.810, 95% CI: 0.700-0.921) and good calibration (Hosmer-Lemeshow test, P = 0.436). Conclusion: This model is the first easy-to-use preoperative prediction model of POD particularly developed for gastrointestinal surgical patients and exhibits high discriminatory accuracy. It enables anesthesiologists to promptly stratify the risk of POD, which will allow them to implement preventive interventions in time.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.