ArticleBMC surgery2025
Development and validation of a nomogram for predicting 30-day major complications in elderly patients undergoing major abdominal surgery.
Article in BMC surgery, 2025. 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo investigate the risk factors related to postoperative major complications in elderly patients undergoing major abdominal surgery, and to construct and validate a nomogram risk prediction model.
methodsThis study analyzed data from 380 elderly patients who underwent major abdominal surgery at the Affiliated Cancer Hospital of Xinjiang Medical University between April and November 2023. The cohort was randomly divided into training and validation sets. Variable selection was performed using Lasso regression, followed by univariate and multivariate logistic regression to identify predictors of major postoperative complications. A nomogram-based risk prediction model was subsequently developed and its predictive performance rigorously evaluated.
resultsThis study analyzed clinical data from 370 elderly patients undergoing major abdominal surgery, of whom 104 (28.1%) developed major complications. Patients were randomly divided into training (n = 259) and validation (n = 111) cohorts in a 7:3 ratio. Using Lasso regression followed by univariate and multivariate logistic regression, gender, ASA classification, CFS, and CCI were identified as significant predictors of major postoperative complications (p < 0.05). The predictive model demonstrated strong performance, with AUCs of 0.884 (95%CI: 0.840-0.929) in the training cohort and 0.855 (95%CI: 0.784-0.927) in the validation cohort.
conclusionThis model is helpful for the clinical prediction of major postoperative complications in elderly patients undergoing major abdominal surgery and assists clinicians in choosing individualized treatment plans to reduce the incidence of serious complications and improve the quality of postoperative recovery of patients.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.