ArticleJournal of thoracic disease2026
Novel nomogram for predicting acute kidney injury after cardiac surgery.
Article in Journal of thoracic disease, 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: Acute kidney injury (AKI) is a common and serious complication after cardiac surgery, significantly impacting patient outcomes and healthcare systems. This study aimed to develop and validate a nomogram for predicting postoperative AKI in adults undergoing elective cardiac valve and coronary artery bypass graft surgery. Methods: A clinical prediction study was conducted. The primary outcome was the occurrence of postoperative AKI. Potential predictors analyzed included demographic characteristics, comorbidities, preoperative laboratory values, anticoagulant medication usage, and intraoperative factors (transfusion volume, transfusion incidence, cardiopulmonary bypass duration, surgery type, perioperative bleeding). Multivariable logistic regression was used to identify independent predictors in a training cohort, and a nomogram was constructed. Model performance was assessed using the area under the receiver operating characteristic (ROC) curve (AUC) and validated in an independent cohort. Results: Multivariable analysis identified older age [odds ratio (OR) =1.03; 95% confidence interval (CI): 1.02-1.04], preoperative hemoglobin (OR =0.98; 95% CI: 0.98-0.98), creatinine (OR =1.03; 95% CI: 1.02-1.03), higher intraoperative red blood cell transfusion volume (OR =1.07; 95% CI: 1.02-1.12), and increased perioperative bleeding (OR =1.00; 95% CI: 1.00-1.00) as independent predictors of AKI. This predictive nomogram demonstrated good discriminatory ability, with an AUC of 0.880 (95% CI: 0.867-0.894) in the training cohort and an AUC of 0.883 (95% CI: 0.863-0.904) in the internal validation cohort, and an AUC of 0.690 (95% CI: 0.671-0.709) in the external validation set. Conclusions: A nomogram incorporating five readily available clinical variables effectively predicts the risk of postoperative AKI in adults undergoing elective cardiac valve and bypass surgery. This tool may assist in preoperative risk stratification and guide perioperative management strategies.
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.