ArticleFrontiers in surgery2025
Development of a nomogram model based on spleen volume change to predict high-risk esophageal varices in patients with liver cirrhosis.
Article in Frontiers in surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Development of a noninvasive ultrasound-based model for predicting high-risk esophageal varices in hepatitis-related cirrhosis.Ultrasonography (Seoul, Korea) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Esophageal variceal (EV) rupture is a life-threatening complication of liver cirrhosis. Although upper gastrointestinal endoscopy is recommended for routine screening and risk assessment of EV bleeding, it is an invasive and often unpleasant procedure. This study aims to develop a non-invasive nomogram model based on spleen volume changes to predict the presence of high-risk esophageal varices (HREVs). Methods: A total of 150 patients with liver cirrhosis (mean age 62.3 ± 10.0 years; 95 men and 55 women) who underwent upper gastrointestinal endoscopy were retrospectively included. Spleen volume was measured using abdominal computed tomography. Predictors were identified through multivariate logistic regression and subsequently used to construct a nomogram model. The discriminative ability, calibration ability, and clinical utility were assessed. Internal validation was performed using 1,000 bootstrap resampling iterations. Results: Based on endoscopic findings, 74 patients were categorized into the HREV group and 76 patients were categorized into the non-HREV group. Multivariate regression identified three independent predictors of HREV: the presence of ascites [odds ratio (OR) = 2.656, 95% confidence interval (CI): 1.224-5.763], prothrombin time (OR = 1.217, 95% CI: 1.043-1.419), and spleen volume enlargement rate (OR = 1.589, 95% CI: 1.276-1.979). These variables were incorporated into the nomogram model. The area under the receiver operating characteristic curve of the nomogram model was 0.793 (95% CI: 0.723-0.863), outperforming previously reported models, such as the platelet-to-spleen volume ratio (0.724), platelet-to-spleen diameter ratio (0.673), aspartate aminotransferase-to-platelet ratio index (0.590), and aspartate aminotransferase-to-alanine aminotransferase ratio (0.558). At a probability cutoff of 0.421, the nomogram demonstrated a sensitivity of 0.797, a specificity of 0.671, a positive predictive value of 0.702, a negative predictive value of 0.773, and an accuracy of 0.733. Internal validation yielded a Conclusion: The nomogram incorporating ascites, prothrombin time, and spleen volume enlargement rate effectively predicts HREVs in patients with liver cirrhosis. This non-invasive and user-friendly tool offers an efficient approach for timely HREV evaluation and preventive treatment of variceal bleeding.
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.