ArticleFrontiers in medicine2026
Development and validation of a nomogram prediction model for cardiovascular comorbidities in COPD patients based on hypertension.
Article in Frontiers in medicine, 2026. 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.
- Multi‑feature Prediction Model for Coronary Heart Disease Comorbidity in Middle‑aged and Older Adults with COPD Based on Machine Learning and SHAP.International journal of chronic obstructive pulmonary disease · 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
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study aimed to examine the association between hypertension and cardiovascular comorbidities in patients with chronic obstructive pulmonary disease (COPD) and to construct a nomogram for predicting the risk of cardiovascular comorbidities in this population. Methods: This retrospective study included 1,447 patients with chronic obstructive pulmonary disease (COPD) and no pre-existing cardiovascular disease (CVD) from January 2018 to February 2022 at the Second Affiliated Hospital of Guangdong Medical University, with follow-up extending until August 2025. Patients were randomly assigned to a training cohort ( Results: The predictors incorporated into the nomogram model were age, diabetes mellitus, hypertension, and edema. The nomogram demonstrated good discriminative performance, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.82 (95% CI: 0.78-0.85) in the training cohort, 0.82 (95% CI: 0.77-0.87) in the internal validation cohort, and 0.90 (95% CI: 0.87-0.93) in the external validation cohort. Conclusion: This study demonstrated that the nomogram shows good discriminative performance and can effectively estimate the risk of cardiovascular disease in patients with chronic obstructive pulmonary disease. Age, diabetes mellitus, hypertension, and edema were identified as independent predictors.
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.