ArticleFrontiers in medicine2026
Nomogram for medication nonadherence risk prediction in post-valve surgery patients: a retrospective study.
Article in Frontiers in medicine, 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
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To develop and internally validate a nomogram for individualized prediction of post-valvular surgery medication nonadherence risk. Materials and methods: We developed a prediction model in 244 post-valvular surgery patients enrolled between March 2025 and July 2025. Medication adherence was assessed using the Adherence to Refills and Medications Scale (ARMS). Among the 244 included patients, 112 were classified as nonadherent (ARMS score >16). Predictor selection was performed using least absolute shrinkage and selection operator (LASSO) regression, followed by multivariable logistic regression for nomogram construction. With 112 outcome events and five predictors in the final model, the events-per-variable ratio was 22.4, supporting sample size adequacy for exploratory prediction model development. Model performance was evaluated by the concordance index (C-index), area under the receiver operating characteristic curve (AUC), calibration, and decision curve analysis (DCA). Internal validation was performed using 1,000 bootstrap resamples in accordance with TRIPOD-oriented reporting principles. Results: The final nomogram incorporated five key predictors: use of warfarin, children accompany, dosing frequency daily, education level, and distance to hospital. The model demonstrated excellent discrimination, with a C-index of 0.839 (95% CI: 0.808-0.870) in the training cohort, and maintained strong predictive performance during internal validation (C-index = 0.833). Calibration plots indicated good agreement between predicted and observed probabilities. Decision curve analysis showed that the nonadherence nomogram was clinically useful when the threshold was between 12 and 68%. The AUC was found to be 0.817 [95% CI = 0.784-0.845] in the training set. Conclusion: This validated nomogram incorporating warfarin use, children accompany, dosing frequency daily, education level, and distance to hospital provides a practical tool for individualized prediction of medication nonadherence risk in post-valvular surgery patients.
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.