Observational studyHealth and quality of life outcomes2020
A nomogram based on a patient-reported outcomes measure: predicting the risk of readmission for patients with chronic heart failure.
Observational study in Health and quality of life outcomes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Characteristics of Cardiovascular Disease Prediction Models Considering Mental Disorders: A Systematic Review.Journal of the American Heart Association · 2026Pooled it
- Can prediction models for hospital readmission be improved by incorporating patient-reported outcome measures? A systematic review and narrative synthesis.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024Pooled it
- Risk factors and prediction models for bronchitis obliterans after severe Mycoplasma pneumoniae pneumonia with plastic bronchitis in children.Pakistan journal of medical sciences · 2026Article
- Construction of a readmission prediction model and development of a decision support system for chronic heart failure patients based on patient-reported outcome measures.Frontiers in medicine · 2026Article
- Predicting death or readmission following heart failure hospitalisation: the VancOuver CoastAL Acute Heart Failure (VOCAL-AHF) registry.Open heart · 2025Article
- Construction and evaluation of a 180-day readmission prediction model for chronic heart failure patients based on sCD40L.Medicine · 2025Article
- Predicting In-Hospital Mortality in Myocardial Infarction: A Nomogram-Based Retrospective Analysis of the MIMIC-IV Database.Vascular health and risk management · 2025Article
- Construction and validation of a prediction model for 90-day readmission risk in patients with chronic heart failure.Frontiers in cardiovascular medicine · 2025Article
- DCP as a biomarker for TACE efficacy in hepatocellular carcinoma.Frontiers in oncology · 2025Article
- The use of nomogram for detecting mild cognitive impairment in patients with type 2 diabetes mellitus.Journal of diabetes · 2023Article
- Machine learning prognosis model based on patient-reported outcomes for chronic heart failure patients after discharge.Health and quality of life outcomes · 2023Article
- A novel web-based calculator to predict 30-day all-cause in-hospital mortality for 7,202 elderly patients with heart failure in ICUs: a multicenter retrospective cohort study in the United States.Frontiers in medicine · 2023Article
- Clinical features and risk factors analysis of bronchitis obliterans due to refractory Mycoplasma pneumoniae pneumonia in children: a nomogram prediction model.BMC infectious diseases · 2021Article
- Development and Validation of a Nomogram to Predict the 180-Day Readmission Risk for Chronic Heart Failure: A Multicenter Prospective Study.Frontiers in cardiovascular medicine · 2021Article
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Authors and funding
14 authors.
Funding
Abstract
backgroundHealth-related quality of life, as evaluated by a patient-reported outcomes measure (PROM), is an important prognostic marker in patients with chronic heart failure. This study aimed to use PROM to establish an effective readmission nomogram for chronic heart failure.
methodsUsing a PROM as a measurement tool, we conducted a readmission nomogram for chronic heart failure on a prospective observational study comprising of 454 patients with chronic heart failure hospitalized between May 2017 to January 2020. A Concordance index and calibration curve were used to evaluate the discriminative ability and predictive accuracy of the nomogram. A bootstrap resampling method was used for internal validation of results.
resultsThe median follow-up period in the study was 372 days. After a final COX regression analysis, the gender, income, health care, appetite-sleep, anxiety, depression, paranoia, support, and independence were identified and included in the nomogram. The nomogram showed moderate discrimination, with a concordance index of 0.737 (95% CI 0.673-0.800). The calibration curves for the probability of readmission for patients with chronic heart failure showed high consistency between the probability, as predicted, and the actual probability.
conclusionsThis model offers a platform to assess the risk of readmission for different populations with CHF and can assist clinicians with personalized treatment recommendations.
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