ArticleJournal of pharmacy & bioallied sciences
Risk factors for hospital readmission of patients with heart failure: A cohort study.
Article in Journal of pharmacy & bioallied sciences. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 7 citations in OpenAlex.
- Implications of the medication regimen complexity index score on hospital readmissions in elderly patients with heart failure: a retrospective cohort study.BMC geriatrics · 2023Article
- Independent predictors for 90-day readmission of emergency department patients admitted with sepsis: a prospective cohort study.BMC infectious diseases · 2021Article
- Predictors of 30-Day Re-admission in Cardiac Patients at Heart Hospital, Qatar.Heart views : the official journal of the Gulf Heart AssociationArticle
Corrections and comments
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Authors and funding
8 authors at 6 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimThe aim of this study was to develop a risk factor model for hospital readmission in patients with heart failure.
backgroundIdentification of risk factors and predictors of readmission to hospital in patients with heart failure is very crucial for improved clinical outcomes.
objectiveThe objective of the current study was to investigate and delineate the risk factors that may be implicated in putting a patient at greater risk of readmission due to uncontrolled heart failure. MATERIALS AND
methodsThis is a prospective follow-up cohort study of 170 patients with heart failure at a tertiary hospital in Al Ain city in the United Arab Emirates. We have developed a risk factor model based on the recommendations of validated published data. We have used univariate and multivariate logistic regression analyses on structured steps based on the published data. The main outcome was the risk factors for readmission to hospital due to heart failure.
resultsA final predictive model (10 variables) was produced for unplanned readmission of patients with heart failure. The risk factors identified in the final model with their odds ratios (ORs) and confidence intervals (CIs) were as follows: four or more prescribed medicines (OR = 4.13; CI = 3.5-4.1;
conclusionThe specificity of the developed risk prediction model was 82.2%, the sensitivity was 74.3%, and the overall accuracy was 72.9%. The model can be emulated in population with similar characteristics to prevent early readmission of patient with heart failure.
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