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Year : 2020  |  Volume : 12  |  Issue : 3  |  Page : 335-343

Risk factors for hospital readmission of patients with heart failure: A cohort study

1 Clinical Pharmacy Program, College of Pharmacy, Al Ain University, Al Ain, United Arab Emirates
2 Shaikh Shakhbout Medical City (SSMC), Abu Dhabi, United Arab Emirates
3 Pharmacy Practice, College of Pharmacy, Trinity University, Dublin, Republic of Ireland
4 Department of Clinical Pharmacy and Pharmacy Practice, Faculty of Pharmacy, Omdurman Islamic University, Khartoum, Sudan
5 Department of Pharmacology and Therapeutics, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
6 College of Health and Human Sciences, Charles Darwin University, Darwin, Northern Territory, Australia
7 Pharmacy Practice, College of Pharmacy, Gulf Medical University, Ajman, United Arab Emirates

Correspondence Address:
Dr. Adel Sadeq
Program of Clinical Pharmacy, College of Pharmacy, Al Ain University, Al Ain, Abu Dhabi
United Arab Emirates
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jpbs.JPBS_323_20

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Aim: The aim of this study was to develop a risk factor model for hospital readmission in patients with heart failure. Background: Identification of risk factors and predictors of readmission to hospital in patients with heart failure is very crucial for improved clinical outcomes. Objective: The 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 Methods: This 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. Results: A 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; P = 0.003), more than twice daily dosing regimen (OR = 2.34; CI = 1.0–5.0; P = 0.023), poor knowledge of prescribed medications (OR = 4.24; CI = 1.213–14.781; P = 0.006), diabetes mellitus (OR = 3.78; CI = 1.6–8.7; P = 0.006), edema (OR = 2.64; CI = 1.2–5.6; P = 0.011), being house bound (OR = 2.77; CI = 1.2–6.2; P = 0.014), and being prescribed diuretics (OR = 3.69; CI = 1.4–9.2; P = 0.042). Conclusion: The 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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