Risk factors for hospital readmission of patients with heart failure: A cohort study.
Heart failure
model
prediction
readmission
risk factors
Journal
Journal of pharmacy & bioallied sciences
ISSN: 0976-4879
Titre abrégé: J Pharm Bioallied Sci
Pays: India
ID NLM: 101537209
Informations de publication
Date de publication:
Historique:
received:
13
05
2020
revised:
16
05
2020
accepted:
30
05
2020
entrez:
26
10
2020
pubmed:
27
10
2020
medline:
27
10
2020
Statut:
ppublish
Résumé
The aim of this study was to develop a risk factor model for hospital readmission in patients with heart failure. Identification of risk factors and predictors of readmission to hospital in patients with heart failure is very crucial for improved clinical outcomes. 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. 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. 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; 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.
Sections du résumé
AIM
OBJECTIVE
The aim of this study was to develop a risk factor model for hospital readmission in patients with heart failure.
BACKGROUND
BACKGROUND
Identification of risk factors and predictors of readmission to hospital in patients with heart failure is very crucial for improved clinical outcomes.
OBJECTIVE
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
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
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;
CONCLUSION
CONCLUSIONS
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.
Identifiants
pubmed: 33100794
doi: 10.4103/jpbs.JPBS_323_20
pii: JPBS-12-335
pmc: PMC7574751
doi:
Types de publication
Journal Article
Langues
eng
Pagination
335-343Informations de copyright
© 2020 Journal of Pharmacy and Bioallied Sciences.
Déclaration de conflit d'intérêts
There are no conflicts of interest.
Références
Eur J Heart Fail. 2015 Aug;17(8):818-27
pubmed: 26011392
Int J Gen Med. 2018 Apr 09;11:127-141
pubmed: 29670391
J Card Fail. 2011 Jan;17(1):54-75
pubmed: 21187265
Circulation. 2015 Jan 27;131(4):e29-322
pubmed: 25520374
Pharmacotherapy. 2013 May;33(5):558-80
pubmed: 23529897
Clin Cardiol. 2016 Aug;39(8):446-52
pubmed: 27175605
ESC Heart Fail. 2017 Nov;4(4):527-534
pubmed: 29154419
Circulation. 2017 Mar 7;135(10):e146-e603
pubmed: 28122885
Am J Hosp Pharm. 1976 Aug;33(8):792-5
pubmed: 949062
Heart. 2014 Jun;100(12):923-9
pubmed: 24647052
Med Care. 2010 Nov;48(11):981-8
pubmed: 20940649
Can J Cardiol. 2014 Jun;30(6):612-8
pubmed: 24882531
Heart. 2001 Nov;86(5):574-8
pubmed: 11602559
Br J Clin Pharmacol. 2002 Feb;53(2):163-71
pubmed: 11851640
Heart Lung. 2017 Sep - Oct;46(5):357-362
pubmed: 28801110
Eur J Heart Fail. 2015 Apr;17(4):374-84
pubmed: 25739882
Nat Rev Cardiol. 2015 Apr;12(4):220-9
pubmed: 25666406
BMJ. 2015 Feb 05;350:h411
pubmed: 25656852
Health Technol Assess. 2015 Sep;19(75):1-120
pubmed: 26393373
Circ Cardiovasc Qual Outcomes. 2011 Jan 1;4(1):60-7
pubmed: 21139093
J Am Geriatr Soc. 1996 Aug;44(8):914-21
pubmed: 8708300
BMC Res Notes. 2012 Sep 26;5:534
pubmed: 23014157
Res Gerontol Nurs. 2018 Jul 1;11(4):190-197
pubmed: 29634848
N Engl J Med. 2005 Aug 4;353(5):487-97
pubmed: 16079372
Eur J Clin Pharmacol. 1997;53(3-4):171-8
pubmed: 9476027