CLINICAL RESEARCH
Which multimorbidity clusters are associated with longer hospital stays in hypertensive patients?
 
More details
Hide details
1
Department of Nursing and Obstetrics, Faculty of Health Sciences, Wroclaw Medical University, Wroclaw, Poland
 
2
Department of Emergency Medical Service, Wroclaw Medical University, Wroclaw, Poland
 
3
Institute of Heart Diseases, University Hospital, Wroclaw, Poland
 
4
Group of Research in Care (GRUPAC), Faculty of Health Science, University of La Rioja, Logroño, Spain
 
 
Submission date: 2023-11-27
 
 
Final revision date: 2024-01-16
 
 
Acceptance date: 2024-02-01
 
 
Online publication date: 2024-08-01
 
 
Corresponding author
Michał Czapla   

Department of Emergency Medical Service, Wroclaw Medical University, 51-616 Wroclaw, Poland
 
 
 
KEYWORDS
TOPICS
ABSTRACT
Introduction:
Hypertension (HT) is one of the world’s most important health problems. This study aimed to identify and characterize multimorbidity clusters in hypertensive patients and to assess which characteristics were responsible for length of hospital stay (LOHS).

Material and methods:
Data were obtained from 489 patients admitted to the cardiology department with HT as the main diagnosis. The Partitioning Around Medoids method was used to divide patients into 12 clusters. Dissimilarity between patients was measured using the Gower distance. The number of clusters was determined using the silhouette method.

Results:
It was noted that myocardial infarction (MI) patients were significantly older than patients without comorbidities and patients from clusters 2, 3, 7, 8, and 10. In addition, patients with diabetes mellitus (DM) only and patients with DM, heart failure (HF), and obesity were significantly older than patients who were only obese. LOHS was significantly longer in patients with HF than in patients from clusters 1, 2, 5, 7, and 10; patients with chronic kidney disease (CKD) but without HF than in clusters 1, 5, and 7; patients with HF and obesity than in clusters 1 and 7; and patients with obesity and DM as well as patients with DM, HF, and often obesity than in patients without comorbidities.

Conclusions:
The presence of additional health conditions impacts the duration of hospital stays for individuals with HT. The conditions HF, CKD, DM and obesity can lead to extended hospitalization. Patients’ clinical profiles provided sufficient insights to predict the necessity for prolonged and more costly medical care.

 
REFERENCES (24)
1.
Mills KT, Stefanescu A, He J. The global epidemiology of hypertension. Nat Rev Nephrol 2020; 16: 223-37.
 
2.
Williams B, Mancia G, Spiering W, et al. 2018 ESC/ESH Guidelines for the management of arterial hypertension: The Task Force for the management of arterial hypertension of the European Society of Cardiology (ESC) and the European Society of Hypertension (ESH). Eur Heart J 2018; 39: 3021-104.
 
3.
NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in blood pressure from 1975 to 2015: a pooled analysis of 1479 population-based measurement studies with 19·1 million participants. Lancet 2017; 389: 37-55. 5.
 
4.
Chow CK, Teo KK, Rangarajan S, et al. Prevalence, awareness, treatment, and control of hypertension in rural and urban communities in high-, middle-, and low-income countries. JAMA 2013; 310: 959-68.
 
5.
Kearney PM, Whelton M, Reynolds K, Muntner P, Whelton PK, He J. Global burden of hypertension: analysis of worldwide data. Lancet 2005; 365: 217-23.
 
6.
Kennard L, O’Shaughnessy KM. Treating hypertension in patients with medical comorbidities. BMJ 2016; 352: i101.
 
7.
Tran J, Norton R, Conrad N, et al. Patterns and temporal trends of comorbidity among adult patients with incident cardiovascular disease in the UK between 2000 and 2014: a population-based cohort study. PLoS Med 2018; 15: e1002513.
 
8.
Tran J, Norton R, Canoy D, et al. Multi-morbidity and blood pressure trajectories in hypertensive patients: a multiple landmark cohort study. PLoS Med 2021; 18: e1003674.
 
9.
Kristjansson K, Sigurdsson JA, Lissner L, Sundh V, Bengtsson C. Blood pressure and pulse pressure development in a population sample of women with special reference to basal body mass and distribution of body fat and their changes during 24 years. Int J Obes 2003; 27: 128-33.
 
10.
Paulsen MS, Andersen M, Thomsen JL, et al. Multimorbidity and blood pressure control in 37 651 hypertensive patients from Danish general practice. J Am Heart Assoc 2013; 2: e004531.
 
11.
Sarkar C, Dodhia H, Crompton J, et al. Hypertension: a cross-sectional study of the role of multimorbidity in blood pressure control. BMC Fam Pract 2015; 16: 98.
 
12.
Violan C, Foguet-Boreu Q, Flores-Mateo G, et al. Prevalence, determinants and patterns of multimorbidity in primary care: a systematic review of observational studies. PLoS One 2014; 9: e102149.
 
13.
Kingston A, Robinson L, Booth H, Knapp M, Jagger C, MODEM project. Projections of multi-morbidity in the older population in England to 2035: estimates from the Population Ageing and Care Simulation (PACSim) model. Age Ageing 2018; 47: 374-80.
 
14.
Multiple Long-Term Conditions (Multimorbidity): a priority for global health research. 5, 2023. https://acmedsci.ac.uk/policy/....
 
15.
Guo Q, Lu X, Gao Y, et al. Cluster analysis: a new approach for identification of underlying risk factors for coronary artery disease in essential hypertensive patients. Sci Rep 2017; 7: 43965.
 
16.
Robertson L, Vieira R, Butler J, Johnston M, Sawhney S, Black C. Identifying multimorbidity clusters in an unselected population of hospitalised patients. Sci Rep 2022; 12: 5134.
 
17.
Overview. Multimorbidity: clinical assessment and management. Guidance.NICE. Published September 21, 2016. Accessed November 5, 2023. https://www.nice.org.uk/guidan....
 
18.
Qian J, Chen Y, Lu D, Ma J, Liu K. The prevalence, disability-adjusted life years, and mortality of hypertensive heart disease and its attributable risk factors: results from the Global Burden Disease study 2019. Arch Med Sci 2023; 19: 1186-200.
 
19.
Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet 2012; 380: 37-43.
 
20.
Prazeres F, Santiago L. Prevalence of multimorbidity in the adult population attending primary care in Portugal: a cross-sectional study. BMJ Open 2015; 5: e009287.
 
21.
Goodman RA, Ling SM, Briss PA, Parrish RG, Salive ME, Finke BS. Multimorbidity patterns in the united states: implications for research and clinical practice. J Gerontol A Biol Sci Med Sci 2016; 71: 215-20.
 
22.
Foguet-Boreu Q, Violán C, Rodriguez-Blanco T, et al. Multimorbidity Patterns in elderly primary health care patients in a South Mediterranean European Region: a cluster analysis. PLoS One 2015; 10: e0141155.
 
23.
Robertson L, Ayansina D, Johnston M, Marks A, Black C. Measuring multimorbidity in hospitalised patients using linked hospital episode data: comparison of two measures. Int J Popul Data Sci 2019; 4: 461.
 
24.
Kirchberger I, Meisinger C, Heier M, et al. Patterns of multimorbidity in the aged population. Results from the KORA-Age study. PLoS One 2012; 7: e30556.
 
eISSN:1896-9151
ISSN:1734-1922
Journals System - logo
Scroll to top