Multimorbidity patterns of chronic conditions and geriatric syndromes in older patients from the MoPIM multicentre cohort study
Open Access
- 15 November 2021
- Vol. 11 (11), e049334
- https://doi.org/10.1136/bmjopen-2021-049334
Abstract
Objectives To estimate the frequency of chronic conditions and geriatric syndromes in older patients admitted to hospital because of an exacerbation of their chronic conditions, and to identify multimorbidity clusters in these patients. Design Multicentre, prospective cohort study. Setting Internal medicine or geriatric services of five general teaching hospitals in Spain. Participants 740 patients aged 65 and older, hospitalised because of an exacerbation of their chronic conditions between September 2016 and December 2018. Primary and secondary outcome measures Active chronic conditions and geriatric syndromes (including risk factors) of the patient, a score about clinical management of chronic conditions during admission, and destination at discharge were collected, among other variables. Multimorbidity patterns were identified using fuzzy c-means cluster analysis, taking into account the clinical management score. Prevalence, observed/expected ratio and exclusivity of each chronic condition and geriatric syndrome were calculated for each cluster, and the final solution was approved after clinical revision and discussion among the research team. Results 740 patients were included (mean age 84.12 years, SD 7.01; 53.24% female). Almost all patients had two or more chronic conditions (98.65%; 95% CI 98.23% to 99.07%), the most frequent were hypertension (81.49%, 95% CI 78.53% to 84.12%) and heart failure (59.86%, 95% CI 56.29% to 63.34%). The most prevalent geriatric syndrome was polypharmacy (79.86%, 95% CI 76.82% to 82.60%). Four statistically and clinically significant multimorbidity clusters were identified: osteoarticular, psychogeriatric, cardiorespiratory and minor chronic disease. Patient-level variables such as sex, Barthel Index, number of chronic conditions or geriatric syndromes, chronic disease exacerbation 3 months prior to admission or destination at discharge differed between clusters. Conclusions In older patients admitted to hospital because of the exacerbation of chronic health problems, it is possible to define multimorbidity clusters using soft clustering techniques. These clusters are clinically relevant and could be the basis to reorganise healthcare circuits or processes to tackle the increasing number of older, multimorbid patients. Trial registration number NCT02830425.Funding Information
- Network for Research into Healthcare in Chronic Diseases (RD16/0001/0002)
- Instituto de Salud Carlos III (PI15/00552)
- Institut d'Investigació i Innovació Parc Taulí (CIR2017/0070)
This publication has 29 references indexed in Scilit:
- A Comparative study Between Fuzzy Clustering Algorithm and Hard Clustering AlgorithmInternational Journal of Computer Trends and Technology, 2014
- Multimorbidity patterns: a systematic reviewJournal of Clinical Epidemiology, 2014
- A Systematic Review of Prevalence Studies on Multimorbidity: Toward a More Uniform MethodologyAnnals of Family Medicine, 2012
- Current Guidelines Have Limited Applicability to Patients with Comorbid Conditions: A Systematic Analysis of Evidence-Based GuidelinesPLOS ONE, 2011
- Updating and Validating the Charlson Comorbidity Index and Score for Risk Adjustment in Hospital Discharge Abstracts Using Data From 6 CountriesAmerican Journal of Epidemiology, 2011
- Epidemiology and impact of multimorbidity in primary care: a retrospective cohort studyBritish Journal of General Practice, 2011
- The Measurement of Multiple Chronic Diseases--A Systematic Review on Existing Multimorbidity IndicesThe Journals of Gerontology, Series A: Biological Sciences and Medical Sciences, 2010
- A Simple Rule for the Selection of Principal ComponentsCommunications in Statistics - Theory and Methods, 2003
- Improving the sensitivity of the Barthel Index for stroke rehabilitationJournal of Clinical Epidemiology, 1989
- A new method of classifying prognostic comorbidity in longitudinal studies: Development and validationJournal of Chronic Diseases, 1987