Association between left ventricular dysfunction, anemia, and chronic renal failure. Analysis of the Heart Failure Prevalence and Predictors in Turkey (HAPPY) cohort

Soft clustering using real-world data for the identification of multimorbidity patterns in an elderly population: cross-sectional study in a Mediterranean population

OBJECTIVES

The aim of this study was to identify, with soft clustering methods, multimorbidity patterns in the electronic health records of a population ≥65 years, and to analyse such patterns in accordance with the different prevalence cut-off points applied. Fuzzy cluster analysis allows individuals to be linked simultaneously to multiple clusters and is more consistent with clinical experience than other approaches frequently found in the literature.

DESIGN

A cross-sectional study was conducted based on data from electronic health records.

SETTING

284 primary healthcare centres in Catalonia, Spain (2012).

PARTICIPANTS

916 619 eligible individuals were included (women: 57.7%).

PRIMARY AND SECONDARY OUTCOME MEASURES

We extracted data on demographics, International Classification of Diseases version 10 chronic diagnoses, prescribed drugs and socioeconomic status for patients aged ≥65. Following principal component analysis of categorical and continuous variables for dimensionality reduction, machine learning techniques were applied for the identification of disease clusters in a fuzzy c-means analysis. Sensitivity analyses, with different prevalence cut-off points for chronic diseases, were also conducted. Solutions were evaluated from clinical consistency and significance criteria.

RESULTS

Multimorbidity was present in 93.1%. Eight clusters were identified with a varying number of disease values: nervous and digestive; respiratory, circulatory and nervous; circulatory and digestive; mental, nervous and digestive, female dominant; mental, digestive and blood, female oldest-old dominant; nervous, musculoskeletal and circulatory, female dominant; genitourinary, mental and musculoskeletal, male dominant; and non-specified, youngest-old dominant. Nuclear diseases were identified for each cluster independently of the prevalence cut-off point considered.

CONCLUSIONS

Multimorbidity patterns were obtained using fuzzy c-means cluster analysis. They are clinically meaningful clusters which support the development of tailored approaches to multimorbidity management and further research.

Demographics of patients with heart failure who were over 80 years old and were admitted to the cardiology clinics in Turkey

Objective:

Heart failure (HF) has a high prevalence and mortality rate in elderly patients; however, there are few studies that have focused on patients older than 80 years. The aim of this study is to describe and compare the age-specific demographics and clinical features of Turkish elderly patients with HF who were admitted to cardiology clinics.

Methods:

The Epidemiology of Cardiovascular Disease in Elderly Turkish population (ELDER-TURK) study was conducted in 73 centers in Turkey, and it recruited a total of 5694 patients aged 65 years or older. In this study, the clinical profile of the patients who were aged 80 years or older and those between 65 and 79 years with HF were described and compared based on the ejection fraction (EF)-related classification: HFrEF and HFpEF (is considered as EF: ≥50%).

Results:

A total of 1098 patients (male, 47.5%; mean age, 83.5±3.1 years) aged ≥80 years and 4596 patients (male, 50.2 %; mean age, 71.1±4.31 years) aged 65-79 years were enrolled in this study. The prevalence of HF was 39.8% for patients who were ≥80 years and 27.1% for patients 65–79 years old. For patients aged ≥80 years with HF, the prevalence rate was 67% for hypertension (HT), 25.6% for diabetes mellitus (DM), 54.3% for coronary artery disease (CAD), and 42.3% for atrial fibrilation. Female proportion was lower in the HFrEF group (p=0.019). The prevalence of HT and DM was higher in the HFpEF group (p<0.01), whereas CAD had a higher prevalence in the HFrEF group (p=0.02). Among patients aged 65–79 years, 43.9% (548) had HFpEF, and 56.1% (700) had HFrEF. In this group of patients aged 65-79 years with HFrEF, the prevalence of DM was significantly higher than in patients aged ≥80 years with HFrEF (p<0.01).

Conclusion:

HF is common in elderly Turkish population, and its frequency increases significantly with age. Females, diabetics, and hypertensives are more likely to have HFpEF, whereas CAD patients are more likely to have HFrEF.