Identifying risk individuals for heart failure diagnosis within two years in the adult population in southern Sweden using gender, age, multimorbidity level, and socioeconomic status - Summary - MDSpire
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Identifying risk individuals for heart failure diagnosis within two years in the adult population in southern Sweden using gender, age, multimorbidity level, and socioeconomic status
To identify individuals at high risk of developing heart failure (HF) over a two-year period using widely available information as risk factors.
Approach:
Data Source: Utilized the Region Skåne healthcare register in southern Sweden for anonymized registry information including gender, age, diagnostic data, and socioeconomic status (SES).
HF Diagnosis Criteria: HF was diagnosed based on ESC guidelines, requiring clinical symptoms, objective findings of impaired cardiac function, and elevated BNP values.
Multimorbidity Assessment: Chronic conditions were identified using a method developed by Calderón-Larrañaga et al., analyzing ICD-10 codes to determine chronicity.
Socioeconomic Status Measurement: SES was measured using the Care Need Index (CNI), categorizing PHCs into groups based on socioeconomic affluence.
Statistical Analysis: Logistic regression was used to estimate the odds ratio of HF diagnosis within two years, considering variables like gender, age, MM level, and SES.
Key Findings:
The study population consisted of 961,190 individuals, with 50.9% being women and 49.1% men.
Multimorbidity and socioeconomic factors were significant in assessing HF risk.
Logistic regression models indicated varying odds of HF diagnosis based on demographic and health factors.
Interpretation:
The findings highlight the importance of demographic and health-related factors in predicting HF risk in the adult population of southern Sweden.
Limitations:
The study is based on registry data, which may have limitations in accuracy and completeness.
The analysis is limited to individuals aged 20 and older without a prior HF diagnosis.
Conclusion:
Identifying high-risk individuals for HF can aid in early diagnosis and treatment, potentially improving patient outcomes.
National survey findings suggest many US adults report making health decisions based on social media despite widespread concerns about the accuracy of health information shared to the platforms.
