Dataset Information

Underuse of heart failure medications and poor long-term prognosis in chronic heart failure patients with polypharmacy - A report from the CHART-2 study.

ABSTRACT:

Background

In patients with chronic heart failure (CHF), comorbidities are often managed with multiple medications, characterized by polypharmacy, leading to increased risk of potentially inappropriate medication and adverse effects.

Methods

We studied 4,876 consecutive patients with CHF (Stage C/D, age 69.0 ± 12.3 years) in the CHART-2 study to evaluate the association among polypharmacy, underuse of HF medications, and all-cause death. Polypharmacy was defined as the daily use of ≥ 8 medications for the survival classification and regression tree analysis.

Results

The average number of medications was 10 in the polypharmacy group and 5 in the non-polypharmacy group, respectively. Over a median of 8.3 (4.1-11.7) years, the incidence rate of all-cause death was significantly higher in the polypharmacy group (n = 2,108) than in the non-polypharmacy group (57.3 % vs. 40.6 %; adjusted hazard ratio [aHR] 1.34 (95 %CI, 1.22-1.48), P < 0.001), even in age < 55 years (26.6 % vs. 14.3 %; adjusted hazard ratio [aHR] 1.61 (95 %CI, 1.04-2.50), P = 0.033). In patients with polypharmacy, those without renin-angiotensin system inhibitors (RAS-I) and/or beta-blockers (N = 1,023) were associated with increased incidence of all-cause death as compared with those with both medications (aHR 1.18; 95 %CI 1.04-1.35, P = 0.012).

Conclusions

Polypharmacy was associated with poor long-term prognosis, even in younger patients with CHF. Among 4,876 patients with CHF, 1023 (20.9%) with polypharmacy and underuse of RAS-I and/or beta-blocker were associated with increased risk of all-cause death.

SUBMITTER: Fujihashi T

PROVIDER: S-EPMC10835349 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

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Publications

Underuse of heart failure medications and poor long-term prognosis in chronic heart failure patients with polypharmacy - A report from the CHART-2 study.

Fujihashi Takahide T Nochioka Kotaro K Yasuda Satoshi S Sakata Yasuhiko Y Hayashi Hideka H Shiroto Takashi T Takahashi Jun J Miyata Satoshi S Shimokawa Hiroaki H

International journal of cardiology. Heart & vasculature 20240123

<h4>Background</h4>In patients with chronic heart failure (CHF), comorbidities are often managed with multiple medications, characterized by polypharmacy, leading to increased risk of potentially inappropriate medication and adverse effects.<h4>Methods</h4>We studied 4,876 consecutive patients with CHF (Stage C/D, age 69.0 ± 12.3 years) in the CHART-2 study to evaluate the association among polypharmacy, underuse of HF medications, and all-cause death. Polypharmacy was defined as the daily use o ...[more]

PMID: 38313451

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Project description:ObjectivesThis study sought to describe the patterns of heart failure (HF)-exacerbating medications used among older adults hospitalized for HF and to examine determinants of HF-exacerbating medication use.BackgroundHF-exacerbating medications can potentially contribute to adverse outcomes and could represent an important target for future strategies to improve post-hospitalization outcomes.MethodsMedicare beneficiaries ≥65 years of age with an adjudicated HF hospitalization between 2003 and 2014 were derived from the geographically diverse REGARDS (Reasons for Geographic and Racial Difference in Stroke) cohort study. Major HF-exacerbating medications, defined as those listed on the 2016 American Heart Association Scientific Statement listing medications that can precipitate or induce HF, were examined. Patterns of prescribing medications at hospital admission and at discharge were examined, as well as changes that occurred between admission and discharge; and a multivariable logistic regression analysis was conducted to identify determinants of harmful prescribing practices following HF hospitalization (defined as either the continuation of an HF-exacerbating medications or an increase in the number of HF-exacerbating medications between hospital admission and discharge).ResultsAmong 558 unique individuals, 18% experienced a decrease in the number of HF-exacerbating medications between admission and discharge, 19% remained at the same number, and 12% experienced an increase. Multivariable logistic regression analysis revealed that diabetes (odds ratio [OR]: 1.80; 95% confidence interval [CI]: 1.18 to 2.75]) and small hospital size (OR: 1.93; 95% CI: 1.18 to 3.16) were the strongest, independently associated determinants of harmful prescribing practices.ConclusionsHF-exacerbating medication regimens are often continued or started following an HF hospitalization. These findings highlight an ongoing need to develop strategies to improve safe prescribing practices in this vulnerable population.

Project description:AimsCurrent approaches to classify chronic heart failure (HF) subpopulations may be limited due to the diversity of pathophysiology and co-morbidities in chronic HF. We aimed to elucidate the clusters of chronic patients with HF by data-driven approaches with machine learning in a hospital-based registry.Methods and resultsA total of 4649 patients with a broad spectrum of left ventricular ejection fraction (LVEF) in the CHART-2 (Chronic Heart Failure Analysis and Registry in the Tohoku District-2) study were enrolled to this study. Chronic HF patients were classified using random forest clustering with 56 multiscale clinical parameters. We assessed the influence of the clusters on cardiovascular death, non-cardiovascular death, all-cause death, and free from hospitalization by HF. Latent class analysis using random forest clustering identified 10 clusters with four primary components: cardiac function (LVEF, left atrial and ventricular diameters, diastolic blood pressure, and brain natriuretic peptide), renal function (glomerular filtration rate and blood urea nitrogen), anaemia (red blood cell, haematocrit, haemoglobin, and platelet count), and nutrition (albumin and body mass index). All 11 significant clinical parameters in the four primary components and two disease aetiologies (ischaemic heart disease and valvular heart disease) showed statistically significant differences among the 10 clusters (P < 0.01). Cluster 1 (26.7% of patients), which is characterized by preserved LVEF (<59%, 37% of the total) with lowest brain natriuretic peptide (>111.3 pg/mL, 0.9%) and lowest left atrial diameter (>42 mm, 37.4%), showed the best 5 year survival rate of 98.1% for cardiovascular death, 95.9% for non-cardiovascular death, 92.9% for all-cause death, and 91.7% for free from hospitalization by HF. Cluster 10 (6.0% of the total), which is co-morbid disorders of all four primary components, showed the worst survival rate of 39.1% for cardiovascular death, 68.9% for non-cardiovascular death, 23.9% for all-cause death, and 28.1% for free from hospitalization by HF.ConclusionsThese results suggest the potential applicability of the machine leaning approach, providing useful clinical prognostic information to stratify complex heterogeneity in patients with HF.

Dataset Information

Underuse of heart failure medications and poor long-term prognosis in chronic heart failure patients with polypharmacy - A report from the CHART-2 study.

Background

Methods

Results

Conclusions

Publications

Underuse of heart failure medications and poor long-term prognosis in chronic heart failure patients with polypharmacy - A report from the CHART-2 study.

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