Laboratory Value-Based Innovation in Heart Failure Improves Patient Health-Related Outcomes

León-Justel, Antonio; Garcia-Polavieja, Jose Ignacio Morgado; Álvarez-Ríos, Ana Isabel; Vázquez-Rico, Ignacio; Rios, Alvaro; Albarrán, Adrián Rodríguez; Rios, Elena; Fernández, J.A. Sevillano

doi:10.7754/clin.lab.2021.210503

Clin. Lab.

2022

DOI: 10.7754/clin.lab.2021.210503

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Laboratory Value-Based Innovation in Heart Failure Improves Patient Health-Related Outcomes

Antonio León-Justel¹,

Jose Ignacio Morgado Garcia-Polavieja²,

Ana Isabel Álvarez-Ríos³

et al.

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2024

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Clustering Based on Laboratory Data in Patients With Heart Failure Admitted to the Intensive Care Unit

Nemati,

Mohammadi,

Hooshanginezhad

2024

Clinical Laboratory Analysis

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BackgroundHeart failure (HF) is a common condition that imposes a significant burden on healthcare systems. We aimed to identify subgroups of patients with heart failure admitted to the ICU using routinely measured laboratory biomarkers.MethodsA large dataset (N = 1176) of patients with heart failure admitted to the ICU at the Beth Israel Deaconess Medical Center in Boston, USA, between June 1, 2001, and October 31, 2012, was analyzed. We clustered patients to identify laboratory phenotypes. Cluster profiling was then performed to characterize each cluster, using a binary logistic model.ResultsTwo distinct clusters of patients were identified (N = 679 and 497). There was a significant difference in the mortality rate between Clusters 1 and 2 (50 [7.4%] vs. 109 [21.9%], respectively, p < 0.001). Patients in the Cluster 2 were significantly older (mean [SD] age = 72.35 [14.40] and 76.37 [11.61] years, p < 0.001) with a higher percentage of chronic kidney disease (167 [24.6%] vs. 262 [52.7%], respectively, p < 0.001). The logistic model was significant (Log‐likelihood ratio p < 0.001, pseudo R2 = 0.746) with an area under the curve of 0.905. The odds ratio for leucocyte count, mean corpuscular volume (MCV), red blood cell (RBC) distribution width, hematocrit (HcT), lactic acid, blood urea nitrogen (BUN), serum potassium, magnesium, and sodium were significant (all p < 0.05).ConclusionLaboratory data revealed two phenotypes of ICU‐admitted patients with heart failure. The two phenotypes are of prognostic importance in terms of mortality rate. They can be differentiated using blood cell count, kidney function status, and serum electrolyte concentrations.

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Clustering Based on Laboratory Data in Patients With Heart Failure Admitted to the Intensive Care Unit

Nemati,

Mohammadi,

Hooshanginezhad

2024

Clinical Laboratory Analysis

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Laboratory Value-Based Innovation in Heart Failure Improves Patient Health-Related Outcomes

Cited by 1 publication

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Clustering Based on Laboratory Data in Patients With Heart Failure Admitted to the Intensive Care Unit

Clustering Based on Laboratory Data in Patients With Heart Failure Admitted to the Intensive Care Unit

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