ArticleESC heart failure2022
Feasibility of the contraction-relaxation coupling index in outcome prediction for patients with acute heart failure.
Article in ESC heart failure, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- Muscle fibre morphometric analysis (MusMA) correlates with muscle function and cardiovascular risk prognosis.International journal of experimental pathology · 2024Article
- Feasibility of the contraction-relaxation coupling index in outcome prediction for patients with acute heart failure.ESC heart failure · 2022Article
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimsContemporary heart failure (HF) classification based on left ventricular (LV) ejection fraction is limited for comprehensive assessment of LV function. We aimed to validate the feasibility of the contraction-relaxation coupling index (CRC) as a novel predictor for clinical outcomes in patients with acute HF. METHODS AND
resultsA total of 3266 consecutive patients (median age: 74 years, 53% male) with acute HF were included. CRC was defined as the ratio of end-diastolic elastance (LV end-diastolic pressure/stroke volume) to end-systolic elastance (LV end-systolic pressure/end-systolic volume). The risk for 1 year composite endpoint of all-cause mortality or hospitalization for HF (primary outcome) was compared after group categorization using CRC tertiles (Tertile 1: CRC ≤ 0.17, Tertile 2: 0.17 < CRC ≤ 0.40, and Tertile 3: 0.40 < CRC). The median CRC was 0.3 and the median LVEF was 42%. After adjustment for clinical and echocardiographic covariates, CRC was an independent predictor for the primary outcome (hazard ratio [HR]: 1.74, 95% confidence interval [CI]: 1.47-2.07 in Tertile 3 and HR: 1.21, 95% CI: 1.02-1.44 in Tertile 2 when compared with Tertile 1; HR: 1.23, 95% CI: 1.14-1.33 per one-standard deviation increment in CRC). The risk model with CRC showed better performance in outcome discrimination than the model with LVEF (c-statistic 0.701 vs. 0.699, P for difference <0.001). Patients with higher CRC demonstrated better effectiveness of neurohormonal blockade for the primary outcome compared with those with lower CRC (HR: 0.38, 95% CI: 0.29-0.50 in Tertile 3 and HR: 0.67, 95% CI: 0.52-0.89 in Tertile 1).
conclusionsCRC provides an independent value for outcome prediction in patients with acute HF. CRC would be a sensitive indicator for prognostic risk stratification and for predicting treatment response to the neurohormonal blockade.
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