Arrhythmic risk prediction in arrhythmogenic right ventricular cardiomyopathy: external validation of the arrhythmogenic right ventricular cardiomyopathy risk calculator.

AIMS: Arrhythmogenic right ventricular cardiomyopathy (ARVC) causes ventricular arrhythmias (VAs) and sudden cardiac death (SCD). In 2019, a risk prediction model that estimates the 5-year risk of incident VAs in ARVC was developed (ARVCrisk.com). This study aimed to externally validate this prediction model in a large international multicentre cohort and to compare its performance with the risk factor approach recommended for implantable cardioverter-defibrillator (ICD) use by published guidelines and expert consensus. METHODS AND RESULTS: In a retrospective cohort of 429 individuals from 29 centres in North America and Europe, 103 (24%) experienced sustained VA during a median follow-up of 5.02 (2.05-7.90) years following diagnosis of ARVC. External validation yielded good discrimination [C-index of 0.70 (95% confidence interval-CI 0.65-0.75)] and calibration slope of 1.01 (95% CI 0.99-1.03). Compared with the three published consensus-based decision algorithms for ICD use in ARVC (Heart Rhythm Society consensus on arrhythmogenic cardiomyopathy, International Task Force consensus statement on the treatment of ARVC, and American Heart Association guidelines for VA and SCD), the risk calculator performed better with a superior net clinical benefit below risk threshold of 35%. CONCLUSION: Using a large independent cohort of patients, this study shows that the ARVC risk model provides good prognostic information and outperforms other published decision algorithms for ICD use. These findings support the use of the model to facilitate shared decision making regarding ICD implantation in the primary prevention of SCD in ARVC.

Impact of haemoconcentration during acute heart failure therapy on mortality and its relationship with worsening renal function.

AIMS: Treatment goals in acute heart failure (AHF) are poorly defined. We aimed to characterize further the impact of in-hospital haemoconcentration and worsening renal function (WRF) on short- and long-term mortality. METHODS AND RESULTS: Haematocrit, haemoglobin, total protein, serum creatinine, and albumin levels were measured serially in 1019 prospectively enrolled AHF patients. Haemoconcentration was defined as an increase in at least three of four of the haemoconcentration-defining parameters above admission values at any time during the hospitalization. Patients were divided into early (Day 1-4) and late haemoconcentration (>Day 4). Ninety-day mortality was the primary endpoint. Haemoconcentration occurred in 392 (38.5%) patients, with a similar incidence of the early (44.6%) and late (55.4%) phenotype. Signs of decongestion (reduction in BNP blood concentrations, P = 0.003; weight loss, P = 0.002) were significantly more pronounced in haemoconcentration patients. WRF was more common in haemoconcentration patients (P = 0.04). After adjustment for established risk factors for AHF mortality, including WRF and HF therapy at discharge, haemoconcentration was significantly associated with a reduction in 90-day mortality [hazard ratio (HR) 0.59, 95% confidence interval (CI) 0.37-0.95, P = 0.01]. The beneficial effect of haemoconcentration seemed to be exclusive for late haemoconcentration (late vs. early: adjusted HR 0.41, 95% CI 0.19-0.90, P = 0.03) and persisted in patients with or without WRF. CONCLUSIONS: Haemoconcentration represents an inexpensive and easily assessable pathophysiological signal of adequate decongestion in AHF and is associated with lower mortality. WRF in the setting of haemoconcentration does not appear to offset the benefits of haemoconcentration.

Prediction of mortality using quantification of renal function in acute heart failure.

BACKGROUND: Renal function, as quantified by the estimated glomerular filtration rate (eGFR), is a predictor of death in acute heart failure (AHF). It is unknown whether one of the clinically-available serum creatinine-based formulas to calculate eGFR is superior to the others for predicting mortality. METHODS AND RESULTS: We quantified renal function using five different formulas (Cockroft-Gault, MDRD-4, MDRD-6, CKD-EPI in patients<70 years, and BIS-1 in patients≥70 years) in 1104 unselected AHF patients presenting to the emergency department and enrolled in a multicenter study. Two independent cardiologists adjudicated the diagnosis of AHF. The primary endpoint was the accuracy of the five eGFR equations to predict death as quantified by the time-dependent area under the receiver-operating characteristics curve (AUC). The secondary endpoint was the accuracy to predict all-cause readmissions and readmissions due to AHF. In a median follow-up of 374 days (IQR: 221 to 687 days), 445 patients (40.3%) died. eGFR as calculated by all equations was an independent predictor of mortality. The Cockcroft-Gault formula showed the highest prognostic accuracy (AUC 0.70 versus 0.65 for MDRD-4, 0.55 for MDRD-6, and 0.67 for the combined formula CKD-EPI/BIS-1, p<0.05). These findings were confirmed in patients with varying degrees of renal function and in three vulnerable subgroups: women, patients with severe left ventricular dysfunction, and the elderly. The prognostic accuracy for readmission was poor for all equations, with an AUC around 0.5. CONCLUSIONS: Calculating eGFR using the Cockcroft-Gault formula assesses the risk of mortality in patients with AHF more accurately than other commonly used formulas.

Prospective validation of a 1-hour algorithm to rule-out and rule-in acute myocardial infarction using a high-sensitivity cardiac troponin T assay.

BACKGROUND: We aimed to prospectively validate a novel 1-hour algorithm using high-sensitivity cardiac troponin T measurement for early rule-out and rule-in of acute myocardial infarction (MI). METHODS: In a multicentre study, we enrolled 1320 patients presenting to the emergency department with suspected acute MI. The high-sensitivity cardiac troponin T 1-hour algorithm, incorporating baseline values as well as absolute changes within the first hour, was validated against the final diagnosis. The final diagnosis was then adjudicated by 2 independent cardiologists using all available information, including coronary angiography, echocardiography, follow-up data and serial measurements of high-sensitivity cardiac troponin T levels. RESULTS: Acute MI was the final diagnosis in 17.3% of patients. With application of the high-sensitivity cardiac troponin T 1-hour algorithm, 786 (59.5%) patients were classified as "rule-out," 216 (16.4%) were classified as "rule-in" and 318 (24.1%) were classified to the "observational zone." The sensitivity and the negative predictive value for acute MI in the rule-out zone were 99.6% (95% confidence interval [CI] 97.6%-99.9%) and 99.9% (95% CI 99.3%-100%), respectively. The specificity and the positive predictive value for acute MI in the rule-in zone were 95.7% (95% CI 94.3%-96.8%) and 78.2% (95% CI 72.1%-83.6%), respectively. The 1-hour algorithm provided higher negative and positive predictive values than the standard interpretation of highsensitivity cardiac troponin T using a single cut-off level (both p < 0.05). Cumulative 30-day mortality was 0.0%, 1.6% and 1.9% in patients classified in the rule-out, observational and rule-in groups, respectively (p = 0.001). INTERPRETATION: This rapid strategy incorporating high-sensitivity cardiac troponin T baseline values and absolute changes within the first hour substantially accelerated the management of suspected acute MI by allowing safe rule-out as well as accurate rule-in of acute MI in 3 out of 4 patients. TRIAL REGISTRATION: ClinicalTrials.gov, NCT00470587.