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Clinical factors related to morbidity and mortality in high-risk heart failure patients: the GUIDE-IT predictive model and risk score.

ABSTRACT: BACKGROUND:Most heart failure (HF) risk scores have been derived from cohorts of stable HF patients and may not incorporate up to date treatment regimens or deep phenotype characterization that change baseline risk over the short- and long-term follow-up period. We undertook the current analysis of participants in the GUIDE-IT (Guiding Evidence-Based Therapy Using Biomarker Intensified Treatment) trial to address these limitations. METHODS AND RESULTS:The GUIDE-IT study randomized 894 high-risk patients with HF and reduced ejection fraction (? 40%) to biomarker-guided treatment strategy vs. usual care. We performed risk modelling using Cox proportional hazards models and analysed the relationship between 35 baseline clinical factors and the primary composite endpoint of cardiovascular (CV) death or HF hospitalization, the secondary endpoint of all-cause mortality, and the exploratory endpoint of 90-day HF hospitalization or death. Prognostic relationships for continuous variables were examined and key predictors were identified using a backward variable selection process. Predictive models and risk scores were developed. Over a median follow-up of 15 months, the cumulative number of HF hospitalizations and CV deaths was 328 out of 894 patients (Kaplan-Meier event rate 34.5% at 12 months). Frequency of all-cause deaths was 143 out of 894 patients (Kaplan-Meier event rate 12.2% at 12 months). Outcomes for the primary and secondary endpoints between strategy arms of the study were similar. The most important predictor that was present in all three models was the baseline natriuretic peptide level. Hispanic ethnicity, low sodium and high heart rate were present in two of the three models. Other important predictors included the presence or absence of a device, New York Heart Association class, HF duration, black race, co-morbidities (sleep apnoea, elevated creatinine, ischaemic heart disease), low blood pressure, and a high congestion score. CONCLUSION:Risk models using readily available clinical information are able to accurately predict short- and long-term CV events and may be useful in optimizing care and enriching patients for clinical trials. CLINICAL TRIAL REGISTRATION:ClinicalTrials.gov ID number NCT01685840.

SUBMITTER: O'Connor C

PROVIDER: S-EPMC6830509 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Clinical factors related to morbidity and mortality in high-risk heart failure patients: the GUIDE-IT predictive model and risk score.

O'Connor Christopher C Fiuzat Mona M Mulder Hillary H Coles Adrian A Ahmad Tariq T Ezekowitz Justin A JA Adams Kirkwood F KF Piña Ileana L IL Anstrom Kevin J KJ Cooper Lawton S LS Mark Daniel B DB Whellan David J DJ Januzzi James L JL Leifer Eric S ES Felker G Michael GM

European journal of heart failure 20190327 6

<h4>Background</h4>Most heart failure (HF) risk scores have been derived from cohorts of stable HF patients and may not incorporate up to date treatment regimens or deep phenotype characterization that change baseline risk over the short- and long-term follow-up period. We undertook the current analysis of participants in the GUIDE-IT (Guiding Evidence-Based Therapy Using Biomarker Intensified Treatment) trial to address these limitations.<h4>Methods and results</h4>The GUIDE-IT study randomized ...[more]

PMID: 30919549

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Project description:BackgroundWe aimed to develop a multivariable statistical model for risk stratification in patients with chronic heart failure with systolic dysfunction, using patient data that are routinely collected and easily obtained at the time of initial presentation.Methods and resultsIn a cohort of 2331 patients enrolled in the HF-ACTION (Heart Failure: A Controlled Trial Investigating Outcomes of Exercise TraiNing) study (New York Heart Association class II-IV, left ventricular ejection fraction ≤0.35, randomized to exercise training and usual care versus usual care alone, median follow-up of 2.5 years), we performed risk modeling using Cox proportional hazards models and analyzed the relationship between baseline clinical factors and the primary composite end point of death or all-cause hospitalization and the secondary end point of all-cause death alone. Prognostic relationships for continuous variables were examined using restricted cubic spline functions, and key predictors were identified using a backward variable selection process and bootstrapping methods. For ease of use in clinical practice, point-based risk scores were developed from the risk models. Exercise duration on the baseline cardiopulmonary exercise test was the most important predictor of both the primary end point and all-cause death. Additional important predictors for the primary end point risk model (in descending strength) were Kansas City Cardiomyopathy Questionnaire symptom stability score, higher serum urea nitrogen, and male sex (all P<0.0001). Important additional predictors for the mortality risk model were higher serum urea nitrogen, male sex, and lower body mass index (all P<0.0001).ConclusionsRisk models using simple, readily obtainable clinical characteristics can provide important prognostic information in ambulatory patients with chronic heart failure with systolic dysfunction.Clinical trial registrationURL: http://www.clinicaltrials.gov. Unique identifier: NCT00047437.

Project description:ObjectivesThe aim of this study was to evaluate the association between vasoactive-inotropic score (VIS), calculated in the 24 h after heart transplantation, and post-transplant mortality and morbidity.MethodsThis was an observational single-centre retrospective study. Patients admitted to surgical intensive care unit after transplantation, between January 2015 and December 2018, were reviewed consecutively. VISmax was calculated as dopamine+ dobutamine+ 100 × epinephrine + 100 × norepinephrine + 50 × levosimendan + 10 × milrinone (all in µg/kg/min) + 10 000 × vasopressin (units/kg/min), using the maximum dosing rates of vasoactive and inotropic medications in the 24 h after intensive care unit admission. The primary outcome was mortality at 1 year post-transplant. The secondary outcomes included length of stay, duration of mechanical ventilation and inotropic support and the occurrence of septic shock, ventilator-associated pneumonia, bloodstream infection or renal replacement therapy.ResultsA total of 151 patients underwent heart transplantation and admitted to intensive care unit. The median VISmax was 39.2 (interquartile range = 19.4-83.0). VISmax was independently associated with 1-year post-transplant mortality, as well as recipient age [hazard ratio (HR) = 1.004, P-value = 0.013], recipient gender (female to male: hazard ratio = 2.23, P-value = 0.047) and combined transplantation (hazard ratio = 2.85, P-value = 0.048). There was a significant association between VISmax and duration of mechanical ventilation (P-value < 0.001), length of stay (P-value = 0.002), duration of infused inotropes (P-value < 0.001), occurrence of bloodstream infections, septic shocks, ventilation-acquired pneumonia and renal replacement therapy.ConclusionsVISmax calculated during the first 24 h after postoperative intensive care unit admission in transplanted patients is independently associated with 1-year mortality. In addition, length of stay, duration of mechanical ventilation and infused inotropes increased with increasing VISmax.

Project description:AimsInformation on the prevalence, outcome and factors associated with heart failure in patients with adult congenital heart disease (CHD) (ACHD-HF) is lacking. We aimed at assessing the prevalence and outcome of ACHD-HF, the variables associated with ACHD-HF, and the differences between major anatomical/pathophysiological ACHD subgroups.Methods and resultsWe included 3905 patients (age 35.4 ± 13.2 years) under active follow-up in our institution (last visit >2010). Outcome of ACHD-HF cases was compared with sex- and age-matched cases. Univariable and multivariable binary logistic regression with ACHD-HF diagnosis as a dependent variable was performed. Overall prevalence of ACHD-HF was 6.4% (mean age 49.5 ± 16.7 years), but was higher in patients with cyanotic CHD (41%), Fontan circulation (30%), and a systemic right ventricle (25%). All-cause mortality was higher in ACHD-HF cases when compared with controls (mortality rate ratio 4.67 (2.36-9.27); P = 0.0001). In multivariable logistic regression analysis, age at latest follow-up [per 10 years; odds ratio (OR) 1.52; 95% confidence interval (CI) 1.31-1.77], infective endocarditis (OR 4.11; 95%CI 1.80-9.38), history of atrial arrhythmia (OR 3.52; 95%CI 2.17-5.74), pacemaker implantation (OR 2.66; 95% CI 1.50-4.72), end-organ dysfunction (OR 2.41; 95% CI 1.03-5.63), New York Heart Association class (OR 9.28; 95% CI 6.04-14.25), heart rate (per 10 bpm; OR 1.27; 95% CI 1.08-1.50), ventricular dysfunction (OR 3.62; 95% CI 2.54-5.17), and pulmonary hypertension severity (OR 1.66; 95% CI 1.21-2.30) were independently related to the presence of ACHD-HF. Some variables (age, atrial arrhythmia, pacemaker, New York Heart Association, and ventricular dysfunction) were related to ACHD-HF in all anatomical/physiological subgroups, whereas others were not.ConclusionsACHD-HF is prevalent especially in complex CHD and is associated with poor prognosis. Our data provide insight in the factors related to ACHD-HF including differences between specific anatomical and physiological subgroups.

Project description:AimsThis study aimed to develop and validate a simple method for predicting long-term all-cause mortality in ambulatory patients with chronic heart failure (CHF) residing in an area where Chagas disease is endemic, which will be important not only for patients living in Latin America but also to those living in developed non-endemic countries.Methods and resultsA total of 677 patients with a wide spectrum of aetiologies for left ventricular systolic dysfunction and receiving optimized evidence-based treatment for CHF were prospectively followed for approximately 11 years. We established a risk score using Cox proportional hazard regression models. After multivariable analysis, four variables were independently associated with mortality and included in the CALL Risk Score: Chagas cardiomyopathy aetiology alone [hazard ratio, 3.36; 95% confidence interval (CI), 2.61-4.33; P < 0.001], age ≥60 years (hazard ratio, 1.36; 95% CI, 1.06-1.74; P = 0.016), left anterior fascicular block (hazard ratio, 1.64; 95% CI, 1.27-2.11; P < 0.001), and left ventricular ejection fraction <40% (hazard ratio, 1.73; 95% CI, 1.30-2.28; P < 0.001). The internal validation considered the bootstrapping, a resampling technique recommended for prediction model development. Hence, we established a scoring system attributing weights according to each risk factor: 3 points for Chagas cardiomyopathy alone, 1 point for age ≥60 years, and 2 points each for left anterior fascicular block and left ventricular ejection fraction <40%. Three risk groups were identified: low risk (score ≤2 points), intermediate risk (score of 3 to 5 points), and high risk (score ≥6 points). High-risk patients had more than two-fold increase in mortality (26.9 events/100 patient-years) compared with intermediate-risk patients (10.1 events/100 patient-years) and almost seven-fold increase compared with low-risk patients (4.3 events/100 patient-years). The CALL Risk Score data sets from the development and internal validation cohorts both displayed suitable discrimination c-index of 0.689 (95% CI, 0.688-0.690; P < 0.001) and 0.687 (95% CI, 0.686-0.688; P < 0.001), respectively, and satisfactory calibration [Greenwood-Nam-D'Agostino test (8) = 7.867; P = 0.447] and [Greenwood-Nam-D'Agostino test (8) = 10.08; P = 0.273], respectively.ConclusionsThe CALL Risk Score represents a simple and validated method with a limited number of non-invasive variables that successfully predicts long-term all-cause mortality in a real-world cohort of patients with CHF. Patients with CHF stratified as high risk according to the CALL Risk Score should be monitored and aggressively managed, including those with CHF secondary to Chagas disease.

Dataset Information

Clinical factors related to morbidity and mortality in high-risk heart failure patients: the GUIDE-IT predictive model and risk score.

Publications

Clinical factors related to morbidity and mortality in high-risk heart failure patients: the GUIDE-IT predictive model and risk score.

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