Dataset Information

Prognostic Importance of Multiple Nutrition Screening Indexes for 1-Year Mortality in Hospitalized Acute Decompensated Heart Failure Patients.

ABSTRACT: Background: The purpose of the study was to evaluate the impact of nutritional status on 1-year mortality in hospitalized patients with acute decompensated heart failure (ADHF). Methods?and?Results: We enrolled 457 hospitalized ADHF patients. Previously established objective nutritional indexes (controlling nutritional status [CONUT], prognostic nutritional index [PNI], geriatric nutritional risk index [GNRI], and subjective global assessment [SGA]) were evaluated at hospital admission. Malnutrition was defined as CONUT score ?5, PNI score <38, GNRI score <92, and SGA scores B and C. The frequencies of malnutrition based on CONUT, PNI, GNRI, and SGA were 31.5%, 21.4%, 44.9%, and 27.8%, respectively. All indexes were related to the occurrence of 1-year mortality on univariate Cox regression analysis (P<0.05). We constructed a reference model using age, body mass index, systolic blood pressure, sodium concentration, and renal function on multivariable Cox regression analysis. Adding SGA to the reference model significantly improved both net reclassification improvement (NRI) and integrated discrimination improvement (0.344, P=0.002; 0.012, P=0.049; respectively). Other indexes (CONUT, PNI, and GNRI scores) significantly improved NRI (0.254, P=0.019; 0.273, P=0.013; 0.306, P=0.006; respectively). Conclusions: Nutritional screening assessed at hospital admission was appropriate for the prediction of 1-year mortality in hospitalized patients with ADHF.

SUBMITTER: Takikawa T

PROVIDER: S-EPMC7890280 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Prognostic Importance of Multiple Nutrition Screening Indexes for 1-Year Mortality in Hospitalized Acute Decompensated Heart Failure Patients.

Takikawa Tomonobu T Sumi Takuya T Takahara Kunihiko K Kawamura Yoshihiro Y Ohguchi Shioh S Oguri Mitsutoshi M Ishii Hideki H Murohara Toyoaki T

Circulation reports 20190111 2

Background: The purpose of the study was to evaluate the impact of nutritional status on 1-year mortality in hospitalized patients with acute decompensated heart failure (ADHF). Methods and Results: We enrolled 457 hospitalized ADHF patients. Previously established objective nutritional indexes (controlling nutritional status [CONUT], prognostic nutritional index [PNI], geriatric nutritional risk index [GNRI], and subjective global assessment [SGA]) were evaluated a ...[more]

PMID: 33693118

Similar Datasets

Project description:Background Although the prognostic importance of pulmonary arterial capacitance (PAC; stroke volume/pulmonary arterial pulse pressure) has been elucidated in heart failure with reduced ejection fraction, whether its significance in patients suffering from heart failure with preserved ejection fraction is not known. We aimed to examine the association of PAC with outcomes in inpatients with heart failure with preserved ejection fraction. Methods and Results We prospectively studied 705 patients (median age, 83 years; 55% women) registered in PURSUIT-HFpEF (Prospective Multicenter Observational Study of Patients With Heart Failure With Preserved Ejection Fraction). We investigated the association of echocardiographic PAC at discharge with the primary end point of all-cause death or heart failure rehospitalization with a mean follow-up of 384 days. We further tested the acceptability of the prognostic significance of PAC in a subgroup of patients (167/705 patients; median age, 81 years; 53% women) in whom PAC was assessed by right heart catheterization. The median echocardiographic PAC was 2.52 mL/mm Hg, with a quartile range of 1.78 to 3.32 mL/mm Hg. Univariable and multivariable Cox regression testing revealed that echocardiographic PAC was associated with the primary end point (unadjusted hazard ratio, 0.82; 95% CI, 0.72-0.92; P=0.001; adjusted hazard ratio, 0.86; 95% CI, 0.74-0.99; P=0.035, respectively). Univariable Cox regression testing revealed that PAC assessed by right heart catheterization (median calculated PAC, 2.82 mL/mm Hg) was also associated with the primary end point (unadjusted HR, 0.70; 95% CI, 0.52-0.91; P=0.005). Conclusions A prospective cohort study revealed that impaired PAC diagnosed with both echocardiography and right heart catheterization was associated with adverse outcomes in inpatients with heart failure with preserved ejection fraction. Registration URL: https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000024414. Unique identifier: UMIN000021831.

Project description:BackgroundPolyvascular disease is associated with increased mortality rates and decreased quality of life. Whether its prevalence or associated outcomes differ for patients hospitalized with heart failure with reduced vs preserved ejection fraction (HFrEF vs HFpEF, respectively) is uncertain.MethodsThe Atherosclerosis Risk in Communities (ARIC) study conducted hospital surveillance of acute decompensated heart failure (ADHF) from 2005-2014. Polyvascular disease (coexisting disease in ≥ 2 arterial beds) was identified based on the finding of prevalent coronary artery disease, peripheral artery disease or cerebrovascular disease. Mortality risks associated with polyvascular disease were analyzed separately for HFpEF and HFrEF, with adjustment for potential confounders. All analyses were weighted by the inverse of the sampling probability.ResultsOf 24,937 weighted (5460 unweighted) hospitalizations due to ADHF (52% female, 32% Black, mean age 75 years), polyvascular disease was prevalent in 22% with HFrEF and in 17% with HFpEF. One-year mortality risks increased sequentially with 0, 1 and ≥ 2 arterial bed involvement, both for patients with HFrEF (29%-32%-38%; P trend = 0.0006) and for those with HFpEF (26%-32%-37%; P trend < 0.0001). After adjustments, polyvascular disease was associated with a 26% higher mortality hazard for patients with HFrEF (HR = 1.26; 95% CI: 1.07-1.50) and a 29% higher hazard for patients with HFpEF (HR = 1.29; 95% CI: 1.03-1.62), with no interaction by HF type (P interaction = 0.9).ConclusionPatients hospitalized with ADHF and coexisting polyvascular disease have an increased risk of death, irrespective of HF type. Clinical attention should be directed toward polyvascular disease, with implementation of secondary prevention strategies to improve the prognosis of this high-risk population.SummaryPolyvascular disease is known to be associated with myocardial infarction, stroke or cardiovascular death and is a major risk factor for decreased quality of life. This study sought to evaluate the relationship between polyvascular disease and mortality in patients hospitalized with acute decompensated heart failure (ADHF), and to understand whether the associations differ based on ejection fraction. Patients hospitalized with ADHF and coexisting polyvascular disease had an increased risk of death, irrespective of heart failure type, implying the need for increased clinical attention directed toward polyvascular disease, along with implementation of secondary prevention strategies to improve prognosis.TweetPatients hospitalized with acute HF and coexisting polyvascular disease face an increased risk of death, irrespective of HF type.

Project description:AimsIndividual risk stratification is a fundamental strategy in managing patients with heart failure (HF). Artificial intelligence, particularly machine learning (ML), can develop superior models for predicting the prognosis of HF patients, and administrative claim data (ACD) are suitable for ML analysis because ACD is a structured database. The objective of this study was to analyse ACD using an ML algorithm, predict the 1 year mortality of patients with HF, and finally develop an easy-to-use prediction model with high accuracy using the top predictors identified by the ML algorithm.Methods and resultsMachine learning-based prognostic prediction models were developed from the ACD on 10 175 HF patients from the Japanese Registry of Acute Decompensated Heart Failure with 17% mortality during 1 year follow-up. The top predictors for prognosis in HF were identified by the permutation feature importance technique, and an easy-to-use prediction model was developed based on these predictors. The c-statistics and Brier scores of the developed ML-based models were compared with those of conventional risk models: Seattle Heart Failure Model (SHFM) and Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC). A voting classifier algorithm (ACD-VC) achieved the highest c-statistics among the six ML algorithms. The permutation feature importance technique enabled identification of the top predictors such as Barthel index, age, body mass index, duration of hospitalization, last hospitalization, renal disease, and non-loop diuretics use (feature importance values were 0.054, 0.025, 0.010, 0.005, 0.005, 0.004, and 0.004, respectively). Upon combination of some of the predictors that can be assessed from a brief interview, the Simple Model by ARTificial intelligence for HF risk stratification (SMART-HF) was established as an easy-to-use prediction model. Compared with the conventional models, SMART-HF achieved a higher c-statistic {ACD-VC: 0.777 [95% confidence interval (CI) 0.751-0.803], SMART-HF: 0.765 [95% CI 0.739-0.791], SHFM: 0.713 [95% CI 0.684-0.742], MAGGIC: 0.726 [95% CI 0.698-0.753]} and better Brier scores (ACD-VC: 0.121, SMART-HF: 0.124, SHFM: 0.139, MAGGIC: 0.130).ConclusionsThe ML model based on ACD predicted the 1 year mortality of HF patients with high accuracy, and SMART-HF along with the ML model achieved superior performance to that of the conventional risk models. The SMART-HF model has the clear merit of easy operability even by non-healthcare providers with a user-friendly online interface (https://hfriskcalculator.herokuapp.com/). Risk models developed using SMART-HF may provide a novel modality for risk stratification of patients with HF.

Project description:AimsThis study explored the association between socio-economic status (SES) and mortality among patients hospitalized for heart failure (HF) in China.Methods and resultsWe used data from the China Patient-centred Evaluative Assessment of Cardiac Events-Prospective Heart Failure Study (China PEACE 5p-HF Study), which enrolled patients hospitalized primarily for HF from 52 hospitals between 2016 and 2018. SES was measured using the income, employment status, educational attainment, and partner status. Individual socio-economic risk factor (SERF) scores were assigned based on the number of coexisting SERFs, including low income, unemployed status, low education, and unpartnered status. We assessed the effects of SES on 1 year all-cause mortality using Cox models. We used the Harrell c statistic to investigate whether SES added incremental prognostic information for mortality prediction. A total of 4725 patients were included in the analysis. The median (interquartile range) age was 67 (57-76) years; 37.6% were women. In risk-adjusted analyses, patients with low/middle income [low income: hazard ratio (HR) 1.61, 95% confidence interval (CI) 1.21-2.14; middle income: HR 1.32, 95% CI 1.00-1.74], unemployment status (HR 1.43, 95% CI 1.10-1.86), low education (HR 1.25, 95% CI 1.03-1.53), and unpartnered status (HR 1.22, 95% CI 1.03-1.46) had a higher risk of death than patients with high income, who were employed, who had a high education level, and who had a partner, respectively. Compared with the patients without SERFs, those with 1, 2, 3, and 4 SERFs had 1.52-, 2.01-, 2.45-, and 3.20-fold increased risk of death, respectively. The addition of SES to fully adjusted model improved the mortality prediction, with increments in c statistic of 0.01 (P < 0.01).ConclusionsIn a national Chinese cohort of patients hospitalized for HF, low income, unemployment status, low education, and unpartnered status were all associated with a higher risk of death 1 year following discharge. In addition, incorporating SES into a clinical-based model could better identify patients at risk for death. Tailored clinical interventions are needed to mitigate the excess risk experienced by those socio-economic deprived HF patients.

Dataset Information

Prognostic Importance of Multiple Nutrition Screening Indexes for 1-Year Mortality in Hospitalized Acute Decompensated Heart Failure Patients.

Publications

Prognostic Importance of Multiple Nutrition Screening Indexes for 1-Year Mortality in Hospitalized Acute Decompensated Heart Failure Patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets