Usefulness of hypochloremia at the time of discharge to predict prognosis in patients with chronic heart failure after hospitalization.

Hypochloremia has been suggested as a strong marker of mortality in hospitalized patients with heart failure (HF). This study aimed to clarify whether incorporating hypochloremia into pre-existing prognostic models improved the performance of the models. We tested the prognostic value of hypochloremia (<97 mEq/L) measured at discharge in hospitalized patients with HF registered in the REALITY-AHF and NARA-HF studies. The primary outcome was 1-year mortality after discharge. Among 2496 patients with HF, 316 (12.6 %) had hypochloremia at the time of discharge, and 387 (15.5 %) deaths were observed within 1 year of discharge. The presence of hypochloremia was strongly associated with higher 1-year mortality compared to those without hypochloremia (log-rank: p < 0.001), and this association remained even after adjustment for the Get With the Guideline-HF risk model (GWTG-HF), anemia, New York Heart Association (NYHA) classification, and log-brain natriuretic peptide (BNP) [hazard ratio (HR) 1.64; p < 0.001]. Furthermore, adding hypochloremia to the prediction model composed of GWTG-HF + anemia + NYHA class + log-BNP yielded a numerically larger area under the curve (0.740 vs 0.749; p = 0.059) and significant improvement in net reclassification (0.159, p = 0.010). Incorporating the presence of hypochloremia at discharge into pre-existing risk prediction models provides incremental prognostic information for hospitalized patients with HF.

Misumi K ，Matsue Y ，Nogi K ，Fujimoto Y ，Kagiyama N ，Kasai T ，Kitai T ，Oishi S ，Akiyama E ，Suzuki S ，Yamamoto M ，Kida K ，Okumura T ，Nogi M ，Ishihara S ，Ueda T ，Kawakami R ，Saito Y ，Minamino T ... -  《-》

Usefulness of Incorporating Hypochloremia into the Get With The Guidelines-Heart Failure Risk Model in Patients With Acute Heart Failure.

Although hypochloremia is strongly associated with adverse prognosis in acute heart failure (AHF), it is unknown whether incorporating hypochloremia into the preexisting risk model improves the model performance. We calculated the Get With The Guidelines-Heart Failure (GWTG-HF) risk score in 1,428 patients with AHF (derivation cohort) and developed 2 risk scores incorporating brain natriuretic peptide (BNP) into the GWTG-HF risk score (GWTG-BNP risk score) and incorporating both BNP and hypochloremia (GWTG-BNP-Cl risk score). Hypochloremia was defined as <98 mmol/L. The external validation and comparison of model performance were performed in an independent group of 1,256 patients with AHF (validation cohort). All models were tested for in-hospital mortality. Hypochloremia was observed in 9.4% and 12.2% of the derivation and validation cohorts, respectively. Hypochloremia was an independent predictor of in-hospital mortality in the derivation cohort (odds ratio 2.02; p = 0.028). In the validation cohort, the GWTG-HF, GWTG-BNP, and GWTG-BNP-Cl risk scores demonstrated good discrimination (area under the curve: 0.742, 0.749, and 0.763, respectively). However, the GWTG-BNP-Cl risk score was more reliable than the GWTG-HF and GWTG-BNP risk scores in risk reclassification (net reclassification improvement: 0.491 and 0.408, respectively; p <0.01 for both). Moreover, this score demonstrated a good calibration of the GWTG-BNP-Cl model (Hosmer-Lemeshow test: p = 0.479). In conclusion, incorporating hypochloremia into the preexisting risk model improves the model performance.

Misumi K ，Matsue Y ，Nogi K ，Sunayama T ，Dotare T ，Maeda D ，Kagiyama N ，Kasai T ，Kitai T ，Oishi S ，Akiyama E ，Suzuki S ，Yamamoto M ，Kida K ，Okumura T ，Nogi M ，Ishihara S ，Ueda T ，Kawakami R ，Saito Y ，Minamino T ... -  《-》

Derivation and validation of a machine learning-based risk prediction model in patients with acute heart failure.

Risk stratification is important in patients with acute heart failure (AHF), and a simple risk score that accurately predicts mortality is needed. The aim of this study is to develop a user-friendly risk-prediction model using a machine-learning method. A machine-learning-based risk model using least absolute shrinkage and selection operator (LASSO) regression was developed by identifying predictors of in-hospital mortality in the derivation cohort (REALITY-AHF), and its performance was externally validated in the validation cohort (NARA-HF) and compared with two pre-existing risk models: the Get With The Guidelines risk score incorporating brain natriuretic peptide and hypochloremia (GWTG-BNP-Cl-RS) and the acute decompensated heart failure national registry risk (ADHERE). In-hospital deaths in the derivation and validation cohorts were 76 (5.1 %) and 61 (4.9 %), respectively. The risk score comprised four variables (systolic blood pressure, blood urea nitrogen, serum chloride, and C-reactive protein) and was developed according to the results of the LASSO regression weighting the coefficient for selected variables using a logistic regression model (4 V-RS). Even though 4 V-RS comprised fewer variables, in the validation cohort, it showed a higher area under the receiver operating characteristic curve (AUC) than the ADHERE risk model (AUC, 0.783 vs. 0.740; p = 0.059) and a significant improvement in net reclassification (0.359; 95 % CI, 0.10-0.67; p = 0.006). 4 V-RS performed similarly to GWTG-BNP-Cl-RS in terms of discrimination (AUC, 0.783 vs. 0.759; p = 0.426) and net reclassification (0.176; 95 % CI, -0.08-0.43; p = 0.178). The 4 V-RS model comprising only four readily available data points at the time of admission performed similarly to the more complex pre-existing risk model in patients with AHF.

Misumi K ，Matsue Y ，Nogi K ，Fujimoto Y ，Kagiyama N ，Kasai T ，Kitai T ，Oishi S ，Akiyama E ，Suzuki S ，Yamamoto M ，Kida K ，Okumura T ，Nogi M ，Ishihara S ，Ueda T ，Kawakami R ，Saito Y ，Minamino T ... -  《-》

Effect of renal function on the prognostic importance of chloride in patients with heart failure.

Çetin Güvenç R ，Güvenç TS ，Temizhan A ，Çavuşuğlu Y ，Çelik A ，Yılmaz MB ... -  《-》

Validation of the MAGGIC (Meta-Analysis Global Group in Chronic Heart Failure) heart failure risk score and the effect of adding natriuretic peptide for predicting mortality after discharge in hospitalized patients with heart failure.

Khanam SS ，Choi E ，Son JW ，Lee JW ，Youn YJ ，Yoon J ，Lee SH ，Kim JY ，Ahn SG ，Ahn MS ，Kang SM ，Baek SH ，Jeon ES ，Kim JJ ，Cho MC ，Chae SC ，Oh BH ，Choi DJ ，Yoo BS ... -  《PLoS One》