Predischarge risk stratification of patients with acute heart failure (AHF) could facilitate tailored treatment and follow-up, however, simple scores to predict short-term risk for HF readmission or death are lacking. We sought to develop a congestion-focused risk score using data from a prospective, two-center observational study in adults hospitalized for AHF. Laboratory data were collected on admission. Patients underwent physical examination, 4-zone, and in a subset 8-zone, lung ultrasound (LUS), and echocardiography at baseline. A second LUS was performed before discharge in a subset of patients. The primary endpoint was the composite of HF hospitalization or all-cause death. Among 350 patients (median age 75 years, 43% women), 88 participants (25%) were hospitalized or died within 90 days after discharge. A stepwise Cox regression model selected four significant independent predictors of the composite outcome, and each was assigned points proportional to its regression coefficient: NT-proBNP ≥2000 pg/mL (admission) (3 points), systolic blood pressure < 120 mmHg (baseline) (2 points), left atrial volume index ≥60 mL/m (baseline) (1 point) and ≥ 9 B-lines on predischarge 4-zone LUS (3 points). This risk score provided adequate risk discrimination for the composite outcome (HR 1.48 per 1 point increase, 95% confidence interval: 1.32–1.67, < 0.001, C-statistic: 0.70). In a subset of patients with 8-zone LUS data ( = 176), results were similar (C-statistic: 0.72). A four-variable risk score integrating clinical, laboratory and ultrasound data may provide a simple approach for risk discrimination for 90-day adverse outcomes in patients with AHF if validated in future investigations.

中文翻译：

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急性心力衰竭患者心力衰竭再入院和全因死亡率的预测因子

急性心力衰竭（AHF）患者的出院前风险分层可以促进量身定制的治疗和随访，但是，缺乏预测心力衰竭再入院或死亡短期风险的简单评分。我们试图利用一项针对因 AHF 住院的成人的前瞻性、两中心观察性研究的数据来制定以拥堵为重点的风险评分。实验室数据在入院时收集。患者在基线时接受了 4 区和子集 8 区体检、肺部超声 (LUS) 和超声心动图检查。一部分患者在出院前进行了第二次 LUS。主要终点是心衰住院或全因死亡的复合终点。在 350 名患者（中位年龄 75 岁，43% 为女性）中，88 名参与者 (25%) 住院或出院后 90 天内死亡。逐步 Cox 回归模型选择了复合结果的四个显着独立预测因子，每个因子都被分配与其回归系数成比例的分数：NT-proBNP ≥2000 pg/mL（入院）（3 分），收缩压 < 120 mmHg（基线） ）（2 分），左心房容积指数≥60 mL/m（基线）（1 分），且出院前 4 区 LUS ≥ 9 条 B 线（3 分）。该风险评分为综合结果提供了充分的风险区分（每增加 1 分，HR 1.48，95% 置信区间：1.32–1.67，< 0.001，C 统计量：0.70）。在具有 8 区 LUS 数据的患者子集中 (= 176)，结果相似（C 统计量：0.72）。如果在未来的研究中得到验证，整合临床、实验室和超声数据的四变量风险评分可能会为 AHF 患者 90 天不良结果的风险区分提供一种简单的方法。