Table_1_A novel web-based calculator to predict 30-day all-cause in-hospital mortality for 7,202 elderly patients with heart failure in ICUs: a multicenter retrospective cohort study in the United States.docx

Background and aimsHeart failure (HF) is a significant cause of in-hospital mortality, especially for the elderly admitted to intensive care units (ICUs). This study aimed to develop a web-based calculator to predict 30-day in-hospital mortality for elderly patients with HF in the ICU and found a relationship between risk factors and the predicted probability of death.Methods and resultsData (N = 4450) from the MIMIC-III/IV database were used for model training and internal testing. Data (N = 2,752) from the eICU-CRD database were used for external validation. The Brier score and area under the curve (AUC) were employed for the assessment of the proposed nomogram. Restrictive cubic splines (RCSs) found the cutoff values of variables. The smooth curve showed the relationship between the variables and the predicted probability of death. A total of 7,202 elderly patients with HF were included in the study, of which 1,212 died. Multivariate logistic regression analysis showed that 30-day mortality of HF patients in ICU was significantly associated with heart rate (HR), 24-h urine output (24h UOP), serum calcium, blood urea nitrogen (BUN), NT-proBNP, SpO2, systolic blood pressure (SBP), and temperature (P < 0.01). The AUC and Brier score of the nomogram were 0.71 (0.67, 0.75) and 0.12 (0.11, 0.15) in the testing set and 0.73 (0.70, 0.75), 0.13 (0.12, 0.15), 0.65 (0.62, 0.68), and 0.13 (0.12, 0.13) in the external validation set, respectively. The RCS plot showed that the cutoff values of variables were HR of 96 bmp, 24h UOP of 1.2 L, serum calcium of 8.7 mg/dL, BUN of 30 mg/dL, NT-pro-BNP of 5121 pg/mL, SpO2 of 93%, SBP of 137 mmHg, and a temperature of 36.4°C.ConclusionDecreased temperature, decreased SpO2, decreased 24h UOP, increased NT-proBNP, increased serum BUN, increased or decreased SBP, fast HR, and increased or decreased serum calcium increase the predicted probability of death. The web-based nomogram developed in this study showed good performance in predicting 30-day in-hospital mortality for elderly HF patients in the ICU.

背景与目标：心力衰竭（HF）是住院死亡率的重要原因，尤其是对于入住重症监护室（ICUs）的老年患者。本研究旨在开发一款基于网络的计算器，以预测入住ICU的老年心力衰竭患者的30天住院死亡率，并发现风险因素与死亡预测概率之间存在关联。方法与结果：本研究采用了来自MIMIC-III/IV数据库的4450份数据用于模型训练和内部测试，以及来自eICU-CRD数据库的2752份数据用于外部验证。采用了Brier分数和曲线下面积（AUC）来评估所提出的评分图。限制性三次样条（RCSs）用于确定变量的截断值。平滑曲线展示了变量与死亡预测概率之间的关系。研究共纳入了7,202例心力衰竭的老年患者，其中1,212例死亡。多变量逻辑回归分析显示，入住ICU的心力衰竭患者的30天死亡率与心率（HR）、24小时尿量（24h UOP）、血清钙、血尿素氮（BUN）、NT-proBNP、SpO2、收缩压（SBP）和体温（P < 0.01）显著相关。评分图在测试集和外部验证集中的AUC和Brier分数分别为0.71（0.67，0.75）和0.12（0.11，0.15），以及0.73（0.70，0.75）、0.13（0.12，0.15）、0.65（0.62，0.68）和0.13（0.12，0.13）。RCS图显示了变量的截断值，包括心率96 bmp、24小时尿量1.2 L、血清钙8.7 mg/dL、BUN 30 mg/dL、NT-pro-BNP 5121 pg/mL、SpO2 93%、收缩压137 mmHg和体温36.4°C。结论：体温降低、SpO2降低、24小时尿量降低、NT-proBNP升高、血清BUN升高、血压升高或降低、心率加快以及血清钙升高或降低均会增加死亡预测概率。本研究开发出的基于网络的评分图在预测入住ICU的老年心力衰竭患者的30天住院死亡率方面表现出良好的性能。