Scholarlink

Objective <p>To evaluate the predictive utility of the initial lactate-to-albumin ratio (LAR) measured within 24&#xa0;h of admission for in-hospital all-cause mortality in critically ill patients with congestive heart failure (CHF) and diabetes mellitus (DM).</p> Methods <p>A retrospective cohort study was performed using the Medical Information Mart for Intensive Care IV (MIMIC-IV; <i>n</i> = 960) and the eICU Collaborative Research Database (eICU-CRD; <i>n</i> = 1,850). Kaplan–Meier curves, Cox regression, restricted cubic splines (RCS), subgroup analyses, and five machine learning models were applied, with predictive performance assessed via receiver operating characteristic (ROC), calibration curves, and decision curve analysis (DCA).</p> Results <p>The highest LAR quartile (Q4) was associated with higher in-hospital mortality (MIMIC-IV: 50.83%; eICU-CRD: 29.71%) than lower quartiles (all <i>P</i> &lt; 0.001). LAR was identified as an independent predictor of in-hospital mortality (MIMIC-IV: HR = 1.878, <i>P</i> = 0.009; eICU-CRD: HR = 3.141, <i>P</i> &lt; 0.001). A nonlinear positive association between LAR and in-hospital mortality was demonstrated by RCS (<i>P</i> &lt; 0.001), with inflection points at 2.73 in MIMIC-IV and 2.50 in eICU-CRD. For both outcomes, higher discriminative performance was observed for LAR than for lactate alone in both cohorts. Model performance was further improved when incorporating into machine learning models.</p> Conclusion <p>Initial LAR is a reliable predictor of in-hospital mortality in critically ill CHF-DM patients.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Lactate-albumin ratio predicts in-hospital mortality in critically Ill patients with congestive heart failure and diabetes

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月25日

查看全文
  • Xiang Huang,
  • Liang Zhao,
  • Zhenxin Feng,
  • Weihua Cai

摘要

Objective

To evaluate the predictive utility of the initial lactate-to-albumin ratio (LAR) measured within 24 h of admission for in-hospital all-cause mortality in critically ill patients with congestive heart failure (CHF) and diabetes mellitus (DM).

Methods

A retrospective cohort study was performed using the Medical Information Mart for Intensive Care IV (MIMIC-IV; n = 960) and the eICU Collaborative Research Database (eICU-CRD; n = 1,850). Kaplan–Meier curves, Cox regression, restricted cubic splines (RCS), subgroup analyses, and five machine learning models were applied, with predictive performance assessed via receiver operating characteristic (ROC), calibration curves, and decision curve analysis (DCA).

Results

The highest LAR quartile (Q4) was associated with higher in-hospital mortality (MIMIC-IV: 50.83%; eICU-CRD: 29.71%) than lower quartiles (all P < 0.001). LAR was identified as an independent predictor of in-hospital mortality (MIMIC-IV: HR = 1.878, P = 0.009; eICU-CRD: HR = 3.141, P < 0.001). A nonlinear positive association between LAR and in-hospital mortality was demonstrated by RCS (P < 0.001), with inflection points at 2.73 in MIMIC-IV and 2.50 in eICU-CRD. For both outcomes, higher discriminative performance was observed for LAR than for lactate alone in both cohorts. Model performance was further improved when incorporating into machine learning models.

Conclusion

Initial LAR is a reliable predictor of in-hospital mortality in critically ill CHF-DM patients.