Association Between Body Temperature and In-Hospital Mortality Among Congestive Heart Failure Patients with Diabetes in Intensive Care Unit: A Retrospective Cohort Study.
Kai ZhangYu HanFangming GuZhaoxuan GuJiaYing LiangJiaYu ZhaoJianguo ChenBowen ChenMin GaoZhengyan HouXiaoqi YuTianyi CaiYafang GaoRui HuJinyu XieTianzhou LiuBo LiPublished in: Therapeutic hypothermia and temperature management (2023)
Body temperature (BT) has been utilized to assess patient outcomes across various diseases. However, the impact of BT on mortality in the intensive care unit (ICU) among patients with congestive heart failure (CHF) and diabetes mellitus (DM) remains unclear. We conducted a retrospective cohort study using data from the Medical Information Mart for Intensive Care (MIMIC)-IV data set. The primary outcome assessed was in-hospital mortality rates. BT was treated as a categorical variable in the analyses. The association between BT on ICU admission and in-hospital mortality was examined using multivariable logistic regression models, restricted cubic spline, and subgroup analysis. The cohort comprised 7063 patients with both DM and CHF (3135 females and 3928 males), with an average age of 71.5 ± 12.2 years. Comparative analysis of the reference group (Q4) revealed increased in-hospital mortality in Q6 and Q1 temperature groups, with fully adjusted odds ratios of 2.08 (95% confidence interval [CI]: 1.45-2.96) and 1.95 (95% CI: 1.35-2.79), respectively. Restricted cubic spline analysis demonstrated a U-shaped relationship between temperature on admission and mortality risk ( p nonlinearity <0.001), with the nadir of risk observed at 36.8°C. The effect sizes and corresponding CIs below and above the threshold were 0.581 (95% CI: 0.434-0.777) and 1.674 (95% CI: 1.204-2.328), respectively. Stratified analyses further validated the robustness of this correlation. Our study establishes a nonlinear association between BT and in-hospital mortality in patients with both CHF and DM, with optimal suitable BT at 36.8°C. Further research is necessary to confirm this relationship.
Keyphrases
- intensive care unit
- heart failure
- emergency department
- mechanical ventilation
- healthcare
- electronic health record
- glycemic control
- left ventricular
- risk factors
- type diabetes
- atrial fibrillation
- big data
- coronary artery disease
- cardiovascular events
- clinical trial
- skeletal muscle
- metabolic syndrome
- insulin resistance
- data analysis
- health information
- deep learning
- acute respiratory distress syndrome
- artificial intelligence
- double blind