Analysis of the Correlation Between Perioperative Temperature Trajectory and All-Cause Mortality in Elderly Cardiac Patients

Background Hypothermia following cardiac surgery can result in negative postoperative outcomes. This study aimed to identify distinct temperature trajectories using Latent Class Trajectory Modeling in elderly cardiac patients during the first three days after surgery and to assess their correlation with all-cause mortality. Methods This retrospective cohort study selected elderly patients who underwent cardiac surgery from the MIMIC-IV (Medical Information Mart for Intensive Care IV) database. The Latent Class Trajectory Model (LCTM) was employed to classify heterogeneous patterns of temperature changes in patients following cardiac surgery over a three-day period. Then, differences in survival across the trajectory groups were analyzed using Kaplan-Meier survival curves. The Cox regression model was used to analyze the relationship between patients' temperature trajectories post-cardiac surgery and their risk of death within one year. A subgroup analysis was performed to identify interaction factors and evaluate the robustness of this finding. Results A total of 1,995 cardiac surgery patients were included in the analysis. Five distinct temperature trajectory groups were identified: Group 1, the Low-Temperature Rising Group (293 patients, 14.69%); Group 2, the Low-Temperature Stable Group (318 patients, 15.94%); Group 3, the Decline-Recovery Group (86 patients, 4.31%); Group 4, the Moderate-Temperature Stable Group (892 patients, 44.71%); and Group 5, the Moderate-Temperature Rising Group (406 patients, 20.35%). Kaplan-Meier analysis showed that patients in Group 1 had the lowest in-hospital and one-year mortality rates. When Group 1 was used as the reference, Group 3 exhibited the highest risk, followed by Group 2, Group 4, and then Group 5. Subgroup analysis showed that the one-year mortality rate was higher in Group 3 patients and remained stable across different complication groups. Conclusion Classifying elderly cardiac patients by their perioperative temperature trajectories helps predict all-cause mortality risk. This predictive ability is robust across patients with different comorbidities, enabling personalized treatment strategies. Trial registration: Not applicable.