Host Response in Critically Ill Patients Aged 65 Years or Older: A Prospective Study

Abstract

Introduction: The host response is a common pathway for all critical illness. Aging, a global trend, leads to changes in host response, which might be crucial for diagnosis and therapy in intensive care unit. Methods All patients aged 65 years or older admitted to our geriatric intensive care unit were included in the study. Demographic, clinical and medication data were collected from the electronic medical records system. The primary endpoint was in-hospital mortality, while secondary endpoints included length of in-hospital stay (LOS), and length of ICU stay. Generalized Additive Mix Model was used to conduct analysis, and nomogram analysiswas used to establish a prediction model for mortality. Results A total of 1, 204 patients admitted to our geriatric ICU (GICU) during the study period. Their mediam age was 75 years, while the maximum age was 110 years old. Host response biomarkers were relatively lower in those very old patients (VOPs, over the age of 85). White blood cell (WBC), lactate dehydrogenase (LDH), interleukin-10 (IL-10), and tumor necrosis factor-α (TNF-α) were positively associated with mortality, while platelet-to-lymphocyte ratio (PLR) was negatively associated with mortality. Lymphocyte count was a risk factor for mortality, risk ratio (RR) 1.2181. Elevated host response biomarkers were negatively associated with length of in-hospital stay and ICU stay. The prediction model combining all the host response biomarkers had an ideal predictive performance. Conclusion Our study discovered that age significantly affects the host response in critically ill patients. Critically ill older patients generally had lower levels of host response biomarkers accompanied by a higher level of mortality, especially in VOPs. Some host response biomarkers were positively associated with in-hospital mortality, and a predictive model was constructed to comprehensively evaluate the prognosis of critically ill older patients by including these inflammation, immunity, and coagulation with good predictive value.