Abstract
Background: Free thyroid hormone levels were analyzed in critically ill patients, admitted to the ICU who were more than 18 years of age without any underlying thyroid illness. APACHE 2, FT3, FT4, and TSH levels were analyzed and compared using ROC curves. Aim of the study: To assess whether free thyroid hormone levels were better predictors of outcomes compared to existing tools. Study design: This is a prospective observational study undertaken in the Department of General medicine at Sri Ramachandra institute of higher education and research, Chennai, Tamilnadu has done between 2019 to 2021 with the approval from the ethics committee. A total of 70 critically ill patients were admitted to the ICU, who were more than 18 years of age without any underlying thyroidal illness. Patients with known thyroid disease, pregnancy, and drugs causing alteration of thyroid hormone levels were excluded from the study. Blood samples were collected immediately after admission and APACHE 2 scores were calculated within 24 hours of admission. Parameters were analyzed using various statistical methods. Results: A total of 70 patients were included in the study, of which 63 were survivors and 7 patients expired. Most of the study population were males (45) and the mean age of the survivors 49.71 ± 10.72 was and for nonsurvivors was 54.29 ± 15.07. Using the Pearson correlation in APACHE 2 and FT3, APACHE 2 and FT4 showed a statistically signicant correlation in survivors (P 0.02; P 0.05), while in non-survivors only APACHE 2 and FT3 showed a signicant correlation ( P 0.008). Using ROC curves, APACHE 2 alone showed signicant predictive validity in predicting mortality in critically ill patients in our study ( AUC 0.985; P <0.001). Conclusion: In our study combined APACHE 2 and FT3 showed a signicant correlation in both survivors and non-survivors as well. APACHE 2 has better predictive value compared to other parameters and FT3 alone did not have predictive validity. So large sample is required to test the value of free thyroid hormones in predicting outcomes in critically ill patients.
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