Prognostic Value of Thyroid Profile in Critical Care Condition.

Background: Patients suffering from critical illness admitted to the Intensive Care Unit (ICU) exhibit alterations in their thyroid hormone levels, collectively termed as euthyroid sick syndrome or nonthyroidal illness syndrome. Our study was conducted to determine the correlation between these changes in thyroid hormone levels and the prognosis of ICU-admitted patients.

Methods: A total of 270 ICU-admitted patients without previous history of thyroid disorder were included in the study. We recorded their baseline characteristics, acute physiology and chronic health evaluation (APACHE-II) score, thyroid hormone levels, lactate, and other parameters on admission. ICU mortality was the primary outcome. We analyzed the ability of each parameter to predict mortality in the participants. Further, we also evaluated whether the combination of thyroid hormone levels with APACHE-II score could improve the mortality prediction.

Results: The mean age of the study population was 38.99 ± 18.32 years. A total of 81 patients (30%) expired during their ICU treatment. Both fT3 and fT4 levels were lower in nonsurvivors compared to survivors. Among the thyroid hormones, fT3 had the highest predictive value for ICU mortality, as seen by the largest area under the curve (AUC) value (0.990 ± 0.007) which was even greater than AUC of APACHE-II score (0.824 ± 0.051) and fT4 (0.917 ± 0.049). Univariate logistic regression analysis showed that fT3 (β = 140.560) had the highest predictive potential for ICU mortality compared with APACHE-II score (β = 0.776), fT4 (β = 17.62) and other parameters. Multivariate logistic regression analysis revealed that the combination of fT3 and APACHE-II (R = 0.652) was superior in predicting mortality than APACHE-II alone (R = 0.286).

Conclusion: We observed that fT3 was the strongest predictor of ICU mortality compared to all other parameters included in our study. Further, the combination of fT3 levels and APACHE-II scores provided for a higher probability for predicting mortality in ICU patients.