The prognostic utility of serum thyrotropin in hospitalized Covid-19 patients: statistical and machine learning approaches

• Published in: Endocrine 2023-04, Vol.80 (1), p.86-92
• Main Authors: Pappa, E., Gourna, P., Galatas, G., Manti, M., Romiou, A., Panagiotou, L., Chatzikyriakou, R., Trakas, N., Feretzakis, G., Christopoulos, C.
• Format: Article
• Language: English
• Subjects: Accuracy; Albumin; Bayes Theorem; Biomarkers; Coronaviruses; COVID-19; Diabetes; Endocrinology; Ferritin; Hospital Mortality; Humanities and Social Sciences; Humans; Internal Medicine; Learning algorithms; Machine Learning; Medicine; Medicine & Public Health; multidisciplinary; Neural networks; Original; Original Article; Prognosis; Regression analysis; Retrospective Studies; Science; Thyroid diseases; Thyroid-stimulating hormone; Thyrotropin
• ISSN: 1559-0100; 1355-008X; 1559-0100
• DOI: 10.1007/s12020-022-03264-9

Purpose To assess the prognostic value of serum TSH in Greek patients with COVID-19 and compare it with that of commonly used prognostic biomarkers. Methods Retrospective study of 128 COVID-19 in patients with no history of thyroid disease. Serum TSH, albumin, CRP, ferritin, and D-dimers were measured at admission. Outcomes were classified as “favorable” (discharge from hospital) and “adverse” (intubation or in-hospital death of any cause). The prognostic performance of TSH and other indices was assessed using binary logistic regression, machine learning classifiers, and ROC curve analysis. Results Patients with adverse outcomes had significantly lower TSH compared to those with favorable outcomes (0.61 versus 1.09 mIU/L, p