Development of a prediction score (ThyroCOVID) for identifying abnormal thyroid function in COVID-19 patients

Area of Science:

• Endocrinology
• Infectious Diseases
• Internal Medicine

Background:

• Thyroid dysfunction is a significant concern in COVID-19 patients, impacting clinical outcomes and prognosis.
• Early identification of thyroid function abnormalities is crucial for timely management.

Purpose of the Study:

• To develop and validate a prediction score, named ThyroCOVID, for identifying abnormal thyroid function (TFT) upon admission in COVID-19 patients.
• To assess the clinical and laboratory predictors of abnormal TFT in the context of COVID-19.

Main Methods:

• Prospective recruitment of COVID-19 patients, measuring thyroid-stimulating hormone (TSH), free thyroxine (fT4), and free triiodothyronine (fT3) on admission.
• Multivariable logistic regression analysis to identify independent determinants of abnormal TFTs.
• Development of the ThyroCOVID score using a clinical model that minimized the Akaike information criteria.

Main Results:

• Out of 546 COVID-19 patients, 15.4% exhibited abnormal TFTs on admission.
• Abnormal TFTs were associated with older age, comorbidities, symptomatic presentation, increased COVID-19 severity, higher viral loads, and altered acute-phase reactants.
• The ThyroCOVID score, incorporating symptoms, comorbidities (ischaemic heart disease/congestive heart failure), and laboratory parameters (lymphocyte count, C-reactive protein, SARS-CoV-2 cycle threshold), achieved an AUROC of 0.73 for predicting abnormal TFTs.

Conclusions:

• The ThyroCOVID score effectively identifies COVID-19 patients at risk for abnormal thyroid function on admission.
• This score was developed and validated in a cohort primarily consisting of non-severe COVID-19 cases.
• ThyroCOVID offers a valuable tool for risk stratification and management of thyroid dysfunction in COVID-19 patients.