Patients with chronic kidney disease (CKD) frequently experience hypothyroidism, which, if undertreated, can have adverse effects on the end organs.

Researchers have developed a prediction tool created and validated to determine the likelihood of incident hypothyroidism in a representative, current cohort of US people with moderate-to-advanced chronic kidney disease (CKD).

The researchers examined data from 15 642 patients with stages 4 to 5 CKD who had no signs of thyroid dysfunction before the study. One thousand six hundred fifty patients (10.5%) experienced incident hypothyroidism throughout their median 3.4-year follow-up. Two-thirds of the cohort (10,428) were utilized to create the prediction model, while the final third (5214) was used for internal validation.

Older age, higher body mass index, low serum albumin, higher baseline TSH, hypertension, congestive heart failure, exposure to iodinated contrast through angiography or computed tomography scan, and use of amiodarone were linked to hypothyroidism. Higher baseline TSH levels and amiodarone use accounted for the highest increase in the likelihood of incident hypothyroidism.

The models discrimination was intense, resulting in comparable C-statistics in the validation datasets C-statistic of 0.76 and the development datasets C-statistic of 0.77, indicating that the model accounts for roughly 76%–77% of the causes of incident hypothyroidism in these patients.

This practical risk-prediction tool, which the researchers claim could be embedded for automated analysis in an electronic health record (EHR), can help the clinical management of these patients by identifying those who require prioritized screening, serial monitoring, and long-term treatment of hypothyroidism. The results may lead to an improvement in the standard of care for CKD patients.

(Source:https://www.medscape.com/viewarticle/993205?src=#vp_1)