Development and Validation of a Prediction Model for Incident Hypothyroidism in a National Chronic Kidney Disease Cohort
| العنوان: | Development and Validation of a Prediction Model for Incident Hypothyroidism in a National Chronic Kidney Disease Cohort |
|---|---|
| المؤلفون: | Connie M Rhee, Amy S You, Yoko Narasaki, Gregory A Brent, John J Sim, Csaba P Kovesdy, Kamyar Kalantar-Zadeh, Danh V Nguyen |
| المصدر: | The Journal of Clinical Endocrinology & Metabolism. |
| بيانات النشر: | The Endocrine Society, 2023. |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | Endocrinology, Endocrinology, Diabetes and Metabolism, Biochemistry (medical), Clinical Biochemistry, Biochemistry |
| الوصف: | Context Hypothyroidism is a common yet under-recognized condition in chronic kidney disease (CKD) patients, which may lead to end-organ complications if left untreated. Objective We developed a prediction tool to identify CKD patients at-risk for incident hypothyroidism. Methods Among 15,642 patients with stages 4-5 CKD without evidence of pre-existing thyroid disease, we developed and validated a risk prediction tool for the development of incident hypothyroidism (defined as TSH > 5.0mIU/L) using the Optum Labs Data Warehouse, which contains de-identified administrative claims, including medical and pharmacy claims and enrollment records for commercial and Medicare Advantage enrollees as well as electronic health record data. Patients were divided into a two-thirds development set and a one-third validation set. Prediction models were developed using Cox models to estimate probability of incident hypothyroidism. Results There were 1650 (11%) cases of incident hypothyroidism during a median follow-up of 3.4 years. Characteristics associated with hypothyroidism included: older age, White race, higher BMI, low serum albumin, higher baseline TSH, hypertension, congestive heart failure, exposure to iodinated contrast via angiogram or CT scan, and amiodarone use. Model discrimination was good with similar C-statistics in the development and validation datasets: 0.77 (95%CI) 0.75-0.78 and 0.76 (95%CI) 0.74-0.78, respectively. Model goodness-of-fit (GOF) tests showed adequate fit in the overall cohort (p = 0.47) as well as in a subcohort of stage 5 CKD patients (p = 0.33). Conclusion In a national cohort of CKD patients, we developed a clinical prediction tool identifying those at-risk for incident hypothyroidism to inform prioritized screening, monitoring, and treatment in this population. |
| تدمد: | 1945-7197 0021-972X |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::222af6b2a7af64994936620ed229d95d https://doi.org/10.1210/clinem/dgad261 |
| حقوق: | CLOSED |
| رقم الأكسشن: | edsair.doi...........222af6b2a7af64994936620ed229d95d |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 19457197 0021972X |
|---|