Name of journal: American journal of surgeryAbstract: BACKGROUND: We employed Machine Learning (ML) to evaluate potential additional clinical factors influencing replacement dosage requirements of levothyroxine.CONCLUSIONS: Along with weight, sex, age, and BMI, ML algorithms indicated that race, ethnicity, lifestyle and comorbidity factors also may impact levothyroxine dosing in post-thyroidectomy patients with benign conditions. Copyright © 2022 Elsevier Inc. All rights reserved.METHOD: This was a retrospective study of patients who underwent total or completion thyroidectomy with benign pathology. Patients who achieved an euthyroid state were included in three different ML models.RESULTS: Of the 487 patients included, mean age was 54.1 +/- 14.1 years, 86.0% were females, 39.0% were White, 53.0% Black, 2.7% Hispanic, 1.4% Asian, and 3.9% Other. The Extreme Gradient Boosting (XGBoost) model achieved the highest accuracy at 61.0% in predicting adequate dosage compared to 47.0% based on 1.6 mcg/kg/day (p < 0.05). The Poisson regression indicated non-Caucasian race (p < 0.05), routine alcohol use (estimate = 0.03, p = 0.02), and osteoarthritis (estimate = -0.10, p < 0.001) in addition to known factors such as age (estimate = -0.003, p < 0.001), sex (female, estimate = -0.06, p < 0.001), and weight (estimate = 0.01, p < 0.001) were associated with the dosing of levothyroxine.All authors: Zheng HFiscal year: FY2023 Digital Object Identifier:

https://dx.doi.org/10.1016/j.amjsurg.2022.11.025

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Item type	Current library	Collection	Call number	Status	Date due	Barcode
Journal Article	MedStar Authors Catalog	Article	36464545	Available		36464545

BACKGROUND: We employed Machine Learning (ML) to evaluate potential additional clinical factors influencing replacement dosage requirements of levothyroxine.

CONCLUSIONS: Along with weight, sex, age, and BMI, ML algorithms indicated that race, ethnicity, lifestyle and comorbidity factors also may impact levothyroxine dosing in post-thyroidectomy patients with benign conditions. Copyright © 2022 Elsevier Inc. All rights reserved.

METHOD: This was a retrospective study of patients who underwent total or completion thyroidectomy with benign pathology. Patients who achieved an euthyroid state were included in three different ML models.

RESULTS: Of the 487 patients included, mean age was 54.1 +/- 14.1 years, 86.0% were females, 39.0% were White, 53.0% Black, 2.7% Hispanic, 1.4% Asian, and 3.9% Other. The Extreme Gradient Boosting (XGBoost) model achieved the highest accuracy at 61.0% in predicting adequate dosage compared to 47.0% based on 1.6 mcg/kg/day (p < 0.05). The Poisson regression indicated non-Caucasian race (p < 0.05), routine alcohol use (estimate = 0.03, p = 0.02), and osteoarthritis (estimate = -0.10, p < 0.001) in addition to known factors such as age (estimate = -0.003, p < 0.001), sex (female, estimate = -0.06, p < 0.001), and weight (estimate = 0.01, p < 0.001) were associated with the dosing of levothyroxine.

English