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Optimizing Levothyroxine Replacement: A Precision Dosage Model for Post-Thyroidectomy Patients.

Authors :
Yang G
Pu J
Zhu S
Shi Y
Yang Y
Mao J
Sun Y
Zhao B
Source :
International journal of general medicine [Int J Gen Med] 2024 Feb 01; Vol. 17, pp. 377-386. Date of Electronic Publication: 2024 Feb 01 (Print Publication: 2024).
Publication Year :
2024

Abstract

Background: Thyroidectomy is commonly performed for benign or malignant thyroid tumors, often resulting in hypothyroidism. Levothyroxine (LT4) supplementation is crucial to maintain hormone levels within the normal range and suppress TSH for cancer control. However, determining the optimal dosage remains challenging, leading to uncertain outcomes and potential side effects.<br />Methods: We analyzed clinical examination data from 510 total thyroidectomy patients, including demographic information, blood tests, and thyroid function. Using R, we applied data preprocessing techniques and identified 274 samples with 98 variables. Principal Component Analysis, correlation analysis, and regression analysis were conducted to identify factors associated with optimal LT4 dosage.<br />Results: The analysis revealed that only eight variables significantly influenced the final satisfactory dosage of LT4 in tablets: Benign0/Malignant1 (benign or malignant), BQB (electrophoretic albumin ratio), TP (total protein), FDP (fibrin degradation products), TRAB_1 (thyroid-stimulating hormone receptor antibody), PT (prothrombin time), MONO# (monocyte count), and HCV0C (hepatitis C antibody). The resulting predictive model was: .<br />Conclusion: Parameters such as benign/malignant status, TRAB_1, and BQB ratio during medication can serve as observational indicators for postoperative LT4 dosage. The calculated linear model can predict the LT4 dosage for patients after thyroidectomy, leading to improved treatment effectiveness and conserving medical resources.<br />Competing Interests: The authors declare no competing interests in this work.<br /> (© 2024 Yang et al.)

Details

Language :
English
ISSN :
1178-7074
Volume :
17
Database :
MEDLINE
Journal :
International journal of general medicine
Publication Type :
Academic Journal
Accession number :
38322508
Full Text :
https://doi.org/10.2147/IJGM.S438397