Efficacy of Urine Asymmetric Dimethylarginine Concentration to Predict Azotemia in Hyperthyroid Cats After Radio-Iodine Treatment

尿液中不对称二甲基精氨酸浓度预测甲状腺功能亢进猫放射性碘治疗后氮质血症的有效性

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Abstract

BACKGROUND: Hyperthyroidism can mask concurrent chronic kidney disease in cats, and no accurate biomarkers are available to predict which cats will develop renal azotemia after radioiodine ((131)I) treatment. HYPOTHESIS/OBJECTIVES: To evaluate the potential of serum and urinary metabolites and metabolite ratios to predict post-(131)I renal azotemia in hyperthyroid cats. ANIMALS: Hyperthyroid cats (n = 31), before and (3-12 months) after treatment with (131)I at the Faculty of Veterinary Medicine (Ghent University, Belgium). METHODS: Retrospective study. Optimized and validated feline extraction and analysis protocols were employed for metabolic profiling of urine and serum samples using ultra-high performance liquid chromatography-high-resolution mass spectrometry. A dual strategy of cross-validated univariate and penalized multivariate logistic regression was applied to determine predictivity (i.e., area under the curve [AUC], accuracy, sensitivity, and specificity) of individual biomarkers and panels. RESULTS: All hyperthyroid cats were non-azotemic before (131)I administration. After (131)I treatment, 7 cats became persistently (≥ 2 timepoints) azotemic while 24 remained non-azotemic. Urinary asymmetric dimethylarginine (ADMA) was identified as a pivotal predictor of post-(131)I azotemia in both univariate and multivariate modeling. When employed as a standalone biomarker, an AUC of 0.851, accuracy of 0.903, sensitivity of 0.714, and specificity of 0.958 were achieved. While pre-treatment USG was significantly different (P = 0.002) between both groups, it did not show enhanced prediction over ADMA, nor in multivariate modeling. CONCLUSIONS AND CLINICAL IMPORTANCE: Urinary ADMA can accurately predict post-(131)I azotemia in hyperthyroid cats becoming euthyroid after (131)I treatment. These findings can aid clinicians in managing owner expectations and modify treatment plans.

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