Abstract
Abstract
Background
Radioisotope scanning is important to diagnose subacute thyroiditis (SAT), but it’s not always available. So we aim to establish a diagnostic scale for SAT without radioisotope scanning.
Methods
The suspected SAT patients hospitalized in Yuebei people’s Hospital from January 2012 to December 2016 were selected and divided into study group and control group according to whether they were diagnosed as SAT. The clinical indexes of two groups were collected and the diagnostic scale of SAT was established by using binary logistic regression analysis. The effectiveness of the scale was evaluated by ROC curve.
Results
Of 309 patients, 58.25% of patients were confirmed with SAT and the remaining 41.75% of patients were not diagnosed with SAT. After univariate analysis, variables which were considered statistically different(P < 0. 05) between the two groups were selected as independent variables and the diagnosis of SAT was taken as dependent variable in the binary logistic regression model. The logistic regression model consisted of 4 variables, each was thyroid tenderness, firm on palpation, increased ESR and elevated thyroid hormone level. The P value of Omnibus tests was≤0. 001 and the Nagelkerke R Square was 0. 915. The diagnostic scoring scale was established with these four variables according to their regression coefficient. The area under the ROC curve for this diagnostic scale was 0. 991(95% confidence interval, 0. 982–0.999). The highest Youden index was 0. 912, the corresponding cut-off point was 7. Internally validation shows a sensitivity of 92. 78% and a specificity of 98.45% of our scale.
Conclusions
We established and validated a diagnostic scale for SAT without the need for radioisotope scanning for the first time. It has good application in institutions that do not have radioisotope machines or among pregnant and lactating women.
Funder
Shaoguan Health Research Project
Shaoguan Science and Technology Plan Project
Publisher
Springer Science and Business Media LLC
Subject
General Medicine,Endocrinology, Diabetes and Metabolism
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