Objective To evaluate the diagnostic significance and to analyze reasons of false negative cases forpreoperative ultrasonography， 99Tcm-sestamibi scintigraphy （MIBI scintigraphy）， and CT in primary hyperparathyroidism（PHPT）. Methods Clinical data of 69 patients with PHPT， who underwent operation in Affiliated Shengjing Hospital of China Medical University between Jan. 2003 and Aug. 2012 were retrospectively analyzed. Results There were 76 parathyroid lesions in 69 PHPT patients proved by operation and pathology， including 58 cases of parathyroid adenoma with 60 lesions， 7 cases of parathyroid hyperplasia with 11 lesions， and 4 cases of parathyroid carcinoma with 5 lesions. The sensitivity of ultrasonography， CT， and 99Tcm-MIBI scintigraphy were 81.94% （59/72）， 61.76% （21/34）， and 69.57% （16/23）， the accuracy of 3 kinds of tests were 78.67% （59/75）， 61.76% （21/34）， and 66.67% （16/24）， the positive predictive value were 95.16% （59/62）， 100% （21/21）， and 94.12% （16/17） respectively. There was significant differ-ence only between ultrasonography and CT in sensitivity （P=0.03）， no other significant difference was found （P＞0.05）.Conclusions Ultrasonography is complementary to 99Tcm-MIBI scintigraphy， but CT has little significance in diagnosis of PHPT. Both of ultrasonography and 99Tcm-MIBI scintigraphy should be used before operation routinely to localize parathyroid lesions.
Objective The purpose of this study was to establish and validate a risk prediction model for post-thrombotic syndrome (PTS) in patients after interventional treatment for acute lower extremity deep vein thrombosis (LEDVT). MethodsA retrospective study was conducted to collect data from 234 patients with acute LEDVT who underwent interventional treatment at Xuzhou Central Hospital between December 2017 and June 2022, serving as the modeling set. Factors influencing the occurrence of PTS were analyzed, and a nomogram was developed. An additional 98 patients from the same period treated at Xuzhou Tumor Hospital were included as an external validation set to assess the reliability of the model. ResultsAmong the patients used to establish the model, the incidence of PTS was 25.2% (59/234), while in the validation set was 31.6% (31/98). Multivariate logistic regression analysis of the modeling set identified the following factors as influencing PTS: age (OR=1.076, P=0.001), BMI (OR=1.163, P=0.004), iliac vein stent placement (OR=0.165, P<0.001), history of varicose veins (OR=5.809, P<0.001), and preoperative D-dimer level (OR=1.341, P<0.001). These 5 factors were used to construct the risk prediction model. The area under the ROC curve (AUC) of the model was 0.869 [95%CI (0.819, 0.919)], with the highest Youden index of 0.568, corresponding to a sensitivity of 79.7% and specificity of 77.1%. When applied to the validation set, the AUC was 0.821 [95%CI (0.734, 0.909)], with sensitivity of 77.4%, specificity of 76.1%, and accuracy of 76.6%. ConclusionsThe risk prediction model for PTS established in this study demonstrates good predictive performance. The included parameters are simple and practical, providing a useful reference for clinicians in the preliminary screening of high-risk PTS patients.