A radiomics nomogram model for predicting prognosis of pancreatic ductal adenocarcinoma after high-intensity focused ultrasound surgery.

OBJECTIVE: To develop and validate a radiomics nomogram for predicting the survival of patients with pancreatic ductal adenocarcinoma (PDAC) after receiving high-intensity focused ultrasound (HIFU) treatment. METHODS: A total of 52 patients with PDAC were enrolled. To select features, the least absolute shrinkage and selection operator algorithm were applied, and the radiomics score (Rad-Score) was obtained. Radiomics model, clinics model, and radiomics nomogram model were constructed by multivariate regression analysis. The identification, calibration, and clinical application of nomogram were evaluated. Survival analysis was performed using Kaplan-Meier (K-M) method. RESULTS: According to conclusions made from the multivariate Cox model, Rad-Score, and tumor size were independent risk factors for OS. Compared with the clinical model and radiomics model, the combination of Rad-Score and clinicopathological factors could better predict the survival of patients. Patients were divided into high-risk and low-risk groups according to Rad-Score. K-M analysis showed that the difference between the two groups was statistically significant (p < 0.05). In addition, the radiomics nomogram model indicated better discrimination, calibration, and clinical practicability in training and validation cohorts. CONCLUSION: The radiomics nomogram effectively evaluates the prognosis of patients with advanced pancreatic cancer after HIFU surgery, which could potentially improve treatment strategies and promote individualized treatment of advanced pancreatic cancer.

Development and validation of a simple-to-use nomogram for predicting minimal change disease based on quantification of color Doppler sonography data from a region of interest.

OBJECTIVES: To establish a simple-to-use nomogram based on quantification of color Doppler sonography data from a region of interest (ROI) to diagnose minimal change disease (MCD) promptly and non-invasively, and to evaluate the prediction capability of the nomogram. METHODS: We recruited 564 patients with pathology-proven renal disease who were admitted to our hospital from July 2020 to July 2021 (388 patients in the training dataset and 176 patients in the validation dataset), and their color Doppler sonography data were acquired from a ROI and underwent ipsilateral renal biopsy. The collected clinical features and ultrasonic features were imported into Rstuido and statistically significant features were selected by stepwise regression using the forward-backward method. Multivariate Logistic regression analysis was combined with clinical analysis to obtain the final modeling features. General and dynamic nomogram models were constructed with the selected features, depending on whether they were MCD or not. Bootstrapping and internal validation were used for internal and external validation of the nomogram, respectively. The performance of the nomogram was assessed by C-index, calibration curve, and receiver operating characteristic (ROC) curve. RESULTS: Age and VI were independent factors in predicting MCD. The value of Age (Best cut-off value: 33.5 years) combined with VI (Best cut-off value: 40.50 points) in the diagnosis of MCD was significantly higher than that of single diagnosis (AUC 0.901, 95% CI 0.863-0.938). The C-index of the nomogram constructed with age and VI in the training and validation datasets was 0.915 [95% confidence interval (CI) 0.874-0.956 and 0.875 95% CI 0.783-0.967], respectively. Calibration curves were fitted well. The sensitivity, specificity, and accuracy were 76.1%, 95.6%, and 78.3%, respectively, in the training dataset, and 74.1%, 94.4%, and 76.1% in the validation dataset, respectively. CONCLUSION: The nomogram constructed with age and VI showed a satisfactory degree of differentiation and accuracy, which is of great significance for early, non-invasively, and individually analysis of the risk of MCD.

Nomogram model for predicting early onset of chronic kidney disease using color Doppler region of interest technique.

PURPOSE: The risk factors of chronic kidney disease were analyzed by using the region of interest quantitative technology of color Doppler combined with QLab software, and a Nomogram was established to conduct an individualized assessment of patients with chronic kidney disease. METHODS: A total of 500 patients with chronic kidney disease diagnosed in our hospital from June 2019 to March 2021 were selected as the chronic kidney disease group, and 300 healthy patients during the same period were selected as the control group. Univariate analysis was performed on the test indexes and the vascularity index, flow index, and vascularization flow index measured by the color doppler region of interest quantitative technique. The above meaningful indicators were included in the Logistics regression analysis to obtain the independent risk factors of early chronic kidney disease. The independent risk factors were imported into R software to draw a Nomogram model for predicting early chronic kidney disease and evaluate the model. RESULTS: Single factor analysis results suggest age, hypertension, diabetes, hyperlipidemia, disease of heart head blood-vessel, body mass index, vascularity index, flow index, and vascularization flow index, fasting blood sugar, triglyceride, total cholesterol, urea nitrogen, creatinine, uric acid, glomerular filtration rate differences statistically significant (P < 0.05). Logistics regression analysis showed that hypertension, diabetes, flow index, and vascularization flow index, urea nitrogen, and albumin were independent risk factors for the early occurrence of chronic kidney disease. The C-index of this Nomogram using independent risk factors is 0.896 (95%CI 0.862-0.930), which indicates that the Nomogram has good discriminant power. The receiver operating curve of the histograph was area under the curve (AUC) 0.884 (95%CI 0.860-0.908). The receiver operator characteristic curve (ROC) of urea nitrogen, albumin, flow index, and vascularization flow index were evaluated. The results indicated that the best cutoff value of urea nitrogen was 5.9 mmol/L, flow index was 14.67, vascularization flow index was 4.6, and albumin was 40.26 g/L. CONCLUSION: In the prediction of chronic kidney disease I-II stage, the quantitative technique of color Doppler region of interest has certain diagnostic value. The model established in this study has good discriminative power and can be applied to clinical practice, giving certain indicative significance.

Effect of body mass index on symptomatic venous thromboembolism and prosthesis revision risk after total knee arthroplasty: a long-term study from China.

OBJECTIVE: To investigate the effect of body mass index (BMI) on the risk of symptomatic VTE and prosthesis revision after total knee arthroplasty (TKA). METHODS: Seven thousand one hundred eighty-two patients with primary unilateral TKA treated in our hospital from 2011 to 2020 were divided into four groups according to BMI: BMI < 25 kg/m2, BMI 25 kg/m2-29.9 kg/m2, BMI 30 kg/m2-34.9 kg/m2 and BMI ≥ 35 kg/m2. Incidence, Odds ratio and Kaplan-Meier survival analysis were used to evaluate the effects of BMI on symptomatic VTE and prosthesis revision risk after TKA. RESULTS: The incidence of VTE after TKA was 8.9‰(64/7182). There was no significant difference in the incidence of VTE among different BMI groups(P = 0.452). Deep vein thrombosis mainly occurred in the distal lower extremities, especially in intermuscular veins. Revision rate of prosthesis after TKA was 6.4‰(46/7182). There was no significant difference in revision rate among different BMI groups(P = 0.718). In the univariate analysis of TKA, compared with patients with normal BMI, the risk of postoperative VTE and prosthesis revision in patients with overweight, obesity class I and obesity class II did not increase. Higher prosthesis revision rate and lower prosthesis survival rate were observed in BMI ≥ 35 kg/m2 group, although the difference was not statistically significant. CONCLUSIONS: Through such a retrospective large sample data of long-term follow-up, we believe that the higher BMI was not associated with the increased risk of symptomatic VTE and prosthesis revision after TKA. When TKA was used for appropriate indications, high BMI should not be considered as a contraindication.