Objective To evaluate the multi-spiral CT(MSCT)imaging features and classification of renal pelvis carcinoma.Meth-ods 76 patients of renal pelvis carcinoma proved pathologically were analyzed retrospectively,and divided into different types ac-cording to the MSCT features.The MSCT differences for different types were analyzed.Results Most of the tumors showed iso-density or slight hyperdensity (95%)on un-enhanced images,and persistent mild-to-moderate enhancement (91%)in enhanced im-ages.All cases were divided into three types:pelvic mass type in 30 cases (39%),substance invasion type in 25 cases (33%),wall thickening type in 21 cases (28%).All cases were also divided into two types:substance invasion type(25 cases,33%)and renal pelvis type(5 1 cases,67%).The occurrence rate of local low enhancement,whole kidney low enhancement,hydronephrosis,lymph node metastasis and vein tumor thrombus were 80%,20%,48%,52%,1 6% in substance invasion type cases,and 4%,42%, 75%,4%,6% in the renal pelvis type cases,respectivily.Conclusion MSCT multiphase enhancement scanning shows important valuation in the diagnosis and classification of renal pelvis carcinoma.Obvious differences of CT features are showed for different types.The diagnosis accuracy may be improved by the knowledge of substance invasion type.

Objective:To establish and validate a predictive model for treatment failure of peritoneal dialysis-related peritonitis(PDAP)in elderly patients.Methods:Clinical data of peritoneal dialysis(PD)patients who were followed up from January 1, 2013 to December 31, 2019 at four Grade A tertiary hospitals in Jilin Province were collected.A total of 362 elderly patients with PDAP were eventually included as study subjects.Subjects recruited from 2013 to 2017 were used for model construction and the logistic regression model was used to screen risk factors for treatment failure of PDAP in elderly patients.A nomogarm was constructed to predict treatment failure of secondary PDAP using R language.The receiver operating curve(ROC)and calibration curve were used to evaluate discrimination accuracy of the model.Subjects from 2018 to 2019 were used as the cohort for validation of discrimination accuracy of the model.Results:Of 258 PDAP patients in the modeling cohort, 29 experienced treatment failure, including 15 PDAP-related deaths and 14 cases requiring catheter removal.The multivariate logistic regression model showed that types of pathogens( OR=8.849, 95% CI: 1.656-47.269, P=0.011), long dialysis age( OR=1.023, 95% CI: 1.005-1.042, P=0.013), pre-hospitalization antibiotic treatment( OR=5.123, 95% CI: 1.338-19.610, P=0.017), and dialysate white blood cell count on day 5>100×10 6/L( OR=7.085, 95% CI: 2.162-23.217, P=0.001)were independent risk factors for treatment failure of PDAP in elderly patients.For the nomogarm predictive model, the areas under the ROC curve(AUC)in the modeling cohort and the validation cohort were 0.818(95% CI: 0.735-0.902)and 0.762(95% CI: 0.656-0.889), respectively, and the calibration curves were close to a straight line with a slope of 1. Conclusions:Our nomogram predictive model based on types of pathogens, months of dialysis, pre-hospital admission antibiotic treatment, and dialysate white blood cell count on day 5 has demonstrated satisfactory discrimination accuracy for treatment failure of PDAP in elderly patients.