Objective To explore the predictive efficacy of XGboost model in predicting risk of relapse and re-admission within 90 d in patients with ischemic stroke,and provide basis for early screening and prevention of high-risk population with ischemic stroke.Methods The clinical data of 6070 primary ischemic stroke patients admitted to our hospital from January 2007 to July 2017 were retrospectively collected.XGboost model and multivariate Logistic regression model were utilized to screen out the influencing factors of relapse and re-admission within 90 d in patients with ischemic stroke.A predictive model was set up.Receiver operating characteristic (ROC) curve was drawn and compared.Sensitivity,specificity and Youden index were calculated and compared to evaluate the prediction performance of XGboost model.Results During the observation period,a total of 520 patients with relapsed ischemic stroke were observed within a period of 90 d,and the incidence density was 8.57％.Multivariate Logistic regression analysis showed that length of first hospital stay,hypertension,pulmonary infection,neutrophil percentage,red blood cell distribution width (variable coefficient),and alkaline phosphatase level were independent influencing factors for re-hospitalization within 90 d of ischemic stroke,(OR=1.016,P=0.000,95％CI:1.008-1.025;OR=4.598,P=0.000,95％CI:3.717-5.687;OR=1.452,P=0.025,95％CI:1.048-2.012;OR=1.013,P=0.006,95％CI:1.004-1.022;OR=1.161,P=0.000,95％CI:1.090-1.237;OR=1.003,P=0.023,95％CI:1.000-1.005).Analysis of importance of risk factors for re-admission of ischemic stroke using XGboost model showed that the top 6 factors were hypertension,red blood cell distribution width,direct bilirubin,length of hospital stay,pulmonary infection,and alkaline phosphatase,and the corresponding importance scores were 32,20,19,18,15 and 14,respectively.ROC curve analysis results indicated that the area under the ROC for re-admission for XGboost model was 0.792 (95％CI:0.717-0.762),which was improved by 5％ as compared with that for multivariate Logistic regression model (0.739 [95％CI:0.764-0.818]).The sensitivity was 89.30％ and the Youden index was 0.444 for XGboost model,which were significantly higher than those for multivariate Logistic regression model (77.3％,0.405).Conclusions XGboost model is superior to multivariate Logistic regression model in predicting recurrence and re-admission of first ischemic stroke patients within 90 d.This model is suitable for prediction and early diagnosis of re-admission of ischemic stroke,which is of great clinical value.

Objective:To explore the features and application value of MRI in the spectrum of fetal cloaca malformation.Methods:The clinical, MRI and ultrasound data of 6 fetuses with spectrum of cloaca malformation were retrospectively analyzed in Guangzhou Women and Children′s Medical Center Affiliated to Guangzhou Medical University from January 2017 to February 2021, and the MRI features of each subtype were analyzed.Results:Among the 6 fetuses of spectrum of the cloaca malformation, 5 were confirmed by postnatal imaging and surgery, and 1 was confirmed by induced labor autopsy, including 3 persistent cloaca, 1 posterior cloaca, 1 cloaca variant, and 1 urogenital sinus. The high signal on T 1WI of the rectal meconium disappeared or became weaker, and the signal on T 2WI of meconium of the dilated colon increased in the 3 cases of persistent cloaca and 1 case of posterior cloaca. All 6 cases showed colonic dilatation. All cases except 1 persistent cloaca showed vaginal and/or uterine effusion. Two cases of persistent cloaca, 1 case of posterior cloaca and 1 case of cloaca variant showed duplicated genital tract. Two cases of persistent cloaca showed only 1 perineal opening, which opened at the urethral orifice. One case of cloaca variant showed 2 openings, which opened at the urethral orifice and in front of the normal anus, respectively. Conclusion:Prenatal MRI can help to clarify the diagnosis of cloacal malformation spectrum and to determine its specific classification.

Objective: To investigate the efficacy and safety of using pegylated recombinant human granulocyte-colonystimulating factor (PEG-rhG-CSF) in preventing neutropenia in multiple chemotherapy cycles. Methods: A multicenter, prospective, open-label, singlearmstudy was designed. Patients with malignant tumors, such as lung, ovarian, and colorectal cancers, who received multiple cycles of chemotherapy with the prophylactic use of PEG-rhG-CSF for 2-4 consecutive cycles participated in the study. Results: After the prophylactic use of PEG-rhG-CSF, the incidence of grade IV neutropenia decreased from 4.76% (13/273) in the first cycle to 1.83% (5/273), 1.15% (2/174), and 2.08% (2/96) in subsequent cycles. Meanwhile, the incidence of grade III neutropenia decreased from 11.36% (31/ 273) in the first cycle to 6.23% (17/273), 2.87% (5/174), and 3.13% (3/96) in subsequent cycles. The incidence of febrile neutropenia (FN) during the first cycle was 0.73% (2/273). The duration of FN was 2 days in one case and 5 days in another case. FN was not observed during the second, third, or fourth cycle. After the secondary prophylactic use of PEG-rhG-CSF, the incidence of grade IV neutropenia decreased from 25% (7/28) to 3.57% (1/28), 0% (0/28), and 6.67% (1/15) in subsequent cycles. Meanwhile, the incidence of grade III neutropenia decreased from 71.43% (20/28) to 10.71% (3/28), 14.29% (4/28), and 0% (0/15) in subsequent cycles. The proportion of patients who received antibiotic therapy during the entire chemotherapy period was 10.48% (44/420). Conclusion: The application of PEG-rhG-CSF once per chemotherapy cycle can effectively reduce the occurrence of neutropenia in patients under multiple cycles of chemotherapy treatment with good safety.