ObjectiveSplenectomy is a vital treatment method for hypersplenism with portal hypertension. However, portal venous system thrombosis (PVST) is a serious problem after splenectomy. Therefore, constructing an effective visual risk prediction model is important for preventing, diagnosing, and treating early PVST in hepatolenticular degeneration (HLD) surgical patients.MethodsBetween January 2016 and December 2021, 309 HLD patients were selected. The data were split into a development set (215 cases from January 2016 to December 2019) and a validation set (94 cases from January 2019 to December 2021). Patients’ clinical characteristics and laboratory examinations were obtained from electronic medical record system, and PVST was diagnosed using Doppler ultrasound. Univariate and multivariate logistic regression analyses were used to establish the prediction model by variables filtered by LASSO regression, and a nomogram was drawn. The area under the curve (AUC) of receiver operating characteristic (ROC) curve and Hosmer–Lemeshow goodness-of-fit test were used to evaluate the differentiation and calibration of the model. Clinical net benefit was evaluated by using decision curve analysis (DCA). The 36-month survival of PVST was studied as well.ResultsSeven predictive variables were screened out using LASSO regression analysis, including grade, POD14D-dimer (Postoperative day 14 D-dimer), POD7PLT (Postoperative day 7 platelet), PVD (portal vein diameter), PVV (portal vein velocity), PVF (portal vein flow), and SVD (splenic vein diameter). Multivariate logistic regression analysis revealed that all seven predictive variables had predictive values (P < 0.05). According to the prediction variables, the diagnosis model and predictive nomogram of PVST cases were constructed. The AUC under the ROC curve obtained from the prediction model was 0.812 (95% CI: 0.756–0.869) in the development set and 0.839 (95% CI: 0.756–0.921) in the validation set. Hosmer–Lemeshow goodness-of-fit test fitted well (P = 0.858 for development set; P = 0.137 for validation set). The nomogram model was found to be clinically useful by DCA. The 36-month survival rate of three sites of PVST was significantly different from that of one (P = 0.047) and two sites (P = 0.023).ConclusionThe proposed nomogram-based prediction model can predict postoperative PVST. Meanwhile, an earlier intervention should be performed on three sites of PVST.

Objective The aim of this study was to examine the predictive value of the multiplication of neutrophil and monocyte counts (MNM) in peripheral blood, and develop a new predictive model for the prognosis of patients with aneurysmal subarachnoid hemorrhage (aSAH). Methods This is a retrospective analysis that included 2 separate cohorts of patients undergoing endovascular coiling for aSAH. The training cohort consisted of 687 patients in the First Affiliated Hospital of Shantou University Medical College; the validation cohort consisted of 299 patients from Sun Yat‐sen University's Affiliated Jieyang People's Hospital. The training cohort was used to develop 2 models to predict unfavorable prognosis (modified Rankin scale of 3–6 at 3 months): one was based on traditional factors (e.g., age, modified Fisher grade, NIHSS score, and blood glucose), and another model that included traditional factors as well as MNM on admission. Results In the training cohort, MNM upon admission was independently associated with unfavorable prognosis (odds ratio after adjustment, 1.06; 95% confidence interval [CI], 1.03–1.10). In the validation cohort, the basic model that included only traditional factors had 70.99% sensitivity, 84.36% specificity, and 0.859 (95% CI, 0.817–0.901) area under the receiver operating characteristic curve (AUC). Adding MNM increased model sensitivity (from 70.99% to 76.48%), specificity (from 84.36% to 88.63%), and overall performance (AUC 0.859 [95% CI, 0.817–0.901] to 0.879 [95% CI, 0.841–0.917]). Interpretation MNM upon admission is associated with unfavorable prognosis in patients undergoing endovascular embolization for aSAH. The nomogram including MNM is a user‐friendly tool to help clinicians quickly predict the outcome of patients with aSAH.

ObjectiveSplenectomy is one crucial solution for hypersplenism with portal hypertension. However, portal vein system thrombosis (PVST) caused by hemodynamic changes affects the prognosis of patients. We analyze the changes in portal vein hemodynamics following splenectomy for Wilson’s disease combined with portal hypertension and the influencing factors that lead to PVST.MethodsA retrospective cohort study was conducted, in which 237 Wilson’s disease patients with hypersplenism underwent splenectomy. The hemodynamic indices of the portal vein were monitored before surgery and on the 1st, 7th, and 14th days around surgery. The patients were divided into PVST and non-PVST groups. The clinical factors were identified by univariate and multivariate logistic regression. The Logit P was calculated according to the logistic regression prediction model, and the ROC curve for each independent factor was plotted.ResultsThe portal vein velocity, flow, and inner diameter showed a downward trend around surgery, with statistically significant differences between each time point (P < 0.01). The PVST incidence rate was 55.7%. Univariate analysis revealed that the platelet (PLT) levels on the postoperative 3rd and 7th days (P = 0.001; P < 0.001), D-dimer (D-D) on the postoperative 7th and 14th days (P = 0.002; P < 0.001), preoperative portal vein velocity, flow, diameter (P < 0.001), and splenic vein diameter (P < 0.001) were all statistically and significantly different between the two groups. Multivariate logistic regression revealed a significant increase in PLT on the postoperative 7th day (OR = 1.043, 95% CI, 1.027–1.060, P < 0.001) and D-D on the postoperative 14th day (OR = 1.846, 95% CI, 1.400–2.435, P < 0.001). Preoperative portal and splenic vein diameters (OR = 1.565, 95% CI, 1.213–2.019, P = 0.001; OR = 1.671, 95% CI, 1.305–2.140, P < 0.001) were the risk factors for PVST. However, preoperative portal vein velocity and flow (OR = 0.578, 95% CI, 0.409–0.818, P = 0.002; OR = 0.987, 95% CI, 0.975–0.990, P = 0.046) were protective factors for PVST. Logit P was calculated using a logistic regression prediction model with a cut-off value of −0.32 and an area under receiver operating characteristic curve of 0.952 with 88.61% accuracy.ConclusionsSplenectomy relieves portal hypertension by reducing the hemodynamics index. PVST is linked to multiple factors, including preoperative portal vein diameter, velocity, flow, and splenic vein diameter, especially PLT on the postoperative 7th day and D-D on the postoperative 14th day. The predictive model is accurate in predicting PVST.