简介：AbstractBackground:Rebleeding can cause a catastrophic outcome after aneurysmal subarachnoid hemorrhage. A clinical + morphology nomogram was promoted in our previous study to assist in discriminating the rupture intracranial aneurysms (RIAs) with a high risk of rebleeding. The aim of this study was to validate the predictive accuracy of this nomogram model.Method:The patients with RIAs in two medical centers from December 2020 to September 2021 were retrospectively reviewed, whose clinical and morphological parameters were collected. The Cox regression model was employed to identify the risk factors related to rebleeding after their admission. The predicting accuracy of clinical + morphological nomogram, ELAPSS score and PHASES score was compared based on the area under the curves (AUCs).Results:One hundred thirty-eight patients with RIAs were finally included in this study, 20 of whom suffering from rebleeding after admission. Hypertension (hazard ratio (HR), 2.54; a confidence interval of 95% (CI), 1.01-6.40; P = 0.047), bifurcation (HR, 3.88; 95% CI, 1.29-11.66; P = 0.016), and AR (HR, 2.68; 95% CI, 1.63-4.41; P < 0.001) were demonstrated through Cox regression analysis as the independent risk factors for rebleeding after admission. The clinical + morphological nomogram had the highest predicting accuracy (AUC, 0.939, P < 0.01), followed by the bifurcation (AUC, 0.735, P = 0.001), AR (AUC, 0.666, P = 0.018), and ELAPSS score (AUC, 0.682, P = 0.009). Hypertension (AUC, 0.693, P = 0.080) or PHASES score (AUC, 0.577, P = 0.244) could not be used to predict the risk of rebleeding after admission. The calibration curve for the probability of rebleeding showed a good agreement between the prediction through clinical + morphological nomogram and actual observation.Conclusion:Hypertension, bifurcation site, and AR were independent risk factors related to the rebleeding of RIAs after admission. The clinical + morphological nomogram could help doctors to identify the high-risk RIAs with a high predictive accuracy.

简介：AbstractBackground:Delayed graft function (DGF) is the main cause of renal function failure after kidney transplantation. This study aims at investigating the value of hypothermic machine perfusion (HMP) parameters combined with perfusate biomarkers on predicting DGF and the time of renal function recovery after deceased donor (DD) kidney transplantation.Methods:HMP parameters, perfusate biomarkers and baseline characteristics of 113 DD kidney transplantations from January 1, 2019 to August 31, 2019 in the First Affiliated Hospital of Xi’an Jiaotong University were retrospectively analyzed using univariate and multivariate logistic regression analysis.Results:In this study, the DGF incidence was 17.7% (20/113); The multivariate logistic regression results showed that terminal resistance (OR: 1.879, 95% CI 1.145-3.56) and glutathione S-transferase (GST)(OR = 1.62, 95% CI 1.23-2.46) were risk factors for DGF; The Cox model analysis indicated that terminal resistance was an independent hazard factor for renal function recovery time (HR = 0.823, 95% CI 0.735-0.981). The model combining terminal resistance and GST (AUC = 0.888, 95% CI: 0.842-0.933) significantly improved the DGF predictability compared with the use of terminal resistance (AUC = 0.756, 95% CI 0.693-0.818) or GST alone (AUC = 0.729, 95% CI 0.591-0.806).Conclusion:According to the factors analyzed in this study, the combination of HMP parameters and perfusate biomarkers displays a potent DGF predictive value.

简介：AbstractBackground:The CHA2DS2–VASc score was initially applied to stratify stroke risk in patients with atrial fibrillation (AF) and was found to be effective in predicting all-cause mortality outcomes. To date, it is still unclear whether circulating long non-coding RNAs (lncRNAs) as emerging biomarkers, can improve the predictive power of the CHA2DS2–VASc score in stroke and all-cause mortality.Methods:Candidate lncRNAs were screened by searching the literature and analyzing previous RNA sequencing results. After preliminary verification in 29 patients with AF, the final selected lncRNAs were evaluated by Cox proportional hazards regression in 192 patients to determine whether their relative expression levels were associated with stroke and all-cause mortality. The c-statistic, net reclassification improvement (NRI), and integrated discrimination improvement of the patients were calculated to evaluate the discrimination and reclassification power for stroke and all-cause mortality when adding lncRNA expression levels to the CHA2DS2–VASc score model.Results:Five plasma lncRNAs associated with stroke and all-cause mortality in AF patients were selected in our screening process. Patients with elevated H19 levels were found to have a higher risk of stroke (hazard ratio [HR] 3.264, 95% confidence interval [CI]: 1.364–7.813, P = 0.008). Adding the H19 expression level to the CHA2DS2–VASc score significantly improved the discrimination and reclassification power of the CHA2DS2–VASc score for stroke in AF patients. In addition, the H19 level showed a marginally significant association with all-cause mortality (HR 2.263, 95% CI: 0.889–5.760, P = 0.087), although it appeared to have no significant improvement for the CHA2DS2–VASc model for predicting all-cause mortality.Conclusions:Plasma expression of H19 was associated with stroke risk in AF patients and improved the discriminatory power of the CHA2DS2–VASc score. Therefore, lncRNA H19 served as an emerging non-invasive biomarker for stroke risk prediction in patients with AF.