(1) Objective: To reveal the correlation between the hemoglobin-to-red cell distribution width ratio (HRR) and all-cause mortality (ACM) among the septic patients with atrial fibrillation. (2) Methods: Specific clinical information was collected from the Medical Information Mart for Intensive IV (MIMIC-IV) database. The optimal cut-off value of HRR was calculated through ROC curve analysis conducted by using the maximum Youden index for the prediction of survival status. In addition, univariable and multivariable Cox regressive analyses were carried out to assess the prognostic significance of HRR and the Kaplan-Meier (K-M) analysis was conducted to draw the survival curves. Then, the 1:1 propensity score matching (PSM) method was adopted to improve the reliability of research result while balancing the unintended influence of underlying confounders. (3) Results: There were 9228 patients participating in this retrospective cohort study. The optimal cut-off value of the HRR was determined as 5.877 for in-hospital mortality. The PSM was performed to identify 2931 pairs of score-matched patients, with balanced differences exhibited by nearly all variables. According to the K-M analysis, those patients with a lower HRR than 5.877 showed a significantly higher level of in-hospital mortality, 28-day mortality, and 90-day mortality, compared to the patients with HRR ≥ 5.877 (p < 0.001). After the adjustment of possible confounders, those patients whose HRR was below 5.877 had a significantly higher level of in-hospital mortality than the patients with HRR ≥ 5.877, as revealed by the multivariable Cox regression analysis (HR = 1.142, 95%CI: 1.210–1.648, p < 0.001). Similarly, the ACM remained substantially higher in those patients with a lower HRR than in the patients with higher HRR after PSM. (4) Conclusion: A lower HRR (<5.877) was evidently associated with an increased risk of ACM, which made it applicable as a prognostic predictor of clinical outcomes for those septic patients with atrial fibrillation.

Ischemic stroke is a common type of stroke that significantly affects human well-being and quality of life. In order to further characterize the pathophysiology of ischemic stroke and develop new treatment strategies, ischemic stroke models with controllable and consistent response to potential clinical treatments are urgently needed. The middle cerebral artery occlusion (MCAO) model is currently the most widely used animal model of ischemic stroke. This review discusses various methods for constructing the MCAO model and compares their advantages and disadvantages in order to provide better approaches for studying ischemic stroke.

(1) Background: To explore the correlation between the blood urea nitrogen to creatinine ratio (UCR) and in-hospital mortality in non-traumatic subarachnoid hemorrhage patients. (2) Methods: Specific clinical information was collected from the Medical Information Mart for Intensive Ⅳ (MIMIC-Ⅳ) database. The optimal cut-off value of the UCR was calculated with ROC curve analysis conducted using the maximum Youden index for the prediction of survival status. Univariable and multivariable logistic regression analyses were also carried out to assess the prognostic significance of UCR, and the Kaplan–Meier (K–M) analysis was conducted to draw the survival curves. Then, the 1:1 propensity score matching (PSM) method was applied to improve the reliability of the research results while balancing the unintended influence of underlying confounders. (3) Results: This retrospective cohort study included 961 patients. The optimal cut-off value of the UCR for in-hospital mortality was 27.208. The PSM was performed to identify 92 pairs of score-matched patients, with balanced differences exhibited for nearly all variables. According to the K–M analysis, those patients with a UCR of more than 27.208 showed a significantly higher level of in-hospital mortality compared to the patients with a UCR of less than 27.208 (p < 0.05). After the adjustment for possible confounders, those patients whose UCR was more than 27.208 still had a significantly higher level of in-hospital mortality than the patients whose UCR was less than 27.208, as revealed by the multivariable logistic regression analysis (OR = 3.783, 95% CI: 1.959~7.305, p < 0.001). Similarly, the in-hospital mortality remained substantially higher for those patients in the higher UCR group than for the patients in the lower UCR group after PSM. (4) Conclusion: A higher level of the UCR was evidently associated with an increased risk of in-hospital mortality, which made the ratio useful as a prognostic predictor of clinical outcomes for those patients with non-traumatic subarachnoid hemorrhage.