Nomogram including indirect bilirubin for the prediction of post-stroke depression at 3 months after mild acute ischemic stroke onset.

Background: Post-stroke depression (PSD) has been proven to be associated with stroke severity. Thus, we hypothesized that the prevalence of PSD would be lower in patients with mild stroke. We aim to explore predictors of depression at 3 months after mild acute ischemic stroke (MAIS) onset and to develop a practical and convenient prediction model for the early identification of patients at high risk. Methods: A total of 519 patients with MAIS were consecutively recruited from three hospitals in Wuhan city, Hubei province. MAIS was defined as a National Institute of Health Stroke Scale (NIHSS) score of ≤5 at admission. Meeting the DSM-V diagnostic criteria and a 17-item Hamilton Rating Scale for Depression (HAMD-17) score of >7 at their 3-month follow-up were considered the primary outcomes. A multivariable logistic regression model was used to determine the factors adjusted for potential confounders, and all independent predictors were brought into the construction of a nomogram to predict PSD. Results: The prevalence of PSD is up to 32% at 3 months after MAIS onset. After adjusting for potential confounders, indirect bilirubin (p = 0.029), physical activity (p = 0.001), smoking (p = 0.025), hospitalization days (p = 0.014), neuroticism (p < 0.001), and MMSE (p < 0.001) remained independently and significantly related with PSD. The concordance index (C-index) of the nomogram jointly constructed by the aforementioned six factors was 0.723 (95% CI: 0.678-0.768). Conclusion: The prevalence of PSD seems equally high even if the ischemic stroke is mild, which calls for great concern from clinicians. In addition, our study found that a higher level of indirect bilirubin can lower the risk of PSD. This finding may provide a potential new approach to PSD treatment. Furthermore, the nomogram including bilirubin is convenient and practical to predict PSD after MAIS onset.

A web based dynamic MANA Nomogram for predicting the malignant cerebral edema in patients with large hemispheric infarction.

BACKGROUND: For large hemispheric infarction (LHI), malignant cerebral edema (MCE) is a life-threatening complication with a mortality rate approaching 80%. Establishing a convenient prediction model of MCE after LHI is vital for the rapid identification of high-risk patients as well as for a better understanding of the potential mechanism underlying MCE. METHODS: One hundred forty-two consecutive patients with LHI within 24 h of onset between January 1, 2016 and August 31, 2019 were retrospectively reviewed. MCE was defined as patient death or received decompressive hemicraniectomy (DHC) with obvious mass effect (≥ 5 mm midline shift or Basal cistern effacement). Binary logistic regression was performed to identify independent predictors of MCE. Independent prognostic factors were incorporated to build a dynamic nomogram for MCE prediction. RESULTS: After adjusting for confounders, four independent factors were identified, including previously known atrial fibrillation (KAF), midline shift (MLS), National Institutes of Health Stroke Scale (NIHSS) and anterior cerebral artery (ACA) territory involvement. To facilitate the nomogram use for clinicians, we used the "Dynnom" package to build a dynamic MANA (acronym for MLS, ACA territory involvement, NIHSS and KAF) nomogram on web ( http://www.MANA-nom.com ) to calculate the exact probability of developing MCE. The MANA nomogram's C-statistic was up to 0.887 ± 0.041 and the AUC-ROC value in this cohort was 0.887 (95%CI, 0.828 ~ 0.934). CONCLUSIONS: Independent MCE predictors included KAF, MLS, NIHSS, and ACA territory involvement. The dynamic MANA nomogram is a convenient, practical and effective clinical decision-making tool for predicting MCE after LHI in Chinese patients.

Predictors of malignant cerebral edema in cerebral artery infarction: A meta-analysis.

Malignant cerebral edema (MCE) is a life-threatening complication of acute cerebral stroke. To date, the focus has been on symptomatic treatment, rather than on prevention. Therefore, to identify high-risk patients and explore potential therapeutic approaches, we investigated the possible predictors of MCE. Specifically, we performed a meta-analysis to identify the potential predictors of MCE in patients with acute cerebral infarction. We searched the MEDLINE, Embase, Cochrane, China National Knowledge Infrastructure, Wanfang Data, and VIP databases from their inception to July 2018 for cohort and case control studies on the predictors of MCE in patients with cerebral infarction. Forty-seven eligible studies containing a total of 45,826 patients were included. Our results suggest that the risk of MCE is higher in case of severe clinical symptoms and large infarct volumes. Additionally, male sex, older age, and a history of stroke and smoking were protective factors against MCE in cerebral infarction patients. Furthermore, thrombolytic therapy and recanalization substantially decreased the risk of MCE in patients with acute stroke. Higher admission temperature (in the subgroup with admission ≤12 h after onset), higher admission blood pressure, and admission leukocytes were also MCE predictors. Our findings facilitate the early prediction of MCE and may contribute to potential therapeutic approaches.