Nomogram Including Neutrophil-to-Lymphocyte Ratio for the Prediction of Stroke-Associated Infections.

Stroke has been a leading cause of mortality in China. Stroke-associated infections (SAI) are common complications, occurring in 5-65% of stroke patients. Faced with SAI, clinicians often are placed in a considerable dilemma. On the one hand, preventive overuse of antibiotics will lead to the emergence of drug-resistant bacteria. On the other hand, treatment delay of the infection will likely result in a poor outcome. Therefore, it is necessary to determine the early predictors of post-stroke infection to screen patients with high infection risk for early clinical intervention, thereby promoting and improving survival rates. We assessed 257 patients with acute ischemic stroke from a consecutive retrospective cohort. Data of these patients were obtained from three hospitals (TongJi Hospital and its two branches) between August 2018 and June 2019. Of these patients, 59 (23.0%) developed SAI. SAI was defined according to the modified Centers for Disease Control and Prevention criteria. There were 38 patients (64.4%) who developed pneumonia, 11 with urinary tract infections (18.6%), and 10 with other infections (16.9%). We found that a higher neutrophil-to-lymphocyte ratio (adjusted odds ratio [aOR] = 1.16; 95% confidence interval [CI], 1.01-1.33; P = 0.034), National Institutes of Health Stroke Scale score (aOR = 1.18; CI, 1.09-1.27; p < 0.001), and dysphagia (aOR = 2.95; CI, 1.40-6.22; P = 0.004) were risk factors for SAI. Of note, hypertriglyceridemia (aOR = 0.35; CI, 0.13-0.90; P = 0.029) was a protective factor, lowering the risk of SAI. To this end, a reliable nomogram was constructed for the prediction of SAI in our study (mean C-index value ± standard deviation = 0.821 ± 0.03). It has the potential to be widely used and may help identify patients at high risk for SAI and make timely clinical decisions. Given our study was based on relatively small dataset, the results should be interpreted with care and external validation in independent datasets is very necessary.

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.

COVID-19 in Wuhan: Sociodemographic characteristics and hospital support measures associated with the immediate psychological impact on healthcare workers.

BACKGROUND: The outbreak of COVID-19 has laid unprecedented threats and challenges to health workers (HWs) in Wuhan, China. We aimed to assess the sociodemographic characteristics and hospital support measures associated with the immediate psychological impact on HWs at Tongji Hospital in Wuhan during COVID-19 outbreak. METHODS: We conducted a single-center, cross-sectional survey of HWs via online questionnaires between February 8th and 10th, 2020. We evaluated stress, depression and anxiety by IES-R, PHQ-9, and GAD-7, respectively. We also designed a questionnaire to assess the perceptions of threat of COVID-19, and the satisfactions of the hospital's support measures. Multivariate logistic regressions were used to identify associated variables of acute stress, depression, and anxiety. FINDINGS: We received 5062 completed questionnaires (response rate, 77.1%). 29.8%, 13.5% and 24.1% HWs reported stress, depression and anxiety symptoms. Women (odds ratio [OR], 1.31; 95% CI, 0.47-0.97; p = 0.032), years of working >10 years (OR, 2.02; 95% CI, 1.47-2.79; p<0.001), concomitant chronic diseases (OR, 1.51; 95% CI, 1.27-1.80; p<0.001), history of mental disorders (OR, 3.27; 95% CI, 1.77-6.05; p<0.001), family members or relatives confirmed or suspected (OR, 1.23; 95% CI, 1.02-1.48; p = 0.03), hospital-based and department-based care (OR, 0.76; 95% CI, 0.60-0.97; p = 0.024) and full coverage of all departments for avoiding nosocomial infection (OR, 0.69; 95% CI, 0.53-0.89; p = 0.004) were associated with stress. INTERPRETATION: Women and those who have more than 10 years of working, concomitant chronic diseases, history of mental disorders, and family members or relatives confirmed or suspected are susceptible to stress, depression and anxiety among HWs during the pandemic. In addition, since HWs often have a greater stigma against mental problems than the general public, it is worthwhile to address the needs of the HWs during this pandemic and to provide appropriate psychological supports for those people at high risk of mental problems.

Common and differentially expressed long noncoding RNAs for the characterization of high and low grade bladder cancer.

Our study aimed to explore long non-coding RNAs (lncRNAs) contributing to the development of bladder cancer, as well as to identify more critical DEGs and lncRNAs that would characterize low- and high-grade bladder cancer. The microarray data of GSE55433 was downloaded from Gene Expression Omnibus database, including 57 urothelial cancer samples (23 low-grade NMI, 14 high-grade NMI and 20 invasive tumors) and 26 normal controls. The differentially expressed genes (DEGs) and differentially expressed lncRNAs were identified in 3 groups (low-grade NMI vs. normal, high-grade NMI vs. normal and invasive UC vs. normal). Functional enrichment analysis was performed upon the DEGs in different groups. Besides, protein-protein interaction (PPI) network was constructed based on common DEGs and remaining DEGs in each group. Co-expression analysis was performed to identify the co-expressed DEG-lncRNAs pairs. Different number of DEGs and differentially expressed lncRNAs were respectively identified from those 3 groups. NONHSAG013805 (down-regulated) and NONHSAG009271 (down-regulated) were common lncRNAs. NONHSAG013805 was connected with the down-regulated gene EIF3E and NONHSAG009271 was linked to MYL12A (down-regulated). Moreover, NONHSAG034203 (up-regulated) was co-expressed with ADM5 (up-regulated) in low-grade NMI cancer, while the down-regulated NONHSAG045391 was connected with the down-regulated DEGs DAD1 and STUB1 in high-grade NMI cancer and invasive bladder cancer. Our study indicates that NONHSAG013805 and NONHSAG009271 may play key roles in bladder cancer via co-expressing with EIF3E and MYL12A, respectively. Moreover, NONHSAG034203 may be involved in low-grade NMI bladder cancer via targeting ADM5, while NONHSAG045391 may contribute to high-grade NMI and invasive bladder cancer via targeting DAD1 and STUB1.