Proteomic landscape subtype and clinical prognosis of patients with the cognitive impairment by Japanese encephalitis infection.

BACKGROUND: Cognitive impairment is one of the primary sequelae affecting the quality of life of patients with Japanese encephalitis (JE). The clinical treatment is mainly focused on life support, lacking of targeted treatment strategy. METHODS: A cerebrospinal fluid (CSF) proteomic profiling study was performed including 26 patients with JE in Gansu province of China from June 2017 to October 2018 and 33 other concurrent hospitalized patients who were excluded central nervous system (CNS) organic or CNS infection diseases. The clinical and proteomics data of patients with JE were undergoing combined analysis for the first time. RESULTS: Two subtypes of JE associated with significantly different prognoses were identified. Compared to JE1, the JE2 subtype is associated with lower overall survival rate and a higher risk of cognitive impairment. The percentages of neutrophils (N%), lymphocyte (L%), and monocytes (M%) decreased in JE2 significantly. CONCLUSIONS: The differences in proteomic landscape between JE subgroups have specificity for the prognosis of cognitive impairment. The data also provided some potential target proteins for treatment of cognitive impairments caused by JE. Trial registration ChiCTR, ChiCTR2000030499. Registered 1st June 2017, http://www.medresman.org.cn/pub/cn/proj/projectshow.aspx?proj=6333.

Performance evaluation of medical service for breast cancer patients based on diagnosis related groups.

BACKGROUND: To evaluate the performance of medical service for patients with breast cancer in Henan Province, China, using diagnosis related groups (DRGs) indicators and to provide data to inform practices and policies for the prevention and control of breast cancer. METHODS: The data were collected from the front pages of medical records (FPMR) of all hospitals above class II that admitted breast cancer patients in Henan Province between 2016 and 2019. Breast cancer patients were the subjects in our study. China DRGs (CN-DRGs) was used as a risk adjustment tool. Three indicators, including the case mix index (CMI), number of DRGs, and total weight, were used to evaluate the range of available services for patients with breast cancer, while indicators including the charge efficiency index (CEI), time efficiency index (TEI) and inpatient mortality of low-risk group cases (IMLRG) were used to evaluate medical service efficiency and medical safety. RESULTS: Between 2016 and 2019, there were 103,760 patients with breast cancer. The total weight increased over the study period at an average annual rate of 21.71%. The TEI decreased over the study period by 15.60%. The CEI exhibited an increasing trend, but the average annual rate of increase was small (2.94%). The IMLRP was 0.02, 0, 0 and 0.01% in 2016, 2017, 2018 and 2019, respectively. CONCLUSION: The performance of medical service improved between 2016 and 2019 for breast cancer patients discharged from study hospitals in Henan Province. The main area of improvement was in the range of available services, but medical institutions must still make efforts to improve the efficiency of medical services and ensure medical safety. DRGs is an effective evaluation tool.

Analysis of clinical features and early warning signs in patients with severe COVID-19: A retrospective cohort study.

Coronavirus disease 2019 (COVID-19) was first identified in Wuhan, China, in December 2019. Although previous studies have described the clinical aspects of COVID-19, few studies have focused on the early detection of severe COVID-19. Therefore, this study aimed to identify the predictors of severe COVID-19 and to compare clinical features between patients with severe COVID-19 and those with less severe COVID-19. Patients admitted to designated hospital in the Henan Province of China who were either discharged or died prior to February 15, 2020 were enrolled retrospectively. Additionally, patients who underwent at least one of the following treatments were assigned to the severe group: continuous renal replacement therapy, high-flow oxygen absorption, noninvasive and invasive mechanical ventilation, or extracorporeal membrane oxygenation. The remaining patients were assigned to the non-severe group. Demographic information, initial symptoms, and first visit examination results were collected from the electronic medical records and compared between the groups. Multivariate logistic regression analysis was performed to determine the predictors of severe COVID-19. A receiver operating characteristic curve was used to identify a threshold for each predictor. Altogether,104 patients were enrolled in our study with 30 and 74 patients in the severe and non-severe groups, respectively. Multivariate logistic analysis indicated that patients aged ≥63 years (odds ratio = 41.0; 95% CI: 2.8, 592.4), with an absolute lymphocyte value of ≤1.02×109/L (odds ratio = 6.1; 95% CI = 1.5, 25.2) and a C-reactive protein level of ≥65.08mg/L (odds ratio = 8.9; 95% CI = 1.0, 74.2) were at a higher risk of severe illness. Thus, our results could be helpful in the early detection of patients at risk for severe illness, enabling the implementation of effective interventions and likely lowering the morbidity of COVID-19 patients.

[Progress in cerebrospinal fluid proteome technology and its clinical application].

Cerebrospinal fluid surrounds and supports the central nervous system, including the ventricles and subarachnoid spaces. Cerebrospinal fluid should be an important source of biomarkers for central nervous system diseases because it is in direct contact with the central nervous system. Many studies are reported on cerebrospinal fluid proteomics, highlighting many recent progresses. Here, we review recent advances in proteomics technology and clinical application of cerebrospinal fluid.