Data Management And Sharing System of China National Clinical Research Center for Neurological Diseases

Journal：Scientific reports

Publication type: Original Contributions

IF(IF): 4.379

PMID: 2016; 6:32342. Link To Pubmed Full text Download

We aimed to validate prognostic value of elevated admission blood glucose (ABG) for clinical outcomes in diabetic and non-diabetic patients with intracerebral hemorrhage (ICH) in a representative large cohort. Data of ICH patients with onset time ≤24 h were derived from the China National Stroke Registry. Clinical outcomes included 3-month poor outcome (death or dependency) and death. Logistic regression was performed for the association between ABG and clinical outcomes, both in the entire cohort and in patients with and without diabetes mellitus. 2951 ICH patients were enrolled, including 267 (9.0%) diabetics. In the entire cohort, there was a trend to increased risk of poor outcome with increasing ABG levels (adjusted OR 1.09; 95% CI, 1.04–1.15; P < 0.001). The risk of poor outcome was significantly greatest for the highest quartile (≥7.53 mmol/L) of ABG (adjusted OR 1.54; 95% CI, 1.17–2.03; p = 0.002, P for trend 0.004). We got similar association in non-diabetics but not in diabetics. Elevated ABG confers a higher risk of poor outcome in non-diabetics than diabetics with similar glucose level. Elevated ABG is an independent predictor of 3-month poor outcome in ICH patients, the prognostic value of which is greater in non-diabetics than diabetics with similar glucose level.

Study Population. The study was based on the CNSR, a nationwide, multi-centre and prospective cohort study, the design, rationale, and baseline information of which has been described in detail elsewhere21. In brief, CNSR was the largest stroke registry of consecutive patients with acute cerebrovascular events between September 2007 and August 2008 in China. 132 hospitals from different regions representing 27 provinces and 4 municipalities in mainland China were selected. CNSR was performed in accordance with the guidelines of the Helsinki Declaration. The protocol and data collection was approved by the Institutional Review Board at Beijing Tiantan Hospital and all participating hospitals. Written informed consent was obtained from each participant or his/her designated relatives. To be eligible for the diagnosis of ICH in our study, subjects had to meet the following criteria: (1) hospital- ized with a primary diagnosis of spontaneous ICH according to the World Health Organization criteria22; (2) not including primary intraventricular ICH, ICH caused by trauma, brain tumor, hemorrhage secondary to malig- nancy, subarachnoid hemorrhage, arteriovenous malformation and hemorrhagic transformation of cerebral infarct; (3) ICH confirmed by brain CT. CT films were collected and assessed for hematoma volume and evaluation of intraventricular extension. All images were prospectively reviewed by a neuroradiologist from each participat- ing center who was blinded to clinical data. The neuroradiologists of the study centres were trained centrally with the CT protocol23. Patients were excluded if no admission blood glucose data available. Considering variable inter- vals between symptom onset and ABG measurement, we excluded patients with onset time over 24 hours as well. Data Collection and Variable Definition. Demographic characteristics, clinical information, radio- graphic findings, treatment during hospitalization and ABG were collected from the database, as well as hem- orrhage evaluation including stroke severity, hematoma volume and hematoma location. Stroke severity was measured using the initial NIHSS score and GCS score. ICH hematoma volumes were measured on the ini- tial brain CT by the ABC/2 method23. Data on hematoma locations, which were classified as supratentorial and infratentorial, and the presence of intraventricular extension were also collected. ABG was the random blood glucose9,24 measured at the initial emergency department or the blood glucose value from in-hospital immediate evaluation, which was generally done within 3 hours of admission. Patients with a history of diabetes or glucose-lowering treatment before ICH were classified as diabetics, according to previously published articles9,10. Outcome Measures. The clinical outcomes was poor outcome defined as death or dependency (modified Rankin scale25 [mRS] score of 3 to 6) and death (mRS score of 6) at 3 months, which was assessed by trained study investigators. The telephone follow-up was conducted centrally for all enrolled patients with a standardized interview protocol. Statistical Analysis. Baseline demographic and clinical characteristics were expressed as mean (standard deviation) or median (interquartile range) for continuous variables and as number (%) for categorical varia- bles. The chi-square test for categorical variables and Mann–Whitney test for continuous variables were used as needed. Associations of ABG, both as continuous and categorical (quartile) variables, and risk of poor outcome and death were evaluated by separate univariable and multivariable logistic regression. ORs with 95% CIs were cal- culated. All significant (P< 0.05) baseline variables in the univariable analysis were included in the multivariable analysis. Collinearity and interaction between variables were also check. We further evaluated the associations between ABG and risk of poor outcome and death using a multivariable logistic regression model with restricted cubic splines for ABG adjusting for all confounding factors. The 5 knots for spline were placed at the 5th, 25th, 50th, 75th, 95th percentiles of ABG. These analyses were performed in the entire cohort and repeated in patients with and without DM. Sensitivity analysis including ordinal regression and different categories of ABG (by tertiles and by diagnostic thresholds of blood glucose for DM) were performed to examine the association between ABG and clinical outcomes. A 2-sided P value <0.05 was set as the level for statistical significance. All analyses were performed with SAS software version 9.4 (SAS Institute Inc, Cary, NC, USA).