Abstract 3000: Epidemiology of Cerebrovascular Diseases Among Chinese with Diabetes Mellitus in Toronto: A Retrospective Ten Years Case-mix Study
Bibliographic record
Abstract
BACKGROUND: An article published in Neurology Asia(2006;11:13-18) by Chu etal provided essential data to investigate whether specific genetic or environmental differences exist within the diabetic-Chinese stroke community. Insight into distinctive epidemiologic and cerebrovascular patterns will bring forth effectively focused treatment and prevention. From that basis, we hypothesized: Chinese who had stroke-history within 15 years are more commonly diabetic than Europeans, and Chinese more frequently have small vessels disease (SVD) than Europeans. METHODS: Patients seen during 2001-2011 at the Toronto Queensway Professional Center Neurology clinic and at William Osler Health System, Brampton Site, were investigated. Chinese diabetic stroke patients were selected by last name and birth country; similarly diagnosed European patients were age-sex matched correspondingly. Risk factors were acknowledged if patients were given explicit medical treatments. Otherwise, guideline values were obtained from the WHO criteria. Data was collected through screening patient charts for the following: diabetic prevalence through screening stroke patients (122 Chinese, 880 European) excluding TIAs, subarachnoid and subdural haemorrhages; etiology and stroke type comparison in patients with DM (48 Chinese, 127 European); risk factors differences between Chinese and Europeans with DM. Odds ratios and unpaired two-sample t-testing were used to confirm significance. RESULTS: Significance confirmed (P<0.05): Chinese had higher DM and stroke incidence than Europeans (28.7% vs. 23.2%). Diabetic Chinese more frequently had SVD (51.1% vs. 44.1%), specifically lacunar stroke (47.9% vs. 36.4%). The co-morbidity of SVD risk factors of hypertension, hyperlipidemia and overweight were more frequent in Chinese (Table 1.0). Furthermore, SVD frequency dominated over large vessels disease (LVD) in the Chinese (Table 1.1). Table 1.0 - RISK FACTOR INCIDENCE Overweight HBP HPL Chinese, SVD 26.9% 53.8% 36.5% European, SVD 16.5% 33.1% 23.6% OR Chinese/Euro.1.86 2.36 1.86 Table 1.1 - STROKE TYPE AND RISK Overweight, SVD Overweight, LVD Hyperlipidemia, SVD Hyperlipidemia, LVD Hypertension, SVD Hypertension, LVD : Chinese 26.9% 7.7% 36.5% 15.0% 53.8% 25.0% OR SVD/LVD 4.42 3.26 3.50 European 16.5% 7.9% 23.6% 15.0% 33.1% 26.0% OR SVD/LVD 2.32 1.76 1.41 CONCLUSIONS: Chinese with stroke are more frequently diabetic than Europeans. Diabetic Chinese are especially susceptible to small vessels disease and certain stroke risk factors are more frequent compared to the Europeans. Risk factor prevalence and stroke types differ considerably between Chinese and Europeans within Toronto, which may imply that specific treatment strategies are required to target towards each population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".