Association of Carotid Artery Stenosis with Diabetes Mellitus in Patients of Acute Ischemic Stroke
Bibliographic record
Abstract
Objective: To determine the association of carotid artery stenosis with diabetes mellitus in patients of acute ischemic stroke Study Setting: The study was conducted in Allama Iqbal Memorial Teaching Hospital, Sialkot. Duration of Study: April 13, 2018 to October 13, 2018 Study Design: Case-Control Study Subjects & Methods: A total 220 (110 cases/ 110 controls) patients fulfilling selection criteria were enrolled from emergency of Department of Medicine, Allama Iqbal Memorial Teaching Hospital, Sialkot. Blood drop was obtained from each patient by pricking in index finger and using glucometer and lentils. Reading of glucometer was obtained. If BSR was >186mg/dl and patient had history of DM, then DM was labeled. Data were entered and analyzed in SPSS v25.0. Results: Total 220 (110 cases/ 110 controls) patients were selected for this study. Among cases, mean age was 54.7±9.1 years and 55.1±8.8 years among controls. Among cases, there were 67(60.9%) males and 43(39.1%) females, while 75(68.2%) males and 35(31.8%) females among controls. By comparing diabetes mellitus between groups, it was found that percentage of DM was 41.8% with carotid artery stenosis and 16.4% without carotid artery stenosis. The difference was significant (p=0.0001). Conclusion: There is an association of carotid artery stenosis with diabetes mellitus in patients of acute ischemic stroke. Patients with carotid artery stenosis have significant chances to have diabetes mellitus. Keywords: Carotid Artery Stenosis, Diabetes Mellitus, Acute Ischemic Stroke.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".