Study of Stress Hyperglycemia as a Prognostic Factor in Acute Ischemic Stroke at a Tertiary Care Hospital
Bibliographic record
Abstract
Background: The second most prevalent cause of disability and death worldwide, stroke is silently taking on the characteristics of an epidemic. Almost 85% of the all strokes are ischemic strokes. Objective: To assess the stress hyperglycemia as a prognostic factor in acute ischemic stroke at a tertiary care hospital. Design of the Study: It was a case control study. Place and Duration of Study: This study was conducted at the Department of medicine & Allied Services Hospital Lahore from March 2022 August 2022. Patients and Methods: Total 100 patients with Computerized Tomography (CT) Brain evidence of acute ischemic stroke who met the inclusion criteria were included in the study. At admission, a thorough history was taken and clinical examination was performed. The National Institutes of Health Stroke Scale (NIHSS scale) was used to measure the patient’s neurological state. Fasting Blood sugar (FBS) and Glycosylated Hemoglobin (HBA1c) were performed. Patients' functional recovery was measured by comparing their NIHSS scores on the day of admission and after 7 days in the hospital. Results of the Study: Most of the patients enrolled in our study had age of 61 to 70 years. In study sample 56% of patients were male and 44% were female. Out of 100 patients 56 had stress hyperglycemia and 44 were without stress hyperglycemia. Functional recovery was greater in patients with normoglycemia than in patients with stress hyperglycemia (based on differences in NIHSS score on day one and day seven). The mortality was observed to be 9.2% in patients who had stress hyperglycemia. The mean NIHSS scores was 3.45±1.64 in patients with stress hyperglycemia and 4.50 ± 1.05 was in participants with normoglycemia. Practical Implication: The present study was carried out to know whether stress hyperglycemia can be a prognostic marker in patients of acute ischemic stroke. Conclusion: When compared to patients with stress hyperglycemia, functional recovery was better in patients with normoglycemia. This study demonstrates that patients with normoglycemia had greater functional recovery as compared to patients with stress hyperglycemia, as measured by the difference between the NIHSS scores. As a result, patients with normoglycemia had better outcomes than those with stress hyperglycemia. Keywords: Stress hyperglycemia, Normoglycemia, Acute Ischemic Stroke, Prognostic Factor, NIHSS
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".