The Impact of Age on Electrocardiographic Findings of Stroke Patients: A Cross-Sectional Analytic Study
Bibliographic record
Abstract
Purpose: To evaluate differences in ECG abnormalities in stroke patients in relation to age groups (less than forty, forty to sixty-five and greater than sixty-five years) in the University of Benin Teaching Hospital (UBTH) Methodology: This was a cross-sectional analytical study carried out at the University of Benin Teaching Hospital (UBTH), Benin. The study subjects consisted of consecutive one hundred and twenty admitted stroke patients who met the inclusion criteria. History and physical examination were carried out for all patients with laboratory investigations and electrocardiographic examinations also performed on all patients. The data was analyzed using SPSS version 21 software with a P-value of less than 0.05 considered significant for all comparisons. Result: In this study, stroke was more in those under sixty-five years (n = 84, 70.00%) than in those above sixty-five years (n = 36, 30.00%). All (100.00%), 56 (77.78%) and 24 (66.67%) of cases less than forty, forty to sixty-five years and greater than sixty-five years respectively in this study had ECG abnormalities, this was significant (p = 0.021). Unique Contribution to Theory, Policy and Practice: Left ventricular hypertrophy predominates in less than forty years old cases while left axis deviation predominates in older than forty years cases. Some ECG abnormalities in certain age groups
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".