Inter-Racial Effect on Electrocardiographic Abnormalities among Stroke Patients in Sub-Saharan Africa
Bibliographic record
Abstract
Purpose: The study aimed to determine the prevalence of electrocardiographic abnormalities in black stroke patients and to find out if the black race predisposes to increased electrocardiographic abnormalities as well as specific electrocardiographic abnormalities among the study population.
 Methodology: This was a cross-sectional analytical study carried out at the University of Benin
 Teaching Hospital Benin. The electrocardiographic abnormalities of one hundred and twenty (120) admitted black stroke patients in this study were compared with Goldstein study on Caucasians in the United States of America. The data were analyzed using the IBM SPSS statistics version 22. A p < 0.05 was considered significant.
 Results: The study demonstrated the prevalence of electrocardiographic abnormalities among black stroke patients to be 76.6% with the associated presence of left axis deviation (52.17% vs 15.22%, p<0.001), left atrial enlargement (17.39% vs 5.80%, p=0.005) and ST segment depression (43.50% vs 21.74%, p=0.001). On the contrary, stroke patients of the Caucasian race were linked to sinus tachycardia (30.44 % vs 13.04%, p=0.002), prolonged QT (49.28% vs 8.70%, p <0.001) and premature ventricular complex (13.04% vs 4.35%, p =0.049) with a concomitant absence of bi-atrial enlargement, low limb lead voltage and non-specific intraventricular block. They had a prevalence of 92%.
 Unique Contribution to Theory, Policy and Practice: The prevalence of electrocardiographic abnormalities is lower among the black stroke individuals compared to the Caucasians even though the former tend to present with features of structural abnormalities compared to the latter who had more electrical abnormalities. Therefore, in resource-poor settings where ECG cannot readily be carried out, the race of the patient may guide the clinician in suspecting the probable cardiac changes in stroke patients.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".