Outcome of Delayed Administration of Alteplase in a Resource-Poor Area: A Case Report
Bibliographic record
Abstract
An acute ischemic stroke, though carrying the risk of debilitating complications, is a preventable and treatable disease. Thrombolysis and endovascular thrombectomy are important components of its management. However, various challenges in resource-poor countries like Nigeria and other developing nations pose a great limitation in the timely intervention of ischemic stroke treatment. The challenges include late presentation, poor awareness of stroke symptoms even among health care workers, poor ambulance service/transportation network, intra-hospital delay, particularly in neuroimaging, and the unavailability of tissue plasminogen activator (alteplase/tenecteplase). We report a 32-year-old African man with an antecedent history of suspected migraine headaches with aura and a family history of hypertension and stroke, admitted 7½ hours after onset of stroke symptoms, scoring 13 on the National Institutes of Health Stroke Scale (NIHSS) with Medical Research Council (MRC) muscle power grades 1 and 3 on the right upper and lower extremities, respectively. Urgent non-contrast brain CT revealed only a hyperdense sign in the left middle cerebral artery (MCA). Intravenous tissue plasminogen activator (tPA) was administered at a lower dose of 0.6 mg/kg, 15½ hours after symptom onset, and a CT angiogram done 24 hours post-thrombolysis showed partial recanalization of the M1 segment of the MCA and intermediate collateral supply (Alberta stroke program early CT {ASPECT} score: 6). By the third day of admission, he had made a significant clinical improvement and was discharged home able to walk unsupported on the fourth day.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".