Long Term Sequelae of Stroke Treated with QIAPI 1®: Case Report
Bibliographic record
Abstract
Despite significant decrease in mortality in stroke since 1950, the annual incidence of strokes in thegeneral population remains at 1 or 2 per 1000 each year. There is an estimated of 50 000 new cases ofstroke in Canada annually. There are approximately six to eight survivors of stroke per 1000 each year.Patients live an average of 7 years after stroke.There appears to be low levels of knowledge of both risk factors and stroke warning signs among bothhigh- and low-risk populations. Usually, knowledge about stroke risk factors is por, and as in myocardialinfarction, delays from symptom onset to decision to seek medical attention are the most significantcauses of delay in patients with stroke.The most frequent symptoms are compatible with diagnoses of stroke, transient ischemic attack,intracerebral hemorrhage, or subarachnoid hemorrhage. It is common for the patients don't be unableto respond to questioning due to speech difficulties or an impaired mental status. Non-stroke diagnosesincluded dizziness/ataxia, seizure, dysarthria not otherwise specified (NOS), numbness NOS, syncope,migraine headache, anxiety, subdural hematoma, visual disturbances NOS, hepatic encephalopathy,alcoholic amnesic syndrome, acute poliomyelitis, soft tissue pain NOS, dementia, and other braincondition NOS. The non-stroke patients were like those with a final diagnosis of stroke in terms of age,race, and sex.Supposedly, interventional thrombolytic stroke therapy (recombinant tissue plasminogen activator) isoptimally effective only when administered within 3 hours of the onset of the vascular event.The pharmacological modulation of the unsuspected capacity of eukaryotic cells to generate their ownoxygen, dissociating the water molecules contained inside the cells, as in plants, opens new horizonsregarding the prevention and treatment of one of the most epidemiologically important diseases.
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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) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".