Long‐term Cognitive Impact of COVID‐19 Infection in Acute Ischemic Stroke Patients
Bibliographic record
Abstract
BACKGROUND: About one in three COVID-19 patients experience neurological problems; and acute ischemic stroke (AIS) is one of the common comorbidities of COVID-19. As stroke doubles the risk of dementia, AIS patients with COVID-19 infection may experience even higher risk of developing poststroke dementia. Still, little is known about the incidence of poststroke dementia in AIS patient with COVID-19 infection. METHOD: Using data from the Get With The Guidelines-Stroke linked Medicare claims, we conducted a retrospective cohort study to estimate the incidence of poststroke dementia in AIS patients (1) with COVID-19 with or without bacterial infection, (2) with bacterial infection only, and (3) with no infection. AIS Patients aged 66+ without pre-stroke dementia from January 1, 2020, to June 30, 2021 were included and followed up for 12 months post discharge. Primary outcome-incident poststroke dementia-was obtained based on the International Classification of Diseases, Tenth Revision, from Medicare claims. Secondary outcomes include incident vascular dementia, poststroke mild cognitive impairment, and composite of poststroke mild cognitive impairment and dementia. Poisson regression was used to model the incidence of poststroke dementia accounting for age and stroke severity. RESULT: Of 103,378 patients (median [interquartile range] age, 79 [73-86], 56,769 [54.9%] female; 84.074 [81.3.9%] white), 1,438 (1.4%) had COVID-19 infection during stroke onset, and 6,084 (5.9%) had bacterial infection only. A total of 12,925 incident dementia cases developed during 1,310,658 person-days after stroke onset. Poststroke dementia incidence rate was 0.011 in patients with COVID-19 infection, 0.011 in patients with bacterial infection only, and 0.010 in patients with no infection. Compared to patients with no infection, the rates of poststroke dementia were significantly higher in patients with only bacterial infection (adjusted rate ratio[aRR]: 1.13 [95% CI, 1.06-1.22]). Similar trends were observed in patients with COVID-19 infection, although not statistically significant (aRR: 1.14 [95% CI, 0.96-1.36]). Similar results were seen in the incidence of vascular dementia and composite cognitive outcome. CONCLUSION: We observed a higher incidence of poststroke dementia in AIS patients with bacterial infection only and those with COVID-19 infection. COVID-19 infection may be associated with higher risk of dementia post stroke.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".