Abstract P417: Critical Knowledge Gaps in Characterizing Cognitive Impairment Among Intracerebral Hemorrhage Patients: Systematic Review of Contemporary Literature
Bibliographic record
Abstract
Introduction: Despite emerging evidence, trajectories of cognitive impairment (CI) among patients with spontaneous intracerebral hemorrhage (ICH) are not well characterized. Methods: We conducted a systematic review of literature within PubMed, using keywords [“Intracerebral hemorrhage” OR “ICH”] AND “Cognitive Impairment,” after 2010. Articles reporting assessments of post ICH CI were included. Articles limited to pre-clinical (animal) studies, non-English literature, other intracranial hemorrhages, traumatic ICH, narrative reviews, and patient under 18 years were excluded. Results: Based on selection criteria, we included 16 articles (graphic) that provide an assessment of post-ICH CI. Post-ICH CI had a reported incidence of up to 85% within the first 2 weeks. The proportion of ICH patients who experience an incident CI across a longer follow up time period have been reported with a high degree of variability; with reports at 3 (32.5 - 71%), 4 (78%), 6 (37 - 63.3%), 9 (47.1 - 100%), 18 (51%), 30 (25.8%), 40 (23%), 45.6 (52 - 64%) and 60 (37.4%) months. Though the assessment scales utilized are variable; 12 (75%) reports employed a version of Montreal Cognitive Assessment or Information Questionnaire on Cognitive Decline in the Elderly. Lobar ICH was well identified, while non-lobar ICHs were variably grouped. Imaging markers have been reported in 10 (62.5%) reports. Though most studies report comorbidities and sociodemographic factors; stroke-specific severity / functional scales and genetic factors have only been considered by 2 (12.5%) articles each. Conclusions: At least 1 in 3 ICH survivors experience post-ICH CI over 12 months. There is an overall paucity of data on post-ICH CI, which highlights a critical need to characterize the natural history of post ICH CI in prospective cohorts and develop standardized assessment protocols for CI among ICH patients.
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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 | 0.017 | 0.088 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.025 | 0.019 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".