The Cognitive Impairment At Acute Stage After Intracerebral Hemorrhage
Bibliographic record
Abstract
Abstract Background: We determined the frequency and factors of cognitive impairment at acute stage and investigate the prognostic effect of the cognitive function at acute stage on the delayed cognitive impairment after acute intracerebral hemorrhage (ICH). Methods: A total of 208 patients with acute ICH were enrolled from January 2017 to February 2019. Cognitive function was assessed during the acute stage and follow-up after ICH using Montreal Cognitive Assessment (MoCA) score. The significant acute stage and delayed cognitive impairment was defined as a MoCA score <20 within 1 week after hospital admission and during follow-up respectively. Results: During a mean 20 (IQC 17-23) months follow-up, 185 patients with follow-up cognitive function data. There are 89 (42.8%) and 86 (46.5%) patients had acute stage and delayed significant cognitive impairment respectively. The older age, large baseline hematoma volume, more severe ICH, and low level of education were significant associated with significant cognitive impairment at acute stage (all P＜0.009). In the multivariable logistic regression model, the low acute phase MoCA score (odds ratio [OR] 0.59; 95% confidence interval [CI] 0.48-0.71; P＜0.001) was the only one independent factor associated with delayed significant cognitive impairment after ICH. Conclusions: Near half of patients have significant cognitive impairment at acute stage after ICH, which is more frequent in the elderly, those with large baseline hematoma volume, and more severe initial neurological deficit. The acute phase MoCA score was independent increased the risk of delayed cognitive impairment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".