Visuospatial function impairment in patients with subacute-chronic isolated frontal lobe ischemic stroke: A cross-sectional study using MoCA-Ina in a private hospital
Bibliographic record
Abstract
Background. Stroke is one of the leading causes of disability, resulting in both limb disability and also cognitive impairment. Cognitive impairment can occur post-stroke due to lesions in specific cortex areas. Visuospatial function, a domain of cognitive function related to visual imaging, is commonly affected by parietal lobe lesions. However, visuospatial processing also requires sustained attention, planning, and error correction, functions of the frontal lobe. There is a paucity of studies evaluating the relationship between isolated frontal lobe stroke and patients’ visuospatial function. Objective. To analyze the relationship between subacute-chronic frontal lobe ischemic stroke and visuospatial function in post-ischemic stroke patients using the MoCA-Ina. Material and methods. Patients from Siloam Karawaci General Hospital’s neurology outpatient department with ages under 65 years, Glasgow Coma Scale of 15, diagnosis of first-time stroke based on CT scan result, and ischemic lesion confined to one brain lobe were recruited using non-probability consecutive sampling for this cross-sectional study. Patients were divided into frontal lobe and non-frontal lobe stroke subgroups. Visuospatial function was assessed using MoCA-Ina and analyzed using Mann Whitney U test. Outcomes. Fifty patients were included; 25 had frontal lobe stroke, and 25 had non-frontal lobe stroke. The median visuospatial score was lower in the frontal lobe group (2, min/max = 0/4) compared to the non-frontal lobe group (3, min/ max = 0/5), with a p-value of 0.044. There was no significant difference in visuospatial scores between different frontal hemisphere locations. Conclusion. Subacute-chronic frontal lobe ischemic stroke affects visuospatial function in post-ischemic stroke 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".