The Value of Event Related Potential P300 and Montreal Cognitive Assessment in Assessing Early Cognitive Function of Patients with Stroke in Different Brain Areas
Bibliographic record
Abstract
Objective To evaluate the value of event related potential P300(P300) and Montreal cognitive assessment(MoCA) in assessing early cognitive function of patients with stroke in different brain areas.Methods A total of 101 patients with stroke who visited the Inpatients and / or Outpatients of Neurology of our hospital between July 2011 and August 2012 were selected based on the inclusion and exclusion criteria and assigned as the study group,and another 100 patients without stroke were assigned as the control group.The patients in the study group were further divided according to the anatomic site of the infarction / bleeding lesion into five subgroups which were frontal lobe group,temporal lobe group,parietal lobe group,occipital lobe group,and basal ganglia group.The MoCA,P300,and mini mental state examination(MMSE) were used to determine the cognitive function of all subjects.Results The patients in the study group had lower MoCA score and P300 amplitude,but longer P300 latency than the control group(P 0.05).Compared with the control group,the frontal lobe and temporal lobe subgroups had lower MoCA score and P300 amplitude,but longer P300 latency;The parietal lobe subgroup had lower MoCA score;The basal ganglia subgroup had lower MoCA and longer P300 latency(P 0.05).The frontal lobe,temporal lobe,and basal ganglia subgroups had longer P300 latency than the parietal lobe and the occipital lobe subgroups,while the frontal lobe and temporal lobe subgroups had lower MoCA score and longer P300 latency than the basal ganglia subgroup(P 0.05).The patients in the study group had lower scores in executive function / visual space,naming,delayed recall,and orientation than the control group(P 0.05).The best cutoff value of MoCA was 22 score,with a sensitivity of 91.5% and a specificity of 85.7%,and that of P300 latency was 397 ms,with a sensitivity of 85.7% and a specificity of 55.3% in the identification of cognitive dysfunction in the stroke patients.The Kappa value was 0.712 and 0.654 compared with MMSE(P 0.01).Conclusion Stroke in the frontal and temporal lobe may cause more serious cognitive dysfunction than stroke in other areas.MoCA and P300 latency can evaluate early cognitive function in stroke patients with high sensitivity and specificity at cutoff value of 22 score and 397 ms.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".