Correlation between Indonesian Version of Montreal Cognitive Assessment Score and Hospital Anxiety and Depression Scale Scores for Post-Stroke Patients
Bibliographic record
Abstract
Background: Cerebrovascular disease, with its complex anatomy, and various parts of the brain can cause neurological deficits. The Oxfordshire Community Stroke Project classification distinguishes a posterior circulation infarct (PCI) from an Anterior Circulation Infarction (ACI) by using radiological examination. Anxiety after stroke occurs in about 24% of patients and it is a problem with quality of life associated with poor health. In Post Stroke Anxiety (PSA), there are still few studies on prevention, risk factors and therapeutic interventions. More than 40% of stroke sufferers have cognitive impairment or post stroke cognitive impairment (PSCI). Objectives: To determine the correlation between Indonesian Version of Montreal Cognitive Assessment Score (MoCA-INA) and the Hospital Anxiety and Depression Scale Scores (HADS-A) for post-stroke patients in neurological road care installation in University of Sumatera Utara Hospital. Methods: This is a numerical correlation study with a cross-sectional approach.. The sampling method is non-probability sampling with consecutive sampling type. The research subjects were then examined for the total MOCAINA score. Then, the research subjects are examined for HADS-A. After all the results of the examination, the questionnaire and the subject's personal data are completely filled in, the questionnaire is collected. The analysis uses the Spearman correlation test Results: The results of the analysis using the Spearman correlation test for the correlation between MoCA-INA total score and HADS-A total score, the value of r is -0.602 with p value <0.001 (the correlation is very significant with negative correlation direction and the strength of the correlation is strong). Conclusions and Suggestions: With the influence of MoCa-INA score on the HADS-A score in post-stroke patients, it can provide an input for health workers to immediately detect and anticipate events of cognitive decline and anxiety in post-stroke patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".