Abstract 112: Internal Consistency Between Cognitive Tests for Survivors of Cardiac Arrest
Bibliographic record
Abstract
Introduction: Cardiac arrest survivors suffer cognitive impairment easily missed on a clinical examination. We evaluated a battery of cognitive tests including the Cerebral Performance Category Extended (CPC-E), Montreal Cognitive Assessment (MoCA), and the Computer Assessment of Cognitive Impairment (CAMCI) to evaluate these deficits. Hypothesis: The CPC-E, MoCA and CAMCI tests correlate with one another, but the internal consistency of each test differs. Methods: Chart review of 201 cardiac arrest survivors occurred between October 2010 and January 2018. Pearson’s correlation was used to assess between-test correlation while Cronbach’s alpha was used to assess internal consistency of each test. We evaluated both the overall measure score and individual items in the measure. Results: Complete assessments were available for 50 subjects, 75 completed both the MoCA and the CAMCI, 57 completed both the CPC-E and the CAMCI, and 76 completed the MoCA and the CPC-E. Internal consistencies existed within both the MoCA and the CPC-E (Cronbach alpha = 0.661, and 0.738, respectively), while only borderline internal consistency was found within the CAMCI (Cronbach alpha = 0.638). At the scale level moderate or limited correlation existed between tests (Figure). At the item level, the CAMCI had little to no correlation with items of the CPC-E or MoCA. Moderate correlations existed between item specific domains of visuospatial, attention and delayed recall items of the MoCA and domains of alert, logical thinking, attention, and short term memory of the CPC-E (r=0.3-0.5). Conclusions: Strong correlation between the CAMCI and MoCA suggests they evaluate similar domains of function. The MoCA is shorter, easily administered and inexpensive, arguing for its use over the CAMCI. The CPC-E’s strong internal consistency and moderate correlation with the MoCA suggests it may provide additional discrimination of cognitive function in the cardiac arrest population.
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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 | 0.014 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".