The Predictive Value of Dysgraphia and Constructional Apraxia for Delirium in Psychiatric Inpatients
Bibliographic record
Abstract
OBJECTIVE: To evaluate the predictive value of dysgraphia and constructional apraxia for delirium among psychiatric inpatients. METHOD: Data were collected from 2 sources. First, a series of nondelirious psychiatric inpatients that had participated in a previous study was selected to determine the specificity of various indices of dysgraphia and constructional apraxia. Second, a series of 56 psychiatric inpatients with delirium as identified using electronic administrative data and clinical records was selected to evaluate sensitivity. RESULTS: Of the various indices of dysgraphia examined, only a global rating of writing quality and evidence of jagged or angled letter loops were informative clinical signs. The predictive value of constructional apraxia resembled the predictive value of the 2 dysgraphia indices. CONCLUSIONS: Dysgraphia and constructional apraxia are useful clinical signs of delirium in the psychiatric inpatient population. Evaluation of these functions can substantially impact diagnostic decisions where diagnostic uncertainty exists. An evaluation of writing and constructional praxis can be easily incorporated into bedside mental status examinations.
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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 | 0.001 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".