Motor Disturbances in Elderly Medical Inpatients and Their Relationship to Delirium
Bibliographic record
Abstract
Motor disturbances in delirious patients are common, but their relationship to cognition and severity of illness has not been studied. We examined motor subtypes in an older age inpatient population, their relationship to clinical variables including delirium, and their association with 1-year mortality in a prospective study, using the Confusion Assessment Method, Acute Physiology and Chronic Health Evaluation II, Montreal Cognitive Assessment (MoCA), Barthel Index, and Delirium Rating Scale-Revised 98 (DRS-R98). Motor subtypes were evaluated using 2 items of DRS-R98. Mortality rates were investigated 1 year later. Two hundred participated (mean age 81.1 [6.5]; 50% female). Thirty-four (17%) were identified with delirium. Motor subtypes were none: 119 (59.5%), hypoactive: 37 (18.5%), hyperactive: 29 (14.5%), and mixed: 15 (7.5%). Hypoactive and mixed subtypes were significantly more frequent in delirious patients. Regression analysis showed that hypoactive subtype was significantly associated with lower MoCA. No relationship between motor subtypes and mortality was found. Motor disturbances are not unique to delirium, with hypoactivity particularly associated with impaired cognition.
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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 | 0.005 |
| 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 | 0.001 |
| 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".