Cumulative Illness and Neuropsychological Decline in Hospitalized Geriatric Patients
Bibliographic record
Abstract
A substantial portion of elderly patients admitted for inpatient rehabilitation treatment evidence cognitive dysfunction. Frequently, such patients also present with considerable medical comorbidity, that is, multiple concurrent illnesses. Identifying the potential role of cumulative illness in the etiology of cognitive decline in this group of frail elderly is limited by a lack of empirical information as little is known about this relationship. The goal of the present research was thus to investigate the relationship between cumulative illness and cognitive dysfunction while controlling for age and neurological and psychiatric symptomatology as these are previously known to affect cognitive function. Results indicate that cumulative illness predicts neuropsychological decline beyond the effects attributable to advanced age, mood, neurological pathology and psychiatric impairments. Even mild illness, if cumulative across several physical systems, can be predictive of cognitive deficits in this frail population. Of 11 organ systems studied, impairment of the vascular system was associated with the most diffuse profile of declined neuropsychological performance. Performances on measures of reasoning and judgment showed the strongest associations with cumulative illness. Implications of findings for neuropsychological diagnosis and prognosis are reviewed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".