Prognosis of delirium in hospitalized elderly: worse than we thought
Bibliographic record
Abstract
BACKGROUND: Despite treatment of the associated condition, delirious persons do not always recover for unknown reasons. We sought to determine early prognostic indicators of poor recovery following an episode of delirium in older medical in-patients. METHODS: Between October 2009 and July 2011, consecutively admitted older (≥70 years old) medical in-patients at the London Health Sciences Centre (Ontario) were screened for delirium. Delirious patients were followed. The primary outcome was poor recovery, in delirious patients, defined by death, long-term institutionalization, or functional decline (decreased activities of daily living), at discharge or 3 months after discharge, elicited from the medical chart or post-discharge caregiver telephone interviews. RESULTS: One thousand two hundred thirty-five in-patients (mean age 82.6 years, 42% men) were screened, delirium occurred in 355 (29%). Follow-up data was known on 342 (96%), and 237 (69%) had poor recovery: 55 died (54 in hospital and one after discharge), 136 were permanently institutionalized (86 directly from hospital and 50 after discharge), and 46 had functional decline (at a median of 103 days after discharge). Poor recovery was associated in the derivation sample with advanced age, lower baseline function, hypoxia, higher delirium severity scores, and acute renal failure; this was predictive of poor recovery in the validation sample (receiver operating characteristic area 0.68, 95% confidence interval: 0.57-0.79); however, even individuals with "low" risk had high (50%) poor recovery rates. INTERPRETATION: Poor recovery after delirium is common and associated with certain characteristics. However, even "lower risk" delirious individuals do poorly. More research is needed to understand prognostic factors in delirium.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".