Structured delirium management in the hospital—a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Delirium is a common and serious complication of inpatient hospital care in older patients. The current approaches to prevention and treatment followed in German hospitals are inconsistent. The aim of this study was to test the effectiveness of a standardized multiprofessional approach to the management of delirium in inpatients. METHODS: The patients included in the study were all >65 years old, were treated for at least 3 days on an internal medicine, trauma surgery, or orthopedic ward at Münster University Hospital between January 2016 and December 2017, and showed cognitive deficits on standardized screening at the time of admission (a score of ≤=25 on the Montreal Cognitive Assessment [MoCA] test). Patients in the intervention group received standardized delirium prevention and treatment measures; those in the control group did not. The primary outcomes measured were the incidence and duration of delirium during the hospital stay; the secondary outcomes measured were cognitive deficits relevant to daily living at 12 months after discharge (MoCA and Instrumental Activities of Daily Living [I-ADL]). RESULTS: The data of 772 patients were analyzed. Both the rate and the duration of delirium were lower in the intervention group than in the control group (6.8% versus 20.5%, odds ratio 0.28, 95% confidence interval [0.18; 0.45]; 3 days [interquartile range, IQR 2-4] versus 6 days [IQR 4-8]). A year after discharge, the patients with delirium in the intervention group showed fewer cognitive deficits relevant to daily living than those in the control group (I-ADL score 2.5 [IQR 2-4] versus 1 [IQR 1-2], P = 0.02). CONCLUSION: Structured multiprofessional management reduces the incidence and duration of delirium and lowers the number of lasting cognitive deficits relevant to daily living after hospital discharge.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".