Review: patients in nursing-led units are better prepared for discharge than those receiving usual careCommentary
Bibliographic record
Abstract
P Griffiths Correspondence to: Dr P Griffiths, King’s College London, London, UK; peter.griffiths@kcl.ac.uk Are nursing-led inpatient units (NLUs) more effective than usual inpatient care in preparing patients for discharge? ### Data sources: Medline, CINAHL, EMBASE/Excerpta Medica, Cochrane Library , Healthcare Management Information Consortium database, and British Nursing Index (to November 2006); Cochrane Effective Practice and Organisation of Care Group’s specialised register (to October 2006); ISI Web of Knowledge (to January 2007); and experts. ### Study selection and assessment: controlled trials that compared nurse-managed care in an NLU with usual inpatient care on a general acute hospital ward (managed by physicians) in adult patients after acute admission for any physical health condition. NLU care must have been a substitute for some or all of the acute hospital stay, rather than an addition to it. 8 randomised controlled trials (n = 1147), 2 quasi-randomised trials (n = 749), and 1 controlled before–after study met the selection criteria (range of …
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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 | 0.007 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".