Nurse clinic versus home delivery of evidence-based community leg ulcer care: A randomized health services trial
Bibliographic record
Abstract
BACKGROUND: International studies report that nurse clinics improve healing rates for the leg ulcer population. However, these studies did not necessarily deliver similar standards of care based on evidence in the treatment venues (home and clinic). A rigorous evaluation of home versus clinic care is required to determine healing rates with equivalent care and establish the acceptability of clinic-delivered care. METHODS: Health Services RCT was conducted where mobile individuals were allocated to either home or nurse clinic for leg ulcer management. In both arms, care was delivered by specially trained nurses, following an evidence protocol. PRIMARY OUTCOME: 3-month healing rates. SECONDARY OUTCOMES: durability of healing (recurrence), time free of ulcers, HRQL, satisfaction, resource use. Data were collected at base-line, every 3 months until healing occurred, with 1 year follow-up. Analysis was by intention to treat. RESULTS: 126 participants, 65 randomized to receive care in their homes, 61 to nurse-run clinics. No differences found between groups at baseline on socio-demographic, HRQL or clinical characteristics. mean age 69 years, 68% females, 84% English-speaking, half with previous episode of ulceration, 60% ulcers at inclusion < 5 cm2 for < 6 months. No differences in 3-month healing rates: clinic 58.3% compared to home care at 56.7% (p = 0.5) or in secondary outcomes. CONCLUSION: Our findings indicate that organization of care not the setting where care is delivered influences healing rates. Key factors are a system that supports delivery of evidence-based recommendations with care being provided by a trained nursing team resulting in equivalent healing rates, HRQL whether care is delivered in the home or in a community nurse-led clinic. TRIAL REGISTRATION: ClinicalTrials.gov Protocol Registration System: NCT00656383.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".