One and done? Outcomes from 3961 patients managed via a virtual fracture clinic pathway for paediatric fractures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: The aim of this paper is to describe our experience with a virtual fracture management pathway in the setting of a paediatric trauma service. METHODS: All patients referred to the virtual fracture clinic service from the Paediatric Emergency Department (PED) were prospectively collected. Outcome data of interest (patients discharged, referred for urgent operative treatment, referred back to emergency department for further evaluation, referred for face-to-face clinical assessment and all patients who re-presented on an unplanned basis for further management of the index injury) were compiled and collated. Cost analysis was performed using established costing for a virtual fracture clinic within the Irish Healthcare System. RESULTS: There were a total of 3961 patients referred to the virtual fracture clinic from the PED. Of these, 70% (n = 2776) were discharged. In all, 26% (n = 1033) were referred to a face-to-face appointment. Of discharged patients, 7.5% (n = 207) required an unplanned face-to-face evaluation. A total of 0.1% (n = 3) subsequently required operative treatment relating to their index injury. Implementation of the virtual fracture clinic model generated calculated savings of €254 120. CONCLUSION: This prospective evaluation has demonstrated that a virtual fracture clinic pathway for minor paediatric trauma is safe, effective and brings significant cost savings. LEVEL OF EVIDENCE: II.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it