177. The Clinical Need for an Out-of-Hours Rheumatology Referral Service in a UK Teaching Hospital
Bibliographic record
Abstract
Background: Hospitals are faced with challenges of delivering an integrated, high-quality, safe and value for money services. This means that many specialist services are being reviewed in order to achieve cost saving. Our rheumatology department in a single teaching London hospital provides 24/7 services for the CTDs referral and general rheumatology services during working hours. Acute hot joints account for majority of rheumatology referral from the emergency department (ED) out of hours. Delayed or inadequate treatment of septic joints leads to joint damage. In the case of crystal arthropathies, this may lead to unnecessary admission and prolong hospital stays. As there is little information on whether a 24/7 service required for general rheumatology, we did a prospective evaluation of all acute hot joints admission via ED over 1-month period. Methods: All admissions to ED dated from 6 May to 4 June 2013 were screened for presenting complaints of pain and swelling in non-prosthetics joints. The case notes, discharge summaries and the ED CAS card were retrieved to examine the subsequent managements, route of referral and discharge destinations.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".