Management of common elective paediatric orthopaedic conditions during the COVID-19 pandemic: The Montreal experience
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: To explore safe delays for the treatment of common paediatric orthopaedic conditions when faced with a life-threatening pandemic, COVID-19, and to propose a categorization system to address this question. METHODS: Review of the literature related to acceptable delays for treatment of common orthopaedic conditions, experience of healthcare professionals from low resource communities and expertise of experienced surgeons. RESULTS: Guidelines for the management of cancellations of elective surgeries during a period of resource reallocation are proposed. Elective cases must not be postponed indefinitely as adverse outcomes may result. Triage of waiting lists should include continuous monitoring of the patient and close communication with families despite social distancing and travel restrictions. Telehealth becomes a necessity. Common orthopaedic conditions are triaged into four groups according to urgency and safe and acceptable delay. Categories proposed are Emergent (life and limb threatening conditions), Urgent (within seven days), Semi-elective (postponed for three months) and Elective (postponed for three to 12 months). In total, 25 common orthopaedic conditions are reviewed and categorized. CONCLUSION: Given the uncertainty within healthcare during a pandemic, it is necessary to determine acceptable delays for elective conditions. We report our experience in developing guidelines and propose categorizing elective cases into four categories, based on the length of delay. Telemedicine plays a key role in determining the gravity of each situation and hence the amount of delay. These guidelines will assist others dealing with elective cases in the midst of a crisis. This paper initiates a coordinated effort to develop a consensus statement on safe delays.Published without peer review.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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