WAITING FOR SPINE SURGERY IN CANADA: AN EVALUATION OF WAIT TIMES, WAIT LISTS, AND SURGERIES PERFORMED BEFORE AND AFTER THE ONSET OF THE COVID-19 PANDEMIC
Bibliographic record
Abstract
To examine the impact of the COVID-19 pandemic on wait times for spinal surgery patients in Canada and quantify the number of patients waiting for spinal surgery and spinal surgeries performed. We included consented surgical patients from the 22 orthopaedic or neurological surgical centers participating in the CSORN registry. Study outcomes included wait times from surgical consult to surgery (T2) and from general practitioner referral to surgery (T3), counts of patients on the waitlist and surgeries performed. These outcomes were measured in three-month intervals from December 01, 2017, to February 01, 2022. All cohorts were categorized by severity of their clinical condition as ‘semi-urgent,’ including myelopathy, fracture, infection, tumour, inflammatory spine disorder, spondylolisthesis types 4, 5, and 6, or motor impairments. The remaining patients were classified as ‘elective.’ Quantile regression was used to model the national change in T2 and T3 median days over time. We reported counts for patients waiting for surgery and surgeries performed. The COVID-19 pandemic negatively impacted the national surgical consultation to surgery (T2) and the general practitioner referral to surgery (T3) wait times for elective and semi-urgent surgery patients. The number of patients on the waitlist for both surgical cohorts nearly doubled during the pandemic, and the number of surgeries performed during the pandemic fell. Evidence suggests a negative impact of the COVID-19 pandemic on wait times for elective and semi-urgent spinal surgery subgroups, a trend of increasing waitlists and decreasing spinal surgeries performed. These findings should inform future healthcare policies in the event of another disruptive health emergency and highlight the need to target the backlog of spinal surgeries. Future research should investigate the post-pandemic environment to identify the persistence of surgical delay and its effects on spinal conditions.
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.
How this classification was reachedexpand
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".