Attitudes of Canadian Plastic Surgeons on Temporal Artery Biopsy in Giant Cell Arteritis Management
Bibliographic record
Abstract
Background: Temporal artery biopsies (TAB) rarely impact management of patients with suspected giant cell arteritis and carry complications. We sought plastic surgeons’ perspectives on this procedure’s risks and benefits. Methods: An email survey was designed, piloted, and refined to elicit Canadian Society of Plastic Surgeons (CSPS) members about TAB’s diagnostic contribution, complications, usefulness as a resident education tool, and surgeons’ insight into emerging diagnostic modalities like ultrasound. Text comments were sought at each question. A reminder was emailed one week later. Data was compared and analyzed using the chi-squared test and student t-test. Results: An estimated 83 responses were received from 435 surgeons (19%). Of the surgeons, 20% voiced uncertainty regarding TAB indications; 40% were unsure if TAB results changed steroid duration and dose; 83% did not see patients postoperatively. Surgeons recalled 29 cases of hematoma and three facial nerve injuries from TAB. In total, 80% felt TAB was a valuable learning opportunity for residents, although residents were involved in only 21% of cases; 65% of surgeons supported a changeover to ultrasound as primary diagnostic modality. Analysis of text comments revealed a sense of futility from TAB and disdain toward being mere technicians. Several participants wished for stakeholders to collaborate and potentially endorse noninvasive diagnostic modalities. Conclusions: This survey demonstrated varying attitudes to TAB. Generally, plastic surgeons were uncertain of TAB’s contribution to treatment, tended not to follow-up on results or patients, and recognized a number of complications. Conversations are desired regarding switching from scalpel to probe to evaluate the temporal artery.
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 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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".