Knowledge, Awareness, and Attitudes Regarding Axial Spondylarthritis Among Nonrheumatology Physicians in the United States
Bibliographic record
Abstract
OBJECTIVE: We surveyed physicians in the United States to assess knowledge, awareness, and attitudes toward axial spondyloarthritis (axSpA). The objective was to identify barriers for referral and opportunities for intervention to reduce diagnostic delay of axSpA. METHODS: An online questionnaire was distributed nationwide to nonrheumatology physicians (NRPs) serving patients with chronic back pain (CBP), namely in family/internal medicine, spine surgery/orthopedics, pain management, physical medicine/rehabilitation, and to rheumatologists as the comparator group. RESULTS: Seven hundred fifty physicians completed the survey (response rate 24%). The majority of NRPs were familiar with inflammatory back pain (IBP); 87% could identify > 4 of 8 IBP items, but only 41% routinely assess for IBP in practice. NRPs screen patients for axSpA risk factors ≤ 50% of the time. NRPs order C-reactive protein and HLA-B27 tests significantly less often, and antinuclear antibodies and rheumatoid factor tests significantly more often than rheumatologists in patients with CBP. Only 50% of NRPs correctly answered sacroiliac/pelvic radiograph as the correct initial imaging test, and 37% correctly selected magnetic resonance imaging of the pelvis as the next imaging test. Unfamiliarity with the terms axSpA and nonradiographic axSpA was reported by 11% and 35% of NRPs, respectively, and NRPs less often consider axSpA as a possible diagnosis in patients with CBP. Formal referral guidelines for patients with suspected axSpA were felt to be important by NRPs and rheumatologists alike. CONCLUSION: There is a substantial lack of knowledge and awareness about nomenclature, laboratory testing, and proper imaging of axSpA among NRPs. Unnecessary laboratory tests are commonly ordered by NRPs and rheumatologists. Formal referral guidelines and improved education may help reduce diagnostic delay of axSpA.
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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 | 0.000 | 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) | 0.002 | 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".