Correlation Between Facial Pain or Headache and Computed Tomography in Rhinosinusitis in Canadian and U.S. Subjects
Bibliographic record
Abstract
OBJECTIVES: Objectives were 1) to determine whether a correlation exists between facial pain or headache and sinus disease severity by computed tomography (CT) scan in patients with rhinosinusitis and 2) to compare disease severity and pain perception in two geographically diverse North American patient populations. STUDY DESIGN: Prospective patient questionnaire before CT scan of the paranasal sinuses. METHODS: Patients with refractory rhinosinusitis were recruited at the University of Texas Medical Branch (Galveston, TX) and the University of Alberta (Edmonton, Alberta, Canada). Before CT scanning, patients completed a pain questionnaire. All scans were interpreted by one neuroradiologist and were scored using the Lund-McKay, Harvard, and Kennedy staging systems for rhinosinusitis. RESULTS: Fifty-one patients completed questionnaires (27 were Canadian). There was no correlation between pain severity and disease severity reflected by any of the three staging systems used (P >.05). The mean pain score for the U.S. patients was 7.3, and for Canadian patients, 5.2. The mean CT scores for U.S. versus Canadian patients were as follows: Lund-McKay, 2.6 versus 6.6; Harvard, 0.7 versus 1.0; and Kennedy, 1.4 versus 2.2. The Canadian patients had more severe disease on CT scan (Lund-McKay, P <or=.001; Harvard, P <or=.005; and Kennedy, P <or=.007) while reporting less severe pain (P <or=.004). CONCLUSIONS: There was no correlation between pain severity and disease severity by sinus CT scan as graded by the Lund-McKay, Harvard, or Kennedy staging system. Facial pain and headache, although frequent complaints of patients with rhinosinusitis, are not useful predictors of sinus disease severity. There appears to be a difference in pain perception between the two North American populations.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".