Safety and usefulness of minor salivary gland biopsy: Retrospective analysis of 502 procedures performed at a single center
Bibliographic record
Abstract
OBJECTIVE: To analyze the safety of our biopsy technique and the effectiveness of minor salivary gland biopsy (MSGB) for the diagnosis of Sjögren's syndrome (SS) and amyloidosis. METHODS: We conducted a retrospective analysis of 452 patients with suspected SS and 50 with suspected amyloidosis and negative periumbilical fat aspiration analysis who underwent MSGB at a single center. Diagnostic evaluation for SS included Schirmer's test, unstimulated whole salivary flow, detection of antinuclear antibodies and anti-SSA/SSB, erythrocyte sedimentation rate, C-reactive protein, IgM rheumatoid factor, and serology for hepatitis C virus. For all biopsy samples, a cumulative focus score on multilevel sections was calculated. SS was diagnosed according to American-European Consensus Group (AECG) criteria. Histologic evaluation for amyloidosis was performed using Congo red staining and polarized-light microscopy. Adverse events were recorded on a questionnaire immediately after the procedure and 7 days, 14 days, and 6 months thereafter. RESULTS: Sixty-four patients (12.7%) reported transient adverse events: 40 paresthesias lasting <7 days, 17 paresthesias lasting <14 days, 27 cases of local swelling, and 8 external hematoma. One patient has had local paresthesia for 2 years. A total of 498 (99.2%) samples provided adequate material for histologic analysis. Of 452 patients evaluated for SS, 378 were finally evaluated. Ninety-three patients (24.5%) had a cumulative focus score > or =1, and 87 (94.5%) of 93 satisfied the AECG criteria. Classification of SS was possible for 124 (32.8%) of 378 patients. In 51 (41%) of 124, MSGB was essential to reach the number of criteria needed for classification. Of 50 patients evaluated for amyloidosis, 10 (20%) had positive Congo red staining. CONCLUSION: MSGB is a simple, safe, and reliable tool for the diagnosis of SS and amyloidosis, and therefore is suitable for more extensive application.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".