Diagnostic Value of Clinical, Laboratory, and Imaging Findings in Patients with a Clinical Suspicion of Gout: A Systematic Literature Review
Bibliographic record
Abstract
OBJECTIVE: To analyze the diagnostic utility of clinical, laboratory, and imaging items for gout. METHODS: A systematic literature search was performed in MEDLINE, EMBASE, and The Cochrane Library; and a manual search of abstracts from the 2010/2011 meetings of the American College of Rheumatology (ACR) and the European League Against Rheumatism, as well as the reference lists of retrieved papers. Studies were included if they evaluated the diagnostic utility of clinical, laboratory, or imaging features or criteria for the diagnosis or classification of gout in adult patients. Two independent reviewers selected papers, extracted the data, and assessed the risk of bias. RESULTS: Nineteen studies were included in the review; 4 used the identification of monosodium urate (MSU) crystals as the reference standard (RS) and the rest used expert opinion or the ACR preliminary criteria. Most features were evaluated in a single study. Evidence for diagnostic utility, using MSU crystals as RS, of over 50 individual clinical, laboratory, and radiographic features was retrieved. Most items showed a positive likelihood ratio (LR+) < 3, except for the following: response of arthritis to colchicine (LR+ 4.3); presence of tophi on physical examination (LR+ 15.6-30.9); identification of the double-contour sign in ultrasound (US) (LR+ 13.6); and detection of urate deposits by dual-energy computed tomography (DECT) (LR+ 9.5). CONCLUSION: Individual clinical features show low diagnostic utility, with the exception of tophi and response to colchicine. Some US and DECT findings show better performance than most clinical features.
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 | 0.011 | 0.065 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.022 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".