Evaluation of Clinical Measures and Different Criteria for Diagnosis of Adult-onset Still’s Disease in a Chinese Population
Bibliographic record
Abstract
OBJECTIVE: To determine the value of clinical measures in diagnosis of adult-onset Still's disease (AOSD), and to identify the optimal set of proposed classification criteria, in a Chinese population. METHODS: A total of 70 patients with AOSD and 140 non-AOSD inpatients with fever were retrospectively identified at Zhongshan Hospital, Shanghai, from January 2003 to December 2009. Clinical measures and 4 sets of diagnostic criteria (Yamaguchi, Calabro, Cush, and Reginato) were evaluated by sensitivity, specificity, positive/negative predictive value (PPV, NPV), and positive/negative likelihood ratio (PLR, NLR) for diagnosis of AOSD. RESULTS: In our series, higher sensitivity included hyperpyrexia (temperature ≥ 39°C, 94.29%), arthralgia (80.0%), polymorphonuclear neutrophils (PMN) ≥ 75% (84.29%), serum ferritin ≥ 2-fold the upper normal value (90.0%), negative antinuclear antibodies (85.29%), and rheumatoid factor (84.38%); while higher specificity included transient erythema (98.57%), sore throat (85.0%), leukocytes ≥ 15,000/mm(3) (87.86%), and PMN ≥ 85% (85.0%). Rash, arthralgia, and sore throat were found to have better sensitivity and specificity (PLR 3.29-4.86). Leukocytes ≥ 10,000/mm(3), PMN ≥ 80%, and serum ferritin ≥ 5-fold the upper normal limit were set as critical points. The Reginato criteria set had the highest specificity, 99.29%. The Yamaguchi set had the highest sensitivity, 78.57%, with a better accuracy of 87.14%. CONCLUSION: The Yamaguchi diagnostic criteria had better accuracy in Chinese patients. Indicators such as rash, arthralgia, sore throat, leukocytes ≥ 10,000/mm(3), PMN ≥ 80%, and serum ferritin ≥ 5-fold the upper normal limit were helpful for diagnosis of AOSD. We recommend using these indicators in combination instead of alone.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".