Implementation of Z-Scores as an Age- and Sex-independent Parameter for Estimating Joint Space Widths in Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: To compare normative data of joint space distances (JSD) with the JSD of patients with rheumatoid arthritis (RA) as measured by computer-aided joint space analysis (CAJSA) at the metacarpophalangeal (MCP) articulations, and to differentiate age- and sex-related alterations from the disease-related joint space narrowing. METHODS: In total, 256 healthy subjects and 248 patients with verified RA (following revised ACR criteria) underwent computerized semiautomated measurements of JSD (CAJSA, version 1.3.6) at the MCP articulation (JSD-MCP) based on digital radiographs. The Z-score, a comparative parameter that differentiates joint space alterations caused by RA-related cartilage destruction from age- and sex-related changes, was calculated. RESULTS: Our data showed a relationship between measured joint space widths (MCP total and MCP thumb to little finger) and age for healthy subjects and also the RA group. The RA group revealed an age-related joint space narrowing that was surpassed by the RA-related narrowing of joint space widths classified by Sharp joint space narrowing score and resulting in smaller Z-scores for RA patients. CONCLUSION: The CAJSA technique seems to distinguish age-related JSD changes in healthy volunteers from RA-induced alterations. In addition the Z-score was also able to differentiate RA-dependent narrowing of JSD. Calculation of the Z-scores based on sex- and age-specific reference data may facilitate earlier identification of patients with RA, allowing initiation of a more optimal, individually adapted therapeutic strategy.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".