Primary Biliary Cirrhosis (PBC), PBC Autoantibodies, and Hepatic Parameter Abnormalities in a Large Population of Systemic Sclerosis Patients
Bibliographic record
Abstract
OBJECTIVE: To investigate the diagnostic accuracy of antimitochondrial antibodies (AMA), sp100, and gp210 antibodies for primary biliary cirrhosis (PBC) in a large population of patients with systemic sclerosis (SSc); to examine concordance of these antibodies with subsets of SSc. Further, to assess the association of SSc-related antibodies with hepatic parameter abnormalities. METHODS: We obtained medical records to verify the diagnoses of SSc and PBC. Sera from all participants were examined for the presence of SSc- and PBC-related antibodies, as well as for abnormalities in hepatic parameters. RESULTS: We examined 817 patients with SSc, of whom 16 (2%) had confirmed PBC. The sensitivity and specificity of AMA by a MIT3 ELISA for PBC were 81.3% and 94.6%, respectively. Sp100 had a sensitivity and specificity of 31.3% and 97.4%, respectively, while gp210 had an even lower sensitivity. We were able to detect all PBC cases using AMA(MIT3) and sp100 as a combined marker, resulting in a significantly improved sensitivity of 100% (p = 0.042) with an incremental decrease in specificity to 92.6%. Independent of AMA or sp100 status, there was an association of anticentromere B (CENP-B) and anti-topoisomerase antibodies (ATA) with higher alkaline phosphatase levels (p = 0.051 and p = 0.003, respectively) while anti-RNA polymerase III (anti-RNAP) was associated with lower alkaline phosphatase levels (p = 0.019) among the patients with SSc. CONCLUSION: Utilization of AMA(MIT3) and sp100 antibodies as a combined diagnostic marker leads to an improved detection of PBC in patients with SSc. CENP-B and ATA are associated with alkaline phosphatase elevation.
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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) | 0.001 | 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".