Scleroderma Clinical Trials Consortium Classification Criteria for Systemic Sclerosis Heart Involvement
Bibliographic record
Abstract
Abstract Objectives Systemic sclerosis (SSc) heart involvement (SHI) is an enigmatic disease manifestation associated with high mortality. The Scleroderma Clinical Trials Consortium (SCTC) Cardiac Working Group developed SHI classification criteria to enable systematic investigation of this condition. Methods An international, inter-disciplinary working group was assembled. Using consensus methods and existing literature, provisional SHI classification criteria items were developed. Continuous consensus exercises and a discrete choice experiment were performed to reduce items and derive individual item weights. The sensitivity and specificity of the classification criteria were tested in an independent cohort (n=168) of SHI (cases) and non-SSc heart disease (controls). Results The working group agreed that the SCTC SHI Classification Criteria should identify the direct effects of SSc on the heart and exclude the complications of other SSc manifestations or cardiac co-morbidities. The final classification criteria include 23 items measuring cardiac fibrosis, inflammation, arrhythmias and small vessel vasculopathy. No single item is pathognomonic for SHI, with a requirement for the presence of abnormalities across multiple histopathological, imaging, serological and, or clinical domains to be present to secure a diagnosis. A classification criteria score of ≥11 identified SHI with a sensitivity of 78% and specificity of 96%, with an area under the curve of 0.87 (0.80-0.93). This threshold correctly identified >90% of cases of SHI. Conclusion The newly derived SCTC SHI Classification Criteria have high sensitivity and specificity for SHI. Application of these criteria will enable standardised classification of patients in studies to facilitate future investigation of this important disease manifestation. Graphical abstract Abbreviations: AUC: area under the curve; IHD: ischaemic heart disease; PAH: pulmonary arterial hypertension; SHI: systemic sclerosis heart involvement; SRC: scleroderma renal crisis Alt text: Flow chart representing the steps to define systemic sclerosis heart involvement criteria, staring from scope and planning, item generation, item reduction and weighting and concluding with defining a classification threshold and testing performance of criteria. A criteria score of 11 or greater classifies a patient as having systemic sclerosis heart involvement. Key messages This study presents the first classification criteria for the identification of systemic sclerosis heart involvement. A score of ≥11 identifies systemic sclerosis heart involvement with high sensitivity and specificity. Standardised criteria enable identification of biomarkers and risk predictions models and lead to effective treatments for heart involvement.
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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 | 0.038 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".