Type-I MI diagnostic-utility explorer
Rank every biomarker for its usefulness in diagnosing Type-I (atherothrombotic) MI. Each marker carries six evidence-anchored sub-scores; you decide how much each one matters using the sliders. The composite and the ranking recompute instantly. Start from a preset (rule-in, deployable-today, novel discovery) or set your own weights. Scores with no evidence show — and are never invented.
Three axes are directly diagnostic — Diagnostic performance (sensitivity/specificity/AUC), Release kinetics (how early it rises), and Incremental value vs troponin — extracted from accuracy studies. Only ~14 markers have any of this data (procalcitonin, troponin T, Cardiac troponin T/I, myoglobin, CK-MB, cMyBP-C for kinetics; MR-proADM, ApoJ-Glyc, IMA, cystatin C for accuracy; GDF-15, ST2, BNP, myoglobin, troponin T, MR-proADM, CK-MB, Creatine kinase-MB, cMyBP-C for incremental value); for everything else these show —. That sparsity is itself the finding: very few candidates have been studied as an MI index test the way troponin has.
ⓘ Methodology — how the criteria and the ranking are built
This explorer scores each biomarker against nine criteria, each normalized to 0–100 (higher is better for a Type-I diagnostic), and combines them into a single composite using weights you set. The criteria fall into three groups. Discrimination criteria — plaque-rupture signal (R), specificity vs demand (the confounder score C, inverted), and direct T1 > T2 evidence (D) — come from the atlas's Type-I-vs-Type-II scoring and capture whether a marker reflects atherothrombosis rather than the supply–demand mismatch of a Type-II MI. Direct diagnostic criteria — diagnostic performance (sensitivity/specificity/AUC), release kinetics (how early it rises), and incremental value vs troponin — are extracted from index-test / accuracy studies in the literature; only ~14 markers have any of this data, and the rest correctly show — rather than a fabricated value. Practical criteria — assay feasibility, evidence strength, and novelty — capture deployability and how under-explored a marker is (incumbents already in clinical use are capped low so they never register as novel).
Composite. The score is a weighted average of the available sub-scores. When “penalize missing data” is on, the average divides by the total weight you assigned, so a marker with unmeasured criteria is pulled down — this rewards markers that have actually been studied across the board. Turn it off to divide only by the weight of the criteria a marker does have, scoring each marker on its own evidence. Presets (rule-in, deployable-today, best diagnostic test, novel discovery) are just saved weight profiles; every weight remains adjustable.
Hover (or tab to) any criterion label or table column header for its definition. Scores are evidence-anchored inferences for hypothesis prioritization, not a validated clinical instrument — see the Methods page for the full harvest and scoring provenance.
How the composite works: each sub-score is 0–100 (higher = better for a Type-I diagnostic). The composite is a weighted average of the sub-scores using your slider weights. “Penalize missing data” divides by the total weight rather than only the covered weight, so markers with gaps rank lower — turn it off to score markers on the evidence they do have. This is a hypothesis-prioritization tool, not a validated clinical instrument.