The First International Consortium for Health Outcomes Measurement (ICHOM) Standard Dataset for Reporting Outcomes in Heart Valve Disease: Moving From Device- to Patient-Centered Outcomes
Bibliographic record
Abstract
Background: Globally significant variation in treatment and course of heart valve disease (HVD) exists, and outcome measurement is procedure focused instead of patient focused. This article describes the development of a patient-related (International Consortium for Health Outcomes Measurement) standard set of outcomes and case mix to be measured in patients with HVD. Methods: A multisociety working group was formed that included patient representatives and representatives from scientific cardiology and cardiothoracic surgery societies that publish current guidelines for HVD. The standard set was developed to monitor the patient's journey from diagnosis to treatment with either a surgical or transcatheter procedure. Candidate clinical and patient-reported outcome measures (PROMs) and case mix were identified through benchmark analyses and systematic reviews. Using an online modified Delphi process, the working group voted on final outcomes/case mix and corresponding definition. Results: Patients with aortic/mitral/tricuspid valve disease or root/ascending aorta >40 mm were included in the standard set. Patients entered the dataset when the diagnosis of HVD was established, allowing outcome measurement in the preprocedural, periprocedural, and postprocedural phases of patients' lives. The working group defined 5 outcome domains: vital status, patient-reported outcomes, progression of disease, cardiac function and durability, and complications of treatment. Subsequently, 16 outcome measures, including 2 patient-reported outcomes, were selected to be tracked in patients with HVD. Case-mix variables included demographic factors, demographic variables, echocardiographic variables, heart catheterization variables, and specific details on aortic/mitral/tricuspid valves and their specific interventions. Conclusions: Through a unique collaborative effort between patients and cardiology and cardiothoracic surgery societies, a standard set of measures for HVD was developed. This dataset focuses on outcome measurement regardless of treatment, moving from procedure- to patient-centered outcomes. Implementation of this dataset will facilitate global standardization of outcome measurement, allow meaningful comparison between health care systems and evaluation of clinical practice guidelines, and eventually improve patient care for those experiencing HVD worldwide.
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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 | 0.083 | 0.178 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.008 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".