Rationale and design of the long‐Term rIsk, clinical manaGement, and healthcare Resource utilization of stable coronary artery dISease in post–myocardial infarction patients (TIGRIS) study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The long-term progression of coronary artery disease as defined by the natural disease course years after a myocardial infarction (MI) is an important but poorly studied area of clinical research. The long-Term rIsk, clinical manaGement, and healthcare Resource utilization of stable coronary artery dISease in post-myocardial infarction patients (TIGRIS) study was designed to address this knowledge gap by evaluating patient management and clinical outcomes following MI in different regions worldwide. TIGRIS (ClinicalTrials.gov Identifier: NCT01866904) is a multicenter, observational, prospective, longitudinal study enrolling patients with history of MI 1 to 3 years previously and high risk of developing atherothrombotic events in a general-practice setting. The primary objective of TIGRIS is to evaluate clinical events (time to first occurrence of any event from the composite cardiovascular endpoint of MI, unstable angina with urgent revascularization, stroke, or death from any cause), and healthcare resource utilization associated with hospitalization for these events (hospitalization duration and procedures) during follow-up. Overall, 9225 patients were enrolled between June 2013 and November 2014 and are being followed in 369 different centers worldwide. This will allow for the description of regional differences in patient characteristics, risk profiles, medical treatment patterns, clinical outcomes, and healthcare resource utilization. Patients will be followed for up to 3 years. Here we report the rationale, design, patient distribution, and selected baseline characteristics of the TIGRIS study. TIGRIS will describe real-world management, quality of life (self-reported health), and healthcare resource utilization for patients with stable coronary artery disease ≥1 year post-MI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 it