The incremental value of exercise ECG to myocardial perfusion SPECT for prediction of cardiac events
Bibliographic record
Abstract
Abstract Background Both myocardial perfusion SPECT (MPS) and exercise ECG (Ex-ECG) are known to carry prognostic information in patients with chronic coronary syndrome (CCS). However, it is not fully understood if combining MPS and Ex-ECG results improves risk prediction. Current guidelines no longer recommend Ex-ECG for diagnostic evaluation of CCS, but adding Ex-ECG results to MPS could be of incremental prognostic importance. Purpose The study aimed to assess the incremental prognostic value of Ex-ECG to MPS results in patients with CCS. Methods A single-center study of 908 consecutive patients with CCS (age 63±9 years, 49% male) who underwent a MPS with Ex-ECG. Subjects were followed for five years. The clinical endpoint was a composite of cardiovascular death (CV), acute myocardial infarction (AMI), unstable angina and unplanned PCI. National registry data and electronic medical charts were used for end point allocation. Results Combining the findings of MPS and Ex-ECG resulted in concordant evidence of ischemia in 72 patients (8%) or absence of ischemia in 634 patients (70%). Dis-concordant results were found in 202 patients (22%; MPS−/Ex-ECG+, n=126 and MPS+/Ex-ECG−, n=76). During follow-up 95 composite cardiac events occurred (CV deaths n=6, AMI n=27, unstable angina n=34 and unplanned PCI n=28). Kaplan-Meier curves display an increased risk of cardiac events in patients with any combination of abnormal stress test results (Figure 1). In a multivariable regression model (adjusting for age, sex, smoking, known IHD, diabetes, dyslipidaemia and exercise capacity) MPS was the strongest predictor of cardiac events regardless of Ex-ECG results (MPS+/Ex-ECG−, Hazard ratio (HR) = 3.0, p=0.001 or MPS+/Ex-ECG+, HR=4.0, p<0.001). However, an abnormal Ex-ECG almost doubled the risk of event in subjects with a normal MPS (MPS−/Ex-ECG+, HR=1.9, p=0.04). Conclusions Combining the results from MPS and Ex-ECG in patients with chronic coronary syndrome lead to an improved prediction of future cardiac events. Even though MPS is the stronger predictor, there is an incremental prognostic value of adding data from Ex-ECG to MPS, especially in patients with normal MPS findings. Funding Acknowledgement Type of funding sources: Public Institution(s). Main funding source(s): Swedish Heart and Lung Foundation, Region of Scania
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".