Evaluating the diagnostic and prognostic value of cardiac biomarkers for heart disease and major adverse cardiac events in patients with muscular dystrophy
Bibliographic record
Abstract
Abstract Background Heart disease is recognized as the leading cause of morbidity and mortality in patients with muscular dystrophy (MD). Validating and testing for heart disease in this vulnerable cohort of patients will allow for early cardiac interventions, monitoring, and improved outcomes. Purpose To evaluate the diagnostic and prognostic value of baseline B-type natriuretic peptide (BNP) and high-sensitive troponin I (hsTnI) for cardiomyopathy and major adverse cardiac events (MACE), respectively, in patients with MD. Methods A prospective cohort study was conducted at our clinic following 117 patients [median age, 42 years (interquartile range [IQR], 26–50); 49 (41.88%) women] diagnosed with a dystrophinopathy, limb-girdle MD, type 1 myotonic dystrophy, or facioscapulohumeral MD. Patients received multifaceted care as part of the multidisciplinary pathway allowing for a complete assessment of patient clinical status. Cardiac assessment included physical exam and electrocardiogram as well as subsequent echocardiogram and cardiac magnetic resonance imaging. Receiver operating curves and corresponding Youden's Indices were utilized to assess the diagnostic abilities of the biomarkers and for subsequent derivation of hazard ratios (adjusted by patient demographics and diagnosis of cardiomyopathy and respiratory disease) for incidence of MACE (defined as the composite of arrhythmia, device implantation, cardiac-related hospitalization, incident heart failure, and cardiac-related mortality). Results At baseline, 35 (29.91%) patients were diagnosed with a cardiomyopathy. B-type natriuretic peptide was an effective diagnostic marker of cardiomyopathy with an area under the curve (AUC) of 0.64 (95% confidence interval (CI), 0.52–0.76; P=0.017), as was hsTnI (AUC, 0.69 [95% CI, 0.58–0.80]; P=0.001). In combination, BNP and hsTnI showed additive diagnostic ability for cardiomyopathy [AUC: 0.72 (95% CI, 0.61–0.83); P<0.001]. Over a median follow-up period of 2.09 years (IQR, 1.17–2.81) there were 36 confirmed MACE. Patients were stratified based on cutoff values of BNP and hsTnI established a priori defined as 30.50 pg/mL and 7.61 ng/L, respectively. Patients with BNP levels above the cutoff value had a 4.76-fold (95% CI, 2.13–10.65; P<0.001) greater risk of MACE than patients with BNP levels below. Patients with hsTnI levels above the cutoff value had a 3.98-fold (95% CI, 1.96–8.12; P<0.001) greater risk of MACE than patients with hsTnI levels below. Importantly, patients with biomarker levels above both cutoff values had a 5.28-fold (95% CI, 2.42–11.51; P<0.001) greater risk of MACE than patients with biomarker levels below both cutoffs. Conclusion Our study demonstrates that by including measures of BNP and hsTnI as part of a comprehensive cardiac assessment, the diagnosis of cardiomyopathy and prognostication of MACE can be improved in patients with MD. Risk Stratification of MACE Funding Acknowledgement Type of funding source: Public hospital(s). Main funding source(s): University Hospital Foundation, University of Alberta
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".