Daily Cardiology Research Analysis
Three impactful cardiology studies stood out: a comprehensive HTA meta-analysis and decision model defines cost-effective pathways for diagnosing acute aortic syndrome using ADD-RS and D-dimer; an AI-enabled strategy using coronary calcium from CT attenuation scans can safely double stress-only SPECT-MPI workflows; and pooled randomized data show IL-1 blockade with anakinra reduces systemic inflammation and improves HF-related outcomes after STEMI irrespective of prior CAD.
Summary
Three impactful cardiology studies stood out: a comprehensive HTA meta-analysis and decision model defines cost-effective pathways for diagnosing acute aortic syndrome using ADD-RS and D-dimer; an AI-enabled strategy using coronary calcium from CT attenuation scans can safely double stress-only SPECT-MPI workflows; and pooled randomized data show IL-1 blockade with anakinra reduces systemic inflammation and improves HF-related outcomes after STEMI irrespective of prior CAD.
Research Themes
- Diagnostic pathways and cost-effectiveness in acute aortic syndrome
- AI-enabled imaging triage to streamline SPECT-MPI
- Targeting inflammation (IL-1 blockade) in STEMI
Selected Articles
1. Diagnostic strategies for suspected acute aortic syndrome: systematic review, meta-analysis, decision-analytic modelling and value of information analysis.
This HTA combined meta-analyses of ADD-RS and D-dimer with decision-analytic and value-of-information modeling to define accurate and cost-effective pathways for suspected acute aortic syndrome. Strategies using ADD-RS>1 alone were cost-effective in unselected low-prevalence settings, while combining ADD-RS with D-dimer became cost-effective when clinicians preselect higher-risk populations.
Impact: Defines evidence-based, cost-effective diagnostic algorithms that can directly inform ED triage and imaging utilization for acute aortic syndrome.
Clinical Implications: Adopt ADD-RS>1-triggered CTA in unselected populations; in clinician-enriched higher pretest probability settings, use ADD-RS with D-dimer (e.g., ADD-RS>1 or D-dimer>500 ng/mL) to safely reduce unnecessary CTA while maintaining near-perfect sensitivity.
Key Findings
- ADD-RS>0: sensitivity 94.6% (90–97.5%), specificity 34.7% (20.7–51.2%); ADD-RS>1: sensitivity 43.4% (31.2–57.1%), specificity 89.3% (80.4–94.8%).
- ADD-RS>0 or D-dimer>500 ng/mL: sensitivity 99.8% (98.7–100%), specificity 21.8% (12.1–32.6%); ADD-RS>1 or D-dimer>500 ng/mL: sensitivity 98.3% (94.9–99.5%), specificity 51.4% (38.7–64.1%).
- Decision modeling: in unselected populations (AAS prevalence 0.26%), only ADD-RS>1-to-CTA was cost-effective; in higher-prevalence cohorts (0.61%), combined ADD-RS/D-dimer strategies were cost-effective and deliverable.
- Population expected value of perfect information approximated £17.75 million at £20,000/QALY thresholds.
Methodological Strengths
- PRISMA-consistent systematic review with QUADAS-2 bias assessment and hierarchical meta-analytic models (multinomial/bivariate).
- Integrated decision-analytic and value-of-information modeling linking diagnostic accuracy to QALYs and costs.
Limitations
- Marked heterogeneity in specificity estimates across studies.
- Uncertainty in defining the suspected AAS population and in modeling delayed diagnosis effects.
Future Directions: Prospective comparative studies of ADD-RS/D-dimer combinations in real-world ED pathways and evaluation of alternative biomarkers to improve specificity.
BACKGROUND: Acute aortic syndrome is a life-threatening condition that requires urgent diagnosis with computed tomographic angiography. Diagnostic technologies, including clinical scores and biomarkers, can be used to select patients presenting with potential symptoms of acute aortic syndrome for computed tomographic angiography. OBJECTIVES: We aimed to estimate the accuracy of clinical scores and biomarkers for diagnosing acute aortic syndrome, the cost-effectiveness of alternative diagnostic strategies and the expected value of future research. METHODS: We searched online databases from inception to February 2024, reference lists of included studies and existing systematic reviews. We included cohort studies evaluating the accuracy of clinical scores or biomarkers for diagnosing acute aortic syndrome compared with a reference standard. Two authors independently selected and extracted data. Risk of bias was appraised using the quality assessment of diagnostic accuracy studies-2 tool. Data were synthesised using either a multinomial or a bivariate normal meta-analysis model. We developed a decision-analytic model to simulate the management of a hypothetical cohort of patients attending hospital with possible acute aortic syndrome. We modelled diagnostic strategies that used the Aortic Dissection Detection Risk Score and D-dimer to select patients for computed tomographic angiography. We used estimates from our meta-analysis, existing literature and clinical experts to model the consequences of diagnostic strategies upon survival, health utility and healthcare costs.
2. Integrating perfusion with AI-derived coronary calcium on CT attenuation scans to improve selection of low-risk studies for stress-only SPECT myocardial perfusion imaging.
In 6,884 patients with stress TPD <5%, an AI-derived CAC=0 from CTAC identified a very low-risk group. Those with minimal perfusion abnormality (TPD 1–4%) and CAC=0 had lower MACE risk than TPD 0% (HR 0.58), whereas TPD 1–4% with CAC>0 had higher risk (HR 1.90). Using CAC=0 could double safe rest-scan cancellations (55% vs 25%).
Impact: Demonstrates a scalable, low-dose, AI-enabled approach to safely expand stress-only SPECT workflows, with immediate operational and radiation-sparing implications.
Clinical Implications: In patients with stress TPD <5%, integrating AI-derived CAC=0 from CTAC can guide safe rest-scan cancellation, streamline throughput, and reduce radiation, while flagging minimal perfusion defects with CAC>0 for full protocols and closer follow-up.
Key Findings
- Among 6,884 patients without known CAD and stress TPD <5%, those with TPD 1–4% and CAC=0 had lower MACE risk than TPD 0% (HR 0.58; 95% CI 0.45–0.76).
- Patients with TPD 1–4% and CAC>0 had higher MACE risk vs TPD 0% (HR 1.90; 95% CI 1.56–2.30).
- Using AI-derived CAC=0 to cancel rest scans could increase rest-scan cancelation from 25% to 55% while maintaining low event risk.
Methodological Strengths
- Large cohort with automated AI CAC quantification from routinely acquired CTAC.
- Time-to-event analyses with hazard ratios stratified by perfusion abnormality and CAC.
Limitations
- Retrospective design with potential selection and treatment biases.
- MACE definition included revascularization, which may be influenced by testing and referral patterns; follow-up duration not specified.
Future Directions: Prospective implementation trials comparing AI CAC–guided stress-only protocols vs standard workflows with patient-level outcomes and cost-effectiveness.
BACKGROUND: In many contemporary laboratories, a completely normal stress perfusion single-photon emission computed tomography myocardial perfusion imaging (SPECT-MPI) is required for rest imaging cancelation. We hypothesized that an artificial intelligence (AI)-derived coronary artery calcium (CAC) score of 0 from computed tomography attenuation correction (CTAC) scans obtained during hybrid SPECT/CT may identify additional patients at a low risk of major adverse cardiovascular events (MACEs) who could be selected for stress-only imaging. METHODS: Patients without known coronary artery disease who underwent SPECT/CT MPI and had stress total perfusion deficit (TPD) <5% were included. Stress TPD was categorized as no abnormality (stress TPD: 0%) or minimal abnormality (stress TPD: 1%-4%). CAC was automatically quantified from the CTAC scans. We evaluated associations with MACEs. RESULTS: In total, 6884 patients (49.4% males and median age: 63 years) were included.
3. Interleukin-1 blockade in patients with ST-segment elevation myocardial infarction with and without history of coronary artery disease.
Pooled randomized data (n=139) show that anakinra, an IL-1 blocker, significantly reduces systemic inflammation (CRP-AUC) after STEMI and improves HF-related outcomes with no interaction by prior CAD status. CRP-AUC was markedly lower with anakinra vs placebo in both CAD-history and CAD-naïve patients.
Impact: Reinforces inflammation as a modifiable therapeutic target post-STEMI and supports broader evaluation of IL-1 blockade across patient subgroups.
Clinical Implications: Consider enrollment in trials or compassionate use of IL-1 blockade for selected STEMI patients at high risk of HF, as benefits appear consistent irrespective of prior CAD; prioritize monitoring inflammation (e.g., CRP) to guide therapy.
Key Findings
- Across 3 RCTs (n=139), anakinra reduced CRP-AUC vs placebo in STEMI, regardless of CAD history: CAD-history 85 vs 349 mg·day/L; no-CAD 86 vs 213 mg·day/L; no treatment-by-history interaction (p=0.27).
- Event-free survival for HF-related composite outcomes improved with anakinra, with no significant interaction by CAD history (p=0.48).
- Findings support IL-1–mediated inflammation as a cross-cutting driver of post-STEMI HF risk.
Methodological Strengths
- Pooled randomized clinical trial data spanning three studies enhances causal inference.
- Consistent biomarker (CRP-AUC) and clinical composite outcomes with interaction testing.
Limitations
- Overall sample size remains modest; heterogeneity across trials may exist.
- Not powered for mortality; long-term outcomes and optimal treatment duration remain uncertain.
Future Directions: Adequately powered multicenter RCTs to test IL-1 blockade on hard outcomes (HF hospitalization, mortality) and to define timing, dose, and duration in contemporary STEMI care.
BACKGROUND: Patients with a history of coronary artery disease (CAD) presenting with ST-elevation myocardial infarction (STEMI) have high risk. We aimed to determine whether patients with CAD history presenting with STEMI had greater systemic inflammation and/or whether they benefitted similarly from IL-1 blockade. METHODS: We pooled data from three randomized clinical trials, including 139 patients with STEMI treated with anakinra or placebo. Patients were stratified by history of CAD defined as prior documented CAD, MI or coronary revascularization. The area under the curve (AUC) for C-reactive protein (CRP) was used to assess systemic inflammation. Event-free survival defined as the time from enrollment to the occurrence of a predefined adverse outcome, including new-onset heart failure, hospitalization for heart failure, or death, was compared using Cox regression analysis. RESULTS: Of the 139 patients, 113 (81 %) had no history of CAD, while 26 (19 %) had a history of CAD. The CRP-AUC was significantly lower in the anakinra group compared placebo, independent of history of CAD: 85 [47-137] vs. 349 [154-580] mg·day/L for anakinra and placebo, respectively, in patients with history of CAD, and 86 [43-179] vs. 213 [115-341] mg·day/L in patients without CAD history; p for interaction = (0.27). No significant interactions were found between history of CAD and treatment allocation for the composite outcome for patients with and without history of CAD, respectively, p for interaction = (0.48). CONCLUSION: IL-1 blockade with anakinra in STEMI leads to similar reductions in systemic inflammation and improvement in HF-related outcomes inpatients both with and without history of CAD.