Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1)

Coronary Calcium Scoring Improves Risk Prediction in Patients With Suspected Obstructive Coronary Artery Disease




Julkaisun tekijät: Winther Simon, Schmidt Samuel E, Foldyna Borek, Mayrhofer Thomas, Rasmussen Laust D, Dahl Jonathan N, Hoffmann Udo, Douglas Pamela S, Knuuti Juhani, Bøttcher Morten

Kustantaja: Elsevier

Julkaisuvuosi: 2022

Journal: Journal of the American College of Cardiology

Tietokannassa oleva lehden nimi: Journal of the American College of Cardiology

Lehden akronyymi: J Am Coll Cardiol

Volyymi: 80

Julkaisunumero: 21

ISSN: 0735-1097

eISSN: 1558-3597

DOI: http://dx.doi.org/10.1016/j.jacc.2022.08.805

Verkko-osoite: https://doi.org/10.1016/j.jacc.2022.08.805


Tiivistelmä

Background

In patients with suspected obstructive coronary artery disease (CAD), the risk factor–weighted clinical likelihood (RF-CL) model and the coronary artery calcium score–weighted clinical likelihood (CACS-CL) model improves the identification of obstructive CAD compared with basic pretest probability (PTP) models.

Objectives

The aim of this study was to assess the prognostic value of the new models.

Methods

The incidences of myocardial infarction and death were stratified according to categories by the RF-CL and CACS-CL and compared with categories by the PTP model. We used cohorts from a Danish register (n = 41,177) and a North American randomized study (n = 3,952). All patients were symptomatic and were referred for diagnostic testing because of clinical indications.

Results

Despite substantial down-reclassification of patients to a likelihood ≤5% of CAD with either the RF-CL (45%) or CACS-CL (60%) models compared with the PTP (18%), the annualized event rates of myocardial infarction and death were low using all 3 models; RF-CL 0.51% (95% CI: 0.46-0.56), CACS-CL 0.48% (95% CI: 0.44-0.56), and PTP 0.37% (95% CI: 0.31-0.44), respectively. Overall, comparison of the predictive power of the 3 models using Harrell’s C-statistics demonstrated superiority of the RF-CL (0.64 [95% CI: 0.63-0.65]) and CACS-CL (0.69 [95% CI: 0.67-0.70]) compared with the PTP model (0.61 [95% CI: 0.60-0.62]).

Conclusions

The simple clinical likelihood models that include classical risk factors or risk factors combined with CACS provide improved risk stratification for myocardial infarction and death compared with the standard PTP model. Hence, the optimized RF-CL and CACS-CL models identify 2.5 and 3.3 times more patients, respectively, who may not benefit from further diagnostic testing.


Last updated on 2022-09-12 at 08:58