You are here

Article Text

Article menu
Coronary artery disease
Original research
Vall d’Hebron Risk Score II for myocardial infarction and cardiac death
  1. Guillermo Romero-Farina1,2,3,4,5,
  2. Santiago Aguadé-Bruix1,2,3 and
  3. Ignacio Ferreira González5,6
  1. 1Nuclear Cardiology, Department, Hospital Universitari Vall d'Hebron, Vall d’Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
  2. 2Centro de Investigación Biomédica en Red: Enfermedades Cardiovasculares (CIBER-CV), Hospital Universitari Vall d'Hebron, Madrid, Spain
  3. 3Grup d'Imatge Mèdica Molecular (GRIMM), Vall d’Hebron University Hospital, Barcelona, Spain
  4. 4Cardiology Department, Consorci Sanitari de l’Alt Penedès i Garraf (CSAPG), Barcelona, Spain
  5. 5Cardiology Department, Hospital Universitari Vall d'Hebron, Valld’Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
  6. 6Centro de Investigación Biomédica en Red: Epidemiología y Salud Pública (CIBER-EP), Madrid, Spain
  1. Correspondence to Dr Guillermo Romero-Farina; guiromfar{at}gmail.com

Abstract

Objectives The aim of this study was to create a new Vall d’Hebron Risk Score-II (VH-RS-II) for non-fatal myocardial infarction (MI) and/or cardiac death (CD), excluding patients with coronary revascularisation (CR) during the follow-up.

Methods We analysed 5215 consecutive patients underwent gated single photon emission CT (SPECT); 2960 patients (age 64.2±11, male 58.1%) had no previous MI and/or CR, and 2255 patients (age 63.3±11, male 81.9%) had previous MI and/or CR. During a follow-up of 4.3±2.6 years, the cardiac event (MI and CD) was evaluated. This study was reviewed and approved by the ethics committee of our institution (number form trial register, PR(AG)168.2012). To obtain the predictor model, multivariate Cox regression analysis and multivariate logistic regression analysis were used. RS-VH-II was validated with 679 patients.

Results In patients without previous MI and/or CR, age (HR: 1.01; p<0.001), diabetes (HR: 2.1, p=0.001), metabolic equivalent (METs) (HR: 0.89, p=0.038), ST segment depression (HR: 1.4, p=0.011), ejection fraction (EF) (HR: 0.97, p<0.001) and summed stress score (HR: 1.2, p<0.001) were the independent predictors of CE (C-statistic: 0.8). In patients with previous MI and/or CR, age (HR: 1.06, p<0.001), male (HR: 1.9, p=0.047), smoker (HR: 1.5, p=0.047), METs (HR: 0.8, p<0.001), ST segment depression (HR: 1.4, p=0.002), EF (HR: 0.96; p<0.001) and summed difference score (HR: 1.03, p=0.06) were the independent predictors of CE (C-statistic:0.8).

Conclusion The VH-RS-II obtained from different clinical exercise and gated SPECT variables allow the risk stratification for MI and CD in patients with or without previous MI and/or CR in due form.

  • Tomography, Emission-Computed, Single-Photon
  • Coronary Artery Disease
  • Risk Factors

Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/openhrt-2023-002431

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    WHAT IS ALREADY KNOWN ON THIS TOPIC

    • Coronary artery disease is the most frequent cause of mortality, and risk stratification for cardiac events remains a challenge.

    WHAT THIS STUDY ADDS

    • This study is interesting, in particular, because the number of evaluated patients is quite high. Furthermore, the Vall d’Hebron Risk Score method has several particular useful features, primarily, it focuses on patients with different clinical variables, who underwent exercise tests, and myocardial perfusion gated single photon emission CT. It also assesses an individual’s cardiac risk for non-fatal myocardial infarction and/or cardiac death.

    HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

    • We must pay attention to the use of multiple clinical and non-clinical variables to improve the risk stratification for the coronary event. Always try to integrate imaging tests to improve the prognostic study.

    • We have two different groups of patients for coronary risk stratification: patients with previous myocardial infarction and/or coronary revascularisation, and patients without previous coronary artery disease. This affects the type of predictor variables.

    Introduction

    There are multiple articles with different scores1–12 of cardiovascular risk stratification, and for decades coronary risk stratification has been a challenge.13–15 The Duke treadmill score (DTS) is most widely used.5 8 DTS is well recognised as a simple prognostic score in patients with suspected coronary artery disease. Furthermore, it is positioned as a valid clinical tool when clinicians need to make a decision about the catheterisation of patients with suspected CAD.16 However, over the years, different non-invasive imaging techniques have been positioned as the gold standard for coronary risk stratification. Recently, the Vall d’Hebron Risk Score (VH-RS) was published.7 This score has several particular useful features. First, it focuses on patients with different clinical variables, and also underwent exercise tests, and myocardial perfusion gated SPECT. Furthermore, it assesses an individual’s cardiac risk for a combined end point (non-fatal myocardial infarction (MI), cardiac death (CD) and coronary revascularisation (CR)).

    In this new analysis of the VH-RS, patients with CR during the follow-up were excluded. The exclusion is due to the possibility that intervening revascularisation either with percutaneous coronary intervention or coronary artery bypass graft in patients with significant ischaemia may have impacted the outcomes of cardiovascular death or MI. Therefore, the aim of this study was to create a new VH-RS (VH-RS-II) for MI and/or CD according to clinical, exercise and gated single photon emission CT (SPECT) variables, excluding patients revascularised during follow-up.

    Materials and methods

    Patients

    This was a prospective study. The cohort consisted of 5215 consecutive patients who underwent gated SPECT (period 2000–2008) (figure 1). This population is superposed with the previous one.7 All patients had been referred to our Nuclear Cardiology Unit for risk stratification or evaluation of their disease. This study conformed to the Declaration of Helsinki and was reviewed and approved by the ethics committee of our institution (number form trial register, PR(AG)168.2012). All patients provided written informed consent for stress-rest myocardial perfusion SPECT.

    Figure 1
    Figure 1

    Flow diagram showing the patients included in the study. CR, coronary revascularisation; MI, myocardial infarction; SPECT, single photon emission CT.

    Exercise stress test

    All patients underwent standard symptom-limited cycle ergometer (50%) or treadmill testing (50%) using standard protocols with a 12-lead recording and continuous monitoring. Bruce protocol or modified Bruce protocol were used until exhaustion, appearance of symptoms, ST segment depression >2 mm, the appearance of arrhythmias, hypertensive response to physical stress (systolic blood pressure >200 mm Hg or diastolic blood pressure >100 mm Hg) or failure of systemic blood pressure to increase. Angina, peak oxygen consumption estimated in metabolic equivalent (METs) and horizontal and downsloping ST depression ≥1 mm at 0.08 s beyond the J point were analysed.

    Myocardial perfusion-gated SPECT

    All patients underwent exercise-rest-gated SPECT. As regard the stress-rest studies, a 1-day protocol with 99mTc-tetrofosmine was performed. The first dose (30–60 s before ending the stress test) was of 8 mCi and the second (at rest) was of 24 mCi, with an interval longer than 45 min in between. The methodology employed for gated SPECT was the same methodology employed in previous publications.17 18

    Clinical outcomes

    The minimum follow-up time was 1 year (maximum 11.4 years), and the mean follow-up was 4.1±2.7 years (median 3.8 years, 25th–75th percentile: 1.6–6.2). All patients were followed up in the hospital, and the follow-up information was obtained by clinical history. There were no missing patients during the follow-up. All patients were followed up for cardiac events (CE). The primary endpoint was the first occurrence of a composite of non-fatal MI (myocardial infarction) and CD.

    Statistical analysis

    All continuous data were expressed as means (SD) and all non-continuous variables were expressed as percentages. Quantitative variables were compared using the Student’s t-test for unpaired samples. Differences between proportions were compared using the χ2 test. Fisher’s exact test was used when <5 patients were expected in any subgroup. The optimal cut-off value for the significant continuous variables related to the CE was determined by analysing the receiver operating characteristic (ROC) curves.

    To create the VH-RS-II, we used the same methodology as in VH-RS (7). We stratified patients into four risk levels according to CE/year: very low risk (VLR; <0.7 CE/year), low risk (LR; between 0.7 and 1 CE/year), moderate risk (MR; >1 and <3 CE/year) and high risk (≥3 CE/year) (7).

    Different Cox regression analyses (FSTEP (LR; forward stepwise, likelihood ratio); the threshold for variable entry into models was p<0.05; and for variable removal, p>0.10) were used to assess the independent predictor variables for CE. There was no evidence of violation of this assumption for any covariate. HR, 95% CIs and statistical significance for each group in the models were determined. Variables were selected for multivariate analysis when they presented significant differences in the univariate analysis or when they were considered of clinical relevance. All statistical tests were two sided. A value of p<0.05 was considered to be indicative of statistical significance. Data were analysed by STATA 18.

    Results

    Of 5215 patients studied, 2960 (age 64.2±11.2, male 58.1%) had no previous MI or CR, and 2255 (age 63.2±11, male 81.9%) had previous MI (n=1726, 76.5%) or CR (n=1136, 50.4%). The baseline characteristics of the patients with and without previous MI or CR are shown in table 1A and table 1B, respectively. Compared with patients without CE, the patients with CE had significantly higher left ventricular volumes, summed rest score (SRS), summed stress score (SSS), summed difference score (SDS), ↓ ST mm, lower left ventricular ejection fraction (LVEF) and METs, and more male, diabetes, hyperlipidaemia, smoker and medical treatment (beta-blockers, nitrates). During the follow-up, postgated SPECT (adjusted by age, gender, hypertension, hypercholesterolemia, diabetes and smoker), the patients with previous MI or CR had more CE (2.7% vs 5.9%) (Wald: 12 149; HR: 1.8 (95% CI 1.3 to 2.3); p<0.001) than patients without previous MI or CR. In the group of patients with previous MI or CR (n=2255), 1726 (76.5%) had previous MI, 36 (2.1%) of them had a second MI during the follow-up post-gated SPECT; 529 patients did not have previous MI and 3 (0.6%) of them had the first MI during the follow-up post-gated SPECT (McNemar test, p<0.001).

    View this table:
    Table 1

    (A) Characteristics of patients without previous myocardial infarction and/or coronary revascularisation according to cardiac events and (B) characteristics of patients with previous myocardial infarction and/or coronary revascularisation according to cardiac events

    In the group of patients without previous myocardial infarction and/or CR 356 (12%) patients had myocardial ischaemia, in 274 of them the ischaemia was mild (SDS between 3 and 4), moderate (SDS between 5 and 7) in 92 and severe (SDS ≥8) in 27 patients.

    In the group of patients with previous myocardial infarction and/or CR, 391 (17%) patients had myocardial ischaemia, in 268 of them, the ischaemia was mild (SDS between 3 and 4), moderate (SDS between 5 and 7) in 103 and severe (SDS ≥8) in 20 patients.

    Patients with myocardial mild ischaemia in both groups continued with medical treatment and coronary angiography was not performed. Also all patients with moderate and severe ischaemia continued with medical treatment, although half of them were studied with invasive coronary angiography or coronary CT. These patients did not undergo CR following medical decision or patient-medical consensus and coronary anatomy. In the rest of the patients, a study of the coronary anatomy was not carried out due to advanced coronary disease with multiple coronary angiographies, medical decision or by patient medical consensus, advanced age, advanced renal failure and stroke.

    Predictors of CEs in patients without previous myocardial infarction and/or coronary revascularisation

    In a first multivariate model, clinical variables (age, gender, diabetes mellitus, angina, hyperlipidaemia, smoker, rest blood pressure, beta-blockers, nitrates) were included. Age (Wald: 32,069; HR: 1.1 (95% CI 1.05 to 1.2), p<0.001), diabetes (Wald: 10 980; HR: 2.2 (95% CI 1.4 to 3.4), p=0.001), angina (Wald: 3,749; HR: 1.8 (95% CI 0.9 to 3.1), p=0.053) and nitrates (Wald: 4439; HR: 1.6 (95% CI 1.03 to 2.5), p=0.035) were the independent predictors of CE. In a second multivariate model stress variables (METs, exercise angina and ST segment depression) were considered. METs (Wald: 23 500; HR: 0.8 (95% CI 0.7 to 0.88), p<0.001) and ‘mm’ of ST segment depression (Wald: 23 738; HR: 1.7 (95% CI 1.4 to 2.1), p<0.001) were the independent predictor of CE. In a third multivariate model gated SPECT variables (left ventricular volumes, EF, SRS, SSS and SDS) were considered. SSS (Wald: 34,631; HR: 1.2 (95% CI 1.1 to 1.3), p<0.001) and the EF (Wald: 10 892; HR: 0.97 (95% CI 0.96 to 0.99), p=0.001) were the independent predictor of CE. In the final model, and for clinical consensus, the significant variables in previous models were included age, gender, diabetes, angina, nitrates, METs, ‘mm’ of ST segment depression, SSS and EF were included. Age (Wald: 24 573; HR: 1.01 (95% CI 104 to 1.1); p<0.001), diabetes (Wald: 10 104; HR: 2.1 (95% CI 1.3 to 3.4), p=0.001); METs (Wald: 4300; HR: 0.89 (95% CI 0.79 to 0.99), p=0.038); ‘mm’ of ST segment depression (Wald: 6512; HR: 1.4 (95% CI 1.1 to 1.8), p=0.011), EF (Wald: 16 549; HR: 0.97 (95% CI 0.95 to 0.98), p<0.001) and SSS (Wald: 19 380; HR: 1.2 (95% CI 1.1 to 1.2), p<0.001) were the independent predictors of CE. The final model with the HR of the optimal cut-off value for the significant qualitative variables related to the CE is shown in table 2A, and the final model with ẞ-coefficients for calculating the probability of CE by means of logistic regression analysis is shown in table 2B. ROC curve analysis was performed to evaluate the ability of this model to predict CE (C-statistic: 0.81 (95% CI 0.75 to 0.85); p<0.001) (figure 2A). When increasing the number of the independent predictors, the prevalence of CE increases too (figure 3A). All patients were stratified in four risk levels: VLR (n=1888), LR (n=611), MR (n=250), HR (n=211). The correlation between the levels of VHRS and number of risk variables, annual CE and relative risk is shown in figure 4A.

    View this table:
    Table 2

    (A) Multivariate Cox regression analysis results in patients without and with previous myocardial infarction and/or coronary revascularisation and (B) multivariate logistic regression analysis model for calculated probability of hard events in patients without and with previous myocardial infarction or coronary revascularisation

    Figure 2
    Figure 2

    ROC curve analysis to evaluate the ability of the final model to predict cardiac events (CE) in patients without (A) and with (B) previous myocardial infarction and/or coronary revascularisation show an acceptable predictive value (AUC, area under curve: 0.8). ROC, receiver operating characteristic.

    Figure 3
    Figure 3

    Kaplan-Meier curve for number of predictive variables. (A) Patients without previous myocardial infarction (MI) and/or coronary revascularisation (CR) (for a one-unit increase in number of variables the rate ratio to CE increases 2.5 (95% CI: 2 to 2.9, p<0.001); and (B) patients with previous MI and/or CR (for a one-unit increase in number of variables the rate ratio to CE increases 2.1 (95% CI: 1.8 to 2.5, p<0.001). CE, cardiac events.

    Figure 4
    Figure 4

    Relationship between the levels of Vall d’Hebron Risk Score-II (VH-RS-II), number of risk variables and CE/year. (A) During the follow-up (mean 3.8±2.3 years) of (i) patients without previous MI and/or CR (n=2960), the annual CE (n=80, 2.7%) was 0.72 %/year. In (ii) patients with previous MI and/or CR (n=2255), the annual CE (n=132, 5.9) was 1.4 %/year. (B) Validation group (n=679). During the follow-up (mean 5.4±0.4 years) of (i) patients without previous MI and/or CR (n=372), the annual CE (n=6, 1.6%) was 0.03 %/year. During the follow-up (mean 2.6±1 years) of (ii) patients with previous MI and/or CR (n=307), the annual CE (n=7, 2.3%) was 1 %/year. CE, cardiac events; CR, coronary revascularisation; MI, myocardial infarction; SSS, summed stress score.

    Predictors of CEs in patients with previous myocardial infarction and/or coronary revascularisation

    In a first multivariate, model clinical variables (age, gender, diabetes mellitus, hyperlipidaemia, smoker, hypertension, nitrates and beta-blockers) were included. Age (Wald: 46 417; HR: 1.07 (95% CI 1.05 to 1.1), p<0.001), male (Wald: 4549; HR: 1.9 (95% CI 1.05 to 3.5), p=0.033), diabetes (Wald: 5216; HR: 1.5 (95% CI 1.1 to 2.1), p=0.022), smoker (Wald: 5699; HR: 1.6 (95% CI 1.1 to 2.4), p=0.017) and nitrates (Wald: 5620; HR: 1.5 (95% CI 1.1 to 2.2), p=0.018) were the independent predictors of CE. In a second multivariate model, stress variables (METs, exercise angina and ST segment depression) were considered. METs (Wald: 23 500; HR: 0.7 (95% CI 0.67 to 0.8), p<0.001) and ‘mm’ of ST segment depression (Wald: 13 351; HR: 1.4 (95% CI 1.2 to 1.7), p<0.001) were the independent predictors of CE. When gated SPECT variables were considered (left ventricular volumes, EF, SRS, SSS and SDS) the EF (Wald: 70,618; HR: 0.95 (95% CI 0.94 to 0.96), p<0.001), and SDS (Wald: 3844; HR: 1.08 (95% CI 1 to 1.2), p=0.05) were the independent predictors of CE. In the final model, and for clinical consensus, the significant variables in previous models were included age, male, diabetes, smoker, nitrates, METs, ‘mm’ of ST segment depression, EF and SDS. Age (Wald: 28 825; HR: 1.06 (95% CI 1.03 to 1.08), p<0.001); male (Wald: 3935; HR: 1.9 (95% CI 1.01 to 3.4), p=0.047); smoker (Wald: 3947; HR: 1.5 (95% CI 1.1 to 2.2), p=0.047); METs (Wald: 22 687; HR: 0.8 (95% CI 0.72 to 0.87), p<0.001); ‘mm’ of ST segment depression (Wald: 9825; HR: 1.4 (95% CI 1.1 to 1.7), p=0.002); EF (Wald: 56 578; HR: 0.96 (95% CI 0.95 to 0.97); p<0.001) and SDS (Wald: 0.322; HR: 1.03 (95% CI 0.9 to 1.2), p=0.06) were the independent predictors of CE. The final model with the HR of the optimal cut-off value for the significant qualitative variables related to the CE is shown in table 2A, and the final model with ẞ coefficients for calculated the probability of CE by means of logistic regression analysis is shown in table 2B. ROC curve analysis was performed to evaluate the ability of this model to predict CE (C-statistic: 0.81 (95% CI 0.75 to 0.82)) (figure 2B). When increasing the number of independent predictors, the prevalence of CE increases too (figure 3B). All patients were stratified in four risk levels: VLR (n=299), LR (n=1145), MR (n=616) and HR (n=195). The correlation between the levels of VH-RS and number of risk variables, annual CE and relative risk is shown in figure 4A.

    Validation group

    To validate the VH-RS-II in patients with and without previous MI and/or CR, the following formula was used: probabilityrisk at 4 years= 1 / 1 + exp – (prognostic index).

    For patients without previous MI and/or CR, the prognostic index was −8.470211 + (age at clinical evaluation x 0.060261) + (diabetes x 1.029161) – (METs x 0.032996) + (ST depression x 0.436628) – (EF x 0.016993) + (SSS x 0.197207).

    For patients with previous MI and/or CR, the prognostic index was −3.700713 + (age at clinical evaluation x 0.047983) + (male x 0.699643) + (smoker x 0.435163) – (METs x 0.175602) + (mm ST depression x 0.357188) – (EF x 0.046193) + (SDS x 0.046383).

    RS-VH-II was validated with 679 patients; 372 patients (age 67.2±13, male 55.1%, follow-up 5.5±1.1 years) had no previous MI and/or CR and 307 patients (age 63.5±11, male 85.3%, follow-up 3±0.5 years) had previous MI. All patients without previous MI and/or CR, and without risk variables had VLR (figure 4B). Only 14.3% of patients with previous MI and/or CR before gated SPECT had VLR (figure 4B).

    Discussion

    This new VH-RS-II has a good accuracy for risk stratification according to MI and/or CD. This VH-RS-II has the same study methodology as the VH-RS published previously (7). The score is based on a large cohort of participants (n=5215, follow-up mean 4.3 years) from a tertiary hospital, with suspected coronary disease who were referred for exercise testing with a mean follow-up of 4 years, and without CR during the follow-up. For patients without previous MI and/or CR, this score included six variables (age, diabetes, METs ≤6.08, ↓ST ≥1 mm, LVEF ≤57 and SSS >6), and for patients with previous MI and/or CR, the score included seven variables (age, males, smoker, METs ≤5.6, ↓ST ≥1 mm, LVEF ≤48 and SDS >2) to quantify an adult’s risk of CE.

    Our scores (VH-RS and VH-RS-II) include, in addition to clinical and exercise test variables, the gated SPECT variables, because they had incremental prognostic value over clinical and exercise test variables in predicting CE both in patients without or with previous MI and/or CR. Furthermore, the higher sensitivity and specificity of stress myocardial perfusion over that of the exercise test may reduce the unnecessary invasive coronary angiography.16 19 20 For patients without previous MI and/or CR, the gated SPECT variables were LVEF and SSS. As for patients with previous MI and/or CR, the gated SPECT variables were LVEF and SDS. The patients with previous MI and/or CR had more perfusion alterations than patients without MI and/or CR. Therefore, the SDS was the predictor variable in contrast with patients without previous MI and/or CR. This finding is in agreement with previous VH-RS study, which include patients with CR during the follow-up postgated SPECT.

    In this new analysis of VH-RS-II, there are some differences from VH-RS: the VH-RS study includes patients with CR during the follow-up post-gSPECT, and the CE was non-fatal MI+CD+CR. The new VH-RS-II study did not include patients with CR during the follow-up post-gSPECT, and the CE was: non-fatal MI and CD.

    Moreover, in VH-RS, the predictor variables for patients with suspected CAD were 9: age >67 years, male, hyperlipidaemia, nitrates, LVEF≤57%, SSS>6, METs≤6.2, exercise angina, and ST segment depression. While in the VH-RS-II the predictor variables for patients without previous MI and/or CR were less (six variables): age>66, diabetes, METs≤6.08, ST segment depression, LVEF≤57%, SSS>6. The gender, hyperlipidaemia and nitrates variables in VH-RS were replaced by diabetes in VH-RS-II.

    On the other hand, in VH-RS, the predictor variables for patients with established CAD were eight: age >67 years, smoker, nitrates, LVEF ≤53%, SDS ≥2, METs ≤6.4, exercise angina and ST segment depression, whereas, in VH-RS-II, the predictor variables for patients with previous MI and/or CR were seven: age >67 years, male, smoker, METs ≤5.6, ST segment depression, LVEF ≤48, S DS≥2. The nitrates and exercise angina variables are not significant in the multivariate analysis and gender appears as a predictor variable.

    Despite these differences, both scores are powerful for stratifying cardiac risk (VH-RS: AUC 0.8, VH-RS-II: AUC 0.8). When we stratify the risk, differences between these different end points (VH-RS, VH-RS-II) are important since the strong events are the non-fatal MI and CD. The CR is a therapeutic procedure that may have impacted the outcomes of cardiovascular death or non-fatal MI.

    Recently in a new series of 673 patients with previous MI and/or CR with LVEF ≤40% (ischaemic cardiomyopathy) who underwent gated SPECT, VH-RS for risk stratification was used.21 These patients were stratified into five-risk levels: VLR, LR, MR, HR and very HR (> 6%/year) for MACEs (MI, CD, CR and heart failure hospitalisation). In addition, the cardiac resynchronisation therapy and the implantable cardioverter defibrillator were investigated. There were no patients with ischaemic cardiomyopathy in VLR and LR. Most patients with MACEs were in very HR level, and the haemoglobin and estimated glomerular filtration rate values do not properly improve the risk stratification obtained by the VH-RS. VH-RS was effective in evaluating risk of patients with stable ischaemic cardiomyopathy (AUC: 0.82, p<0.001).21

    In VH-RS-II, the risk of each patient was analysed and then grouped into four risk levels: VLR (≤0.4%/year); LR (0.5 to <1%/year); MR (≥1 to <3%/year) and HR (≥3%/year) with a mean 4-year follow-up. The majority of patients without previous MI and/or CR had VLR (63.8%). Patients, with or without previous MI and/or CR, without predictor variables, corresponded to VLR level; and the majority of patients with MR to HR risk level had two or more prognostic variables (figure 4). In patients with previous MI and/or CR, the prevalence of patients with VLR was low (13.3%); and the percentage of patients with MR to HR levels was higher (35.9%) than in group of patients without previous MI and/or CR (15.5%) (figure 4). This is because these patients had already had these events before gated SPECT.

    As we can see, in the coronary risk stratification of patients with or without previous coronary artery disease, it is necessary to include different clinical variables associated with a non-invasive imaging test. This study shows the risk stratification from a nuclear cardiology Unit, although the same variables could be obtained by other imaging modalities.

    It is indeed true that coronary CT with analysis of atheromatous plaque has a very important prognostic and diagnostic value, especially in non-revascularised patients. However, having plate/atherosclerotic burden information does not mean that it is better than information on myocardial ischemia. Both complement each other. On the other hand, in our study, we do not have coronary CT in all patients, hence, opting out of analysing it. Furthermore, It should be noted that the VH-RS includes in the model different clinical variables that as a whole have a good prognostic capacity (C-statistic: 0.8), and this could improve or complement the information of the coronary CT.

    In the future, we will study whether the effect of left ventricular synchrony, remodelling, coronary CT and the study of myocardial flow influence the risk stratification obtained by the VH-RS and VH-RS-II.

    Limitations

    First, this analysis was conducted in a single tertiary teaching hospital. Therefore, indiscriminate extrapolation of the findings should be used with caution; although this study presents a high number of enrolled patients who have been followed up for a long period of time. On the other hand, in the group of patients for external validation, the number of CEs is low. Despite this, all CEs were correctly detected and classified.

    Conclusions

    The VH-RS-II obtained from different clinical exercise and gated SPECT variables allow the risk stratification for MI and CD in patients with or without previous MI and/or CR in due form.

    Abstract translation

    This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

    Data availability statement

    All data relevant to the study are included in the article or uploaded as supplementary information.

    Ethics statements

    Patient consent for publication

    Ethics approval

    This study involves human participants and was approved by Ethics Committee of our institution (number form trial register, PR(AG)168.2012). Participants gave informed consent to participate in the study before taking part.

    Acknowledgments

    The authors are grateful to Rosemay Chehab (London) for her grammatical English correction.

    References

    1. ↵
      Relationship of blood pressure, serum cholesterol, smoking habit, relative weight and ECG abnormalities to incidence of major coronary events: final report of the pooling project. J Chronic Dis 1978;31:201–306. doi:10.1016/0021-9681(78)90073-5
      OpenUrlCrossRefPubMedWeb of Science
    2. ↵
      1. Shaper AG,
      2. Pocock SJ,
      3. Phillips AN, et al
      . Identifying men at high risk of heart attacks: strategy for use in general practice. Br Med J (Clin Res Ed) 1986;293:474–9. doi:10.1136/bmj.293.6545.474
      OpenUrlAbstract/FREE Full Text
    3. ↵
      1. Anderson KM,
      2. Odell PM,
      3. Wilson PW, et al
      . Cardiovascular disease risk profiles. Am Heart J 1991;121:293–8. doi:10.1016/0002-8703(91)90861-b
      OpenUrlCrossRefPubMedWeb of Science
    4. ↵
      1. Tunstall-Pedoe H
      . The Dundee coronary risk-disk for management of change in risk factors. BMJ 1991;303:744–7. doi:10.1136/bmj.303.6805.744
      OpenUrlAbstract/FREE Full Text
    5. ↵
      1. Mark DB,
      2. Shaw L,
      3. Harrell FE, et al
      . Prognostic value of a treadmill exercise score in outpatients with suspected coronary artery disease. N Engl J Med 1991;325:849–53. doi:10.1056/NEJM199109193251204
      OpenUrlCrossRefPubMedWeb of Science
    6. ↵
      1. Coppola WG,
      2. Whincup PH,
      3. Papacosta O, et al
      . Scoring system to identify men at high risk of stroke: a strategy for general practice. Br J Gen Pract 1995;45:185–9.
      OpenUrlAbstract/FREE Full Text
    7. ↵
      1. Romero-Farina G,
      2. Candell-Riera J,
      3. Aguadé-Bruix S, et al
      . A novel clinical risk prediction model for myocardial infarction, coronary revascularization, and cardiac death according to clinical, exercise, and Gated SPECT variables (VH-RS). Eur Heart J Cardiovasc Imaging 2020;21:210–21. doi:10.1093/ehjci/jez078
      OpenUrl
    8. ↵
      1. Alexander KP,
      2. Shaw LJ,
      3. Shaw LK, et al
      . Value of exercise treadmill testing in women. J Am Coll Cardiol 1998;32:1657–64. doi:10.1016/s0735-1097(98)00451-3
      OpenUrlFREE Full Text
    9. ↵
      1. D’Agostino RB,
      2. Russell MW,
      3. Huse DM, et al
      . Primary and subsequent coronary risk appraisal: new results from the Framingham study. Am Heart J 2000;139:272–81. doi:10.1067/mhj.2000.96469
      OpenUrlCrossRefPubMedWeb of Science
    10. ↵
      1. Pocock SJ,
      2. McCormack V,
      3. Gueyffier F, et al
      . A score for predicting risk of death from cardiovascular disease in adults with raised blood pressure, based on individual patient data from randomised controlled trials. BMJ 2001;323:75–81. doi:10.1136/bmj.323.7304.75
      OpenUrlAbstract/FREE Full Text
    11. ↵
      1. Cullen P,
      2. von Eckardstein A,
      3. Assmann G
      . Diagnosis and management of new cardiovascular risk factors. Eur Heart J 1998;19 Suppl O:13–9.
      OpenUrl
    12. ↵
      1. Reiner Z,
      2. Catapano AL,
      3. De Backer G, et al
      . ESC committee for practice guidelines (CPG) 2008-2010 and 2010-2012 committees. ESC/EAS guidelines for the management of dyslipidaemias: the task force for the management of dyslipidaemias of the European society of cardiology (ESC) and the European atherosclerosis society (EAS). Eur Heart J 2011;32:1769–818. doi:10.1093/eurheartj/ehr158
      OpenUrlCrossRefPubMedWeb of Science
    13. ↵
      1. Diamond GA,
      2. Forrester JS
      . Analysis of probability as an aid in the clinical diagnosis of coronary-artery disease. N Engl J Med 1979;300:1350–8. doi:10.1056/NEJM197906143002402
      OpenUrlCrossRefPubMedWeb of Science
    14. ↵
      1. Epstein SE
      . Implications of probability analysis on the strategy used for noninvasive detection of coronary artery disease. role of single or combined use of exercise electrocardiographic testing, radionuclide cineangiography and myocardial perfusion imaging. Am J Cardiol 1980;46:491–9. doi:10.1016/0002-9149(80)90020-x
      OpenUrlCrossRefPubMedWeb of Science
    15. ↵
      1. Pryor DB,
      2. Harrell FE,
      3. Lee KL, et al
      . Estimating the likelihood of significant coronary artery disease. Am J Med 1983;75:771–80. doi:10.1016/0002-9343(83)90406-0
      OpenUrlCrossRefPubMedWeb of Science
    16. ↵
      1. Matsumoto N,
      2. Hirayama A
      . Clinical value of high duke treadmill score with myocardial perfusion SPECT. J Nucl Cardiol 2016;23:1301–3. doi:10.1007/s12350-015-0187-3
      OpenUrl
    17. ↵
      1. Candell-Riera J,
      2. Ferreira-González I,
      3. Marsal JR, et al
      . Usefulness of exercise test and myocardial perfusion-gated single photon emission computed tomography to improve the prediction of major events. Circ Cardiovasc Imaging 2013;6:531–41. doi:10.1161/CIRCIMAGING.112.000158
      OpenUrlAbstract/FREE Full Text
    18. ↵
      1. Romero-Farina G,
      2. Candell-Riera J,
      3. Aguadé-Bruix S, et al
      . Warranty periods for normal myocardial perfusion stress SPECT. J Nucl Cardiol 2015;22:44–54. doi:10.1007/s12350-014-9957-6
      OpenUrl
    19. ↵
      1. Vítola JV,
      2. Wanderley MRB,
      3. Cerci RJ, et al
      . Outcome of patients with high-risk duke treadmill score and normal myocardial perfusion imaging on SPECT. J Nucl Cardiol 2016;23:1291–300. doi:10.1007/s12350-015-0156-x
      OpenUrl
    20. ↵
      1. Shaw LJ,
      2. Hachamovitch R,
      3. Peterson ED, et al
      . Using an outcomes-based approach to identify candidates for risk stratification after exercise treadmill testing. J Gen Intern Med 1999;14:1–9. doi:10.1046/j.1525-1497.1999.00273.x
      OpenUrlPubMedWeb of Science
    21. ↵
      1. Romero-Farina G,
      2. Aguadé-Bruix S,
      3. Ródenas-Alesina E, et al
      . Usefulness of the Vall D'Hebron risk score to stratify the risk of patients with ischemic cardiomyopathy. J Nucl Cardiol 2023;30:751–63. doi:10.1007/s12350-022-03074-6
      OpenUrl

    Supplementary materials

    • Supplementary Data

      This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

    Footnotes

    • Contributors GR-F designed the project, all authors interpreted the gated SPECT studies. GR-F performed the statistical analysis; and all authors revised this manuscript. GR-F is responsible for the overall content as guarantor.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests None declared.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.