Evidence reviews for the US Preventive Services Task Force (USPSTF) use an analytic framework to visually display the key questions (KQs) that the review will address to allow the USPSTF to evaluate the effectiveness and safety of a preventive service. The questions are depicted by linkages that relate to interventions and outcomes. Outcomes of interest are depicted using a rectangle; intermediate outcomes are in rounded rectangles and health outcomes have squared corners. Further details are available from the USPSTF procedure manual.8 CVD indicates cardiovascular disease; ECG, electrocardiography.
aIncludes adults regardless of their CVD risk (those with low, intermediate, or high risk are eligible) as assessed by traditional risk factors (those included in Framingham risk models): male sex, older age, cigarette smoking, hypertension, dyslipidemia (high total cholesterol level, high low-density lipoprotein cholesterol level, or low high-density lipoprotein cholesterol level), and diabetes.
bThis systematic review does not include KQs about the benefits and harms of preventive medications to reduce cardiovascular risk (ie, aspirin and lipid-lowering therapy) or the benefits and harms of lifestyle counseling, because those have been addressed by other systematic reviews for the USPSTF.
CHD indicates coronary heart disease; CVD, cardiovascular disease; ECG, electrocardiography; ICTRP, International Clinical Trials Registry Platform; KQ, key question; USPSTF, US Preventive Services Task Force; WHO, World Health Organization.
aThe sum of the number of studies per KQ exceeds the total number of studies because some studies were applicable to multiple KQs.
Size of data markers indicates relative number of events in the study compared with other studies reporting the same outcome. For the DYNAMIT (Do You Need to Assess Myocardial Ischemia in Type-2 Diabetes) trial, the primary composite outcome was defined as death from all causes, nonfatal myocardial infarction, nonfatal stroke, or heart failure requiring hospitalization or emergency service intervention. DYNAMIT did not report data for cardiovascular-related deaths. For other cardiovascular events, DYNAMIT reported no significant differences between groups for revascularization (18 vs 21, P = .61). For the DADDY-D (Does Coronary Atherosclerosis Deserve to Be Diagnosed Early in Diabetic Patients) trial, the primary composite outcome was defined as first cardiac event, specifically nonfatal myocardial infarction or cardiac death. DADDY-D reported 19 total deaths (6 cardiac and 13 noncardiac) and 7 total strokes but did not report in which group those occurred. Relative risks (RRs) and 95% CIs calculated using the numbers of events reported by the trials. The trials also reported hazard ratios (HRs) for the primary outcomes (HR, 1.00 [95% CI, 0.59-1.71] in DYNAMIT; HR, 0.85 [95% CI, 0.39-1.84] in DADDY-D). KQ indicates key question.
Black data markers indicate base model; orange data markers, base model plus electrocardiography (ECG). AUC indicates area under the curve; CHD, coronary heart disease; CVD, cardiovascular disease; FRS, Framingham Risk Score; IHD, ischemic heart disease; NR, not reported; PCE, Pooled Cohort Equations.
aStudy reported C statistic rather than AUC.
Total net reclassification improvement (NRI; black data markers) indicates the sum of the event NRI (net upward reclassification among persons who had an event; orange data markers) and the nonevent NRI (net downward reclassification among persons who did not have an event; blue data markers). For some studies, only the total NRI is provided because the data for event and nonevent NRI were not reported. Nonevent NRI is calculated as the proportion of persons without an event who were appropriately reclassified into a lower risk group minus the proportion of those without an event who were inappropriately reclassified into a higher risk group. Event NRI is calculated as the proportion of persons with an event who were appropriately reclassified into a higher risk group minus the proportion of those with an event who were inappropriately reclassified into a lower risk group. Although an overall positive value of NRI indicates net appropriate reclassification, the clinical implications can be very different if the majority of patients are those with events being shifted into higher-risk categories (event NRI), vs those without events being shifted into lower-risk categories (nonevent NRI). The addition of electrocardiographic (ECG) abnormalities to conventional risk factors improves total NRI in both cases, but one might lead to an increase in preventive medications, while the other suggests a possible reduction in the use of preventive medications. CHD indicates coronary heart disease; CVD, cardiovascular disease; FRS, Framingham Risk Score; NR, not reported; PCE, Pooled Cohort Equations.
aCategories of 10-year risk: <1%, 1% to <5%, 5% to <10%, ≥10%.
bCategories of 10-year risk: <5%, 5% to <10%, 10% to <20%, ≥20%.
cCategories of 10-year risk: <7.5%, 7.5% to <15%, ≥15%.
eTable 1. Eligibility Criteria
eTable 2. Test Performance Measures for Comparing Risk Assessment or Prediction Models
eTable 3. Quality Assessment of Randomized, Clinical Trials (KQs 1 and 3): Part 1
eTable 4. Quality Assessment of Randomized, Clinical Trials (KQs 1 and 3): Part 2
eTable 5. Quality Assessment of Randomized, Clinical Trials: Additional Questions for Studies Reporting Harms (KQ3)
eTable 6. Quality Assessment for Studies Reporting Reclassification, Calibration, and Discrimination (KQ2): Part 1
eTable 7. Quality Assessment for Studies Reporting Reclassification, Calibration, and Discrimination (KQ2): Part 2
eTable 8. Quality Assessment for Studies Reporting Reclassification, Calibration, and Discrimination (KQ2): Part 3
eTable 9. Results of Included Randomized, Clinical Trials Reporting Health Outcomes (KQ1)
eTable 10. Number and Percentage of Exercise ECGs With Abnormalities in Studies Included for KQ2
eTable 11. Results of Included Studies for KQ2 That Evaluated Exercise ECG
eFigure 1. Effect on Discrimination of Adding Exercise or Resting ECG Variables to Framingham Risk Score, Pooled Cohort Equation, Systemic Coronary Risk Evaluation, or Conventional Risk Factor Base Models
eFigure 2. Effect on Reclassification of Adding Exercise or Resting ECG Variables to Framingham Risk Score, Pooled Cohort Equation, or Conventional Risk Factor Base Models
eTable 12. Number and Percentage of Resting ECGs With Abnormalities in Studies Included for KQ2
eTable 13. Results of Included Studies for KQ2 That Evaluated Resting ECG
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Jonas DE, Reddy S, Middleton JC, et al. Screening for Cardiovascular Disease Risk With Resting or Exercise ElectrocardiographyEvidence Report and Systematic Review for the US Preventive Services Task Force. JAMA. 2018;319(22):2315–2328. doi:10.1001/jama.2018.6897
Cardiovascular disease (CVD) is the leading cause of death in the United States.
To review the evidence on screening asymptomatic adults for CVD risk using electrocardiography (ECG) to inform the US Preventive Services Task Force.
MEDLINE, Cochrane Library, and trial registries through May 2017; references; experts; literature surveillance through April 4, 2018.
English-language randomized clinical trials (RCTs); prospective cohort studies reporting reclassification, calibration, or discrimination that compared risk assessment using ECG plus traditional risk factors vs traditional risk factors alone. For harms, additional study designs were eligible. Studies of persons with symptoms or a CVD diagnosis were excluded.
Data Extraction and Synthesis
Dual review of abstracts, full-text articles, and study quality; qualitative synthesis of findings.
Main Outcomes and Measures
Mortality, cardiovascular events, reclassification, calibration, discrimination, and harms.
Sixteen studies were included (N = 77 140). Two RCTs (n = 1151) found no significant improvement for screening with exercise ECG (vs no screening) in adults aged 50 to 75 years with diabetes for the primary cardiovascular composite outcomes (hazard ratios, 1.00 [95% CI, 0.59-1.71] and 0.85 [95% CI, 0.39-1.84] for each study). No RCTs evaluated screening with resting ECG. Evidence from 5 cohort studies (n = 9582) showed that adding exercise ECG to traditional risk factors such as age, sex, current smoking, diabetes, total cholesterol level, and high-density lipoprotein cholesterol level produced small improvements in discrimination (absolute improvements in area under the curve [AUC] or C statistics, 0.02-0.03, reported by 3 studies); whether calibration or appropriate risk classification improves is uncertain. Evidence from 9 cohort studies (n = 66 407) showed that adding resting ECG to traditional risk factors produced small improvements in discrimination (absolute improvement in AUC or C statistics, 0.001-0.05) and appropriate risk classification for prediction of multiple cardiovascular outcomes, although evidence was limited by imprecision, quality, considerable heterogeneity, and inconsistent use of risk thresholds used for clinical decision making. Total net reclassification improvements ranged from 3.6% (2.7% event; 0.6% nonevent) to 30% (17% event; 19% nonevent) for studies using the Framingham Risk Score or Pooled Cohort Equations base models. Evidence on potential harms (eg, from subsequent angiography or revascularization) in asymptomatic persons was limited.
Conclusions and Relevance
RCTs of screening with exercise ECG found no improvement in health outcomes, despite focusing on higher-risk populations with diabetes. The addition of resting ECG to traditional risk factors accurately reclassified persons, but evidence for this finding had many limitations. The frequency of harms from screening is uncertain.
Cardiovascular disease (CVD) is the leading cause of death in US adults.1,2 Traditional risk factors for CVD are male sex, older age, cigarette smoking, hypertension, dyslipidemia, and diabetes. Risk prediction equations, such as the Framingham Risk Score (FRS) or Pooled Cohort Equations (PCE), that integrate and weight these traditional risk factors are used commonly in clinical practice to assess 10-year risk of CVD events and to guide treatment decisions. The US Preventive Services Task Force (USPSTF) recommends using the PCE to calculate 10-year risk for adults aged 40 to 75 years to inform clinical decisions, for example, about statin use (B recommendation for those with 10-year risk ≥10%) and aspirin use (B recommendation for adults aged 50-59 years with 10-year risk ≥10%) for primary prevention.3-5 The PCE include age, sex, race, cholesterol levels, systolic blood pressure, antihypertension treatment, presence of diabetes, and smoking status as risk factors and focus on prediction of hard outcomes such as heart attack and death from coronary heart disease (CHD), ischemic stroke, and stroke-related death.4 None of the currently recommended equations include electrocardiography (ECG) findings.
Because many patients do not have symptoms of CVD or a prior diagnosis of CVD before a serious first event (eg, myocardial infarction [MI], stroke), identifying high-risk, asymptomatic individuals may reduce future morbidity and mortality.6,7 Screening with ECG could potentially reclassify people (into higher- or lower-risk categories) in a manner that results in treatment changes that improve health outcomes. In 2012, the USPSTF recommended against screening with ECG in asymptomatic adults at low risk for CHD events (D recommendation) and concluded that evidence was insufficient to assess the balance of benefits and harms of screening for those at intermediate or high risk (I statement). To inform an updated recommendation by the USPSTF, the evidence on adding resting or exercise ECG to traditional risk factor assessment (vs using traditional risk factor assessment alone) for screening asymptomatic adults for CVD risk in populations and settings relevant to US primary care was reviewed.
Detailed methods and additional details of results and analyses are available in the full evidence report at https://www.uspreventiveservicestaskforce.org/Page/Document/UpdateSummaryFinal/cardiovascular-disease-risk-screening-with-electrocardiography. Figure 1 shows the analytic framework and key questions (KQs) that guided the review.
PubMed/MEDLINE and the Cochrane Library were searched for English-language articles published through May 2017. Search strategies are listed in the eMethods in the Supplement. ClinicalTrials.gov and the World Health Organization International Clinical Trials Registry platform were searched for unpublished studies. To supplement electronic searches, investigators reviewed reference lists of pertinent articles, studies suggested by peer and federal partner reviewers, and comments received during public commenting periods. Since May 2017, ongoing surveillance was conducted through article alerts and targeted searches of journals to identify major studies published in the interim that may affect the conclusions or understanding of the evidence and the related USPSTF recommendation. The last surveillance was conducted on April 4, 2018, and identified no additional eligible studies.
Two investigators independently reviewed titles, abstracts, and full-text articles to determine eligibility using prespecified criteria for each KQ (eTable 1 in the Supplement). Disagreements were resolved by discussion. The review included English-language studies of adults conducted in countries categorized as “very high” on the United Nations Human Development Index. Only studies rated as good or fair quality were included. Studies that focused on adults with a history of CVD or symptoms suggesting CVD were excluded.
For all KQs, randomized clinical trials (RCTs) and nonrandomized controlled intervention studies comparing groups that were screened using ECG with groups that were not screened (ie, comparing risk stratification using ECG plus traditional risk factors vs risk stratification using traditional risk factors alone) were eligible. For KQ1 (direct evidence that screening improves health outcomes), eligible outcomes included all-cause mortality, cardiovascular mortality, and cardiovascular events (MI, angina, stroke, congestive heart failure, composite cardiovascular outcomes).
For KQ2 (calibration, discrimination, and reclassification), prospective cohort studies comparing CVD risk assessment models that included ECG findings with those that did not include ECG findings were also eligible. Studies were not required to specifically use the PCE or FRS to be eligible, although such studies have greatest applicability to current practice. Studies were required to report reclassification (ability to correctly reassign persons into clinically meaningful risk categories), calibration (agreement between observed and predicted outcomes), or discrimination (ability to distinguish between persons who will and will not have an event) (eTable 2 in the Supplement). Studies that only assessed the association between ECG findings and outcomes (eg, with adjusted hazard ratios) were excluded.
For KQ3 (harms), prospective cohort studies, large retrospective cohort studies, and well-designed case-control studies (only for rare events) were also eligible. Eligible harms included mortality, arrhythmia, cardiovascular events, or injuries from exercise ECG; anxiety; labeling; and harms of subsequent interventions initiated as a result of screening. For studies reporting rates of harms from exercise ECG or subsequent interventions, large registries or multicenter studies without a control group that report rates of harms for asymptomatic persons were eligible.
For each included study, 1 investigator extracted pertinent information about the populations, tests or treatments, comparators, outcomes, settings, and designs, and a second investigator reviewed this information for completeness and accuracy. Two independent investigators assessed the quality of studies as good, fair, or poor, using predefined criteria developed by the USPSTF and adapted for this topic (eMethods in the Supplement).8 Disagreements were resolved by discussion. Individual study quality ratings are reported in the eResults and eTables 3-8 in the Supplement.
Findings for each question were summarized in tabular and narrative format. To determine whether meta-analyses were appropriate, clinical heterogeneity and methodological heterogeneity were assessed following established guidance.9 For KQ1, pooled effects were not estimated because fewer than 3 similar studies were found, but risk ratios and 95% CIs were calculated for binary outcomes reported by the included RCTs. Statistical significance was assumed when 95% CIs did not cross the null. All testing was 2-sided.
For KQ2, considerable heterogeneity was found for ECG findings assessed, base prediction models, outcomes, and duration of follow-up; therefore, the results are presented in tabular format and in figures. Results are presented separately for exercise and resting ECG. Within the studies of resting ECG, results were stratified by whether studies evaluated the addition of a constellation of ECG abnormalities vs single or specific ECG changes. Results were categorized by the base models used as “published coefficient models,” meaning the model preserved the coefficients of original published models that have been externally validated (eg, FRS or PCE), or as “model development.” For KQ2, the C statistic (Harrell C) and area under the curve (AUC) were used as the primary measures of discrimination and were summarized together. Measures of overall performance were summarized with those of calibration. Net reclassification improvement (NRI) was the primary measure of reclassification, with event and nonevent NRIs reported separately when possible. Analyses were conducted and figures were produced using Stata version 14 (StataCorp) and Microsoft Excel.
The overall strength of the body of evidence was assessed for each KQ as high, moderate, low, or insufficient using methods developed for the USPSTF (and the Evidence-based Practice Center program), based on the overall quality of studies, consistency of results between studies, precision of findings, and risk of reporting bias.8
A total of 16 studies (17 articles) with 77 140 participants were included (Figure 2).
Key Question 1a. Does the addition of screening with resting or exercise ECG improve health outcomes compared with traditional CVD risk factor assessment alone in asymptomatic adults?
Key Question 1b. Does improvement in health outcomes vary for subgroups defined by baseline CVD risk (eg, low, intermediate, or high risk), age, sex, or race/ethnicity?
No eligible trials evaluated screening with resting ECG. Two fair-quality RCTs (DYNAMIT [Do You Need to Assess Myocardial Ischemia in Type-2 Diabetes]10 and DADDY-D [Does Coronary Atherosclerosis Deserve to Be Diagnosed Early in Diabetic Patients]11) with a total of 1151 participants that evaluated screening with exercise ECG in high-risk, asymptomatic adults aged 50 to 75 years with diabetes were included (Table 1). DYNAMIT evaluated a bicycle exercise test,10 whereas DADDY-D evaluated an exercise treadmill test.11 Neither trial reached its sample size target.
Neither study found a statistically significant reduction in any category of events for screening compared with no screening, including their primary composite outcomes—all-cause mortality, cardiovascular-related mortality, MI, heart failure, or stroke—although findings were imprecise (Figure 3; eTable 9 in the Supplement). In DYNAMIT, there was no significant difference between groups for the primary composite end point—death from all causes, nonfatal MI, nonfatal stroke, or heart failure requiring hospitalization or emergency service intervention (28 vs 26 events; hazard ratio, 1.00 [95% CI, 0.59-1.71]). In DADDY-D, there was no significant difference between groups for the primary outcome—cardiac events defined as a composite of nonfatal MI or cardiac death (12 vs 14 events; hazard ratio, 0.85 [95% CI, 0.39-1.84]). Subgroup analyses from the DADDY-D trial found no statistically significant differences between groups based on sex, age, or cardiovascular risk for the primary outcome.
Key Question 2. Does the addition of screening with resting or exercise ECG to traditional CVD risk factor assessment accurately reclassify persons into different risk groups (eg, high-, intermediate-, and low-risk groups) or improve measures of calibration and discrimination?
Of the 14 included studies for KQ2, 5 fair-quality cohort studies (9582 participants) evaluated exercise ECG (Table 2).12-16 All participants were from cardiology or prevention centers in hospitals. Four of the studies reported that all participants were asymptomatic; 1 reported that 16.5% had atypical chest pain symptoms and had undergone both coronary artery calcium scoring and single-photon emission computed tomography for “clinically indicated reasons.”13 Mean baseline FRS score was 10.8 to 12.3 in studies reporting it.13-15 The frequency of abnormal exercise test findings across included studies ranged from 6.4% to 16.7% (eTable 10 in the Supplement). Mean duration of follow-up ranged from 6 to 8 years in 4 studies; 1 had 26 years of follow-up.16
Results of the included studies are shown in Figure 4 and Figure 5, and in eTable 5 and eFigures 1 and 2 in the Supplement. All 3 of the studies reporting discrimination for the addition of exercise ECG variables to traditional risk factors12,13,15 reported small absolute improvements in AUC or C statistics (0.02-0.03). None of the studies reported CIs, and only 1 reported a P value; that value indicated no statistically significant difference between models (P = .3).13 Of the 4 studies that reported calibration or overall performance of models that added exercise ECG findings to traditional risk factors,13-16 none reported figures such as calibration plots, but 1 provided a table of predicted and observed events for quintiles of risk.16 All 4 studies reported different measures, and results were inconsistent (eResults and eTable 11 in the Supplement).
The 1 study that reported on reclassification from adding exercise ECG to traditional CVD risk factor assessment (Chang et al, 201513; 988 participants) used categories defined by 10-year risk of cardiac events of less than 6%, 6% to 20%, and more than 20%.13 Although adding exercise testing variables to the base model (FRS variables) did not significantly improve discrimination (change in AUC, 0.02; P = .3), the study found that adding the presence or absence of stress-induced ischemia detected during symptom-limited exercise treadmill testing to the base model improved risk classification in participants both overall (total NRI, 9.6%; P = .007) and in the intermediate-risk group (18.9%; P = .01). It did not report event NRI and nonevent NRI.
Of the included studies for KQ2, 9 (68 475 participants) evaluated resting ECG (Table 3).17-25 Five evaluated multiple ECG changes, including either a constellation of major and minor ECG changes or an ECG risk equation (that included multiple ECG changes).17,18,20,23,24 Four evaluated only single ECG changes.19,21,22,25 Duration of follow-up ranged from 620 to 19 years.24 Overall, the studies reported little or no information about participants’ baseline symptoms.
Of the 5 studies that evaluated the addition of multiple ECG abnormalities to traditional risk factors,17,18,20,23,24 4 used FRS or PCE base models (with published coefficients) for some analyses.17,18,20,24 The frequency of ECG abnormalities across these studies ranged from 31% to 55% (eTable 12 in the Supplement). The studies reported absolute improvements in AUC or C statistics of 0.001 to 0.05 (Figure 4; eFigure 1 in the Supplement). Of the 3 studies that reported calibration or overall performance for the addition of multiple ECG abnormalities,17,18,20 none reported figures such as calibration plots. The studies reported a variety of measures indicating improved calibration among the 2 studies using published coefficients of FRS18,20 but poor calibration in 1 model development of older adults aged 70 to 79 years17 (eResults and eTable 13 in the Supplement).
Four of the 5 studies evaluating multiple ECG changes reported NRI, and all but 123 provided event NRI or nonevent NRI data (or the data to calculate them) for some models (Figure 5; eResults, eTable 13, and eFigure 2 in the Supplement).17,18,23,24 One study used the base model for risk prediction (ie, PCE) and some risk thresholds corresponding to current USPSTF recommendations for preventive medications.24 Overall, total net reclassification improvements ranged from 3.6% (2.7% event; 0.6% nonevent) to 30% (17% event; 19% nonevent) for studies using FRS or PCE base models (95% CIs were rarely reported) (Figure 5). Evidence was limited by imprecision (or unknown precision), quality, and considerable heterogeneity. Consistency of findings for specific risk thresholds is unknown because all studies used different risk categories. Results of studies that evaluated single ECG changes are provided in the eResults in the Supplement.
Key Question 3a. What are the harms of screening with resting or exercise ECG, including harms of subsequent procedures or interventions initiated as a result of screening?
Key Question 3b. Do the harms of screening vary for subgroups defined by baseline CVD risk (eg, low, intermediate, or high risk), age, sex, or race/ethnicity?
One RCT described in KQ1, the DADDY-D trial, was included for this KQ. It reported on harms from subsequent interventions initiated as a result of screening.11 Twenty of 262 participants (7.6%) in the screened group had positive exercise treadmill test findings. Of those 20 participants, 17 underwent coronary angiography (6.5% of the 262 in the screened group). Angiography revealed critical stenosis (not defined) in 12 of those 17 (71%), and all patients with critical stenosis underwent revascularization procedures (7 percutaneous and 5 surgical). One patient undergoing percutaneous revascularization had a nonfatal acute MI 3 days after the procedure and underwent a second percutaneous angioplasty. His ejection fraction was reported to be normal 6 months later.
The other trial described in KQ1 (DYNAMIT) reported the number of some subsequent tests but did not report whether any of the tests or interventions resulted in harms.10
Table 4 provides the summary of findings. The overall strength of evidence was low or insufficient for each of the questions evaluated. No RCTs of screening with resting ECG were found. RCTs of exercise ECG in asymptomatic participants found no improvement in health outcomes despite focusing on higher-risk populations with diabetes, although those trials were limited by not reaching sample size targets. Evidence on whether the addition of exercise ECG to traditional CVD risk factors results in accurate reclassification is lacking. For resting ECG, the addition of multiple abnormalities to traditional CVD risk factors accurately reclassified persons and improved discrimination and calibration, but evidence was limited by imprecision, quality, considerable heterogeneity, and inconsistent use of risk thresholds that align with recommendations and current clinical practice.
Two RCTs evaluated screening with exercise ECG. The participants were higher-risk groups that would be, in theory, more likely to benefit from screening to identify silent ischemia. However, screening with exercise ECG, followed by referral to cardiology (DYNAMIT) or recommendation for coronary angiography (DADDY-D) for those with abnormal exercise ECG findings, did not improve health outcomes. Some key limitations of the trials include not reaching sample size targets and only following up participants for about 3.5 years. Findings from the 2 studies were consistent, but the overall strength of evidence for whether screening with exercise ECG improves health outcomes was low (for no benefit) because of imprecision and risk of bias.
Limited direct evidence was found on harms of screening asymptomatic adults. Potential harms of screening with exercise or resting ECG include mortality, arrhythmia, cardiovascular events, injuries, anxiety, labeling, and harms of subsequent procedures or interventions. Both DYNAMIT and DADDY-D reported on subsequent interventions after abnormal exercise test findings, but only DADDY-D reported whether any of those resulted in harms (1/12 had an MI). No other eligible studies reported harms for asymptomatic adults. Studies without control groups were eligible if they were multicenter studies or registries that reported rates of harms from exercise ECG or subsequent procedures or interventions specifically for asymptomatic persons. This approach excluded a single-site study of 377 asymptomatic military officers (mean age, 37 years) that reported no complications during exercise testing.26
Many other studies have reported rates of angiography (but no information on harms) for asymptomatic persons after exercise ECG, ranging from 0.6% to 13%, and usually less than 3%.12,14,26-34 Rates of subsequent revascularization have also been reported by some, with those studies estimating lower rates than those reported by DADDY-D and DYNAMIT (eg, 0.1%-0.5% in 2 studies with 1051-3554 participants).12,14 Little is known about the harms of revascularization procedures for adults without symptoms or a prior diagnosis of CVD (eContextual Questions in the Supplement). Regardless of symptom status, some tests that follow an abnormal ECG finding expose patients to radiation, including coronary angiography, computed tomography angiography, and myocardial perfusion imaging.35 Coronary angiography can expose patients to as much radiation as 600 to 800 chest radiographs.36
Studies that focused on symptomatic adults have reported rates of harms of exercise ECG and harms of subsequent interventions. Recommendations for exercise laboratories estimate a complication rate of 1 in 10 000,37 referencing a review that reported rates of sudden cardiac death from 0 to 5 per 100 000 tests.37,38 The recommendations also provided estimates from survey data for hospitalization including serious arrhythmias (≤0.2%), MI (0.04%), or sudden cardiac death (0.01%).37,39
No consensus exists for the thresholds that should be considered clinically significant changes in discrimination, calibration, or reclassification. Appropriate reclassification has the most direct clinical meaning, but studies must use meaningful risk categories (ie, that correspond to clinical decisions, such as 7.5% or 10% 10-year risk) to provide NRI results applicable to current clinical practice.
For exercise ECG, although evidence from cohort studies shows that the addition of exercise ECG to traditional CVD risk factors results in small absolute improvements in discrimination, it is uncertain whether calibration or appropriate risk classification improves. Evidence was limited by imprecision and risk of bias for all outcomes and by inconsistency or unknown consistency for calibration and reclassification outcomes. Also, there was an absence of evidence related to exercise ECG for healthy, low-risk persons (eg, mean baseline FRS was 10.8-12.3 in studies reporting it).
For resting ECG, evidence from cohort studies shows that the addition of ECG findings to traditional CVD risk factors results in small improvements (at best) in discrimination and in improvements for calibration and appropriate risk classification for prediction of all-cause mortality, CVD mortality, CHD events, or CVD events. However, evidence was limited by imprecision, risk of bias, and considerable heterogeneity in prediction models, risk thresholds (all studies used different risk categories), type of ECG abnormalities, and outcomes assessed. The reported discrimination of base models varied widely, ranging from inadequate to excellent (AUC or C statistics from 0.58 to 0.85), likely because of the different outcomes, patient populations, and base models used.
Figure 5 might suggest potential value in reclassification based on the addition of major and minor resting ECG changes to existing models (PCE or FRS) because studies reported increases in total appropriate reclassification (total NRI), appropriate reclassification of persons with events to higher-risk categories (event NRI), and appropriate reclassification of persons without events to lower-risk categories (nonevent NRI).
However, there are important limitations. First, no 2 studies evaluated the same model, risk category thresholds, and outcome. Second, no CIs were provided for most of those data. Third, NRI is highly dependent on risk category thresholds, which varied widely across studies. Fourth, evaluating risk reclassification using 4 categories to determine NRI may inflate the NRI because each reclassification increases NRI, regardless of whether the change would correspond to different treatment decisions. Fifth, a single study24 accounts for 6 of the 9 rows in Figure 5. It reported NRI for 3 different base models for prediction of several mortality outcomes but did not evaluate prediction of CHD or CVD events because it used data that do not have that capability. The study did not report the full reclassification table to show how much of the NRI was accounted for by reclassification that should change clinical decisions (eg, from 5%-9.9% to ≥10%) vs how much was accounted for by reclassification that would have no effect on clinical decisions and outcomes (eg, from 1%-4.9% to <1% for persons without events).24It was also the only study that evaluated adding an ECG risk equation to base models. Sixth, another study17 in Figure 5 had only 7.5 years of follow-up and focused on elderly participants aged 70 to 79 years. It is uncertain whether risk reclassification could provide clinically useful information for this population, given recent evidence on lack of benefit of statins for primary prevention in persons of similar age40 and the USPSTF I statement on initiation of aspirin for primary prevention for older adults.
Additionally, for the studies of resting ECG, it is unclear what proportion of participants was truly asymptomatic. The proportion with symptoms may be relatively low, given that the studies were population based and most of them excluded persons with a history of CVD, but it is uncertain whether enrolling even a small percentage of symptomatic participants could artificially inflate estimates of appropriate reclassification.
To better understand whether risk classification is improved in a way that is likely to improve health outcomes, risk prediction studies that evaluate the addition of ECG abnormalities to the PCE (as the base model) would be most informative. Use of the PCE is recommended by the USPSTF and American College of Cardiology/American Heart Association to inform decisions about preventive medications. Only 1 included study used the PCE as the base model. Studies of a constellation of resting ECG changes show greater potential than those of single ECG changes and could be the focus of future research. Future studies should use clinically meaningful risk categories that correspond to recommendations about preventive medications to determine how many persons are appropriately reclassified in a manner that would lead to use of additional or fewer preventive medications. When considering the USPSTF recommendations for statins and aspirin, evaluating NRI related to the 10% 10-year risk threshold is of great interest. Future studies should evaluate asymptomatic populations and should exclude those with a history of CVD. Measures of discrimination, calibration, and reclassification (including total, event, and nonevent NRI) and their corresponding CIs should be reported. Future studies detailing harms of screening are also needed.
RCTs of screening with exercise ECG found no improvement in health outcomes, despite focusing on higher-risk populations with diabetes. The addition of resting ECG to traditional risk factors accurately reclassified persons, but evidence for this finding had many limitations. The frequency of harms from screening is uncertain.
Corresponding Author: Daniel E. Jonas, MD, MPH, University of North Carolina at Chapel Hill, 5034 Old Clinic Bldg, Chapel Hill, NC 27599 (firstname.lastname@example.org).
Accepted for Publication: May 3, 2018.
Author Contributions: Dr Jonas had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Jonas, Asher.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: All authors.
Critical revision of the manuscript for important intellectual content: Jonas, Reddy, Asher.
Statistical analysis: Jonas.
Obtained funding: Jonas.
Administrative, technical, or material support: Jonas, Reddy, Middleton, Barclay, Green, Baker.
Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.
Funding/Support: This research was funded under contract HHSA-290-2015-00011-I, Task Order 5, from the Agency for Healthcare Research and Quality (AHRQ), US Department of Health and Human Services, under a contract to support the USPSTF.
Role of the Funder/Sponsor: Investigators worked with USPSTF members and AHRQ staff to develop the scope, analytic framework, and key questions for this review. AHRQ had no role in study selection, quality assessment, or synthesis. AHRQ staff provided project oversight, reviewed the report to ensure that the analysis met methodological standards, and distributed the draft for peer review. Otherwise, AHRQ had no role in the conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript findings. The opinions expressed in this document are those of the authors and do not reflect the official position of AHRQ or the US Department of Health and Human Services.
Additional Contributions: We gratefully acknowledge the following individuals for their contributions to this project, including AHRQ staff (Howard Tracer, MD; Elisabeth Kato, MD, MRP; and Tracy Wolff, MD, MPH) and RTI International–University of North Carolina Evidence-based Practice Center staff (Carol Woodell, BSPH; Christiane Voisin, MSLS; Sharon Barrell, MA; and Loraine Monroe). USPSTF members, expert consultants, peer reviewers, and federal partner reviewers did not receive financial compensation for their contributions. Mss Woodell, Voisin, Barrell, and Monroe received compensation for their role in this project.
Additional Information: A draft version of the full evidence report underwent external peer review from 4 content experts (Joy Melnikow, MD, MPH, University of California, Davis; Amit Shah, MD, MSCR, Emory University; Fabrizio Turrini, MD, Nuovo Ospedale Civile Sant’Agostino Estense, AUSL Modena, Modena, Italy; Timothy Wilt, MD, University of Minnesota) and 1 federal partner reviewer from the National Institutes of Health. Comments from reviewers were presented to the USPSTF during its deliberation of the evidence and were considered in preparing the final evidence review.
Editorial Disclaimer: This evidence report is presented as a document in support of the accompanying USPSTF Recommendation Statement. It did not undergo additional peer review after submission to JAMA.