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Cost-Effectiveness of Preparticipation Screening for Prevention of Sudden Cardiac Death in Young Athletes

Matthew T. Wheeler, MD, PhD; Paul A. Heidenreich, MD, MS; Victor F. Froelicher, MD; Mark A. Hlatky, MD; and Euan A. Ashley, MB ChB, DPhil
[+] Article and Author Information

From Stanford University, Stanford, California, and Veterans Affairs Palo Alto Health Care System, Palo Alto, California.


Grant Support: From the Breetwor Foundation and the Stanford Cardiovascular Institute. Dr. Wheeler was supported by a U.S. Public Health Service training grant (5HL 07034) from the National Heart, Lung, and Blood Institute, National Institutes of Health.

Potential Conflicts of Interest: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M08-2738.

Reproducible Research Statement:Study protocol, statistical code, and data set: Available from Dr. Ashley (e-mail, euan@stanford.edu).

Requests for Single Reprints: Euan A. Ashley, MB ChB, DPhil, Division of Cardiovascular Medicine, Stanford University, 300 Pasteur Drive, Falk Cardiovascular Research Building, Stanford, CA 94305; e-mail, euan@stanford.edu.

Current Author Addresses: Drs. Wheeler and Ashley: Division of Cardiovascular Medicine, Stanford University School of Medicine, 300 Pasteur Drive, Falk Cardiovascular Research Building, Stanford, CA 94305-5406.

Dr. Hlatky: Department of Health Research and Policy, Stanford University School of Medicine, Redwood Building, T150A, Stanford, CA 94305-5405.

Drs. Froelicher and Heidenreich: Veterans Affairs Palo Alto Healthcare System, 3801 Miranda Avenue, Palo Alto, CA 94304.

Author Contributions: Conception and design: M.T. Wheeler, P.A. Heidenreich, V.F. Froelicher, M.A. Hlatky, E.A. Ashley.

Analysis and interpretation of the data: M.T. Wheeler, P.A. Heidenreich, V.F. Froelicher, M.A. Hlatky, E.A. Ashley.

Drafting of the article: M.T. Wheeler, M.A. Hlatky.

Critical revision of the article for important intellectual content: M.T. Wheeler, P.A. Heidenreich, V.F. Froelicher, M.A. Hlatky, E.A. Ashley.

Final approval of the article: P.A. Heidenreich, V.F. Froelicher, M.A. Hlatky, E.A. Ashley.

Statistical expertise: M.T. Wheeler.

Collection and assembly of data: M.T. Wheeler.


Ann Intern Med. 2010;152(5):276-286. doi:10.7326/0003-4819-152-5-201003020-00005
Text Size: A A A

Background: Inclusion of 12-lead electrocardiography (ECG) in preparticipation screening of young athletes is controversial because of concerns about cost-effectiveness.

Objective: To evaluate the cost-effectiveness of ECG plus cardiovascular-focused history and physical examination compared with cardiovascular-focused history and physical examination alone for preparticipation screening.

Design: Decision-analysis, cost-effectiveness model.

Data Sources: Published epidemiologic and preparticipation screening data, vital statistics, and other publicly available data.

Target Population: Competitive athletes in high school and college aged 14 to 22 years.

Time Horizon: Lifetime.

Perspective: Societal.

Intervention: Nonparticipation in competitive athletic activity and disease-specific treatment for identified athletes with heart disease.

Outcome Measure: Incremental health care cost per life-year gained.

Results of Base-Case Analysis: Addition of ECG to preparticipation screening saves 2.06 life-years per 1000 athletes at an incremental total cost of $89 per athlete and yields a cost-effectiveness ratio of $42 900 per life-year saved (95% CI, $21 200 to $71 300 per life-year saved) compared with cardiovascular-focused history and physical examination alone. Compared with no screening, ECG plus cardiovascular-focused history and physical examination saves 2.6 life-years per 1000 athletes screened and costs $199 per athlete, yielding a cost-effectiveness ratio of $76 100 per life-year saved ($62 400 to $130 000).

Results of Sensitivity Analysis: Results are sensitive to the relative risk reduction associated with nonparticipation and the cost of initial screening.

Limitations: Effectiveness data are derived from 1 major European study. Patterns of causes of sudden death may vary among countries.

Conclusion: Screening young athletes with 12-lead ECG plus cardiovascular-focused history and physical examination may be cost-effective.

Primary Funding Source: Stanford Cardiovascular Institute and the Breetwor Foundation.

Figures

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Figure 1.
Decision analysis model.

CV = cardiovascular; ECG = 12-lead electrocardiography; H & P = history and physical examination; M = Markov node.

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Appendix Figure 1.
Characteristics of the unscreened student-athlete population.

Student-athletes who harbor cardiac abnormalities have a potential increased risk for sudden cardiac death. The shaded bars represent the athletes expected to have underlying cardiac abnormalities participating in at-risk athletic activities. An estimate of the total number of student-athletes in at-risk activities is 3.7 million. Mitral valve prolapse and left ventricular hypertrophy do not carry similar risk for early death compared with other findings in the population.

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Appendix Figure 2.
Expected prevalence and risk for sudden cardiac death per year in young athletes.

ARVC = arrhythmogenic right ventricular cardiomyopathy; CAD = coronary artery disease. Top. Expected frequencies of student-athletes who harbor underlying cardiac abnormalities were calculated from figures for total student-athlete participants and prevalence of cardiac abnormalities in samples of adolescent and young adult populations (see Appendix Table 1 for references). The number of athletes at risk was then divided by the number of athletes found to have sudden cardiac death in registry data (13) to generate an estimated yearly risk for sudden cardiac death by underlying diagnosis. Bottom. Many athletes who harbor potential causes of sudden cardiac death have comparatively low risk versus others. Sudden deaths in the left ventricular hypertrophy group are assumed to be due to subclinical forms of hypertrophic cardiomyopathy; those from mitral valve prolapse may be due to mechanical or arrhythmic causes.

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Figure 2.
Univariate sensitivity analyses.

The incremental cost-effectiveness ratios (ICERs) of ECG + H & P versus no screening (top) and versus H & P alone (bottom) are shown as changed by varying critical measurements through possible ranges. The base-case estimates (top [$76 100 per life-year saved] and bottom [$42 900 per life-year saved]) are shown (vertical lines). The horizontal solid boxes represent the ICER resulting from inputting the described variable over the expected range of the mean value (also used in probabilistic sensitivity analysis); the horizontal lines represent the ICER found using expected minimum and maximum inputs, which may be applicable to certain specific subgroups or particular payers. The table shows the low-value input, the low-value input used for probabilistic sensitivity analysis, the high-value input used for probabilistic sensitivity analysis, and the high-value input for each variable or combination of variables. In the bottom panel, the ICER between ECG + H & P and H & P alone is dependent not on H & P cost but on the interpretation of H & P results before ECG interpretation. “Risk ratio: athlete versus DQ” is the mortality risk reduction associated with disqualification and treatment of athletes with underlying occult heart disease versus continued participation without diagnosis. “ECG cost” is cost of ECG greater than H & P cost. All costs are all screening cost variables, including primary and secondary screening tests and initial and recurring screening-related treatment costs, input into the model concurrently. DQ = disqualified; ECG = 12-lead electrocardiography; H & P = cardiovascular-focused history and physical examination; SCD = sudden cardiac death; sens/spec = sensitivity/specificity.

* Per 100 000 life-years.

x-fold risk reduction.

‡ Base-case assumption. § ECG + H & P found to be both cost- and life-saving versus comparator.

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Figure 3.
Probabilistic sensitivity analysis.

ECG = 12-lead electrocardiography; H & P = cardiovascular-focused history and physical examination; ICER = incremental cost-effectiveness ratio. Top. Scatterplot of simulation done for each of 3 base-case comparisons, varying each input variable over the expected range of the population median. In nearly all simulations, H & P is weakly dominated by ECG +H & P because it is less costly, is less effective, and has a higher ICER. The ICERs can be measured by dividing the discounted life-years saved by the incremental discounted cost. Reference lines for ICERs of $50 000 per life-year saved and $100 000 per life-year saved are shown. Dots below each of these lines represent simulations, with ICERs shown below these willingness-to-pay thresholds. Bottom. Willingness-to-pay curves for comparisons between ECG + H & P and H & P, ECG + H & P and no screening, and H & P and no screening. Proportion of simulations plotted versus ICER for each of 3 base-case comparisons are shown. Simulations that were not life-saving are included in the proportion of simulations greater than $300 000 per life-year saved. The probability of preferring ECG + H & P over H & P alone is 68% at a willingness-to-pay threshold of $50 000 per life-year saved and 99.9% at $100 000 per life-year saved. ECG + H & P is cost-effective and life-saving in 0.2% of simulations versus H & P alone. The probability of preferring ECG + H & P over no screening is 0% at a willingness-to-pay threshold of $50 000 per life-year and 79.9% at $100 000 per life-year. The probability of preferring H & P over no screening is 0% at $100 000 per life-year.

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Appendix Figure 3.
Cost-effectiveness of screening athletes to prevent sudden cardiac death.

Data reported with each symbol are the estimated sensitivity and specificity, as well as criteria (reference). Evaluation of different screening methods and test characteristics derived from the athlete-screening literature. Test methods and reported test results were used as inputs in the model and compared with a strategy of no screening. The discounted incremental life-years gained per 1000 athletes screened are plotted against the cost per athlete screened for each method. The incremental cost-effectiveness ratio, screening method, and threshold for a positive test result are shown together with the reference from which test characteristic estimates were derived. Because of significant heterogeneity between the populations studied and methods used in the studies compared, the test characteristics derived from each study may not be entirely applicable to the screened population described for the base case. In addition, the methods of FH, H, and H & P are not uniform across the studies referenced. References from which input estimates have been derived are shown in parentheses. Details of incremental cost-effectiveness ratio versus no screening for each study and comparison with a baseline of H & P for those including history can be found in Appendix Table 4. Estimated test sensitivity and specificity for each graphed incremental cost-effectiveness ratio is shown and is derived from references in parentheses. Incremental cost-effectiveness ratios versus no screening and test sensitivity and specificity are as follows: cost-effectiveness ratio, $51 400 (sensitivity 40%, specificity 98%), $63 400 (45%, 95.2%), $64 000 (25%, 98.8%), $76 100 (68%, 95%), $78 800 (73%, 93.1%), $81 000 (55%, 89.7%), $81 600 (90%, 84.9%), $153 900 (25%, 97.5%), $174 000 (75%, 61.5%), $199 200 (15%, 97%), $232 500 (34%, 84.7%), $264 000 (85%, 35%), and $275 000 (5%, 97.1%); life costing (5%, 70.1%). ECG = 12-lead electrocardiography; FH = family history; H & P = cardiovascular-focused history and physical examination; LVH = left ventricular hypertrophy.

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Appendix Figure 4.
Univariate sensitivity analyses for ECG strategies.

The incremental cost-effectiveness ratios (ICERs) of ECG alone versus no screening (top) and versus ECG + H & P (bottom) are shown. The ECG + H & P versus ECG alone strategies were compared by varying critical measurements through possible ranges. The comparison of ECG alone versus H & P alone is not shown because the ECG alone strategy is dominant (costs less and is more effective) in all cases except when ECG specificity is low, the cost of ECG is more than $65, and the cost of H & P is less than $42. Vertical lines show the base-case estimates. Horizontal solid boxes represent the ICER resulting from inputting the described variable over the expected range of the mean value (also used in probabilistic sensitivity analysis). Horizontal lines represent the ICER found using expected minimum and maximum inputs, which may be applicable to specific subgroups or particular payers. The table shows low-value input, the low-value input used for probabilistic sensitivity analysis, the high-value input used for probabilistic sensitivity analysis, and the high-value input for each variable or combination of variables. “Risk ratio: athlete vs. DQ” represents the ratio of risk reduction associated with disqualification and treatment of athletes with underlying occult heart disease. DQ = disqualified; ECG = 12-lead electrocardiography; H & P = cardiovascular-focused history and physical examination; SCD = sudden cardiac death; sens/spec = sensitivity/specificity.

* Per 100 000 life-years.

x-fold risk reduction.

‡ Base-case assumption.

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Appendix Figure 5.
Probabilistic sensitivity analysis results evaluating screening athletes using ECG alone versus other screening methods.

ECG = 12-lead electrocardiography; H & P = cardiovascular-focused history and physical examination; ICER = incremental cost-effectiveness ratio. Top. Scatter plot of life-saving versus incremental increase in cost for each of 10 000 Monte Carlo simulations randomly varying each variable over estimated ranges (see Table 1 and Appendix Table 1 for inputs). ECG alone has sensitivity of 40% and specificity of 98%, based on data from Nora and colleagues (51) together with estimate of prevalence of screened athletes potentially at risk (Appendix Table 1). Lines representing the willingness-to-pay threshold ICERs of $50 000 per life-year and $100 000 per life-year are shown for comparison. Simulations with negative incremental cost are cost-saving versus the comparator. Average values and CIs for incremental cost-effectiveness ratios based on probabilistic simulations are shown in Appendix Table 3. Bottom. Cost-effectiveness acceptability curve, showing the proportion of simulations less than the ICER at given values in discounted dollars per discounted life-years saved. The probability of preferring ECG alone to no screening is 12.6% at a willingness-to-pay threshold of $50 000 per life-year and 97% at $100 000 per life-year. ECG alone is cost-effective and life-saving in more than 93.6% of simulations vs. H & P alone and less than $50 000 per life-year saved in more than 99.9% of simulations.

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Appendix Figure 6.
Effect of repeated testing on screening cost-effectiveness.

Because the primary analysis assumes a single episode of screening, yet current recommendation statements advise yearly or biannual screening, the effects of repeated screening for each methodology in terms of change in cost-effectiveness were modeled. Yearly screening costs (screening test plus secondary testing costs) are assumed to recur with each additional year of screening, as an upper bound of cost of screening (see Appendix Table 5 for more information). More conservative estimates about the cost of repeated screening in reduction of repeated secondary testing costs may lead to costs intermediate between those shown and the base-case estimate. Efficacy was assumed to be independent of the number of tests, although the veracity of this assumption is not well known. Cardiovascular-focused ECG = 12-lead electrocardiography; H & P = history and physical examination.

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Appendix Figure 7.
Sensitivity analysis of cost-effectiveness of screening as a function of total students and student-athletes potentially at risk for sudden cardiac death.

Assuming a constant number of athletic sudden cardiac deaths. ECG = 12-lead electrocardiography; H & P = cardiovascular-focused history and physical examination. Top. Sensitivity analysis examining total number of athletes at risk versus cost-effectiveness ratio for ECG + H & P or H & P, compared with no screening. The total number of sudden cardiac deaths in athletes was assumed to be independent of the number screened for this analysis; however, nonathletic death and background nonsudden cardiac death remained constant on a per-individual basis for each risk group. A total of 26 million students is the middle school– and high school–aged population in the United States (90). Ten million students is the estimated total school-aged population participating in any sports. A total of 3.7 million students (base case) is the estimated high school– and college-aged population participating in high-intensity, interscholastic and intercollegiate sports. Bottom. The sensitivity analysis examining the total number of athletes at risk versus the incremental cost-effectiveness ratio assuming underlying at-risk heart disease prevalence of 0.1%, with proportionally higher yearly incidence of death in the high-risk subgroup, modeled after the risk estimates in reference (13).

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Comments

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missing bicusped aortic valve
Posted on April 2, 2010
Mayada H. Issa
West Virginia University
Conflict of Interest: None Declared

The extent of pre-participation athletics evaluation remains controversial. We need to remember that these athletes feel pressured to achieve and maintain excellence and many would use performance enhancing agents for that purpose. Many of these agents have well documented cardiovascular toxicity such as direct myocardial cell injury, hypercoagulability, atherogenic lipoprotein abnormalities and endothelial dysfunction. (1) The use of these agents by an individual with an existing structural cardiac abnormality will have the highest deleterious impact on health. Bicuspid aortic valve is one of the most common congenital cardiac disease in the general population. If the valve is functioning normally it does not pose a risk for participation in competitive sports. However, establishing diagnosis is crucial for regular follow up. Physical examination and EKG may miss the diagnosis initially, however when complications such as aortic valve stenosis or insufficiency occur findings will be more prominent. Individuals with bicuspid aortic valve can also have significant progressive increase in the aortic diameter and left ventricular measurements over time(2) This pathological adaptation is different from what is called athletes heart which is a physiologic adaptation to regular training characterized by increased left ventricular chamber size and proportional increase in the wall mass in endurance trained athletes where as it mainly involves increase in the wall mass with gradual increase in the aortic root size with resultant aortic valve regurgitation in strength and power trained athletes. (3) The combination of both types of adaptations puts these individuals at a higher risk for aortic dissection. Athletes with such a diagnosis will require yearly follow up with echocardiographic evaluation. We took care of a young college student, with no known past medical history after his admition to the medicine intensive care unit for respiratory failure due to acute Gamma Hydroxybutyrate (GHB) overdose use. He would later admit that he was a body builder who used injectable steroids in addition to other performance enhancing substances such as GHB which is usually undetected by the regular drug screening test. Electrocardiogram done in the emergency department revealed voltage criteria for left ventricular hypertrophy, chest x-ray revealed cardiomegaly and he had a soft systolic murmur on exam. Subsequent echocardiogram revealed a bicuspid aortic valve with raphe, mild aortic stenosis, and at least moderate aortic valve regurgitation. The patient was counseled and an outpatient referral to cardiology was made. This case indicates that an EKG sometime during the course of training may pick up cases that have been missed in the pre- participation screening. In addition educating young athletes about cardiac side effects of different performance enhancing agents is need.

References

1. R. Dhar, C.W.Stout, M.S.Link, et al. cardiovascular toxicities of performance- enhancing substances in sports. Mayo clinic proc. October 2005;80(10):1307-1315.

2. L. Stephani, R.Mercuri, L.Toncelli, et al. Bicusped aortic valve in athletes: an echocardiographic follow up. Medicine and science in aports and exercise. May 2008;40(5):S473.

3. P.De Mozzi, U.G. Longo, G.Galanti and N.Maffuli. Bicusped aortic valve: a literature review and its impact on sport activity. British Medical Bulletin 2008;1-23

Conflict of Interest:

None declared

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Summary for Patients

Cost-Effectiveness of Different Types of Evaluations Before Sports Participation in Young Athletes

The summary below is from the full report titled “Cost-Effectiveness of Preparticipation Screening for Prevention of Sudden Cardiac Death in Young Athletes.” It is in the 2 March 2010 issue of Annals of Internal Medicine (volume 152, pages 276-286). The authors are M.T Wheeler, P.A. Heidenreich, V.F. Froelicher, M.A. Hlatky, and E.A. Ashley.

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