|Year : 2020 | Volume
| Issue : 2 | Page : 40-45
Ankle and arm pressure recordings for the diagnosis of exercise-induced arterial endofibrosis
G Zegar1, J Hersant1, O Rouvière2, A Bruneau3, P Ramondou1, P Feugier4, Pierre Abraham5
1 Department of Vascular Medicine, University Hospital, Angers, France
2 Department of Imaging, University Hospital, Lyon, France
3 Department of Vascular Medicine; Department of Sports Medicine, University Hospital, Angers, France
4 Department of Vascular Surgery, University Hospital, Lyon, France
5 Department of Vascular Medicine; Department of Sports Medicine, University Hospital; Medical School, UMR Mitovasc CNRS6015-INSERM 1083, University of Angers, Angers, France
|Date of Submission||11-May-2020|
|Date of Decision||20-May-2020|
|Date of Acceptance||22-May-2020|
|Date of Web Publication||09-Jul-2020|
Dr. Pierre Abraham
Department of Sports Medicine, University Hospital, 4 Rue Larrey, 49933 Angers, Cedex 9
Source of Support: None, Conflict of Interest: None
BACKGROUND: Measurement of ankle and brachial blood pressure after maximal exercise is largely used to diagnose exercise-induced arterial endofibrosis (EIAE).
AIMS AND OBJECTIVES: We aimed to compare the different available methods and combination of these and propose a method based on graphical interpretation, for the diagnosis of EIAE.
MATERIALS AND METHODS: Finally, we propose a discriminant analysis, allowing an easy graphical interpretation of data. We studied 52 patients with EIAE and 156 asymptomatic controls.
RESULTS: Diagnosis accuracy for EIAE was at best 90.9% when using preexisting diagnostic thresholds alone. A combination of these thresholds increased the diagnostic accuracy up to 95.7%. A discriminant analysis equation with a 96.6% accuracy rate was inferred from a simplified algorithm.
CONCLUSION: Our graphical representation is an accurate, simple, fast, and inexpensive manner for analyzing the results of exercise arterial pressures for detecting EIAE in athletes.
Keywords: Ankle–brachial index, diagnosis, exercise, exercise-induced arterial endofibrosis, peripheral artery disease
|How to cite this article:|
Zegar G, Hersant J, Rouvière O, Bruneau A, Ramondou P, Feugier P, Abraham P. Ankle and arm pressure recordings for the diagnosis of exercise-induced arterial endofibrosis. Vasc Invest Ther 2020;3:40-5
|How to cite this URL:|
Zegar G, Hersant J, Rouvière O, Bruneau A, Ramondou P, Feugier P, Abraham P. Ankle and arm pressure recordings for the diagnosis of exercise-induced arterial endofibrosis. Vasc Invest Ther [serial online] 2020 [cited 2020 Nov 30];3:40-5. Available from: https://www.vitonline.org/text.asp?2020/3/2/40/289241
| Introduction|| |
Exercise-induced arterial endofibrosis (EIAE) is an arterial disease affecting highly trained athletes.,,, EIAE physiopathology is unknown.,,, The diagnostic value of ultrasonography remains poor in EIAE,,, and radiologic investigations are only presurgical investigations., Final diagnosis is based on histopathological findings.
Measurement of ankle and brachial pressure before and after exercise shows a good performance for diagnosing EIAE, but numerous methods of interpretation have been proposed.,,,,, The aim of this study was to test these methods or associate them in a large group of athletes and to define a diagnostic algorithm based on a linear regression discrimination analysis.
| Materials and Methods|| |
In this retrospective study, data were collected from anonymized files of 52 patients who have undergone surgery for EIAE at Angers University Hospital (AUH) and Lyon University Hospital (LUH) between January 1, 2000, and January 1, 2017, constituting the EIAE group, and selected according to the respective diagnostic criteria. EIAE patients met the inclusion criterion if they were trained cyclist (>10,000 km/year), had surgically proven iliac or femoral endofibrosis, and had no associated atheromatous or other inflammatory arterial diseases. The control group was established by the selection of 156 asymptomatic trained athletes with no cardiovascular disease history among the VICTOR cohort carried out at the AUH. The VICTOR cohort aims at recording pre- and post-exercise ankle pressure in 1760 asymptomatic athletes of various age ranges. Therefore, each patient was paired with three age-matching (±5 years) and gender-matching controls, resulting in a total study population of 208 subjects [Figure 1].
|Figure 1: Study population. Fifty-two patients with surgically proven exercise-induced arterial endofibrosis were selected at the Angers and Lyon University Hospitals. Control cases were selected among asymptomatic athletes of the VICTOR cohort managed at the Angers University Hospital. Three gender- and age-matched control subjects were paired to each exercise-induced arterial endofibrosis patients, constituting a total of 208 participants|
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In both participating centers, ankle and brachial systolic arterial blood pressure (SBP) were measured using automatic devices and the exercise tests were carried out on a CYCLUS ergometer (RBM Elektronik-Automation, Leipzig, Germany) under the supervision of healthcare professionals trained to conduct sports and cardiac stress tests.
Maximal power output, brachial SBP at rest and at 1 min postexercise in both arms, and ankle systolic blood pressure (ASBP) at rest and at 1 min postexercise in both legs were recorded during examination with 4 Dynamap (Kriticons, Johnson and Johnson). From these values, the ankle–brachial index (ABI) at rest and at 1 min postexercise and the difference of ABI between the affected leg and the healthy leg at rest and at 1 min postexercise were calculated. For optimal accuracy, the leg considered as the “pathological” one in control subjects was the same as the EIAE-affected leg in paired patient.
Various methods of interpretation have been proposed, based on ABI, ASBP and absolute difference between the healthy lower limb and the pathological lower limb (AD); ABI <0.54 or AD ASBP >23 mmHg;, ABI <0.50 or AD ABI >0.18; ABI <0.66; ABI <0.50;([0.06 × ASBPp] – [0.042 × ASBPh] + [1.734 × ABIp] – [0.103 × ABIh] −1.3531) <0, where “P” is pathological leg and “h” is healthy leg.
First, we tested the available reported thresholds in our large population. Second, we created additive (“and”) and relative (“or”) pairings of these diagnostic thresholds with the aim of improving the diagnostic performance of EIAE. All combinations were tested (i.e. Abraham et al. and/or Taylor and George; Schep et al., and Fernández-García et al.; Taylor and George and/or Schep et al., and Chevalier et al.; Chevalier et al. and/or Schep et al., and Fernández-García et al.; Schep et al., and/or Fernández-García et al.), except the combinations of the thresholds described in Abraham et al. and Chevalier et al., given the single use of ABI values in both cases.
Third, we developed a diagnostic algorithm based on our results to define a diagnostic threshold that combined ease of use and diagnostic performance. This was constructed using univariate and bivariate analyses with the aim of highlighting the variables that best separated the EIAE and control groups. Thereafter, a multivariate analysis taking into account several variables together allowed the creation of a decision tree. This methodology corresponded to a repetitive process where the first stage consisted of finding the variable that, through its methods, best separated the data of each group, thereby creating a subspace. In this subspace, the same process was repeated twice to refine the classification rules between the two groups and result in the creation of a decision tree and allow a graphical representation.
The data were integrated into an Excel spreadsheet using the software MATLAB 2014a (MathWorks, Natick, MA, USA) for statistical analyses with Student's t-test, ANOVA test, and univariate, bivariate, and multivariate analyses. Discriminative analyses were also conducted to calculate sensitivity, specificity, positive predictive value, negative predictive value, and error rate. For all statistical tests, a two-tailed value of P < 0.05 was considered statistically significant.
The VICTOR study is a prospective study (ClinicalTrials.gov Identifier: NCT01812343) and the patients provided informed written consent, while for the retrospective analysis of EIAE patients, the study was approved by the Ethics Committee of AUH under the number 2017/47 and conforms to the ethical rules from the Declaration of Helsinki. All participants were aware that the results of the routine medical file could be used for research purpose. They could exercise their right to deny this use but no written consent was required according to the French law. The data that support the findings of this study are available from the corresponding author (PA), upon reasonable request.
Patient and public involvement
Patients were not involved in the research question (s) and outcome measures, in the design of, the recruitment to, and conduction of the study. Neither were they asked to assess the burden of the intervention and time required to participate or plans to disseminate the study results.
| Results|| |
Despite the pairing of each EIAE patient with three control subjects, due to the interval of acceptable age matching, we finally noted significant differences between the two groups in terms of age, height, weight, heart rate, BP, and developed power [Table 1].
Exercise-induced arterial endofibrosis diagnostic accuracy of existing thresholds
The diagnostic accuracy of various combinations of previously reported thresholds,,,,, was evaluated in our participants. With this objective, we performed additive and relative combinations of these diagnostic thresholds. EIAE diagnostic accuracy was increased by the additive pairing of three thresholds, with an error rate below 5% [Table 2], while relative pairing did not drastically affect the results [Table 2].
|Table 2: Sensitivity, specificity, positive predictive value, negative predictive value and error rate of the additive (“and”) or the relative (“or”) paired diagnostic thresholds from the studies by Schep et al.,, Taylor et al., Abraham et al., Chevalier et al., and Fernández-García et al.|
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Creation of exercise-induced arterial endofibrosis diagnostic algorithms
A diagnostic algorithm was generated by analysis of initial parameters (i.e. ABI and ASBP) through the construction of receiver operator characteristic curves and calculation of their areas under the curve (AUC). First, we observed a better diagnostic accuracy of the ABI and ASBP values at 1 min poststress as compared to those taken at rest. Besides, the most discriminative parameters were the difference in SBP between the affected and the healthy leg (AUC = 0.84), the ABI of the affected leg (AUC = 0.96) and the difference of ABI between the affected and the healthy leg (AUC = 0.96). The significance of these three parameters was further confirmed by ANOVA, univariate, bivariate, and multivariate analyses, and their combination allowed building a two-step algorithm to diagnose EIAE based on ABI of the affected leg at 1 min poststress and ABI difference between the healthy and the affected leg [Figure 2]. This allowed EIAE diagnosis with an error rate of 3.9%, a sensitivity of 92.3%, a specificity of 97.4%, a positive predictive value of 92.3%, and a negative predictive value of 97.4%.
|Figure 2: Two-variable diagnostic algorithm of exercise-induced arterial endofibrosis. PPV: predictive positive value, NPV: negative predictive value|
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Generation of a graphical exercise-induced arterial endofibrosis diagnostic tool
Finally, a linear discrimination analysis of the ABI difference between the healthy and the affected leg of the 208 participants plotted against the ABI of the affected leg [Figure 3] resulted in the following equation where the diagnostic of EIAE is made when Z > 0:
|Figure 3: (a) Distribution of the two most discriminant parameters in the study population. The ankle–brachial index difference between the healthy and the affected leg was plotted against the ankle–brachial index of the exercise-induced arterial endofibrosis-affected leg for each of the 208 participants. Patients with exercise-induced arterial endofibrosis presented a lower ankle–brachial index in the affected leg associated with a higher difference of ankle–brachial index between the affected and the healthy leg as compared to healthy controls. (b) A linear discrimination analysis of the data distribution resulted in the equation Z = -17.08 × ankle–brachial index + 26.83 × ankle–brachial index AD + 5.06, where the diagnostic of exercise-induced arterial endofibrosis is made when Z > 0|
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Z = −17.08 × ABI + 26.83 × ABI AD + 5.06
The use of this equation as an EIAE diagnostic tool remains pretty accurate with a sensitivity of 86.5%, a specificity of 100%, a positive predictive value of 100%, a negative predictive value of 95.7%, and an error rate of 3.4%.
| Discussion|| |
EIAE is an arterial disease affecting highly trained athletes (mainly cyclists), which in 95% of cases affects men aged 18–61 years (average diagnosis age is 27) without cardiovascular risk factors. EIAE affects the external iliac artery in 90% of cases, the remaining localizations being the primary iliac artery, the internal iliac artery, the lateral circumflex femoral artery, and the common, superficial, or deep femoral artery.,,, EIAE physiopathology is unknown and still largely debated.,,, Symptoms, generally described as a paralyzing pain, a swelling of the thigh, or even a loss of power in the affected leg, appear at maximum exercise, improve within a few minutes after maximum workload exercise has ended, and are absent in nonsports activities.,,,
EIAE remains an uncommon and difficult-to-diagnose peripheral artery disease of highly trained athletes. Several authors previously evaluated the accuracy of classical biological measurements such as ABI and ASBP to diagnose EIAE.,,,,, However, most of these studies lack a sufficient number of patients, and as a consequence, critical parameters such as sensitivity and error rates were frequently below acceptable limits. To the best of our knowledge, the present work represents the largest study, in terms of number of participants, evaluating the accuracy of arterial pressure measurements for EIAE diagnosis in both patients with proven EIAE and healthy athletes.
Interest of the study
One of the strengths of this study relies on the fact that the EIAE group exclusively contains patients with surgically proven EIAE and the control group strictly asymptomatic healthy athletes. Moreover, the AUH and LUH are experienced centers in the diagnosis and treatment of EIAE.,,,,, Finally, automated BP monitors were used in both participating centers to decrease measurement variability.
The previously described thresholds failed to diagnose EIAE in our participants with acceptable accuracy. Their diagnostic accuracy was increased by additive pairing, particularly the addition of the thresholds defined by Taylor and George and Fernández-García et al. However, the threshold defined by Fernández-García et al. seemed too complicated to be used in clinical practice.
Therefore, we constructed a decision algorithm based on our observations and demonstrated that it was more accurate than previous thresholds for the diagnosis of EAIE. To facilitate routine use while maintaining a highly satisfying diagnostic performance, a linear equation was calculated from this two-variable algorithm and allowed to conclusively categorize the patients as probably healthy or highly suspected of EIAE using a simple graphic representation of ABI measurements [Figure 3].
Technical issue in exercise-induced arterial endofibrosis investigations
Requiring necessary equipment for a cardiac stress test (treadmill, bike, electrocardiogram, and automatic BP monitors) and qualified personnel, the poststress ABI measurement is not feasible in all medical centers. Nevertheless, this technique remains more accessible than current diagnostic techniques such as angio-tomodensitometry or digital angiography.
It is also important to recall that the ABI measurement must be performed in the strict dorsal recumbent position during measurement and simultaneously (then with automatic devices) to achieve a reliable BP report. It is also important that values are started no later than 1 min after exercise because the diagnostic performance of pressure measurements decreases with time in the recovery period.,
First, it is important to specify that only EIAE and not the kinking (narrowing and pinching) of an artery, was used as an endpoint. It was not possible to predict the diagnostic capacity of this methodology in the diagnosis of artery kinking, another sports-induced iliac disease.
Further, despite pairing of each patient with three age- and gender-matched controls, the population of the EIAE group was fitter than the control group in terms of height, weight, maximum heart rate, BP 1 min postexercise, and developed power. These differences may introduce a bias in the interpretation of the results.
Second, it is impossible to completely rule out the presence of asymptomatic lesions in control patients as well as the absence of EIAE on the contralateral leg of EIAE patients. Specifically, in this latter case, pain on the symptomatic side could mask the occurrence of pain due to contralateral less severe EIAE. Patients with bilateral arterial endofibrosis cannot benefit from this diagnostic tool. However, it is important to note that this disease can be bilateral (15% of cases) but in this case is rarely symmetrical. Patients with arterial endofibrosis in branches that shall not result in ABI changes (internal iliac artery, lateral circumflex artery, and deep femoral artery) also cannot benefit from this diagnostic tool.
Third, the patients in the study were diagnosed and treated in Angers and Lyon using diagnostic thresholds from the studies by Abraham et al. and Chevalier et al. and using automatic devices. On the one hand, this clearly is a bias leading to overestimating the performance of these two criteria for the whole studied group. This is possible but, the diagnosis in general is made by adding clinical history and clinical factors and does not only rely on the use of these sole pressure diagnostic thresholds. On the other hand, manual recordings are generally recommended in postwalking tests, but measurements after heavy load exercise require simultaneous (then automatic) recordings.
Finally, it can be argued that our algorithm performed better than the others simply because it was designed for maximum accuracy in the test dataset. Obviously, a prospective validation study is needed to know how these algorithms perform in clinical practice.
| Conclusion|| |
An evident lack of any efficient tool to diagnose EIAE led us to conduct the largest study, in terms of number of participants, performed to evaluate the diagnostic accuracy of standard vascular parameters in both healthy and EIAE-suffering highly trained cyclists. ABIs' determination is a relatively easy recorded parameter to provide arguments for EIAE. In light of our results, it seems wise, for sports medicine physicians, to use the graphic representation of our two-variable decision algorithm for a simple, fast, and inexpensive interpretation of pressure measurements for the diagnosis of EAIE in trained cyclists.
PA and PF conceptualized and supervised the research. GZ, JH, OR, AB, PR, PF, and PA provided the patients and performed medical examinations. GZ JH, and PA drafted, reviewed, and edited the manuscript and analyzed the data. OR, AB, PR, and PF critically revised the manuscript. All authors approved the final version as submitted.
We thank Dr. Patrick Vandeputte for careful proofreading of the manuscript and writing assistance.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest
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[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2]