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Vascular OnlineFirst, published on April 28, 2015 as doi:10.1177/1708538115584506
Original Article
Individual variations in ankle brachial index measurement among Turkish adults
Vascular 0(0) 1–6 ! The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/1708538115584506 vas.sagepub.com
Orhan Demir1, Ilker Tasci1, Cengizhan Acikel2, Kenan Saglam1, Mustafa Gezer1, Ramazan Acar1, Birol Yildiz1, Fatih Bulucu1, Hasan Kutsi Kabul3, Mustafa Inanc Dogan1 and Bayram Koc1
Abstract Purpose: Variability of ankle brachial index (ABI) measured by the same observer in the same individual on three different occasions was examined. Basic methods: A single morning ABI was initially determined (measurement 1) with handheld Doppler device. One to four weeks apart, another morning (measurement 2) and afternoon (measurement 3) ABI was measured on the same day. Principal findings: A total of 161 adults were enrolled. Mean ABI was similar among the three measurements. ABI differed more than 0.15 in 15 individuals between measurement 1 and 3, in 10 subjects between measurement 1 and 2, and in 12 individuals between measurement 2 and 3. Intra-group correlation coefficients of reproducibility of ABI were 0.808 for single measurements (coefficient of the values lacking association with each other), and 0.927 for average measurements (coefficient of the values that were associated with each other). Conclusions: Although reproducibility of ABI values was found satisfactory, up to 12% of participants displayed more than 0.15 alternations between measurements, either on the same day or more than a week apart.
Keywords Peripheral arterial disease, ankle-brachial index, reproducibility, variation
Introduction Ankle brachial index (ABI) is a non-invasive, inexpensive, simple and efficient diagnostic tool to detect peripheral arterial disease (PAD) and can easily be administered in an outpatient setting.1 An ABI value below 0.9 has a sensitivity of 90% and a specificity of 98% for the diagnosis of PAD.2–4 Although the technique has limited value in estimating the level of occlusion, it is useful for predicting the severity of PAD. Normal ABI value ranges between 1.0 and 1.3 or 1.4, and higher values indicate presence of calcified incompressible vessels.5,6 ABI values that range between 0.9 and 0.99 were defined as borderline low values.7 Low extremity Duplex ultrasound is the only non-invasive technique other than ABI testing, which not only has good agreement with arteriography but also some limitations including low accuracy in infrapopliteal disease as well as cost.8 Repeatability and reliability of non-invasive diagnostic tests have always been a source concern as well as a research area, because, obtaining different results
in a repeat test may lead to a suspicion about the decision made. Well-known examples include oral glucose tolerance test, spirometry, and arterial blood pressure measurement.9–11 Limitations in obtaining similar results when non-invasive tests are repeated constitute the basic rationale of the present study. In other words, few studies have yet searched whether there is a similar concern for ABI measurement which is a widely used non-invasive test to identify PAD. Indeed, some authors reported around 8.5% difference between two measurements performed even 10 min apart by different observers.12 ABI measurements may also differ 1 Department of Internal Medicine, Gulhane School of Medicine, Ankara, Turkey 2 Department of Epidemiology, Gulhane School of Medicine, Ankara, Turkey 3 Department of Cardiology, Gulhane School of Medicine, Ankara, Turkey
Corresponding author: Ilker Tasci, GATA Ic Hastaliklari Bilim Dali, Etlik, 06018 Ankara, Turkey. Email: [email protected]
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depending on the experience of the observer or tools used.13 In this study, we examined the degree of variations in ABI values on the same individual when performed by the same observer, equipment, and device on the same day and on different occasions.
Materials and methods Research type, settings, and subject selection This single center, cross sectional and observational study was performed in the settings generated in a silent room in the Department of Internal Medicine, Gulhane School of Medicine, Ankara, Turkey. A written approval of Gulhane School of Medicine Medical Ethics Committee was obtained and all subjects gave informed, written consent. Inclusion criteria were age 18–80 years, ability to understand and respond to questions, and signing a written informed consent. Exclusion criteria were having medical or surgical diseases that require hospitalization, having a disease with short prognosis (i.e. cancer) and being in the recovery period following conditions such as myocardial infarction, stroke, or surgery.
Procedures All ABI measurements were performed by the same observer who underwent specific training and gained experience for several months by participating in two other ongoing ABI studies in the same clinic. After successful standardization of the environment and the observer, variability of ABI value was tested by recording intraday and weekly differences. For this purpose, three measurements on different occasions were performed for each participant. The definitions were as follows: Measurement 1: ABI measured on any day (between 08:00 and 12:00). Measurement 2: ABI measured 1–4 weeks apart measurement 1 (between 08:00 and 12:00). Measurement 3: ABI measured in the afternoon on the same day of measurement 2 (between 14:00 and 16:00). Participants were considered to complete the study when they underwent all three measurements. Anthropometric variables including body mass index (BMI), waist circumference, hip circumference and waist-to-hip ratio (WHR) were properly recorded. Smoking status, history of hypertension, diabetes mellitus, dyslipidemia, coronary heart disease (CHD), heart failure, stroke, PAD, and history of cardiovascular disease (CVD) in the first grade relatives were questioned and recorded in the patient monitoring chart.
Table 1. Demographics and basic laboratory data of the participants. Parameter (n ¼ 161)
Mean SD (min.–max.)
Age Gender, male, n (%) Height (cm) Weight (kg) BMI Waist circumference (cm) Hip circumference (cm) Waist-to-hip ratio Hemoglobin (g/dL) Platelet (x103/mL) Fasting plasma glucose (mg/dL) Urea (mg/dL) Creatinine (mg/dL) Total cholesterol (mg/dL) Triglyceride (mg/dL) HDL-cholesterol (mg/dL) LDL-cholesterol (mg/dL) TSH (mU/L) Calcium (mg/dL) Vitamin B12 (pg/mL)
52.03 18.99 87 165.12 8.88 75.61 13.4 27.93 5.57 97.06 15.11 105.13 12.97 0.92 0.07 14.16 1.65 245.08 59.72 113.96 51.78 31.97 12.63 0.95 0.15 206.6 49.59 184.27 130.44 46.95 11.42 125.99 39.52 2.15 3.31 9.59 0.62 245.83 174.3
(19–83) (54%) (149–185) (46–109) (15.37–47.18) (65–138) (75–142) (0.77–1.14) (8.3–17.8) (62–470) (56–455) (13–115) (0.62–1.46) (68–412) (44–837) (16–75) (25–245) (0–29) (7.98–10.5) (79–956)
BMI: body mass index, HDL: high density lipoprotein cholesterol, LDL: low density lipoprotein cholesterol, TSH: thyroid stimulating hormone.
Risk factors for CVD defined in ATP-III and Framingham cohorts were also adapted to the present work. Results of conventional blood analyses listed in Table-1 were recorded.
ABI measurement The technique described by Grenon et al. was used for ABI test14 with small environmental improvements as described previously.15–17 The measurement was performed with the patient supine. To ensure the comfort of the arms, two metal plates 80 x 15 cm were placed on the head of the stretcher with an angel of 30 . For systolic pressure measurement, four brand new fully calibrated aneroid sphygmomanometers with Velcro cuffs were used (ERKA, D-83646, Germany). Cuff width was 12 cm and cuff length was 29–40 cm. Four extremities of the patient were wrapped with the cuffs at the same time and, during this process the participants were allowed to rest for at least 5 min. Both of the brachial pulses in the upper extremities and, tibialis anterior and tibialis posterior pulses in the lower extremities were recorded. Measurements were obtained using a hand-held 8 MHz Doppler instrument (Hadeco Echo Sounder ES-101EX, Japan). The first
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blood flow sound heard as the cuff was deflated was recorded. In the case of weak sounds, an earphone was used. The readings were started from the right arm, followed by the right ankle, left ankle, and left arm. The cycle was repeated and two values were recorded for each vessel, and the mean of two measurements was considered as the final result for the respective vessel.
variations in ABI measured by different observers and finally reported 12–20% variations. By estimating a variation rate of 16% among our participants, with 6% error estimation and using 95% confidence level, 144 subjects would be sufficient to enroll.
Calculation of ABI
Results Demographics, anthropometrics, and laboratory data
ABI was calculated based on Trans-Atlantic InterSociety Consensus Document on Management of Peripheral Arterial Disease II (TASC-II) guidelines.18 First, right and left ABI values were separately calculated by dividing the highest systolic blood pressures measured in each limb (a. tibialis posterior or a. tibialis anterior) to the highest systolic blood pressure measured in the right or left brachial artery. The lowest of the right and left ABI values recorded were considered as the final ABI value of the tested individual.
A total of 227 subjects fulfilling the inclusion criteria were enrolled initially. Of these subjects, 161 completed the study by having all three measurements. A total of 66 participants were excluded after enrollment due to missing of at least one measurement of the second and third rounds. One participant was also excluded from the study due to malignancy diagnosed during the research period. Demographics and basic laboratory data of the participants are shown in Table 1.
Statistics
Frequency of major risk factors for CVD and established CVD
Variation criterion was considered as an increase or a decrease of ABI by 0.15 or greater between two measurements, and this model was defined by a widely accepted international guideline.18 Besides, we also ran the same analysis using a threshold of 0.10 to provide more comparisons. We presented descriptive statistics as number (%) for discrete categorical variables and as mean standard deviation for continuous variables. Chi-square test was used to compare categorical variables between groups, when the expected number of cells was greater than 20% of total number of cells, using Fisher’s exact test. To evaluate the distribution of continuous variables one-sample Kolmogorov Smirnov test was used. Pairwise comparisons were performed by using Mann-Whitney U test. To evaluate the repeatability of ABI measurements, intraclass correlation coefficients were calculated. Coefficient of the values lacking association with each other, and the coefficient when the values were associated with each other were separately calculated. Variation rates between the measurements by the number of existing risk factors were compared using McNemar test. Differences between the repeated measurements were compared using Friedman and Wilcoxon tests. For subgroup comparisons, Bonferroni adjustment was done. Concomitant changes in continuous variables were evaluated by calculating Spearman correlation coefficient. p values 30), and 101 subjects (62.7%) had hypertension. Eighteen participants (11.2%) had a history of CHD and three participants (1.9%) had a history of stroke.
Variation of ABI values and repeatability coefficients A total of 483 ABI measurements on three occasions as described above were evaluated. Mean ABI was 1.14 0.14 for measurement 1, 1.13 0.14 for measurement 2, and 1.12 0.14 for measurement 3. Variation rates of ABI are shown in Table 2. Ten participants (6.2%) showed differences equal to or greater than 0.15 between measurement 1 and measurement 2, 15 participants (9.3%) between measurement 1 and measurement 3, and 12 participants (7.5%) between measurement 2 and measurement 3. However, variation rates among the three measurements did not differ significantly (p ¼ 0.791 for measurement 1 to 2 vs. measurement 2 to 3, p ¼ 0.332 for measurement 1 to 2 vs. measurement 1 to 3, p ¼ 0.629 for measurement 1 to 3 vs. measurement 2 to 3; McNemar test). Noticeably, 25 out of 37 (67.6%) variations were recorded in the same participants.
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When a change of 0.10 in ABI values was considered as a variation, we found significant differences between measurement 1 and measurement 2 in 25 (15.5%) participants, between measurement 1 and measurement 3 in 24 (14.9%) participants and between measurement 2 and measurement 3 in 20 (12.4%) participants. Among these variations 44 of 69 (63.8%) were observed in the same subjects. Finally, for a maximum of 0.15 points variations in three measurements intra-group correlation coefficient was calculated as 0.808 for single measurements and 0.927 for mean measurements (Table 3).
Subjects with variation in ABI*, n (%)
#1 to #2 #1 to #3 #2 to #3
10 (6.2) 15 (9.3) 12 (7.5)
a Variation criterion was considered as a chance of ABI value by 0.15 or greater between two measurements.18 Mean ABI; measurement 1: 1.14 0.14, measurement 2: 1.13 0.14, measurement 3: 1.12 0.14. *25 of 37 variation events occurred in the same participants.
Table 3. Repeatability coefficients for ABI performed in three occasions. Intraclass correlation coefficients Single measurement Mean
Due to the design of the study, as the lower limit of age was considered 18 years in the inclusion criteria, the frequency of PAD was lower than that expected in a Turkish sample.19,20 A low ABI was recorded in four (2.5%) subjects in measurement 1, three (1.9%) subjects in measurement 2, and five (3.1%) subjects in measurement 3. These ratios did not differ significantly. Frequency of a high ABI (>1.3) was also similar among the three measurements; 11.8% (n ¼ 19) by measurement 1, 9.9% (n ¼ 16) by measurement 2, and 11.2% (n ¼ 18) by measurement 3.
Associates of variations in ABI
Table 2. Variation rates of 161 ABI tests repeated three times in the same individualsa. Measurements
Number of patients diagnosed with low and high ABI
0.808* 0.927**
*Coefficient regardless of the presence of an association between the values, i.e. when all values are obtained from different subjects. **Coefficient obtained when the values are intercorrelated, i.e. all three measurements were done on the same subjects.
Because almost two-third of ABI variations were detected in the same participants, we needed to explore factors contributing to this result. When subjects were categorized into CVD risk as ‘‘low’’, ‘‘moderate’’, and ‘‘high’’, we noticed that the ratio of subjects with ABI variation in the high risk category was lower than those of moderate and low risk categories between measurements 1 and 2 (Table 4). The same was also true for measurements 1 and 3 in moderate risk category. However, neither difference was significant, most probably due to small number of individuals in the low as well as moderate risk categories in the study. Waist circumference was found significantly lower in subjects with variations in ABI compared to those without (90.24 18.93 cm vs. 98.33 14.02 cm, p ¼ 0.015); however, when gender based categorizations were applied for an increased waist circumference (male; >88 cm, female; >102 cm), there was no effect of waist circumference on the outcome. Similarly, WHR was significantly lower in the group with ABI variation (0.9 0.09 vs. 0.93 0.07) (p ¼ 0.011) but a categorical analysis (WHR increased: male; >0.95, female; >0.8) revealed no significant influence on ABI variations. Among the parameters listed in Table 1, LDL-cholesterol level was different in subjects with and without ABI variations on three occasions (p ¼ 0.036) but high frequency of statin use (29.2%) precluded significance of this finding.
Table 4. Number of individuals with ABI variations across CVD risk categoriesa. Low risk
Moderate risk
High risk
Measurements
n ¼ 7/161 (4.3%)
n ¼ 29/161 (18%)
n ¼ 125/161 (77.7%)
p
#1 to #2 #1 to #3 #2 to #3
2 (28.6%) 3 (42.9%) 0
8 (27.6%) 3 (10.3%) 4 (13.8%)
15 (12.0%) 18 (14.4%) 16 (12.8%)
0.07 0.09 0.58
a
Risk categories: low: 1 major risk factor, moderate: 2 major risk factors, high: 3 major risk factors that were listed in the methods. Variation criterion was considered as a chance of ABI value by 0.15 or greater between two measurements.18
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Discussion The aim of the present study on Turkish adults was to examine the repeatability of the ABI test used for the diagnosis of PAD. Considering a cut off value of 0.9, a variation of 0.15 points might be worthy but this was not observed in more than 90% of measurements in this study, suggesting that especially values around normal ABI range (1.1 to 1.3 or 1.4) are not subject to misclassifications. Nevertheless, being aware of such a variation might help users of the test to decide on a retest when they find values around 0.90. Whether ABI measurement performed by the same observer showed a variation in the same individual on different occasions was not previously tested in such a large group. Several studies reported low rates of inter-observer errors and thus satisfactory repeatability of ABI test but the number of trials that tested this issue is limited. In an early investigation performed by Fowkes et al.,21 four inexperienced technicians performed the ABI measurements on four separate time points with 40-min and two weeks apart in a group primarily consisted of subjects with symptomatic PAD. They concluded that both ankle and arm measurements changed considerably in those subjects with PAD. High variation rates (16%) in their patients with PAD were particularly important because the test is used primarily to detect this group of people. In another study that included repeated ABI measurements performed by seven different observers with various experience levels on 19 patients with critical limb ischemia, 16% of all measurements showed a variation of 0.15 units or more.22 Jeelani et al. reported that ABI values measured by two different observers displayed a borderline error of 20%.23 When ABI taken on six patients by two experienced and 24 less experienced observers were compared, total intra-observer variability was found 11.8%, whereas inter-observer variability ranged between 7.3% and 12%.24 In another study, measurements done by the nurse, family physicians and cardiovascular surgeons displayed a non-significant an error of 8%, intra-observer variability on the same patients with 10-min intervals was also not significant (9%).12 Nevertheless, almost equal rates of inter- and intra-observer variations around 10% in that study were noteworthy, suggesting a repeated test may be needed at least for some individuals. Indeed, positive predictive value of ABI
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Vascular OnlineFirst, published on April 28, 2015 as doi:10.1177/1708538115584506
Original Article
Individual variations in ankle brachial index measurement among Turkish adults
Vascular 0(0) 1–6 ! The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/1708538115584506 vas.sagepub.com
Orhan Demir1, Ilker Tasci1, Cengizhan Acikel2, Kenan Saglam1, Mustafa Gezer1, Ramazan Acar1, Birol Yildiz1, Fatih Bulucu1, Hasan Kutsi Kabul3, Mustafa Inanc Dogan1 and Bayram Koc1
Abstract Purpose: Variability of ankle brachial index (ABI) measured by the same observer in the same individual on three different occasions was examined. Basic methods: A single morning ABI was initially determined (measurement 1) with handheld Doppler device. One to four weeks apart, another morning (measurement 2) and afternoon (measurement 3) ABI was measured on the same day. Principal findings: A total of 161 adults were enrolled. Mean ABI was similar among the three measurements. ABI differed more than 0.15 in 15 individuals between measurement 1 and 3, in 10 subjects between measurement 1 and 2, and in 12 individuals between measurement 2 and 3. Intra-group correlation coefficients of reproducibility of ABI were 0.808 for single measurements (coefficient of the values lacking association with each other), and 0.927 for average measurements (coefficient of the values that were associated with each other). Conclusions: Although reproducibility of ABI values was found satisfactory, up to 12% of participants displayed more than 0.15 alternations between measurements, either on the same day or more than a week apart.
Keywords Peripheral arterial disease, ankle-brachial index, reproducibility, variation
Introduction Ankle brachial index (ABI) is a non-invasive, inexpensive, simple and efficient diagnostic tool to detect peripheral arterial disease (PAD) and can easily be administered in an outpatient setting.1 An ABI value below 0.9 has a sensitivity of 90% and a specificity of 98% for the diagnosis of PAD.2–4 Although the technique has limited value in estimating the level of occlusion, it is useful for predicting the severity of PAD. Normal ABI value ranges between 1.0 and 1.3 or 1.4, and higher values indicate presence of calcified incompressible vessels.5,6 ABI values that range between 0.9 and 0.99 were defined as borderline low values.7 Low extremity Duplex ultrasound is the only non-invasive technique other than ABI testing, which not only has good agreement with arteriography but also some limitations including low accuracy in infrapopliteal disease as well as cost.8 Repeatability and reliability of non-invasive diagnostic tests have always been a source concern as well as a research area, because, obtaining different results
in a repeat test may lead to a suspicion about the decision made. Well-known examples include oral glucose tolerance test, spirometry, and arterial blood pressure measurement.9–11 Limitations in obtaining similar results when non-invasive tests are repeated constitute the basic rationale of the present study. In other words, few studies have yet searched whether there is a similar concern for ABI measurement which is a widely used non-invasive test to identify PAD. Indeed, some authors reported around 8.5% difference between two measurements performed even 10 min apart by different observers.12 ABI measurements may also differ 1 Department of Internal Medicine, Gulhane School of Medicine, Ankara, Turkey 2 Department of Epidemiology, Gulhane School of Medicine, Ankara, Turkey 3 Department of Cardiology, Gulhane School of Medicine, Ankara, Turkey
Corresponding author: Ilker Tasci, GATA Ic Hastaliklari Bilim Dali, Etlik, 06018 Ankara, Turkey. Email: [email protected]
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depending on the experience of the observer or tools used.13 In this study, we examined the degree of variations in ABI values on the same individual when performed by the same observer, equipment, and device on the same day and on different occasions.
Materials and methods Research type, settings, and subject selection This single center, cross sectional and observational study was performed in the settings generated in a silent room in the Department of Internal Medicine, Gulhane School of Medicine, Ankara, Turkey. A written approval of Gulhane School of Medicine Medical Ethics Committee was obtained and all subjects gave informed, written consent. Inclusion criteria were age 18–80 years, ability to understand and respond to questions, and signing a written informed consent. Exclusion criteria were having medical or surgical diseases that require hospitalization, having a disease with short prognosis (i.e. cancer) and being in the recovery period following conditions such as myocardial infarction, stroke, or surgery.
Procedures All ABI measurements were performed by the same observer who underwent specific training and gained experience for several months by participating in two other ongoing ABI studies in the same clinic. After successful standardization of the environment and the observer, variability of ABI value was tested by recording intraday and weekly differences. For this purpose, three measurements on different occasions were performed for each participant. The definitions were as follows: Measurement 1: ABI measured on any day (between 08:00 and 12:00). Measurement 2: ABI measured 1–4 weeks apart measurement 1 (between 08:00 and 12:00). Measurement 3: ABI measured in the afternoon on the same day of measurement 2 (between 14:00 and 16:00). Participants were considered to complete the study when they underwent all three measurements. Anthropometric variables including body mass index (BMI), waist circumference, hip circumference and waist-to-hip ratio (WHR) were properly recorded. Smoking status, history of hypertension, diabetes mellitus, dyslipidemia, coronary heart disease (CHD), heart failure, stroke, PAD, and history of cardiovascular disease (CVD) in the first grade relatives were questioned and recorded in the patient monitoring chart.
Table 1. Demographics and basic laboratory data of the participants. Parameter (n ¼ 161)
Mean SD (min.–max.)
Age Gender, male, n (%) Height (cm) Weight (kg) BMI Waist circumference (cm) Hip circumference (cm) Waist-to-hip ratio Hemoglobin (g/dL) Platelet (x103/mL) Fasting plasma glucose (mg/dL) Urea (mg/dL) Creatinine (mg/dL) Total cholesterol (mg/dL) Triglyceride (mg/dL) HDL-cholesterol (mg/dL) LDL-cholesterol (mg/dL) TSH (mU/L) Calcium (mg/dL) Vitamin B12 (pg/mL)
52.03 18.99 87 165.12 8.88 75.61 13.4 27.93 5.57 97.06 15.11 105.13 12.97 0.92 0.07 14.16 1.65 245.08 59.72 113.96 51.78 31.97 12.63 0.95 0.15 206.6 49.59 184.27 130.44 46.95 11.42 125.99 39.52 2.15 3.31 9.59 0.62 245.83 174.3
(19–83) (54%) (149–185) (46–109) (15.37–47.18) (65–138) (75–142) (0.77–1.14) (8.3–17.8) (62–470) (56–455) (13–115) (0.62–1.46) (68–412) (44–837) (16–75) (25–245) (0–29) (7.98–10.5) (79–956)
BMI: body mass index, HDL: high density lipoprotein cholesterol, LDL: low density lipoprotein cholesterol, TSH: thyroid stimulating hormone.
Risk factors for CVD defined in ATP-III and Framingham cohorts were also adapted to the present work. Results of conventional blood analyses listed in Table-1 were recorded.
ABI measurement The technique described by Grenon et al. was used for ABI test14 with small environmental improvements as described previously.15–17 The measurement was performed with the patient supine. To ensure the comfort of the arms, two metal plates 80 x 15 cm were placed on the head of the stretcher with an angel of 30 . For systolic pressure measurement, four brand new fully calibrated aneroid sphygmomanometers with Velcro cuffs were used (ERKA, D-83646, Germany). Cuff width was 12 cm and cuff length was 29–40 cm. Four extremities of the patient were wrapped with the cuffs at the same time and, during this process the participants were allowed to rest for at least 5 min. Both of the brachial pulses in the upper extremities and, tibialis anterior and tibialis posterior pulses in the lower extremities were recorded. Measurements were obtained using a hand-held 8 MHz Doppler instrument (Hadeco Echo Sounder ES-101EX, Japan). The first
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blood flow sound heard as the cuff was deflated was recorded. In the case of weak sounds, an earphone was used. The readings were started from the right arm, followed by the right ankle, left ankle, and left arm. The cycle was repeated and two values were recorded for each vessel, and the mean of two measurements was considered as the final result for the respective vessel.
variations in ABI measured by different observers and finally reported 12–20% variations. By estimating a variation rate of 16% among our participants, with 6% error estimation and using 95% confidence level, 144 subjects would be sufficient to enroll.
Calculation of ABI
Results Demographics, anthropometrics, and laboratory data
ABI was calculated based on Trans-Atlantic InterSociety Consensus Document on Management of Peripheral Arterial Disease II (TASC-II) guidelines.18 First, right and left ABI values were separately calculated by dividing the highest systolic blood pressures measured in each limb (a. tibialis posterior or a. tibialis anterior) to the highest systolic blood pressure measured in the right or left brachial artery. The lowest of the right and left ABI values recorded were considered as the final ABI value of the tested individual.
A total of 227 subjects fulfilling the inclusion criteria were enrolled initially. Of these subjects, 161 completed the study by having all three measurements. A total of 66 participants were excluded after enrollment due to missing of at least one measurement of the second and third rounds. One participant was also excluded from the study due to malignancy diagnosed during the research period. Demographics and basic laboratory data of the participants are shown in Table 1.
Statistics
Frequency of major risk factors for CVD and established CVD
Variation criterion was considered as an increase or a decrease of ABI by 0.15 or greater between two measurements, and this model was defined by a widely accepted international guideline.18 Besides, we also ran the same analysis using a threshold of 0.10 to provide more comparisons. We presented descriptive statistics as number (%) for discrete categorical variables and as mean standard deviation for continuous variables. Chi-square test was used to compare categorical variables between groups, when the expected number of cells was greater than 20% of total number of cells, using Fisher’s exact test. To evaluate the distribution of continuous variables one-sample Kolmogorov Smirnov test was used. Pairwise comparisons were performed by using Mann-Whitney U test. To evaluate the repeatability of ABI measurements, intraclass correlation coefficients were calculated. Coefficient of the values lacking association with each other, and the coefficient when the values were associated with each other were separately calculated. Variation rates between the measurements by the number of existing risk factors were compared using McNemar test. Differences between the repeated measurements were compared using Friedman and Wilcoxon tests. For subgroup comparisons, Bonferroni adjustment was done. Concomitant changes in continuous variables were evaluated by calculating Spearman correlation coefficient. p values 30), and 101 subjects (62.7%) had hypertension. Eighteen participants (11.2%) had a history of CHD and three participants (1.9%) had a history of stroke.
Variation of ABI values and repeatability coefficients A total of 483 ABI measurements on three occasions as described above were evaluated. Mean ABI was 1.14 0.14 for measurement 1, 1.13 0.14 for measurement 2, and 1.12 0.14 for measurement 3. Variation rates of ABI are shown in Table 2. Ten participants (6.2%) showed differences equal to or greater than 0.15 between measurement 1 and measurement 2, 15 participants (9.3%) between measurement 1 and measurement 3, and 12 participants (7.5%) between measurement 2 and measurement 3. However, variation rates among the three measurements did not differ significantly (p ¼ 0.791 for measurement 1 to 2 vs. measurement 2 to 3, p ¼ 0.332 for measurement 1 to 2 vs. measurement 1 to 3, p ¼ 0.629 for measurement 1 to 3 vs. measurement 2 to 3; McNemar test). Noticeably, 25 out of 37 (67.6%) variations were recorded in the same participants.
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When a change of 0.10 in ABI values was considered as a variation, we found significant differences between measurement 1 and measurement 2 in 25 (15.5%) participants, between measurement 1 and measurement 3 in 24 (14.9%) participants and between measurement 2 and measurement 3 in 20 (12.4%) participants. Among these variations 44 of 69 (63.8%) were observed in the same subjects. Finally, for a maximum of 0.15 points variations in three measurements intra-group correlation coefficient was calculated as 0.808 for single measurements and 0.927 for mean measurements (Table 3).
Subjects with variation in ABI*, n (%)
#1 to #2 #1 to #3 #2 to #3
10 (6.2) 15 (9.3) 12 (7.5)
a Variation criterion was considered as a chance of ABI value by 0.15 or greater between two measurements.18 Mean ABI; measurement 1: 1.14 0.14, measurement 2: 1.13 0.14, measurement 3: 1.12 0.14. *25 of 37 variation events occurred in the same participants.
Table 3. Repeatability coefficients for ABI performed in three occasions. Intraclass correlation coefficients Single measurement Mean
Due to the design of the study, as the lower limit of age was considered 18 years in the inclusion criteria, the frequency of PAD was lower than that expected in a Turkish sample.19,20 A low ABI was recorded in four (2.5%) subjects in measurement 1, three (1.9%) subjects in measurement 2, and five (3.1%) subjects in measurement 3. These ratios did not differ significantly. Frequency of a high ABI (>1.3) was also similar among the three measurements; 11.8% (n ¼ 19) by measurement 1, 9.9% (n ¼ 16) by measurement 2, and 11.2% (n ¼ 18) by measurement 3.
Associates of variations in ABI
Table 2. Variation rates of 161 ABI tests repeated three times in the same individualsa. Measurements
Number of patients diagnosed with low and high ABI
0.808* 0.927**
*Coefficient regardless of the presence of an association between the values, i.e. when all values are obtained from different subjects. **Coefficient obtained when the values are intercorrelated, i.e. all three measurements were done on the same subjects.
Because almost two-third of ABI variations were detected in the same participants, we needed to explore factors contributing to this result. When subjects were categorized into CVD risk as ‘‘low’’, ‘‘moderate’’, and ‘‘high’’, we noticed that the ratio of subjects with ABI variation in the high risk category was lower than those of moderate and low risk categories between measurements 1 and 2 (Table 4). The same was also true for measurements 1 and 3 in moderate risk category. However, neither difference was significant, most probably due to small number of individuals in the low as well as moderate risk categories in the study. Waist circumference was found significantly lower in subjects with variations in ABI compared to those without (90.24 18.93 cm vs. 98.33 14.02 cm, p ¼ 0.015); however, when gender based categorizations were applied for an increased waist circumference (male; >88 cm, female; >102 cm), there was no effect of waist circumference on the outcome. Similarly, WHR was significantly lower in the group with ABI variation (0.9 0.09 vs. 0.93 0.07) (p ¼ 0.011) but a categorical analysis (WHR increased: male; >0.95, female; >0.8) revealed no significant influence on ABI variations. Among the parameters listed in Table 1, LDL-cholesterol level was different in subjects with and without ABI variations on three occasions (p ¼ 0.036) but high frequency of statin use (29.2%) precluded significance of this finding.
Table 4. Number of individuals with ABI variations across CVD risk categoriesa. Low risk
Moderate risk
High risk
Measurements
n ¼ 7/161 (4.3%)
n ¼ 29/161 (18%)
n ¼ 125/161 (77.7%)
p
#1 to #2 #1 to #3 #2 to #3
2 (28.6%) 3 (42.9%) 0
8 (27.6%) 3 (10.3%) 4 (13.8%)
15 (12.0%) 18 (14.4%) 16 (12.8%)
0.07 0.09 0.58
a
Risk categories: low: 1 major risk factor, moderate: 2 major risk factors, high: 3 major risk factors that were listed in the methods. Variation criterion was considered as a chance of ABI value by 0.15 or greater between two measurements.18
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Discussion The aim of the present study on Turkish adults was to examine the repeatability of the ABI test used for the diagnosis of PAD. Considering a cut off value of 0.9, a variation of 0.15 points might be worthy but this was not observed in more than 90% of measurements in this study, suggesting that especially values around normal ABI range (1.1 to 1.3 or 1.4) are not subject to misclassifications. Nevertheless, being aware of such a variation might help users of the test to decide on a retest when they find values around 0.90. Whether ABI measurement performed by the same observer showed a variation in the same individual on different occasions was not previously tested in such a large group. Several studies reported low rates of inter-observer errors and thus satisfactory repeatability of ABI test but the number of trials that tested this issue is limited. In an early investigation performed by Fowkes et al.,21 four inexperienced technicians performed the ABI measurements on four separate time points with 40-min and two weeks apart in a group primarily consisted of subjects with symptomatic PAD. They concluded that both ankle and arm measurements changed considerably in those subjects with PAD. High variation rates (16%) in their patients with PAD were particularly important because the test is used primarily to detect this group of people. In another study that included repeated ABI measurements performed by seven different observers with various experience levels on 19 patients with critical limb ischemia, 16% of all measurements showed a variation of 0.15 units or more.22 Jeelani et al. reported that ABI values measured by two different observers displayed a borderline error of 20%.23 When ABI taken on six patients by two experienced and 24 less experienced observers were compared, total intra-observer variability was found 11.8%, whereas inter-observer variability ranged between 7.3% and 12%.24 In another study, measurements done by the nurse, family physicians and cardiovascular surgeons displayed a non-significant an error of 8%, intra-observer variability on the same patients with 10-min intervals was also not significant (9%).12 Nevertheless, almost equal rates of inter- and intra-observer variations around 10% in that study were noteworthy, suggesting a repeated test may be needed at least for some individuals. Indeed, positive predictive value of ABI
