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Relation of Obstructive Sleep Apnea to Coronary Artery Calcium in Non-Obese Versus Obese Men and Women Aged 45–75 Years

Published:September 14, 2014DOI:https://doi.org/10.1016/j.amjcard.2014.08.040

      Highlights

      • Greater sleep apnea severity is associated with CAC.
      • This association may exist primarily in nonobese subjects.
      • Treatment of sleep apnea may be important for attenuating atherosclerotic progression.
      Sleep apnea and obesity are strongly associated, and both increase the risk for coronary artery disease. Several cross-sectional studies have reported discrepant results regarding the role obesity plays in the relation between sleep apnea and coronary artery calcium (CAC), a marker of subclinical coronary disease. The aim of the present study was to investigate the association between sleep apnea and the presence of CAC in a community cohort of middle-aged men and women without preexisting cardiovascular disease, stratified by body mass index (<30 vs ≥30 kg/m2). Participants underwent electron-beam computed tomography to measure CAC and underwent home sleep testing for sleep apnea. The presence of CAC was defined as an Agatston score >0. Sleep apnea was analyzed categorically using the apnea-hypopnea index. The sample was composed of primarily men (61%) and Caucasians (56%), with a mean age of 61 years. The prevalence of CAC was 76%. In participants with body mass indexes <30 kg/m2 (n = 139), apnea-hypopnea index ≥15 (vs <5) was associated with 2.7-fold odds of having CAC, but the effect only approached significance. Conversely, in participants with body mass indexes ≥30 kg/m2, sleep apnea was not independently associated with CAC. In conclusion, sleep apnea is independently associated with early atherosclerotic plaque burden in nonobese patients.
      In the present study, we investigated the association of sleep apnea and subclinical coronary atherosclerosis as defined by coronary artery calcium (CAC) scoring in a community cohort of middle-aged men and women without preexisting cardiovascular disease. We anticipated that the association between sleep apnea and CAC would be masked or minimized by the presence of obesity given the known effects of obesity on coronary atherosclerotic burden.
      • Kramer C.K.
      • von Mühlen D.
      • Gross J.L.
      • Barrett-Connor E.
      A prospective study of abdominal obesity and coronary artery calcium progression in older adults.
      • Reis J.P.
      • Loria C.M.
      • Lewis C.E.
      • Powell-Wiley T.M.
      • Wei G.S.
      • Carr J.J.
      • Terry J.G.
      • Liu K.
      Association between duration of overall and abdominal obesity beginning in young adulthood and coronary artery calcification in middle age.
      Data were stratified by body mass index (BMI) (<30 vs ≥30 kg/m2). We hypothesized that the effect of sleep apnea on CAC presence would be stronger in nonobese relative to obese participants.

      Methods

      Participants were recruited from a prospective, community-based cohort study, Heart Strategies Concentrating on Risk Evaluation (Heart SCORE), designed to investigate racial disparities in cardiovascular risk in 2,000 participants.
      • Aiyer A.N.
      • Kip K.E.
      • Marroquin O.C.
      • Mulukutla S.R.
      • Edmundowicz D.
      • Reis S.E.
      Racial differences in coronary artery calcification are not attributed to differences in lipoprotein particle sizes: the Heart Strategies Concentrating on Risk Evaluation (Heart SCORE) study.
      Heart SCORE eligibility criteria included age 45 to 75 years, residence in the greater Pittsburgh metropolitan area, ability to undergo baseline and annual follow-up visits, and absence of a known co-morbidities expected to limit life expectancy to <5 years. Participants were classified into 1 of 3 groups: preexisting cardiovascular disease (previous myocardial infarction, coronary revascularization, or stroke), moderate or high (>10%) probability of a cardiovascular disease event in the next 10 years, or low probability of cardiovascular disease events on the basis of Framingham risk score profiles.
      • Anderson K.M.
      • Wolson P.
      • Odell P.M.
      • Kannel W.B.
      An updated coronary risk profile: a statement for health professionals.
      For the present analysis, we examined baseline data and excluded participants with preexisting cardiovascular disease and/or missing data on cardiovascular risk factors. Electron-beam computed tomography and home sleep testing for sleep apnea were not performed on all participants, so CAC and sleep apnea data were available for a total of 324 participants. We included participants who underwent electron-beam computed tomography and home sleep testing within 24 months of each other (n = 276) and excluded participants who had changes in BMI of ±2 kg/m2 within the period between electron-beam computed tomography and home sleep testing assessments (n = 24), to account for potentially altered CAC profiles. The final sample for the present analysis included 252 participants. The present analysis had greater proportions of men and subjects with diabetes and/or hypertension compared with the Heart SCORE population. The Heart SCORE protocol was approved by the institutional review board at the University of Pittsburgh Medical Center, and all participants provided written informed consent.
      During the baseline visit, detailed demographic and medical histories were collected. Height and weight were measured to calculate BMI. The medical history inquired about histories of previously diagnosed hypertension, hyperlipidemia, and diabetes mellitus, as well as current medications. Rest blood pressure measurement was based on the average of 2 seated blood pressure measurements by trained nurses. Laboratory assessment of lipoprotein levels were performed on venous blood drawn in the fasting state. Age, gender, race and ethnicity, and smoking status (current or past smoker, yes or no) were self-reported.
      Dyslipidemia was defined as high-density lipoprotein cholesterol ≤40 mg/dl, total cholesterol ≥200 mg/dl, or self-reported treatment for dyslipidemia. Hypertension was defined as diastolic blood pressure ≥90 mm Hg and/or systolic blood pressure ≥140 mm Hg, or self-reported use of antihypertensive medication. Diabetes was defined as a self-reported diagnosis, current use of antidiabetic medication, or fasting glucose ≥110 mg/dl.
      Sleep apnea was assessed with a previously validated portable monitor that measures airflow and snoring by a nasal pressure signal (ApneaLink; ResMed Corp, San Diego, California).
      • Oktay B.
      • Rice T.B.
      • Atwood Jr., C.W.
      • Passero Jr., M.
      • Gupta N.
      • Givelber R.
      • Drumheller O.J.
      • Houck P.
      • Gordon N.
      • Strollo P.J.
      Evaluation of a single-channel portable monitor for the diagnosis of obstructive sleep apnea.
      An apnea was defined as a decrease in airflow of ≥80% from baseline for ≥10 seconds. A hypopnea was defined as a decrease in airflow of >30% to <80% from baseline for ≥10 seconds. Sleep apnea was analyzed categorically using the apnea-hypopnea index (AHI): 0 to 4, 5 to 14, and ≥15 events/hour.
      Electron-beam computed tomographic image acquisition was performed with an Imatron C150 scanner (GE Imatron Inc., South San Francisco, California). To evaluate the coronary arteries, 30 to 40 contiguous 3-mm-thick transverse images were obtained from the level of the aortic root to the apex of the heart during maximal breath holding. Images were acquired by using electrocardiographic triggering (80% of the RR interval) of 100-ms exposure during the same phase of the cardiac cycle. Calcium scores were calculated by the Agatston method, on the basis of the detection of ≥3 contiguous pixels >130 Hounsfield units.
      • Agatston A.S.
      • Janowitz W.R.
      • Hildner F.J.
      • Zusmer N.R.
      • Viamonte Jr., M.
      • Detrano R.
      Quantification of coronary artery calcium using ultrafast computed tomography.
      Presence of CAC was defined as an Agatston score >0.
      Differences in demographic characteristics were compared among the 3 sleep apnea groups (AHI <5, 5 to 14, and ≥15) using chi-square tests for categorical variables and analysis of variance with post hoc comparison for continuous variable. The nonparametric Kruskal-Wallis test was used to compare the median values of CAC scores among the sleep apnea groups. Frequencies of the presence of CAC were calculated among the 3 groups in the overall population and within nonobese and obese (BMI <30 vs ≥30 kg/m2). Multivariate logistic regression controlling for age, gender, race and ethnicity (Caucasian and other vs African-American), smoking status, diabetes, hypertension, dyslipidemia, and BMI was used to calculate the odds ratio of the presence of CAC among subjects with no sleep apnea (AHI <5 [the reference group]), mild sleep apnea (AHI 5 to 14), and moderate to severe sleep apnea (AHI ≥15). SPSS for Windows version 20 (SPSS, Inc., Chicago, Illinois) was used for all statistical analyses.

      Results

      Demographic and clinical characteristics of the sample are listed in Table 1. The prevalence of CAC in the total sample was 75%. The frequency of CAC presence increased with the severity of sleep apnea (chi-square = 6.54, p <0.05; Figure 1). In analysis adjusted for age, gender, race and ethnicity, smoking status, diabetes, hypertension, and dyslipidemia, the odds ratio for the presence of CAC was 2.33 (95% confidence interval 1.01 to 5.38) for participants with AHIs ≥15 compared with those with AHIs <5 (p <0.05; Table 2). The association was no longer significant after adjusting for BMI. No significant difference in presence of CAC was found between those with AHIs of 5 to 14 and those with AHIs <5.
      Table 1Demographic and clinical characteristics by apnea hypopnea index and in overall sample
      VariableApnea Hypopnea IndexTotal

      sample

      (N = 252)
      p-value
      P values based on Pearson χ2 test and analysis of variance.
      < 5

      (n = 61)
      5-14

      (n = 97)
      ≥ 15

      (n = 94)
      Age, mean (SD) (years)59.1 ± 7.860.9 ± 7.662.0 ± 6.560.9 ± 7.30.05
       Male29 (48%)48 (49%)64 (68%)141 (56%)0.008
       Female32 (52%)49 (51%)30 (32%)111 (44%)
       European American29 (52%)66 (68%)59 (63%)156 (62%)0.84
       African American32 (48%)31 (32%)35 (37%)96 (38%)
      BMI, mean (SD) (kg/m2)29.0 ± 5.829.9 ± 4.530.4 ± 5.029.9 ± 5.00.26
      AHI, mean (SD)2.7 ± 1.19.0 ± 2.726.9 ± 12.314.1 ± 12.7
      Current/past smoker33 (54%)60 (62%)46 (49%)137 (55%)0.19
      Diabetes Mellitus10 (16%)22 (23%)19 (20%)50 (20%)0.63
      Prehypertension13 (21%)19 (20%)18 (19%)50 (20%)0.94
      Hypertension
      Hypertension was defined as diastolic blood pressure ≥ 90 mm Hg and/or systolic blood pressure ≥ 140 mm Hg, or self-reported usage of antihypertensive medication.
      43 (71%)65 (67%)71 (75%)179 (71%)0.53
      Dyslipidemia
      Dyslipidemia was defined as having blood lipid concentrations within the following parameters, HDL cholesterol ≤ 40 mg/dL, total cholesterol ≥ 200 mg/dL, or self-reported treatment for dyslipidemia.
      45 (77%)81 (83%)65 (69%)192 (76%)0.10
      CAC score, median (range)18.3 (0 – 786)18.1 (0 – 1359)64.2 (0 – 1115)38.5 (0 – 1359)0.01
      P value based on Kruskall-Wallis test.
      AHI = apnea hypopnea-index; BMI = body mass index; CAC, coronary artery calcium.
      P values based on Pearson χ2 test and analysis of variance.
      P value based on Kruskall-Wallis test.
      Hypertension was defined as diastolic blood pressure ≥ 90 mm Hg and/or systolic blood pressure ≥ 140 mm Hg, or self-reported usage of antihypertensive medication.
      § Dyslipidemia was defined as having blood lipid concentrations within the following parameters, HDL cholesterol ≤ 40 mg/dL, total cholesterol ≥ 200 mg/dL, or self-reported treatment for dyslipidemia.
      Figure thumbnail gr1
      Figure 1Percentage of participants with CAC by AHI in the overall sample and stratified by BMI.
      Table 2Logistic regression analysis of adjusted odds ratios of coronary artery calcium in relation to apnea hypopnea index in the total sample and stratified by body mass index
      AHI Score (compared to < 5)OR95% CIp-value
      Adjusted for age, gender, race/ethnicity, smoking status, diabetes, hypertension, and dyslipidemia
      Total Sample (n = 252)5-140.97(0.46 – 2.06)0.94
      ≥ 152.33(1.01 – 5.38)0.04
      AHI Score (compared to < 5)OR95% CIp-value
      Adjusted for above covariates + BMI
      Total Sample (n = 252)5-140.72(0.33 – 1.61)0.43
      ≥ 151.71(0.71 – 4.13)0.23
      AHI Score (compared to < 5)OR
      Adjusted for age, gender, race/ethnicity, smoking status, diabetes, hypertension, and dyslipidemia.
      95% CIp-value
      BMI < 30 (n = 139)5-141.12(0.40 – 3.14)0.83
      ≥ 152.70(0.88 – 8.33)0.08
      AHI Score (compared to < 5)OR
      Adjusted for age, gender, race/ethnicity, smoking status, diabetes, hypertension, and dyslipidemia.
      95% CIp-value
      BMI ≥ 30 (n = 113)5-140.29(0.05 – 1.62)0.16
      ≥ 150.73(0.12 – 4.48)0.74
      AHI = apnea-hypopnea index; BMI = body mass index; CI = confidence interval; OR = odds ratio.
      Adjusted for age, gender, race/ethnicity, smoking status, diabetes, hypertension, and dyslipidemia.
      The percentage of participants with CAC increased with sleep apnea severity among those with BMIs <30 kg/m2 (chi-square = 6.77, p <0.05; Figure 1). Specifically, among those with BMIs <30 kg/m2, 53% of participants with AHIs <5, 66% of those with AHIs of 5 to 14, and 79% of those with AHIs ≥30 had evidence of CAC. Among those with BMIs ≥30 kg/m2, there was no significant difference in the percentage of participants with CAC among the 3 AHI groups (<5, 5 to 14, and ≥30) (Figure 1). There were similar trends among men and women (data not shown). Consistent results were observed in logistic regression analyses adjusted for age, gender, race and ethnicity, smoking status, diabetes, hypertension, and dyslipidemia. Among 113 participants with BMIs ≥30 kg/m2, AHI was not independently associated with CAC (Table 2). Conversely, among 139 participants with BMIs <30 kg/m2, AHI ≥15 (vs AHI <5) was associated with 2.7-fold odds of having CAC (adjusted odds ratio 2.70, 95% confidence interval 0.88 to 8.33, p = 0.08), but the effect only approached conventional level of statistical significance. The formal test of interaction between BMI (dichotomous) and AHI ≥15 in relation to CAC presence was not statistically significant (p = 0.13).

      Discussion

      In this community cohort of middle-aged adults without preexisting cardiovascular disease, we found an AHI ≥15 to be associated with 2.3-fold odds of having CAC compared with an AHI <5; however, adjustment for cardiovascular risk factors and BMI reduced the strength of the association to nonsignificant levels. No difference in CAC presence was found between AHI of 5 to 14 and AHI <5. In analyses stratified by BMI, no significant association between AHI severity and presence of CAC was found among obese (BMI ≥30 kg/m2) subjects. Conversely, among nonobese subjects, those with AHIs ≥15 had 2.7-fold odds of having CAC compared with no sleep apnea after adjustment for cardiovascular risk factors and BMI, but the effect only approached statistical significance. Our sample was composed primarily of participants with mild sleep apnea, thus a sample enriched with more severe sleep apnea may have revealed a stronger effect. Nevertheless, these findings suggest that sleep apnea, in particular moderate to severe sleep apnea (AHI ≥15), is independently associated with subclinical coronary atherosclerosis among nonobese subjects.
      Sleep apnea and obesity often coexist,
      • Daltro C.
      • Gregorio P.B.
      • Alves E.
      • Abreu M.
      • Bomfim D.
      • Chicourel M.H.
      • Araújo L.
      • Cotrim H.P.
      Prevalence and severity of sleep apnea in a group of morbidly obese patients.
      • Resta O.
      • Foschino-Barbaro M.
      • Legari G.
      • Talamo S.
      • Bonfitto P.
      • Palumbo A.
      • Minenna A.
      • Giorgino R.
      • De Pergola G.
      Sleep-related breathing disorders, loud snoring and excessive daytime sleepiness in obese subjects.
      and each is strongly associated with cardiovascular disease, including the development of coronary artery disease.
      • Shahar E.
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      • Redline S.
      • Lee E.T.
      • Newman A.B.
      • Javier Nieto F.
      • O’Connor G.T.
      • Boland L.L.
      • Schwartz J.E.
      • Samet J.M.
      Sleep-disordered breathing and cardiovascular disease: cross-sectional results of the Sleep Heart Health Study.
      • Hubert H.B.
      • Feinleib M.
      • McNamara P.M.
      • Castelli W.P.
      Obesity as an independent risk factor for cardiovascular disease: a 26-year follow-up of participants in the Framingham Heart Study.
      Obesity has been identified as an independent risk factor for atherosclerosis.
      • Kramer C.K.
      • von Mühlen D.
      • Gross J.L.
      • Barrett-Connor E.
      A prospective study of abdominal obesity and coronary artery calcium progression in older adults.
      • Kronmal R.A.
      • McClelland R.L.
      • Detrano R.
      • Shea S.
      • Lima J.A.
      • Cushman M.
      • Bild D.E.
      • Burke G.L.
      Risk factors for the progression of coronary artery calcification in asymptomatic subjects results from the Multi-Ethnic Study of Atherosclerosis (MESA).
      • Lee C.D.
      • Jacobs D.R.
      • Schreiner P.J.
      • Iribarren C.
      • Hankinson A.
      Abdominal obesity and coronary artery calcification in young adults: the Coronary Artery Risk Development in Young Adults (CARDIA) Study.
      A randomized trial evaluating the effects of 4 months of continuous positive airway pressure therapy on early markers of atherosclerosis found a decrease in intima-media thickness, which was associated with reductions in C-reactive protein and catecholamines, suggesting that sleep apnea is an independent risk factor for atherosclerosis.
      • Drager L.F.
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      • Figueiredo A.C.
      • Krieger E.M.
      • Lorenzi-Filho G.
      Effects of continuous positive airway pressure on early signs of atherosclerosis in obstructive sleep apnea.
      Given that obesity and sleep apnea have similar cardiovascular consequences, it is important to explore whether the effect of sleep apnea on atherosclerotic burden may be masked or minimized by obesity. Results from previous community-based studies examining the association between sleep apnea and subclinical coronary atherosclerosis, as measured by CAC, are similar to our findings showing no association between AHI severity and CAC after adjustment for BMI.
      • Kim S.
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      • Kim J.
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      • Lee J.
      • Lim H.
      • Lim S.
      • Park J.
      • Shin C.
      Association of coronary artery calcification with obstructive sleep apnea and obesity in middle-aged men.
      • Matthews K.A.
      • Strollo P.J.
      • Hall M.
      • Mezick E.J.
      • Kamarck T.W.
      • Owens J.F.
      • Buysse D.J.
      • Reis S.E.
      Associations of Framingham risk score profile and coronary artery calcification with sleep characteristics in middle-aged men and women: Pittsburgh SleepSCORE study.
      In a population-based cohort of 258 Korean men and a community sample of 224 middle-aged men and women, higher AHI was associated with having any measureable CAC; however, adjustment for BMI reduced the strength of the associations to nonsignificant levels.
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      • Cho G.-Y.
      • Baik I.
      • Kim J.
      • Kim S.
      • Lee J.
      • Lim H.
      • Lim S.
      • Park J.
      • Shin C.
      Association of coronary artery calcification with obstructive sleep apnea and obesity in middle-aged men.
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      • Mezick E.J.
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      • Owens J.F.
      • Buysse D.J.
      • Reis S.E.
      Associations of Framingham risk score profile and coronary artery calcification with sleep characteristics in middle-aged men and women: Pittsburgh SleepSCORE study.
      Conversely, in patients with suspected sleep disorders, more severe sleep apnea was associated with CAC after controlling for BMI.
      • Sorajja D.
      • Gami A.S.
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      • Behrenbeck T.R.
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      • Lopez-Jimenez F.
      Independent association between obstructive sleep apnea and subclinical coronary artery disease.
      • Arik B.
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      • Ege M.R.
      • Dogan O.T.
      • Zorlu A.
      Advanced age and apnea-hypopnea index predict subclinical atherosclerosis in patients with obstructive sleep apnea syndrome.
      We extended previous investigations by stratifying our sample by BMI (<30 vs ≥30 kg/m2). Moderate to severe sleep apnea was independently associated with greater odds of having CAC but only among nonobese participants, suggesting that obesity is a confounder of the association between sleep apnea and subclinical coronary atherosclerosis.
      Pathogenic mechanisms linking sleep apnea to atherosclerosis have been proposed.
      • Drager L.F.
      • Polotsky V.Y.
      • Lorenzi-Filho G.
      Obstructive sleep apnea: an emerging risk factor for atherosclerosis.
      Inflammation is one possible mechanism underlying the proatherogenic effects of sleep apnea. More specifically, C-reactive protein, a serum maker of systemic inflammation, plays a direct role in the manifestation of atherosclerosis
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      • Boekholdt S.M.
      • Vergeer M.
      • Stroes E.S.
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      C-reactive protein is a mediator of cardiovascular disease.
      • Zwaka T.P.
      • Hombach V.
      • Torzewski J.
      C-reactive protein–mediated low density lipoprotein uptake by macrophages implications for atherosclerosis.
      and is elevated in those with sleep apnea independent of BMI
      • Shamsuzzaman A.S.
      • Winnicki M.
      • Lanfranchi P.
      • Wolk R.
      • Kara T.
      • Accurso V.
      • Somers V.K.
      Elevated C-reactive protein in patients with obstructive sleep apnea.
      and visceral obesity.
      • Lui M.M.
      • Lam J.C.
      • Mak H.K.
      • Xu A.
      • Ooi C.
      • Lam D.C.
      • Mak J.C.
      • Khong P.L.
      • Ip M.S.
      C-reactive protein is associated with obstructive sleep apnea independent of visceral obesity.
      Other possible mechanisms associated with sleep apnea that may contribute to the progression of atherosclerosis include increased oxidative stress,
      • Lavie L.
      Obstructive sleep apnoea syndrome–an oxidative stress disorder.
      endothelial dysfunction,
      • Ip M.S.
      • Tse H.F.
      • Lam B.
      • Tsang K.W.
      • Lam W.K.
      Endothelial function in obstructive sleep apnea and response to treatment.
      • Kato M.
      • Roberts-Thomson P.
      • Phillips B.G.
      • Haynes W.G.
      • Winnicki M.
      • Accurso V.
      • Somers V.K.
      Impairment of endothelium-dependent vasodilation of resistance vessels in patients with obstructive sleep apnea.
      and sustained sympathetic nerve activity due to decreased baroreflex-mediated suppression of chemoreceptor-mediated sympathoexcitation.
      • Abboud F.
      • Kumar R.
      Obstructive sleep apnea and insight into mechanisms of sympathetic overactivity.
      Sleep apnea could also contribute to atherosclerosis indirectly, by causing insulin resistance due to elevated leptin levels
      • Ip M.S.
      • Lam K.S.
      • Ho C.
      • Tsang K.W.
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      and dyslipidemia.
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      • Jun J.
      • Polotsky V.Y.
      Obstructive sleep apnea and dyslipidemia: implications for atherosclerosis.
      Study limitations include the cross-sectional study design, which precludes causal relations between sleep apnea and subclinical coronary atherosclerosis, and slight differences in gender distribution and rates of diabetes and hypertension between the present study population and the Heart SCORE cohort. AHI was assessed using a single-channel portable monitor (ApneaLink) instead of polysomnography. However, the portable monitor we used has been previously validated with acceptable performance to identify obstructive sleep apnea.
      • Oktay B.
      • Rice T.B.
      • Atwood Jr., C.W.
      • Passero Jr., M.
      • Gupta N.
      • Givelber R.
      • Drumheller O.J.
      • Houck P.
      • Gordon N.
      • Strollo P.J.
      Evaluation of a single-channel portable monitor for the diagnosis of obstructive sleep apnea.
      • Ayappa I.
      • Norman R.G.
      • Suryadevara M.
      • Rapoport D.M.
      Comparison of limited monitoring using a nasal-cannula flow signal to full polysomnography in sleep-disordered breathing.
      • Erman M.K.
      • Stewart D.
      • Einhorn D.
      • Gordon N.
      • Casal E.
      Validation of the ApneaLink™ for the screening of sleep apnea: a novel and simple single-channel recording device.
      There was a low prevalence of severe sleep apnea (AHI ≥30; n = 25) in our sample.

      Disclosures

      Dr. Strollo has received research support from ResMed Corp, Philips-Respironics, ResMed Foundation, Inspire Medical, and the National Football League. Dr. Strollo has served as a paid consultant for Apnicure and PimMed.

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      Linked Article

      • Obstructive Sleep Apnea and Coronary Artery Calcium With Special Emphasis on Obesity
        American Journal of CardiologyVol. 116Issue 10
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          Luyster et al investigated the association between obstructive sleep apnea (OSA) and the presence of coronary artery calcium (CAC) in inhabitants with a mean age of 61 years without cardiovascular disease, stratified by body mass index (BMI).1 Obesity is a risk factor of sleep apnea, and CAC is a marker of subclinical coronary disease. The presence of CAC was defined as an Agatston score >0, and adjusted odds ratios (ORs; 95% confidence intervals [CIs]) of apnea–hypopnea index (AHI) ≥15 for the presence of CAC was 2.33 (1.01 to 5.38) and 1.71 (0.71 to 4.13) by excluding and including BMI as an adjusting variable, respectively.
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      • The Arduous Task of Differentiating Takotsubo Syndrome from Myocardial Infarction With Normal Coronary Arteries
        American Journal of CardiologyVol. 116Issue 10
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          I read the study by Daniel et al,1 published online ahead of print on June 25, 2015, in the AJC, about a series of 100 patients with a myocardial infarction with angiographically normal coronary arteries (MINCA), 25 of whom had been diagnosed as having takotsubo syndrome (TTS), as per the Mayo Clinic criteria. The investigators have focused on the risk factors and markers of the patients with MINCA, a cohort of 100 patients with myocardial infarction and coronary heart disease, and 100 subjects considered as normal controls.
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