466
Letters to the Editor
Obstructive sleep apnea and risk of stroke: A meta-analysis of prospective studies Min Li, Wen-Shang Hou, Xiao-Wei Zhang, Zhen-Yu Tang ⁎ Department of Neurology, The Second Affiliated Hospital, School of Medicine, Nanchang University, Nanchang 330006, Jiangxi Province, China
a r t i c l e
i n f o
Article history: Received 3 December 2013 Accepted 30 December 2013 Available online 10 January 2014 Keywords: Obstructive sleep apnea Stroke Meta-analysis
Stroke is the second leading cause of death worldwide [1]. 78% of strokes are first attacks [2], and about 780,000 Americans experience a new or recurrent stroke each year, on average, one stroke every 40 s [3]. Any possible means to prevent stroke should, therefore, be a key public health priority. Obesity is one of the leading risk factors for stroke and a target for stroke prevention [4,5]. Interestingly, human observational studies strongly suggest that obesity is the most important risk factor for obstructive sleep apnea (OSA), which is characterized by repeated obstructions of the upper airway during sleep which result in oxygen desaturations and alterations in blood pressure and cerebral blood flow [6]. Whether OSA independently increases stroke incidences, or whether this relationship is confounded by this population's prevalent cardiovascular risk factors, remains debated. The latest published metaanalysis of 12 prospective cohort studies showed a significant positive association between OSA and fatal and non-fatal stroke (pooled relative risk = 2.15, 95% confidence interval: 1.42–3.24) [7]. However, that meta-analysis found insufficient evidence in the subgroup meta-analyses by type of prevention, study design, geographical area, duration of follow-up, and methodological quality. Therefore, we carried out a meta-analysis of cohort studies to systematically identify whether OSA independently increases the risk of fatal or non-fatal stroke. We followed standard criteria for the performing and reporting of the meta-analyses of observational studies [8]. A systematic search of published articles (through 26 September 2013) was performed by using electronic databases including PubMed, Cochrane Library, and ISI Web of Science databases. We used the following keywords: sleep disordered breathing, obstructive sleep apnea, OSA, sleep apnea, stroke, cerebral infarction, cerebrovascular disease, hemorrhage, cardiovascular disease, coronary artery disease, prospective study, cohort study, and follow-up study. There were no language restrictions. Studies were included for the metaanalysis if they fulfilled the following criteria: (1) the study of adult patients had a community-based or population-based or clinicbased, prospective cohort design; (2) the exposed population was patients with OSA; (3) reported quantitative estimates of the multivariate-adjusted relative risk (RRs) and 95% confidence intervals (CIs) for stroke associated with OSA, hazard ratio/odds ratios were considered equivalent to RRs; and (4) longer than
⁎ Corresponding author at: Department of Neurology, The Second Affiliated Hospital, Nanchang University, No. 1, Minde Road, Nanchang 330006, Jiangxi, People's Republic of China. Tel.: + 86 791 86311759; fax: +86 791 86292217. E-mail address: [email protected] (Z.-Y. Tang).
1 year of follow-up. Studies were excluded if they fulfilled the following criteria: (1) the study design was a nonprospective cohort (for example, cross-sectional and retrospective case–control studies); (2) unadjusted RRs and 95% CIs were reported; and (3) shorter than 1 year of follow-up. The Newcastle–Ottawa Scale (NOS) was used to assess the quality of studies [9]. A maximum of 9 points can be given for each study in the categories of selection, outcome, and comparability. We defined studies of high or low quality based on the median overall score among all studies. The RRs were pooled using the random-effects model [10]. All the statistical analyses were performed in Stata 11 (StataCorp LP, College Station, TX). P values were 2-sided and p b 0.05 was considered statistically significant. Ten cohort studies met the inclusion criteria [11–20] (Fig. 1). The main characteristics of studies in the meta-analysis were presented in Tables 1A and 1B. A total of eleven comparisons (one study did have sex specific data) investigated the association between OSA and risk of stroke. The ascertainment of stroke, duration of follow up, study design, assessment of OSA, and methodological quality varied across studies. Pooling all 11 comparisons, OSA was associated with a significantly increased risk of fatal or non-fatal stroke (RR, 2.10; 95% CI, 1.50 to 2.93; p = 0.000) (Fig. 2). Fig. 3 showed the pooled RR for stroke stratified by history of stroke, study design, geographical area, duration of follow-up, and methodological quality. The RR for primary prevention studies was 2.06 (95% CI 1.53–2.79; p = 0.000). Increases in stroke events were also found in the subgroup of study design (clinic-based study: RR 2.44, 95% CI 1.24– 4.80, p = 0.010; and population-based study: RR 2.13, 95% CI 1.45– 3.13, p = 0.000, respectively). In addition, we found significant
Fig. 1. Flow chart of study selection. OSA: obstructive sleep apnea.
Letters to the Editor
467
Table 1A Characteristic of included cohort studies. First author, publication (year)
Study design
Mooe et al. (2001) [11] Arzt et al. (2005) [12]
Clinic-based Population-based
Country/ population
Participants (% male)
Sweden/European 408 patients with CAD (68) United States 1189 participants with no history of stroke (55) Yaggi et al. (2005) [13] Clinic-based United States 1022 patients with no history of stroke (71) Elwood et al. (2006) [14] Population-based United States 1986 men with no history of stroke (100) Munoz et al. (2006) [15] Population-based Spain/European 394 subjects with no history of stroke (57) Valham et al. (2008) [16] Clinic-based Sweden/European 392 patients with CAD (67) Redline et al. (2010) [17] Community-based United States 5422 participants with no history of stroke (45) Yeboah et al. (2011) [18] Community-based United States 5338 participants with no history of stroke (50) Hudgel et al. (2012) [19] Clinic-based United States 1519 participants (62) Martinez-Garcia et al. (2012) [20] Clinic-based Spain/European 939 participants (64)
Age rang or mean Follow-up duration OSA assessment (year) (year) (method) ≤70 30–60
Median 5.1 4
PSG PSG
≥50
3.4
PSG
55–69
10
Self-reports
70–100
6
PSG
≤70 ≥40
10 Mean 8.7
PSG PSG
45–84
Mean 7.5
Self-reports
≥18 ≥65
Median 6.3 Median 5.8
PSG PSG
OSA: obstructive sleep apnea; CAD: coronary artery disease; PSG: polysomnography.
Table 1B Characteristic of included cohort studies. First author, publication (yr) Stroke ascertainment
No. of stroke cases
Adjustment for confounders
Mooe et al. (2001) [11]
33
Age, sex, BMI, HTN, diabetes, LVD, and CI AHI ≥ 10 vs AHI b 10, RR, 2.98 (1.43–6.20) Age, sex, BMI AHI ≥ 20 vs AHI b 5, RR, 3.08 (0.74–12.81) Age, sex, race, smoking, alcohol, BMI, DM, AHI N 36 vs AHI b 3, RR, 3.30 hyperlipidemia, AF, and HTN (1.74–6.26)
6
Age, social class, smoking, alcohol, BMI, and neck circumference Sex
Yes vs no, RR, 1.97 (1.26–3.09)
6
AHI ≥ 30 vs AHI b 30, RR, 2.52 (1.04–6.10) AHI ≥ 15 vs AHI b 5, RR, 3.56 (1.56–8.16) AHI N 19 vs AHI b 4, RR (men), 2.86 (1.10–7.39); (women), 1.21 (0.65–2.24)
7
Arzt et al. (2005) [12] Yaggi et al. (2005) [13]
Elwood et al. (2006) [14] Munoz et al. (2006) [15] Valham et al. (2008) [16] Redline et al. (2010) [17]
Yeboah et al. (2011) [18]
Any type of stroke based on WHO definition Any type of stroke based on selfreported and physician-diagnosed Any type of stroke based on mailed questionnaire of telephone contacting patients or relatives Ischaemic stroke based on ICD 10 codes Ischemic stroke based on ICD 9 codes and medical records Any type of stroke based on ICD 9 and ICD 10 codes Ischemic stroke based on death certificates, hospital discharge information and mailings to participants Any type of stroke based on medical records, death certificates, contacting participants
14 88 (stroke or death) 107 (ischemic) 20 (ischemic) 47 193 (ischemic)
76
Hudgel et al. (2012) [19]
Any type of stroke based on medical 72 records and physician notes Martinez-Garcia et al. (2012) Any type of stroke based on medical 28 [20] records and physician diagnosis
Age, BMI, gender, LVF, CAI, DM, HTN, previous stroke/TIA, AF, current smoking Age, BMI, smoking, SBP, use of antihypertensive medications, DM, and race
Age, sex, BMI, race/ethnicity, smoking, DM, total and HDL-C, TC, SBP, BP medication use, statin use, benzodiazepine use, alcohol Age, BMI, sex, HTN, CVA, MI, CHF
Results
Study quality
5 7
7 9
Yes vs no, RR, 1.15 (0.36–3.74)
8
AHI ≥ 30 vs AHI b 5, RR, 0.73 (0.36–1.46) Age, sex, type of sleep study, sleep clinic, AHI ≥ 30 vs AHI b 15, RR, 4.63 BMI, DM, smoking, ESS, dyslipidemia, (1.03–20.81) cardiovascular events, HTN
7 7
WHO: World Health Organization; HTN: hypertension; BMI: body mass index; DM: diabetes mellitus; AHI: apnea–hypopnea index; MI: myocardial infarction; HDL-C: high-density lipoprotein cholesterol; TC: total cholesterol; SBP: systolic blood pressure; BP: blood pressure; LVF: left ventricular function; AF: atrial fibrillation; TIA: transient ischemic attack; ICD: international classification of disease; ESS: Epworth Sleepiness Scale; CI: coronary intervention; LVD: left ventricular dysfunction; CAI: coronary artery intervention; CVA: cerebral vascular accident; CHF: congestive heart failure.
associations in the overall subgroup meta-analysis by geographical area (United States or Europe), duration of follow-up (≥ 5 years or b5 years), method for OSA assessment (PSG or Non-PSG), and methodological quality (≥ 7 or b7). Our meta-analysis of 10 cohort studies found a significant association between OSA and the risk of fatal or non-fatal stroke after adjustment of established cardiovascular risk factors. For the moment, the mechanisms underlying the increase of consequent stroke events in OSA patients are not well understood. Results in endothelial dysfunction pathways, including intermittent hypoxia, intrathoracic pressure swings, and recurrent arousals, may link the
development of atherosclerosis with the pathogenesis of stroke event [21]. To efficiently assess the efficacy and causality of OSA on stroke, future clinical trials should be done among the general or base on clinic subjects and individuals without a history of stroke. ZYT and ML conceived and designed the experiments. WSH, ML and XWZ analyzed the data. ML and ZYT wrote the paper. WSH, XWZ and ZYT performed the literature search and the data extraction. All authors saw and approved the final version of the manuscript. We thank the editors of the International Journal of Cardiology for editing the manuscript.
468
Letters to the Editor
Study
RR (95% CI)
Mooe (2001)
2.98 (1.43, 6.20)
Arzt (2005)
3.08 (0.74, 12.81)
Yaggi (2005)
3.30 (1.74, 6.26)
Elwood (2006)
1.97 (1.26, 3.09)
Munoz (2006)
2.52 (1.04, 6.10)
Valham (2008)
3.56 (1.56, 8.16)
Redline(W) (2010)
1.21 (0.65, 2.24)
Redline(M) (2010)
2.86 (1.10, 7.39)
Yeboah (2011)
1.15 (0.36, 3.74)
Hudgel (2012)
0.73 (0.36, 1.46)
Martinez-Garcia (2012)
4.63 (1.03, 20.81)
Overall (I-squared = 47.5%, p = 0.040)
2.10 (1.50, 2.93)
NOTE: Weights are from random effects analysis .05
Decreased risk
1
Increased risk
20
Fig. 2. Association between OSA and risk of stroke. OSA: obstructive sleep apnea.
Fig. 3. Analyses of subgroups relating OSA to stroke. OSA: obstructive sleep apnea; PSG: polysomnography.
Letters to the Editor
References [1] Donnan GA, Fisher M, Macleod M, et al. Stroke. Lancet 2008;371:1612–23. [2] Roger VL, Go AS, Lloyd-Jones DM, et al. Heart disease and stroke statistics—2012 update: a report from the American Heart Association. Circulation 2012;125 e2-2e220. [3] Sidney S, Rosamond WD, Howard VJ, et al. The “heart disease and stroke statistics—2013 update” and the need for a national cardiovascular surveillance system. Circulation 2013;127:21–3. [4] Metabolic mediators of the effects of body-mass index, overweight, and obesity on coronary heart disease and stroke: a pooled analysis of 97 prospective cohorts with 1.8 million participants. Lancet 2013, http://dx.doi.org/10.1016/ S0140-6736(13)61836-X. [5] Syed AM, Talbot-Smith A, Gemmell I. The use of epidemiological measures to estimate the impact of primary prevention interventions on CHD, stroke and cancer outcomes: experiences from Herefordshire, UK. J Epidemiol Global Health 2012;2:111–24. [6] Sleep-related breathing disorders in adults: recommendations for syndrome definition and measurement techniques in clinical research. The Report of an American Academy of Sleep Medicine Task Force. Sleep 1999;22:667–89. [7] Wang X, Ouyang Y, Wang Z, et al. Obstructive sleep apnea and risk of cardiovascular disease and all-cause mortality: a meta-analysis of prospective cohort studies. Int J Cardiol 2013;169:207–14. [8] Stroup DF, Berlin JA, Morton SC, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 2000;283:2008–12. [9] Stang A. Critical evaluation of the Newcastle–Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol 2010;25:603–5. [10] DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials 1986;7:177–88.
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[11] Mooe T, Franklin KA, Holmstrom K, et al. Sleep-disordered breathing and coronary artery disease: long-term prognosis. Am J Respir Crit Care Med 2001;164:1910–3. [12] Arzt M, Young T, Finn L, et al. Association of sleep-disordered breathing and the occurrence of stroke. Am J Respir Crit Care Med 2005;172:1447–51. [13] Yaggi HK, Concato J, Kernan WN, et al. Obstructive sleep apnea as a risk factor for stroke and death. N Engl J Med 2005;353:2034–41. [14] Elwood P, Hack M, Pickering J, et al. Sleep disturbance, stroke, and heart disease events: evidence from the Caerphilly cohort. J Epidemiol Community Health 2006;60:69–73. [15] Munoz R, Duran-Cantolla J, Martinez-Vila E, et al. Severe sleep apnea and risk of ischemic stroke in the elderly. Stroke 2006;37:2317–21. [16] Valham F, Mooe T, Rabben T, et al. Increased risk of stroke in patients with coronary artery disease and sleep apnea: a 10-year follow-up. Circulation 2008;118:955–60. [17] Redline S, Yenokyan G, Gottlieb DJ, et al. Obstructive sleep apnea–hypopnea and incident stroke: the sleep heart health study. Am J Respir Crit Care Med 2010;182:269–77. [18] Yeboah J, Redline S, Johnson C, et al. Association between sleep apnea, snoring, incident cardiovascular events and all-cause mortality in an adult population: MESA. Atherosclerosis 2011;219:963–8. [19] Hudgel DW, Lamerato LE, Jacobsen GR, et al. Assessment of multiple health risks in a single obstructive sleep apnea population. J Clin Sleep Med 2012;8:9–18. [20] Martinez-Garcia MA, Campos-Rodriguez F, Catalan-Serra P, et al. Cardiovascular mortality in obstructive sleep apnea in the elderly: role of long-term continuous positive airway pressure treatment: a prospective observational study. Am J Respir Crit Care Med 2012;186:909–16. [21] Kohler M, Stradling JR. Mechanisms of vascular damage in obstructive sleep apnea. Nat Rev Cardiol 2010;7:677–85.
0167-5273/$ – see front matter © 2014 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ijcard.2013.12.230
Outcomes with short-term versus long-term antiplatelet dual therapy after drugeluting stenting: Quantifying the equivalence margins Andrea Messori ⁎, Valeria Fadda, Dario Maratea, Sabrina Trippoli HTA Unit, ESTAV Toscana Centro, Regional Health Service, 50100 Firenze, Italy
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Article history: Received 21 November 2013 Accepted 30 December 2013 Available online 10 January 2014 Keywords: Antiplatelet Stenting Meta-analysis Equivalence Dual therapy
In evaluating short-term versus long-term antiplatelet dual therapy after drug-eluting stenting, the efforts of many researchers worldwide have permitted us to generate a sufficiently large body of evidence-based data. The two most recent meta-analyses in this area have been focused, respectively, on the information obtained from randomized controlled trials [1] and from all types of clinical studies [2]. While the best quality of evidence is likely to derive from the first meta-analysis, two randomized studies (namely, the RESET [3] and
⁎ Corresponding author at: ESTAV Centro, Area Vasta Centro Toscana, Regional Health System, Via San Salvi 12, 50100 Firenze, Italy. Tel.: +39 338 9513583; fax: + 39 0574 701319. E-mail addresses: [email protected], [email protected] (A. Messori).
the OPTIMIZE [4] trials) were too recent for being examined by Valgimigli and co-coworkers [1]. On the other hand, an increasing amount of evidence-based research [5] has recently been aimed at differentiating between no proof of difference (i.e. failed demonstration of superiority) and proof of no difference (demonstration of non-inferiority/equivalence or futility where futility is essentially represented by equivalence with no treatment). Clearly, proof of no difference is a much more informative result than no proof of difference; the former however requires that an equivalence (or non-inferiority margin) is incorporated in the analysis. To study the differences between short-term versus long-term antiplatelet dual therapy, we re-analyzed the meta-analytical results published by Valgimigli and co-workers [1] by incorporating the data of both the RESET [3] and the OPTIMIZE [4] trials. Then, we carried out a formal equivalence test based on confidence intervals (CIs). All of our analyses evaluated the same composite end-point originally measured in the clinical trials. Since our objective was to determine to what extent short-term and long-term dual antiplatelet therapies are equivalent regarding the incidence of the composite end-point, our analysis was carried out as a meta-analysis of equivalence [6,7]. Our design was of equivalence and not of noninferiority, mainly because the end-point was a mixture of effectiveness and safety, and so we could not exclude results in either direction. The incidences of the above-mentioned end-point were estimated by a standard (random-effect) meta-analysis in which the results were firstly expressed as risk difference (RD) and
Letters to the Editor
Obstructive sleep apnea and risk of stroke: A meta-analysis of prospective studies Min Li, Wen-Shang Hou, Xiao-Wei Zhang, Zhen-Yu Tang ⁎ Department of Neurology, The Second Affiliated Hospital, School of Medicine, Nanchang University, Nanchang 330006, Jiangxi Province, China
a r t i c l e
i n f o
Article history: Received 3 December 2013 Accepted 30 December 2013 Available online 10 January 2014 Keywords: Obstructive sleep apnea Stroke Meta-analysis
Stroke is the second leading cause of death worldwide [1]. 78% of strokes are first attacks [2], and about 780,000 Americans experience a new or recurrent stroke each year, on average, one stroke every 40 s [3]. Any possible means to prevent stroke should, therefore, be a key public health priority. Obesity is one of the leading risk factors for stroke and a target for stroke prevention [4,5]. Interestingly, human observational studies strongly suggest that obesity is the most important risk factor for obstructive sleep apnea (OSA), which is characterized by repeated obstructions of the upper airway during sleep which result in oxygen desaturations and alterations in blood pressure and cerebral blood flow [6]. Whether OSA independently increases stroke incidences, or whether this relationship is confounded by this population's prevalent cardiovascular risk factors, remains debated. The latest published metaanalysis of 12 prospective cohort studies showed a significant positive association between OSA and fatal and non-fatal stroke (pooled relative risk = 2.15, 95% confidence interval: 1.42–3.24) [7]. However, that meta-analysis found insufficient evidence in the subgroup meta-analyses by type of prevention, study design, geographical area, duration of follow-up, and methodological quality. Therefore, we carried out a meta-analysis of cohort studies to systematically identify whether OSA independently increases the risk of fatal or non-fatal stroke. We followed standard criteria for the performing and reporting of the meta-analyses of observational studies [8]. A systematic search of published articles (through 26 September 2013) was performed by using electronic databases including PubMed, Cochrane Library, and ISI Web of Science databases. We used the following keywords: sleep disordered breathing, obstructive sleep apnea, OSA, sleep apnea, stroke, cerebral infarction, cerebrovascular disease, hemorrhage, cardiovascular disease, coronary artery disease, prospective study, cohort study, and follow-up study. There were no language restrictions. Studies were included for the metaanalysis if they fulfilled the following criteria: (1) the study of adult patients had a community-based or population-based or clinicbased, prospective cohort design; (2) the exposed population was patients with OSA; (3) reported quantitative estimates of the multivariate-adjusted relative risk (RRs) and 95% confidence intervals (CIs) for stroke associated with OSA, hazard ratio/odds ratios were considered equivalent to RRs; and (4) longer than
⁎ Corresponding author at: Department of Neurology, The Second Affiliated Hospital, Nanchang University, No. 1, Minde Road, Nanchang 330006, Jiangxi, People's Republic of China. Tel.: + 86 791 86311759; fax: +86 791 86292217. E-mail address: [email protected] (Z.-Y. Tang).
1 year of follow-up. Studies were excluded if they fulfilled the following criteria: (1) the study design was a nonprospective cohort (for example, cross-sectional and retrospective case–control studies); (2) unadjusted RRs and 95% CIs were reported; and (3) shorter than 1 year of follow-up. The Newcastle–Ottawa Scale (NOS) was used to assess the quality of studies [9]. A maximum of 9 points can be given for each study in the categories of selection, outcome, and comparability. We defined studies of high or low quality based on the median overall score among all studies. The RRs were pooled using the random-effects model [10]. All the statistical analyses were performed in Stata 11 (StataCorp LP, College Station, TX). P values were 2-sided and p b 0.05 was considered statistically significant. Ten cohort studies met the inclusion criteria [11–20] (Fig. 1). The main characteristics of studies in the meta-analysis were presented in Tables 1A and 1B. A total of eleven comparisons (one study did have sex specific data) investigated the association between OSA and risk of stroke. The ascertainment of stroke, duration of follow up, study design, assessment of OSA, and methodological quality varied across studies. Pooling all 11 comparisons, OSA was associated with a significantly increased risk of fatal or non-fatal stroke (RR, 2.10; 95% CI, 1.50 to 2.93; p = 0.000) (Fig. 2). Fig. 3 showed the pooled RR for stroke stratified by history of stroke, study design, geographical area, duration of follow-up, and methodological quality. The RR for primary prevention studies was 2.06 (95% CI 1.53–2.79; p = 0.000). Increases in stroke events were also found in the subgroup of study design (clinic-based study: RR 2.44, 95% CI 1.24– 4.80, p = 0.010; and population-based study: RR 2.13, 95% CI 1.45– 3.13, p = 0.000, respectively). In addition, we found significant
Fig. 1. Flow chart of study selection. OSA: obstructive sleep apnea.
Letters to the Editor
467
Table 1A Characteristic of included cohort studies. First author, publication (year)
Study design
Mooe et al. (2001) [11] Arzt et al. (2005) [12]
Clinic-based Population-based
Country/ population
Participants (% male)
Sweden/European 408 patients with CAD (68) United States 1189 participants with no history of stroke (55) Yaggi et al. (2005) [13] Clinic-based United States 1022 patients with no history of stroke (71) Elwood et al. (2006) [14] Population-based United States 1986 men with no history of stroke (100) Munoz et al. (2006) [15] Population-based Spain/European 394 subjects with no history of stroke (57) Valham et al. (2008) [16] Clinic-based Sweden/European 392 patients with CAD (67) Redline et al. (2010) [17] Community-based United States 5422 participants with no history of stroke (45) Yeboah et al. (2011) [18] Community-based United States 5338 participants with no history of stroke (50) Hudgel et al. (2012) [19] Clinic-based United States 1519 participants (62) Martinez-Garcia et al. (2012) [20] Clinic-based Spain/European 939 participants (64)
Age rang or mean Follow-up duration OSA assessment (year) (year) (method) ≤70 30–60
Median 5.1 4
PSG PSG
≥50
3.4
PSG
55–69
10
Self-reports
70–100
6
PSG
≤70 ≥40
10 Mean 8.7
PSG PSG
45–84
Mean 7.5
Self-reports
≥18 ≥65
Median 6.3 Median 5.8
PSG PSG
OSA: obstructive sleep apnea; CAD: coronary artery disease; PSG: polysomnography.
Table 1B Characteristic of included cohort studies. First author, publication (yr) Stroke ascertainment
No. of stroke cases
Adjustment for confounders
Mooe et al. (2001) [11]
33
Age, sex, BMI, HTN, diabetes, LVD, and CI AHI ≥ 10 vs AHI b 10, RR, 2.98 (1.43–6.20) Age, sex, BMI AHI ≥ 20 vs AHI b 5, RR, 3.08 (0.74–12.81) Age, sex, race, smoking, alcohol, BMI, DM, AHI N 36 vs AHI b 3, RR, 3.30 hyperlipidemia, AF, and HTN (1.74–6.26)
6
Age, social class, smoking, alcohol, BMI, and neck circumference Sex
Yes vs no, RR, 1.97 (1.26–3.09)
6
AHI ≥ 30 vs AHI b 30, RR, 2.52 (1.04–6.10) AHI ≥ 15 vs AHI b 5, RR, 3.56 (1.56–8.16) AHI N 19 vs AHI b 4, RR (men), 2.86 (1.10–7.39); (women), 1.21 (0.65–2.24)
7
Arzt et al. (2005) [12] Yaggi et al. (2005) [13]
Elwood et al. (2006) [14] Munoz et al. (2006) [15] Valham et al. (2008) [16] Redline et al. (2010) [17]
Yeboah et al. (2011) [18]
Any type of stroke based on WHO definition Any type of stroke based on selfreported and physician-diagnosed Any type of stroke based on mailed questionnaire of telephone contacting patients or relatives Ischaemic stroke based on ICD 10 codes Ischemic stroke based on ICD 9 codes and medical records Any type of stroke based on ICD 9 and ICD 10 codes Ischemic stroke based on death certificates, hospital discharge information and mailings to participants Any type of stroke based on medical records, death certificates, contacting participants
14 88 (stroke or death) 107 (ischemic) 20 (ischemic) 47 193 (ischemic)
76
Hudgel et al. (2012) [19]
Any type of stroke based on medical 72 records and physician notes Martinez-Garcia et al. (2012) Any type of stroke based on medical 28 [20] records and physician diagnosis
Age, BMI, gender, LVF, CAI, DM, HTN, previous stroke/TIA, AF, current smoking Age, BMI, smoking, SBP, use of antihypertensive medications, DM, and race
Age, sex, BMI, race/ethnicity, smoking, DM, total and HDL-C, TC, SBP, BP medication use, statin use, benzodiazepine use, alcohol Age, BMI, sex, HTN, CVA, MI, CHF
Results
Study quality
5 7
7 9
Yes vs no, RR, 1.15 (0.36–3.74)
8
AHI ≥ 30 vs AHI b 5, RR, 0.73 (0.36–1.46) Age, sex, type of sleep study, sleep clinic, AHI ≥ 30 vs AHI b 15, RR, 4.63 BMI, DM, smoking, ESS, dyslipidemia, (1.03–20.81) cardiovascular events, HTN
7 7
WHO: World Health Organization; HTN: hypertension; BMI: body mass index; DM: diabetes mellitus; AHI: apnea–hypopnea index; MI: myocardial infarction; HDL-C: high-density lipoprotein cholesterol; TC: total cholesterol; SBP: systolic blood pressure; BP: blood pressure; LVF: left ventricular function; AF: atrial fibrillation; TIA: transient ischemic attack; ICD: international classification of disease; ESS: Epworth Sleepiness Scale; CI: coronary intervention; LVD: left ventricular dysfunction; CAI: coronary artery intervention; CVA: cerebral vascular accident; CHF: congestive heart failure.
associations in the overall subgroup meta-analysis by geographical area (United States or Europe), duration of follow-up (≥ 5 years or b5 years), method for OSA assessment (PSG or Non-PSG), and methodological quality (≥ 7 or b7). Our meta-analysis of 10 cohort studies found a significant association between OSA and the risk of fatal or non-fatal stroke after adjustment of established cardiovascular risk factors. For the moment, the mechanisms underlying the increase of consequent stroke events in OSA patients are not well understood. Results in endothelial dysfunction pathways, including intermittent hypoxia, intrathoracic pressure swings, and recurrent arousals, may link the
development of atherosclerosis with the pathogenesis of stroke event [21]. To efficiently assess the efficacy and causality of OSA on stroke, future clinical trials should be done among the general or base on clinic subjects and individuals without a history of stroke. ZYT and ML conceived and designed the experiments. WSH, ML and XWZ analyzed the data. ML and ZYT wrote the paper. WSH, XWZ and ZYT performed the literature search and the data extraction. All authors saw and approved the final version of the manuscript. We thank the editors of the International Journal of Cardiology for editing the manuscript.
468
Letters to the Editor
Study
RR (95% CI)
Mooe (2001)
2.98 (1.43, 6.20)
Arzt (2005)
3.08 (0.74, 12.81)
Yaggi (2005)
3.30 (1.74, 6.26)
Elwood (2006)
1.97 (1.26, 3.09)
Munoz (2006)
2.52 (1.04, 6.10)
Valham (2008)
3.56 (1.56, 8.16)
Redline(W) (2010)
1.21 (0.65, 2.24)
Redline(M) (2010)
2.86 (1.10, 7.39)
Yeboah (2011)
1.15 (0.36, 3.74)
Hudgel (2012)
0.73 (0.36, 1.46)
Martinez-Garcia (2012)
4.63 (1.03, 20.81)
Overall (I-squared = 47.5%, p = 0.040)
2.10 (1.50, 2.93)
NOTE: Weights are from random effects analysis .05
Decreased risk
1
Increased risk
20
Fig. 2. Association between OSA and risk of stroke. OSA: obstructive sleep apnea.
Fig. 3. Analyses of subgroups relating OSA to stroke. OSA: obstructive sleep apnea; PSG: polysomnography.
Letters to the Editor
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Outcomes with short-term versus long-term antiplatelet dual therapy after drugeluting stenting: Quantifying the equivalence margins Andrea Messori ⁎, Valeria Fadda, Dario Maratea, Sabrina Trippoli HTA Unit, ESTAV Toscana Centro, Regional Health Service, 50100 Firenze, Italy
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Article history: Received 21 November 2013 Accepted 30 December 2013 Available online 10 January 2014 Keywords: Antiplatelet Stenting Meta-analysis Equivalence Dual therapy
In evaluating short-term versus long-term antiplatelet dual therapy after drug-eluting stenting, the efforts of many researchers worldwide have permitted us to generate a sufficiently large body of evidence-based data. The two most recent meta-analyses in this area have been focused, respectively, on the information obtained from randomized controlled trials [1] and from all types of clinical studies [2]. While the best quality of evidence is likely to derive from the first meta-analysis, two randomized studies (namely, the RESET [3] and
⁎ Corresponding author at: ESTAV Centro, Area Vasta Centro Toscana, Regional Health System, Via San Salvi 12, 50100 Firenze, Italy. Tel.: +39 338 9513583; fax: + 39 0574 701319. E-mail addresses: [email protected], [email protected] (A. Messori).
the OPTIMIZE [4] trials) were too recent for being examined by Valgimigli and co-coworkers [1]. On the other hand, an increasing amount of evidence-based research [5] has recently been aimed at differentiating between no proof of difference (i.e. failed demonstration of superiority) and proof of no difference (demonstration of non-inferiority/equivalence or futility where futility is essentially represented by equivalence with no treatment). Clearly, proof of no difference is a much more informative result than no proof of difference; the former however requires that an equivalence (or non-inferiority margin) is incorporated in the analysis. To study the differences between short-term versus long-term antiplatelet dual therapy, we re-analyzed the meta-analytical results published by Valgimigli and co-workers [1] by incorporating the data of both the RESET [3] and the OPTIMIZE [4] trials. Then, we carried out a formal equivalence test based on confidence intervals (CIs). All of our analyses evaluated the same composite end-point originally measured in the clinical trials. Since our objective was to determine to what extent short-term and long-term dual antiplatelet therapies are equivalent regarding the incidence of the composite end-point, our analysis was carried out as a meta-analysis of equivalence [6,7]. Our design was of equivalence and not of noninferiority, mainly because the end-point was a mixture of effectiveness and safety, and so we could not exclude results in either direction. The incidences of the above-mentioned end-point were estimated by a standard (random-effect) meta-analysis in which the results were firstly expressed as risk difference (RD) and
