Obstructive Sleep Apnea and Risk of Cardiovascular Events and All-Cause Mortality: A Decade-Long Historical Cohort Study
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{"title"=>"Obstructive Sleep Apnea and Risk of Cardiovascular Events and All-Cause Mortality: A Decade-Long Historical Cohort Study", "type"=>"journal", "authors"=>[{"first_name"=>"Tetyana", "last_name"=>"Kendzerska", "scopus_author_id"=>"54383390000"}, {"first_name"=>"Andrea S.", "last_name"=>"Gershon", "scopus_author_id"=>"24760464400"}, {"first_name"=>"Gillian", "last_name"=>"Hawker", "scopus_author_id"=>"7006287689"}, {"first_name"=>"Richard S.", "last_name"=>"Leung", "scopus_author_id"=>"7101875684"}, {"first_name"=>"George", "last_name"=>"Tomlinson", "scopus_author_id"=>"7102612572"}], "year"=>2014, "source"=>"PLoS Medicine", "identifiers"=>{"issn"=>"15491676", "scopus"=>"2-s2.0-84895501178", "pmid"=>"24503600", "doi"=>"10.1371/journal.pmed.1001599", "pui"=>"372525539", "isbn"=>"1549-1277", "sgr"=>"84895501178"}, "id"=>"b5c80ce8-b015-34ee-80d9-2725d318a967", "abstract"=>"BACKGROUND Obstructive sleep apnea (OSA) has been reported to be a risk factor for cardiovascular (CV) disease. Although the apnea-hypopnea index (AHI) is the most commonly used measure of OSA, other less well studied OSA-related variables may be more pathophysiologically relevant and offer better prediction. The objective of this study was to evaluate the relationship between OSA-related variables and risk of CV events. METHODS AND FINDINGS A historical cohort study was conducted using clinical database and health administrative data. Adults referred for suspected OSA who underwent diagnostic polysomnography at the sleep laboratory at St Michael's Hospital (Toronto, Canada) between 1994 and 2010 were followed through provincial health administrative data (Ontario, Canada) until May 2011 to examine the occurrence of a composite outcome (myocardial infarction, stroke, congestive heart failure, revascularization procedures, or death from any cause). Cox regression models were used to investigate the association between baseline OSA-related variables and composite outcome controlling for traditional risk factors. The results were expressed as hazard ratios (HRs) and 95% CIs; for continuous variables, HRs compare the 75th and 25th percentiles. Over a median follow-up of 68 months, 1,172 (11.5%) of 10,149 participants experienced our composite outcome. In a fully adjusted model, other than AHI OSA-related variables were significant independent predictors: time spent with oxygen saturation <90% (9 minutes versus 0; HR = 1.50, 95% CI 1.25-1.79), sleep time (4.9 versus 6.4 hours; HR = 1.20, 95% CI 1.12-1.27), awakenings (35 versus 18; HR = 1.06, 95% CI 1.02-1.10), periodic leg movements (13 versus 0/hour; HR = 1.05, 95% CI 1.03-1.07), heart rate (70 versus 56 beats per minute [bpm]; HR = 1.28, 95% CI 1.19-1.37), and daytime sleepiness (HR = 1.13, 95% CI 1.01-1.28).The main study limitation was lack of information about continuous positive airway pressure (CPAP) adherence. CONCLUSION OSA-related factors other than AHI were shown as important predictors of composite CV outcome and should be considered in future studies and clinical practice.", "link"=>"http://www.mendeley.com/research/obstructive-sleep-apnea-risk-cardiovascular-events-allcause-mortality-decadelong-historical-cohort-s-1", "reader_count"=>110, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>9, "Librarian"=>4, "Researcher"=>23, "Student > Doctoral Student"=>8, "Student > Ph. D. Student"=>14, "Student > Postgraduate"=>9, "Other"=>10, "Student > Master"=>12, "Student > Bachelor"=>11, "Lecturer"=>4, "Lecturer > Senior Lecturer"=>3, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>9, "Librarian"=>4, "Researcher"=>23, "Student > Doctoral Student"=>8, "Student > Ph. D. Student"=>14, "Student > Postgraduate"=>9, "Other"=>10, "Student > Master"=>12, "Student > Bachelor"=>11, "Lecturer"=>4, "Lecturer > Senior Lecturer"=>3, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>5, "Agricultural and Biological Sciences"=>13, "Arts and Humanities"=>1, "Economics, Econometrics and Finance"=>1, "Engineering"=>2, "Biochemistry, Genetics and Molecular Biology"=>2, "Nursing and Health Professions"=>3, "Medicine and Dentistry"=>74, "Neuroscience"=>2, "Sports and Recreations"=>2, "Psychology"=>2, "Social Sciences"=>2, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>74}, "Social Sciences"=>{"Social Sciences"=>2}, "Sports and Recreations"=>{"Sports and Recreations"=>2}, "Psychology"=>{"Psychology"=>2}, "Unspecified"=>{"Unspecified"=>5}, "Arts and Humanities"=>{"Arts and Humanities"=>1}, "Engineering"=>{"Engineering"=>2}, "Neuroscience"=>{"Neuroscience"=>2}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>13}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>3}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>2}}, "reader_count_by_country"=>{"Sweden"=>1, "Hong Kong"=>2, "United States"=>1, "Japan"=>1, "Brazil"=>2, "Denmark"=>1, "Italy"=>1, "Germany"=>1, "Spain"=>2, "Croatia"=>1, "Costa Rica"=>1, "India"=>1}, "group_count"=>14}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1374634"], "description"=>"<p>For a unified presentation of all results and figures, the findings shown are for a single imputed data set (the third data set). For OSA-related variables, HRs and 95% CIs in this data set were all within 2% of coefficients pooled across five imputed data sets.</p>a<p>TST90SaO<sub>2</sub> variable was transformed using restricted cubic spline transformation with 4 knots at 0.5, 4, 9, and 100 minutes.</p><p>AWK, total number of awakenings in TST; bpm, beats per minute; df, degree of freedom; HR, hazard ratio; LR, likelihood ratio; PLMI, periodic limb movement index; TST90SaO<sub>2</sub>, sleep time spent with SaO<sub>2</sub> less than 90%.</p>", "links"=>[], "tags"=>["cardiovascular", "Acute cardiovascular problems", "Heart failure", "Myocardial infarction", "stroke", "Clinical research design", "Cohort studies", "epidemiology", "Longitudinal studies", "Observational studies", "Retrospective studies", "Statistical methods", "Cardiovascular disease epidemiology", "Clinical epidemiology", "Pulmonology", "Sleep and ventilation disorders", "fitting", "predictors"], "article_id"=>924909, "categories"=>["Medicine"], "users"=>["Tetyana Kendzerska", "Andrea S. Gershon", "Gillian Hawker", "Richard S. Leung", "George Tomlinson"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001599.t002", "stats"=>{"downloads"=>0, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Model_fitting_and_effect_of_predictors_n_10_149_events_1_172_/924909", "title"=>"Model fitting and effect of predictors (<i>n</i> = 10,149, events = 1,172).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-02-04 02:49:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/1374619"], "description"=>"<p>*Split night, diagnostic study night when treatment was initiated due to severe OSA.</p>", "links"=>[], "tags"=>["cardiovascular", "Acute cardiovascular problems", "Heart failure", "Myocardial infarction", "stroke", "Clinical research design", "Cohort studies", "epidemiology", "Longitudinal studies", "Observational studies", "Retrospective studies", "Statistical methods", "Cardiovascular disease epidemiology", "Clinical epidemiology", "Pulmonology", "Sleep and ventilation disorders", "diagram"], "article_id"=>924894, "categories"=>["Medicine"], "users"=>["Tetyana Kendzerska", "Andrea S. Gershon", "Gillian Hawker", "Richard S. Leung", "George Tomlinson"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001599.g001", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Flow_diagram_of_the_final_cohort_/924894", "title"=>"Flow diagram of the final cohort.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-02-04 02:49:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/1374633"], "description"=>"<p>Person 1, male, 50 years old without signs of OSA and without comorbidities, never smoked, with mean heart rate of 70 and 7 hours of TST; Person 2, person 1+ moderate-severe OSA; Person 3, male, 50 years old with comorbidities, smoked, mean heart rate of 80 and 7 hours of TST; Person 4, person 3+ moderate-severe OSA.</p>a<p>The sum of points attributable for each patient's characteristic.</p>b<p>Corresponds to the total number of points.</p><p>AWK, total number of awakenings in TST; bpm, beats per minute; PLMI, periodic limb movement index; TST90SaO<sub>2</sub>, sleep time spent with SaO<sub>2</sub> less than 90%.</p>", "links"=>[], "tags"=>["cardiovascular", "Acute cardiovascular problems", "Heart failure", "Myocardial infarction", "stroke", "Clinical research design", "Cohort studies", "epidemiology", "Longitudinal studies", "Observational studies", "Retrospective studies", "Statistical methods", "Cardiovascular disease epidemiology", "Clinical epidemiology", "Pulmonology", "Sleep and ventilation disorders", "nomogram"], "article_id"=>924908, "categories"=>["Medicine"], "users"=>["Tetyana Kendzerska", "Andrea S. Gershon", "Gillian Hawker", "Richard S. Leung", "George Tomlinson"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001599.t003", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Example_of_clinical_nomogram_point_system_usage_/924908", "title"=>"Example of clinical nomogram (point system) usage.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-02-04 02:49:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/1374630"], "description"=>"a<p>Significant association (<i>p</i> < 0.05).</p>b<p>TST90SaO<sub>2</sub> was transformed using a restricted cubic spline with 4 knots at 0.5, 4, 9, and 100 minutes.</p><p>AWK, total number of awakenings in TST; bpm, beats per minute; df, degree of freedom; LR, likelihood ratio; PLMI, periodic limb movement index; TST90SaO<sub>2</sub>, sleep time spent with SaO<sub>2</sub> less than 90%.</p>", "links"=>[], "tags"=>["cardiovascular", "Acute cardiovascular problems", "Heart failure", "Myocardial infarction", "stroke", "Clinical research design", "Cohort studies", "epidemiology", "Longitudinal studies", "Observational studies", "Retrospective studies", "Statistical methods", "Cardiovascular disease epidemiology", "Clinical epidemiology", "Pulmonology", "Sleep and ventilation disorders", "re-fitted", "components", "composite"], "article_id"=>924905, "categories"=>["Medicine"], "users"=>["Tetyana Kendzerska", "Andrea S. Gershon", "Gillian Hawker", "Richard S. Leung", "George Tomlinson"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001599.t004", "stats"=>{"downloads"=>4, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Final_model_re_fitted_for_separate_components_of_cardiovascular_composite_outcome_n_10_149_/924905", "title"=>"Final model re-fitted for separate components of cardiovascular composite outcome (<i>n</i> = 10,149).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-02-04 02:49:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/1374628"], "description"=>"<p>To obtain the nomogram predicted probability of three- and five-year event-free survival and to estimate median event-free survival, locate patient values at each axis, then draw a vertical line to the “Point” scale (axis) to determine how many points are attributed for each predictor. Sum the points for all predictors. Locate the sum on the “Total Points” scale. Draw a vertical line towards the “3-year Survival,” “5-year Survival,” and “Median Survival Time” axes to determine the three-year composite CV outcome-free survival, the five-year event-free survival, and to estimate median survival respectively. PLMI, periodic limb movement index; TST90SaO<sub>2</sub>, sleep time spent with SaO<sub>2</sub> less than 90%.</p>", "links"=>[], "tags"=>["cardiovascular", "Acute cardiovascular problems", "Heart failure", "Myocardial infarction", "stroke", "Clinical research design", "Cohort studies", "epidemiology", "Longitudinal studies", "Observational studies", "Retrospective studies", "Statistical methods", "Cardiovascular disease epidemiology", "Clinical epidemiology", "Pulmonology", "Sleep and ventilation disorders", "nomogram", "obstructive", "apnea"], "article_id"=>924903, "categories"=>["Medicine"], "users"=>["Tetyana Kendzerska", "Andrea S. Gershon", "Gillian Hawker", "Richard S. Leung", "George Tomlinson"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001599.g006", "stats"=>{"downloads"=>2, "page_views"=>17, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Clinical_nomogram_for_obstructive_sleep_apnea_patients_/924903", "title"=>"Clinical nomogram for obstructive sleep apnea patients.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-02-04 02:49:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/1374629"], "description"=>"a<p>Subcohort of patients who underwent a diagnostic sleep study since 2004; patients who claimed CPAP through ADP data set before event of interested occurred were censored at the time of a CPAP claim.</p>b<p>TST90SaO<sub>2</sub> was transformed using a restricted cubic spline with 4 knots at 0.5, 4, 9, and 100 minutes.</p><p>AWK, total number of awakenings in TST; bpm, beats per minute; PLMI, periodic limb movement index; TST90SaO<sub>2</sub>, sleep time spent with SaO<sub>2</sub> less than 90%.</p>", "links"=>[], "tags"=>["cardiovascular", "Acute cardiovascular problems", "Heart failure", "Myocardial infarction", "stroke", "Clinical research design", "Cohort studies", "epidemiology", "Longitudinal studies", "Observational studies", "Retrospective studies", "Statistical methods", "Cardiovascular disease epidemiology", "Clinical epidemiology", "Pulmonology", "Sleep and ventilation disorders", "osa-related", "variables", "composite", "cv", "untreated", "subsample"], "article_id"=>924904, "categories"=>["Medicine"], "users"=>["Tetyana Kendzerska", "Andrea S. Gershon", "Gillian Hawker", "Richard S. Leung", "George Tomlinson"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001599.t005", "stats"=>{"downloads"=>0, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Association_between_OSA_related_variables_and_the_composite_CV_outcome_on_untreated_subsample_versus_entire_cohort_/924904", "title"=>"Association between OSA-related variables and the composite CV outcome on untreated subsample versus entire cohort.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-02-04 02:49:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/1374627"], "description"=>"<p>(comparing 75th percentile [9 min] to 25th percentile [0 min]) controlling for potential confounders (BMI = 29, age = 50, sex = men, never smoked, without prior hypertension, diabetes, MI, stroke or heart failure, TST = 5.8, AWK = 25, PLMI, 1.2, mean heart rate, 63, without reporting excessive DS).</p>", "links"=>[], "tags"=>["cardiovascular", "Acute cardiovascular problems", "Heart failure", "Myocardial infarction", "stroke", "Clinical research design", "Cohort studies", "epidemiology", "Longitudinal studies", "Observational studies", "Retrospective studies", "Statistical methods", "Cardiovascular disease epidemiology", "Clinical epidemiology", "Pulmonology", "Sleep and ventilation disorders", "curves"], "article_id"=>924902, "categories"=>["Medicine"], "users"=>["Tetyana Kendzerska", "Andrea S. Gershon", "Gillian Hawker", "Richard S. Leung", "George Tomlinson"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001599.g005", "stats"=>{"downloads"=>4, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Predicted_survival_curves_to_show_the_effect_of_oxygen_saturation_/924902", "title"=>"Predicted survival curves to show the effect of oxygen saturation", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-02-04 02:49:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/1374623"], "description"=>"<p>(BMI = 29, age = 50, sex = men, never smoked, without prior hypertension, diabetes, MI, stroke, or heart failure).</p>", "links"=>[], "tags"=>["cardiovascular", "Acute cardiovascular problems", "Heart failure", "Myocardial infarction", "stroke", "Clinical research design", "Cohort studies", "epidemiology", "Longitudinal studies", "Observational studies", "Retrospective studies", "Statistical methods", "Cardiovascular disease epidemiology", "Clinical epidemiology", "Pulmonology", "Sleep and ventilation disorders", "osa", "adjusted", "cv"], "article_id"=>924898, "categories"=>["Medicine"], "users"=>["Tetyana Kendzerska", "Andrea S. Gershon", "Gillian Hawker", "Richard S. Leung", "George Tomlinson"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001599.g003", "stats"=>{"downloads"=>6, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Predicted_survival_by_OSA_severity_adjusted_for_traditional_CV_risk_factors_/924898", "title"=>"Predicted survival by OSA severity, adjusted for traditional CV risk factors", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-02-04 02:49:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/1374636", "https://ndownloader.figshare.com/files/1374637", "https://ndownloader.figshare.com/files/1374638", "https://ndownloader.figshare.com/files/1374639", "https://ndownloader.figshare.com/files/1374640", "https://ndownloader.figshare.com/files/1374641", "https://ndownloader.figshare.com/files/1374642"], "description"=>"<div><p>Background</p><p>Obstructive sleep apnea (OSA) has been reported to be a risk factor for cardiovascular (CV) disease. Although the apnea-hypopnea index (AHI) is the most commonly used measure of OSA, other less well studied OSA-related variables may be more pathophysiologically relevant and offer better prediction. The objective of this study was to evaluate the relationship between OSA-related variables and risk of CV events.</p><p>Methods and Findings</p><p>A historical cohort study was conducted using clinical database and health administrative data. Adults referred for suspected OSA who underwent diagnostic polysomnography at the sleep laboratory at St Michael's Hospital (Toronto, Canada) between 1994 and 2010 were followed through provincial health administrative data (Ontario, Canada) until May 2011 to examine the occurrence of a composite outcome (myocardial infarction, stroke, congestive heart failure, revascularization procedures, or death from any cause). Cox regression models were used to investigate the association between baseline OSA-related variables and composite outcome controlling for traditional risk factors. The results were expressed as hazard ratios (HRs) and 95% CIs; for continuous variables, HRs compare the 75th and 25th percentiles. Over a median follow-up of 68 months, 1,172 (11.5%) of 10,149 participants experienced our composite outcome. In a fully adjusted model, other than AHI OSA-related variables were significant independent predictors: time spent with oxygen saturation <90% (9 minutes versus 0; HR = 1.50, 95% CI 1.25–1.79), sleep time (4.9 versus 6.4 hours; HR = 1.20, 95% CI 1.12–1.27), awakenings (35 versus 18; HR = 1.06, 95% CI 1.02–1.10), periodic leg movements (13 versus 0/hour; HR = 1.05, 95% CI 1.03–1.07), heart rate (70 versus 56 beats per minute [bpm]; HR = 1.28, 95% CI 1.19–1.37), and daytime sleepiness (HR = 1.13, 95% CI 1.01–1.28).The main study limitation was lack of information about continuous positive airway pressure (CPAP) adherence.</p><p>Conclusion</p><p>OSA-related factors other than AHI were shown as important predictors of composite CV outcome and should be considered in future studies and clinical practice.</p><p><i>Please see later in the article for the Editors' Summary</i></p></div>", "links"=>[], "tags"=>["cardiovascular", "Acute cardiovascular problems", "Heart failure", "Myocardial infarction", "stroke", "Clinical research design", "Cohort studies", "epidemiology", "Longitudinal studies", "Observational studies", "Retrospective studies", "Statistical methods", "Cardiovascular disease epidemiology", "Clinical epidemiology", "Pulmonology", "Sleep and ventilation disorders", "apnea", "all-cause", "decade-long", "cohort"], "article_id"=>924911, "categories"=>["Medicine"], "users"=>["Tetyana Kendzerska", "Andrea S. Gershon", "Gillian Hawker", "Richard S. Leung", "George Tomlinson"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1001599.s001", "https://dx.doi.org/10.1371/journal.pmed.1001599.s002", "https://dx.doi.org/10.1371/journal.pmed.1001599.s003", "https://dx.doi.org/10.1371/journal.pmed.1001599.s004", "https://dx.doi.org/10.1371/journal.pmed.1001599.s005", "https://dx.doi.org/10.1371/journal.pmed.1001599.s006", "https://dx.doi.org/10.1371/journal.pmed.1001599.s007"], "stats"=>{"downloads"=>31, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Obstructive_Sleep_Apnea_and_Risk_of_Cardiovascular_Events_and_All_Cause_Mortality_A_Decade_Long_Historical_Cohort_Study_/924911", "title"=>"Obstructive Sleep Apnea and Risk of Cardiovascular Events and All-Cause Mortality: A Decade-Long Historical Cohort Study", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-02-04 02:49:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/1374632"], "description"=>"a<p>The differences between groups considered as clinically important as indicated by a systematic review <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001599#pmed.1001599-Kendzerska1\" target=\"_blank\">[7]</a> and expert opinion.</p><p>AHIO, total and obstructive apnea-hypopnea index; ArI, total arousals index; AWK, total number of awakenings; bpm, beats per minute; CABG, coronary artery bypass graft surgery; ESS, Epworth Sleepiness Scale; TST90SaO<sub>2</sub>, sleep time spent with SaO<sub>2</sub> less than 90%.</p>", "links"=>[], "tags"=>["cardiovascular", "Acute cardiovascular problems", "Heart failure", "Myocardial infarction", "stroke", "Clinical research design", "Cohort studies", "epidemiology", "Longitudinal studies", "Observational studies", "Retrospective studies", "Statistical methods", "Cardiovascular disease epidemiology", "Clinical epidemiology", "Pulmonology", "Sleep and ventilation disorders", "included", "excluded", "samples", "patients", "full-night", "diagnostic"], "article_id"=>924907, "categories"=>["Medicine"], "users"=>["Tetyana Kendzerska", "Andrea S. Gershon", "Gillian Hawker", "Richard S. Leung", "George Tomlinson"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001599.t001", "stats"=>{"downloads"=>10, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_included_and_excluded_samples_for_patients_with_a_full_night_diagnostic_sleep_study_/924907", "title"=>"Comparison of included and excluded samples for patients with a full-night diagnostic sleep study.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-02-04 02:49:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/1374626"], "description"=>"<p>AWK, number of awakenings in TST; TST90SaO<sub>2</sub>, sleep time spent with SaO<sub>2</sub> less than 90%; PLMI, periodic leg movement index; HR, mean heart rate during sleep; day sleep, DS, identified by a positive answer to the question “During the day, do you ever fall asleep unintentionally?”.</p>", "links"=>[], "tags"=>["cardiovascular", "Acute cardiovascular problems", "Heart failure", "Myocardial infarction", "stroke", "Clinical research design", "Cohort studies", "epidemiology", "Longitudinal studies", "Observational studies", "Retrospective studies", "Statistical methods", "Cardiovascular disease epidemiology", "Clinical epidemiology", "Pulmonology", "Sleep and ventilation disorders", "multivariable", "cox", "regression", "presented", "ratios", "shading"], "article_id"=>924901, "categories"=>["Medicine"], "users"=>["Tetyana Kendzerska", "Andrea S. Gershon", "Gillian Hawker", "Richard S. Leung", "George Tomlinson"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001599.g004", "stats"=>{"downloads"=>2, "page_views"=>24, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Results_from_multivariable_Cox_regression_model_presented_as_hazard_ratios_with_shading_representing_confidence_levels_99_95_90_80_and_70_/924901", "title"=>"Results from multivariable Cox regression model presented as hazard ratios with shading representing confidence levels (99%, 95%, 90%, 80%, and 70%).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-02-04 02:49:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/1374622"], "description"=>"<p>The numbers at risk are presented above the x-axis: from the top to the bottom, AHI<5; 5≤AHI<15; 15≤AHI<30; AHI>30.</p>", "links"=>[], "tags"=>["cardiovascular", "Acute cardiovascular problems", "Heart failure", "Myocardial infarction", "stroke", "Clinical research design", "Cohort studies", "epidemiology", "Longitudinal studies", "Observational studies", "Retrospective studies", "Statistical methods", "Cardiovascular disease epidemiology", "Clinical epidemiology", "Pulmonology", "Sleep and ventilation disorders", "kaplan-meier", "curves", "obstructive", "apnea", "severity", "apnea-hypopnea"], "article_id"=>924897, "categories"=>["Medicine"], "users"=>["Tetyana Kendzerska", "Andrea S. Gershon", "Gillian Hawker", "Richard S. Leung", "George Tomlinson"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001599.g002", "stats"=>{"downloads"=>3, "page_views"=>104, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Unadjusted_Kaplan_Meier_survival_curves_by_obstructive_sleep_apnea_severity_as_expressed_by_the_apnea_hypopnea_index_/924897", "title"=>"Unadjusted Kaplan-Meier survival curves by obstructive sleep apnea severity as expressed by the apnea-hypopnea index.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-02-04 02:49:11"}

PMC Usage Stats | Further Information

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