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Sleep apnoea phenotypes in women: A cluster analysis from the ESADA cohort
A. Pataka, JL. Pepin, MR. Bonsignore, S. Schiza, T. Saaresranta, I. Bouloukaki, P. Steiropoulos, G. Trakada, R. Riha, Z. Dogas, D. Testelmans, OK. Basoglu, S. Mihaicuta, F. Fanfulla, L. Grote, S. Bailly, ESADA Study Group
Jazyk angličtina Země Nizozemsko
Typ dokumentu časopisecké články
- MeSH
- fenotyp * MeSH
- index tělesné hmotnosti * MeSH
- kohortové studie MeSH
- komorbidita * MeSH
- lidé středního věku MeSH
- lidé MeSH
- obezita epidemiologie MeSH
- obstrukční spánková apnoe * epidemiologie MeSH
- prevalence MeSH
- senioři MeSH
- shluková analýza MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Evropa MeSH
INTRODUCTION: and Objectives: The clinical presentation of Obstructive Sleep Apnoea (OSA) differs between genders. This study aimed to identify the specific OSA phenotypes of women in the European Sleep Apnoea Database (ESADA) cohort. MATERIALS AND METHODS: Latent class cluster analysis was applied to data from 9710 female OSA patients. Variables used included age, Body Mass Index (BMI), Epworth Sleepiness Scale (ESS), comorbidities (cardiovascular, pulmonary, psychiatric, metabolic, other) and the Apnoea Hypopnea Index (AHI). RESULTS: Four different clusters were found: Cluster 1"Women with ischemic heart disease" (38.3 %):middle aged (59 years [53-65]),overweight to obese (BMI 30.1 kg/m2 [26.9-33.5]), AHI 22.9 events/h[17.4-30], ESS 9 [5,12] with the highest prevalence of ischemic heart disease (56 %). Cluster 2"Elderly women with comorbidities" (23 %): oldest (66 years[60-71]), obese (BMI 36 kg/m2 [31.6-40.4]),AHI 46 events/h [30-60.1]),ESS 9 [6-13] with the highest prevalence of comorbidities. Cluster 3"Sleepy obese women" (16.2 %): the youngest (49 years [42-55]), sleepiest (ESS 12 [8-16]), most obese(BMI 43 kg/m2[37.6-48.9]) females with severe OSA (AHI 53.3 events/h [32-80.5]). Cluster 4 "Women with mild OSA and low comorbidities" (22.5 %): middle aged (53.5 years [46-60]) with BMI 29 kg/m2[25-34.1],ESS9 [5,13]),AHI 8.6events/h[6.9-10.4])and low prevalence of comorbidities. The distribution of the clusters differed across Europe. PAP administration was higher in Clusters 2 and 3 but low in Cluster 4. CONCLUSION: Four distinct female phenotypes were identified with different clinical presentation and comorbidities. Sex-based phenotyping may provide improved risk stratification and personalized treatment.
Democritus University of Thrace Sleep Unit Department of Pneumonology Alexandroupolis Greece
Ege University Department of Respiratory Medicine Izmir Turkey
Gothenburg University Sahlgrenska Academy Center of Sleep and Wake Disorders Gothenburg Sweden
Royal Infirmary Edinburgh Department of Sleep Medicine Edinburgh UK
Sleep Disorders Centre University Hospitals Leuven Leuven Belgium
University of Palermo Respiratory Medicine PROMISE Department and IFT CNRPalermo Italy
Citace poskytuje Crossref.org
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- $a Pataka, A $u Respiratory Failure Unit G Papanikolaou Hospital Thessaloniki, Aristotle University of Thessaloniki, Greece. Electronic address: patakath@yahoo.gr
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- $a INTRODUCTION: and Objectives: The clinical presentation of Obstructive Sleep Apnoea (OSA) differs between genders. This study aimed to identify the specific OSA phenotypes of women in the European Sleep Apnoea Database (ESADA) cohort. MATERIALS AND METHODS: Latent class cluster analysis was applied to data from 9710 female OSA patients. Variables used included age, Body Mass Index (BMI), Epworth Sleepiness Scale (ESS), comorbidities (cardiovascular, pulmonary, psychiatric, metabolic, other) and the Apnoea Hypopnea Index (AHI). RESULTS: Four different clusters were found: Cluster 1"Women with ischemic heart disease" (38.3 %):middle aged (59 years [53-65]),overweight to obese (BMI 30.1 kg/m2 [26.9-33.5]), AHI 22.9 events/h[17.4-30], ESS 9 [5,12] with the highest prevalence of ischemic heart disease (56 %). Cluster 2"Elderly women with comorbidities" (23 %): oldest (66 years[60-71]), obese (BMI 36 kg/m2 [31.6-40.4]),AHI 46 events/h [30-60.1]),ESS 9 [6-13] with the highest prevalence of comorbidities. Cluster 3"Sleepy obese women" (16.2 %): the youngest (49 years [42-55]), sleepiest (ESS 12 [8-16]), most obese(BMI 43 kg/m2[37.6-48.9]) females with severe OSA (AHI 53.3 events/h [32-80.5]). Cluster 4 "Women with mild OSA and low comorbidities" (22.5 %): middle aged (53.5 years [46-60]) with BMI 29 kg/m2[25-34.1],ESS9 [5,13]),AHI 8.6events/h[6.9-10.4])and low prevalence of comorbidities. The distribution of the clusters differed across Europe. PAP administration was higher in Clusters 2 and 3 but low in Cluster 4. CONCLUSION: Four distinct female phenotypes were identified with different clinical presentation and comorbidities. Sex-based phenotyping may provide improved risk stratification and personalized treatment.
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- $a Pepin, J L $u Grenoble Alpes University, HP2 Laboratory, INSERM U1300and Grenoble Alpes University Hospital, Grenoble, France. Electronic address: jpepin@chu-grenoble.fr
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- $a Bonsignore, M R $u University of Palermo, Respiratory Medicine, PROMISE Department - and IFT-CNRPalermo, Italy. Electronic address: mariarosaria.bonsignore@unipa.it
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- $a Saaresranta, T $u Turku University Hospital, Division of Medicine, Department of Pulmonary Diseases, and Sleep Research Centre, University of Turku, Turku, Finland. Electronic address: tasaare@utu.fi
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- $a Dogas, Z $u Department of Neuroscience and Sleep Medicine Center, University of Split School of Medicine and University Hospital - Split, Croatia. Electronic address: zdogas@mefst.hr
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- $a Testelmans, D $u Sleep Disorders Centre, University Hospitals Leuven, Leuven, Belgium. Electronic address: dries.testelmans@uzleuven.be
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- $a Basoglu, O K $u Ege University, Department of Respiratory Medicine, Izmir, Turkey. Electronic address: ozen.basoglu@ege.edu.tr
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- $a Mihaicuta, S $u Center for Research and Innovation in Precision Medicine of Respiratory Diseases, Department of Pulmonology, University of Medicine and Pharmacy Timisoara, Timisoara, Romania. Electronic address: stefan.mihaicuta@umft.ro
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- $a Fanfulla, F $u Unità Operativa di Fisiopatologia Respiratoria e Medicina del Sonno, IstitutoScientifico di Pavia e Montescano IRCCS, Pavia, Italy. Electronic address: francesco.fanfulla@icsmaugeri.it
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- $a Grote, L $u Gothenburg University, Sahlgrenska Academy, Center of Sleep and Wake Disorders, Gothenburg, Sweden. Electronic address: ludger.grote@lungall.gu.se
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- $a Bailly, S $u Grenoble Alpes University, HP2 Laboratory, INSERM U1300and Grenoble Alpes University Hospital, Grenoble, France. Electronic address: sbailly@chu-grenoble.fr
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