Circadian Patterns of Patients with Type 2 Diabetes and Obstructive Sleep Apnea

Sleep apnea, a condition that modifies sleep and circadian rhythms, is highly prevalent in patients with diabetes. However, it is not known if there is an association between sleep apnea, circadian alterations and glycemic regulation in this type of patient. Here, a polysomnographic study was carried out on 21 women and 25 men (mean age = 64.3 ± 1.46 years) with diagnoses of type 2 diabetes to detect the presence of sleep apnea. Moreover, patients wore an actigraph and a temperature sensor on the wrist for one week, to study the manifestation of the circadian rhythms. The correlations of circadian and polysomnographic variables with the severity of apnea, measured by the apnea-hypopnea index, and with glycemic dysregulation, measured by the percentage of glycated hemoglobin, were analyzed. The mean apnea-hypoapnea index of all the participants was 39.6 ± 4.3. Apnea-hypoapnea index correlated with % N1, negatively with % N3, and also the stability of the active circadian rhythm. However, no significant correlation was found between the apnea-hypopnea index and wrist temperature rhythm and glycated hemoglobin. Glycated hemoglobin levels were negatively associated with the percentage of variance explained by the wrist temperature circadian rhythm (calculated via 24 and 12 h rhythms). This association was independent of body mass index and was strongest in patients with severe apnea. In conclusion, patients with diabetes showed altered circadian rhythms associated with a poor glycemic control and this association could partially be related to the coexistence of sleep apnea.

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Sleep Architecture Following a Weight Loss Intervention in Overweight and Obese Patients with Obstructive Sleep Apnea and Type 2 Diabetes: Relationship to Apnea-Hypopnea Index

Journal of Clinical Sleep Medicine ◽

10.5664/jcsm.4202 ◽

2014 ◽

Vol 10 (11) ◽

pp. 1205-1211 ◽

Cited By ~ 6

Author(s):

Ari Shechter ◽

Marie-Pierre St-Onge ◽

Samuel T. Kuna ◽

Gary Zammit ◽

Arindam RoyChoudhury ◽

...

Keyword(s):

Type 2 Diabetes ◽

Weight Loss ◽

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

Sleep Architecture ◽

Apnea Hypopnea Index ◽

Obese Patients ◽

Weight Loss Intervention ◽

Obstructive Sleep

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Usefulness of Cathepsin S to Predict Risk for Obstructive Sleep Apnea among Patients with Type 2 Diabetes

Disease Markers ◽

10.1155/2020/8819134 ◽

2020 ◽

Vol 2020 ◽

pp. 1-8

Author(s):

Wanwan Wen ◽

Haili Sun ◽

Yunxiao Yang ◽

Yifan Jia ◽

Fang Fang ◽

...

Keyword(s):

Type 2 Diabetes ◽

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

Fasting Blood Glucose ◽

Area Under The Curve ◽

Cathepsin S ◽

Control Group ◽

Apnea Hypopnea Index ◽

Obstructive Sleep

Background. Obstructive sleep apnea (OSA) was highly prevalent in patients with type 2 diabetes (T2D). Cathepsin S (CTSS), a cysteine protease, is involved in the inflammatory activity in T2D and hypoxia conditions. The aim of the study was to evaluate whether CTSS could be involved in the inflammatory reaction of OSA in patients with T2D. Methods. We included 158 participants in this study matched for age, gender, and body mass index in 4 groups (control, non-OSA&T2D, OSA&non-T2D, and OSA&T2D). After overnight polysomnography, we collected the clinical data including anthropometrical characteristics, blood pressure, and fasting blood samples in the morning. Plasma CTSS concentration was evaluated using the human Magnetic Luminex Assay. Results. Compared with the control group, both the non-OSA&T2D group and the OSA&non-T2D group showed higher CTSS levels. Plasma CTSS expression was significantly increased in subjects with OSA&T2D compared to subjects with non-OSA&T2D. The OSA&T2D group had higher CTSS levels than the OSA&non-T2D group, but there were no statistically significant differences. Plasma CTSS levels showed significant correlation with the apnea-hypopnea index (AHI) (r=0.559, P<0.001) and plasma fasting blood glucose (r=0.427, P<0.001). After adjusting confounding factors, plasma CTSS levels were independently associated with the AHI (Beta: 0.386, 95% confidence intervals (CI): 21.988 to 57.781; P<0.001). Furthermore, we confirmed the higher pinpoint accuracy of plasma CTSS in the diagnosis of OSA (area under the curve: 0.868). Conclusions. Plasma CTSS expression was significantly elevated in the OSA&T2D group and was independently associated with the AHI; it could be a biomarker with a positive diagnostic value on diagnosing OSA among patients with T2D.

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Nocturnal Oxygen Saturation Parameters as Independent Risk Factors for Type 2 Diabetes Mellitus among Obstructive Sleep Apnea Patients

Journal of Clinical Medicine ◽

10.3390/jcm10173770 ◽

2021 ◽

Vol 10 (17) ◽

pp. 3770

Author(s):

Agata Gabryelska ◽

Jędrzej Chrzanowski ◽

Marcin Sochal ◽

Piotr Kaczmarski ◽

Szymon Turkiewicz ◽

...

Keyword(s):

Type 2 Diabetes ◽

Obstructive Sleep Apnea ◽

Risk Factor ◽

Sleep Apnea ◽

Oxygen Saturation ◽

Cox Regression ◽

Apnea Hypopnea Index ◽

Cart Analysis ◽

Obstructive Sleep

Obstructive sleep apnea (OSA) is a recognized independent risk factor for metabolic disorders, type 2 diabetes mellites (DM2) in particular. Therefore, the study aimed to assess the influence of nocturnal oxygen saturation parameters on the onset of DM2 among OSA patients. The study consisted of 549 participants, who underwent polysomnography examination. Based on apnea hypopnea index (AHI), 465 patients were diagnosed with OSA. One hundred and seven individuals had comorbid DM2. Cox regression models were used to assess the effect of oxygen saturation parameters on the onset of DM2. Classification and regression trees (CART) analysis was used to assess the onset of the DM2 in the study group in context of oxygen saturation variables. One-way Cox regression showed higher risk of earlier DM2 for increased values of BMI, AHI, decreased basal O2 and O2 nadir value, while lowered mean O2 desaturation has not shown statistical significance. In the CART analysis, the following cut-off points 92.2%, 81.7%, 87.1% were determined for basal O2, O2 nadir and mean O2 desaturation, respectively, with the first two parameters being statistically significant. Therefore, basal O2 is independent from AHI, BMI and age is a risk factor of DM2 among OSA patients.

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The Relationship between Diabetes-Related Complications and Obstructive Sleep Apnea in Type 2 Diabetes

Journal of Diabetes Research ◽

10.1155/2018/9269170 ◽

2018 ◽

Vol 2018 ◽

pp. 1-9 ◽

Cited By ~ 11

Author(s):

Nantaporn Siwasaranond ◽

Hataikarn Nimitphong ◽

Areesa Manodpitipong ◽

Sunee Saetung ◽

Naricha Chirakalwasan ◽

...

Keyword(s):

Type 2 Diabetes ◽

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

Apnea Hypopnea Index ◽

Obstructive Sleep ◽

Lower Egfr ◽

Osa Treatment ◽

Severe Degree ◽

The Relationship

This study explored the relationship between obstructive sleep apnea (OSA) and the presence of any diabetes-related complications in type 2 diabetes and whether this was mediated by hypertension. Secondly, the relationship between OSA severity and estimated glomerular filtration rate (eGFR) was investigated. A total of 131 patients participated. OSA was diagnosed using a home monitor, and severity was measured by apnea-hypopnea index (AHI) and oxygen desaturation index (ODI). OSA was found in 75.6% of the participants, 40.5% with moderate-to-severe degree. Any diabetes-related complications (retinopathy, neuropathy, nephropathy, or coronary artery disease) were present in 55.5%, and 70.2% of the participants had hypertension. Mediation analysis indicated that, compared to those with mild or no OSA, those with moderate-to-severe OSA were 3.05 times more likely to have any diabetes-related complications and that this relationship was mediated by the presence of hypertension. After adjusting for confounders, ODI (B = −0.036,p=0.041), but not AHI, was significantly associated with lower eGFR. In conclusion, moderate-to-severe OSA was related to the presence of any diabetes-related complications in type 2 diabetes, and the relationship was mediated by hypertension. The severity of intermittent hypoxia was associated with lower eGFR. Whether OSA treatment will delay or reduce diabetes-related complications should be investigated.

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Serum Uric Acid Is Independently Associated with Risk of Obstructive Sleep Apnea-Hypopnea Syndrome in Chinese Patients with Type 2 Diabetes

Disease Markers ◽

10.1155/2019/4578327 ◽

2019 ◽

Vol 2019 ◽

pp. 1-6 ◽

Cited By ~ 3

Author(s):

Caiyu Zheng ◽

Haiqu Song ◽

Shunhua Wang ◽

Jing Liu ◽

Tingting Lin ◽

...

Keyword(s):

Type 2 Diabetes ◽

Obstructive Sleep Apnea ◽

Uric Acid ◽

Sleep Apnea ◽

Serum Uric Acid ◽

Control Group ◽

Apnea Hypopnea Index ◽

Obstructive Sleep ◽

Hypopnea Syndrome

Purpose. We aimed to investigate the association between serum uric acid (SUA) levels and obstructive sleep apnea-hypopnea syndrome (OSAHS) in patients with type 2 diabetes. Methods. A cross-sectional study of 212 type 2 diabetes mellitus (T2DM) patients was conducted in Xiamen, China. All patients underwent polysomnography (PSG) recordings for OSAHS diagnosis. Patients were grouped according to the apnea-hypopnea index (AHI) as mild (5-14.9), moderate (15-29.9), and severe (≧30) OSAHS. Patients with AHI≤4.9 served as the control group. Weight, body mass index (BMI), SUA, liver function, renal function, blood pressure, lipid profiles, and glycemic parameters were measured. Results. A total of 158 patients (101 men and 57 women) with complete data were analyzed in this study. 127 patients were identified as OSAHS. Among the 127 patients with OSAHS, 56 (44.1%), 37 (29.1%), and 34 (26.8%) had mild, moderate, and severe OSAHS, respectively. Correlation analyses showed that the SUA level was significantly related to the apnea-hypopnea index (AHI) (r=0.194, p=0.016). The level of SUA was significantly higher among OSAHS patients compared to the control group (control group: 333.14±80.52 μmol/L, mild group: 345.50±90.27 μmol/L, moderate group: 363.59±134.26 μmol/L, and severe group: 428.37±123.58 μmol/L and p=0.029). Multivariable logistic regression analyses showed that SUA was the independent risk factor for OSAHS (OR: 1.006, 95% CI: 1.001-1.011, p=0.020). Conclusions. The SUA level is significantly associated with the severity of OSAHS and should be controlled when managing OSAHS.

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Inverse Cross-sectional and Longitudinal Relationships between Diabetic Retinopathy and Obstructive Sleep Apnea in Type 2 Diabetes

Ophthalmology Science ◽

10.1016/j.xops.2021.100011 ◽

2021 ◽

Vol 1 (1) ◽

pp. 100011

Author(s):

Jakob Grauslund ◽

Lonny Stokholm ◽

Anne S. Thykjær ◽

Sören Möller ◽

Caroline S. Laugesen ◽

...

Keyword(s):

Type 2 Diabetes ◽

Obstructive Sleep Apnea ◽

Diabetic Retinopathy ◽

Sleep Apnea ◽

Cross Sectional ◽

Obstructive Sleep ◽

Longitudinal Relationships

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Glycemic variability and cardiovascular disease in patients with type 2 diabetes

BMJ Open Diabetes Research & Care ◽

10.1136/bmjdrc-2020-002032 ◽

2021 ◽

Vol 9 (1) ◽

pp. e002032

Author(s):

Marcela Martinez ◽

Jimena Santamarina ◽

Adrian Pavesi ◽

Carla Musso ◽

Guillermo E Umpierrez

Keyword(s):

Type 2 Diabetes ◽

Blood Glucose ◽

Glycated Hemoglobin ◽

Glucose Monitoring ◽

Glycemic Variability ◽

Cardiovascular Complications ◽

Glucose Levels ◽

Increased Risk ◽

Patients With Diabetes

Glycated hemoglobin is currently the gold standard for assessment of long-term glycemic control and response to medical treatment in patients with diabetes. Glycated hemoglobin, however, does not address fluctuations in blood glucose. Glycemic variability (GV) refers to fluctuations in blood glucose levels. Recent clinical data indicate that GV is associated with increased risk of hypoglycemia, microvascular and macrovascular complications, and mortality in patients with diabetes, independently of glycated hemoglobin level. The use of continuous glucose monitoring devices has markedly improved the assessment of GV in clinical practice and facilitated the assessment of GV as well as hypoglycemia and hyperglycemia events in patients with diabetes. We review current concepts on the definition and assessment of GV and its association with cardiovascular complications in patients with type 2 diabetes.

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