scholarly journals Sleep Disordered Breathing in Patient with Type 2 Diabetes Mellitus and its Association with Diabetic Retinopathy: Single Center Study

2019 ◽  
Vol 2 (1) ◽  
pp. 160-163
Author(s):  
Milesh Jung Sijapati ◽  
Minalma Pandey ◽  
Poojyashree Karki ◽  
Nirupama Khadka

Introduction: Sleep-disordered breathing comprises of obstructive sleep apnea, central sleep apnea, and periodic breathing. There is a link between obesity diabetes and sleep apnea with its association with retinopathy. Therefore this study was done to find out the association of sleep-disordered breathing in uncontrolled diabetes mellitus and association with retinopathy.Materials and Methods: This study was done from 2015 September to 2018 September in Sleep center, Nepal.  Patients diagnosed with Type 2 diabetes mellitus were included. Diabetes mellitus was diagnosed as blood sugar fasting ≥ 126mg/dl, or blood sugar postprandial ≥200mg/dl and glycosylated hemoglobin above 6.5%. Obstructive sleep apnea risk was determined using the STOP-BANG questionnaire. Relationships between the risk of Obstructive sleep apnea and clinical variables along with its association with diabetic retinopathy were evaluated using bivariate analyses and covariate-adjusted logistic regression models.Results: A total of 150 diabetic patients were analyzed. Among them 30 (20.0%) patients had mild Obstructive sleep apnea, 14 (9.3%) patients had moderate Obstructive sleep apnea and 15 (10.0%) patients had severe sleep apnea. Among patients with diabetes mellitus on multivariate regression analysis Obstructive sleep apnea was associated with diabetes mellitus OR 2.05, 95% CI (1.69- 8.83) and diabetic retinopathy OR 1.20 (0.67-5.89).Conclusions: This study concludes that those individuals having diabetes may be suffering from obstructive sleep apnea and association with retinopathy these individuals can be considered for the screening of sleep-disordered breathing by polysomnography.

2020 ◽  
Vol 61 (1) ◽  
pp. 32
Author(s):  
VictorAniedi Umoh ◽  
EffiongEkong Akpan ◽  
UdemeEkpeyong Ekrikpo ◽  
AlphonsusUdo Idung ◽  
EyoEffiong Ekpe

2015 ◽  
Vol 35 (S2) ◽  
pp. 189-193 ◽  
Author(s):  
Khosro Sadeghniiat-Haghighi ◽  
Mohammad Reza Mohajeri-Tehrani ◽  
Ahmad Khajeh-Mehrizi ◽  
Farhad Fathi ◽  
Farzad Saremi-Rasouli ◽  
...  

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Ye Zhang ◽  
Yanpeng Xing ◽  
Haibo Yuan ◽  
Xiaokun Gang ◽  
Weiying Guo ◽  
...  

Aims. Obstructive sleep apnea (OSA) is a very common disorder which is associated with metabolic comorbidities. The aims of this study were to analyze clinical data of patients with OSA and evaluate influence of sleep-disordered breathing on glycometabolism and its underlying mechanisms. Methods. We designed a cross-sectional study involving 53 OSA patients in The First Hospital of Jilin University from March 2015 to March 2016. They underwent a full-night polysomnography, measurement of fasting blood glucose and blood lipid profiles. Besides, we chose 20 individuals with type 2 diabetes mellitus (T2DM) as a subgroup for an in-depth study. This group additionally underwent a steamed bread meal test and measurement of HbA1c, C-reactive protein, tumor necrosis factor-α, interleukin 6, morning plasma cortisol, and growth hormone. Results. The two groups which with or without T2DM showed no significant differences in baseline characteristics. As for OSA patients with T2DM, the severe OSA group had higher homeostasis model assessment of insulin resistance (HOMA-IR) (P=0.013) than the mild-to-moderate OSA group, whereas had lower morning plasma cortisol levels (P=0.005) than the mild-to-moderate OSA group. AHI was positive correlated with HOMA-IR (r=0.523, P=0.018), yet negative correlated with morning plasma cortisol (r=−0.694, P=0.001). However, nadir SpO2 was positive correlated with morning plasma cortisol (rs=0.646, P=0.002), while negative correlated with HOMA-IR (rs=−0.489, P=0.029). Conclusions. Our study showed that sleep-disordered breathing exerted negative influence on glucose metabolisms. The impairment of hypothalamic-pituitary-adrenal axis activity may be one of the underlying mechanisms of the glycometabolic dysfunctions in OSA with T2DM patients.


Obesity ◽  
2011 ◽  
Vol 19 (1) ◽  
pp. 17-22 ◽  
Author(s):  
Susie Yim-Yeh ◽  
Shilpa Rahangdale ◽  
Anh Tu Duy Nguyen ◽  
Karen E. Stevenson ◽  
Victor Novack ◽  
...  

2021 ◽  
Vol 55 (1) ◽  
Author(s):  
Maria Lowella F. De Leon ◽  
Nina R. Alibutod ◽  
Manuel Peter Paul C. Jorge II

Objectives. We determined the prevalence of patients at risk for obstructive sleep apnea (OSA) with uncontrolled type 2 diabetes mellitus (T2DM) at the out-patient department (OPD) of the University of the Philippines-Philippine General Hospital (UP-PGH) from December 1, 2018 - February 28, 2019. We described the demographic characteristics of patients with uncontrolled T2DM and compared them with high and low OSA risk, its association, and correlation with the quality of sleep. Methods. This is a prospective cross-sectional study among uncontrolled T2DM. The questionnaires were Berlin Questionnaire (screen OSA-HR) and Epworth Sleepiness Score (level of sleepiness). Clinicodemographic profile and significant laboratory data were obtained. Descriptive statistics utilized. Chi-square test was used to compare categorical variables between patients with high vs low OSA risk and to determine if an association exists between OSA-HR and sleep quality. Results. A total of 240 participants, 88 males and 151 females, were included in the study. The overall prevalence of OSA-HR among patients with uncontrolled type 2DM is 58.33%. The majority of the OSA–HR patients (105/140) was 46 years old and above. There is a significant association of tonsillar grade, Mallampati score, BMI, HbA1c, hypercholesterolonemia, and Epworth sleepiness on OSA High risk. There is also a substantial association with age, BMI, Mallampati score, tonsillar grade, hypertension, asthma, HbA1c, and hypercholesterelonemia on the level of sleepiness of OSA-HR. Conclusion. There is a high prevalence of high OSA-risk among patients with uncontrolled DM. Factors associated with high OSA-risk among uncontrolled diabetes mellitus include HbA1c, dyslipidemia, BMI, Mallampati score, tonsillar grade, and Epworth score.


2021 ◽  
Vol 55 (1) ◽  
Author(s):  
Maria Lowella F. De Leon ◽  
Nina R. Alibutod ◽  
Manuel Peter Paul C. Jorge II

Objectives. We determined the prevalence of patients at risk for obstructive sleep apnea (OSA) with uncontrolled type 2 diabetes mellitus (T2DM) at the out-patient department (OPD) of the University of the Philippines-Philippine General Hospital (UP-PGH) from December 1, 2018 - February 28, 2019. We described the demographic characteristics of patients with uncontrolled T2DM and compared them with high and low OSA risk, its association, and correlation with the quality of sleep. Methods. This is a prospective cross-sectional study among uncontrolled T2DM. The questionnaires were Berlin Questionnaire (screen OSA-HR) and Epworth Sleepiness Score (level of sleepiness). Clinicodemographic profile and significant laboratory data were obtained. Descriptive statistics utilized. Chi-square test was used to compare categorical variables between patients with high vs low OSA risk and to determine if an association exists between OSA-HR and sleep quality. Results. A total of 240 participants, 88 males and 151 females, were included in the study. The overall prevalence of OSA-HR among patients with uncontrolled type 2DM is 58.33%. The majority of the OSA–HR patients (105 /140) was 46 years old and above. There is a significant association of tonsillar grade, Mallampati score, BMI, HbA1c, hypercholesterolonemia, and Epworth sleepiness on OSA High risk. There is also a substantial association with age, BMI, Mallampati score, tonsillar grade, hypertension, asthma, HbA1c, and hypercholesterelonemia on the level of sleepiness of OSA-HR. Conclusion. There is a high prevalence of high OSA-risk among patients with uncontrolled DM. Factors associated with high OSA-risk among uncontrolled diabetes mellitus include HbA1c, dyslipidemia, BMI, Mallampati score, tonsillar grade, and Epworth score.


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