Cardiovascular autonomic neuropathy contributes to sleep apnea in young and lean type 1 diabetes mellitus patients

Obstructive Sleep Apnoea and Type 1 Diabetes Mellitus: A Neglected Relationship?

Obstructive sleep apnoea (OSA) is regarded as a major health condition, progressively affecting an increased number of people around the world. The interplay between OSA and type 2 diabetes mellitus (T2DM) has been extensively studied. However, little is known about the relationship between OSA and type 1 diabetes mellitus (T1DM). This review provides insight into the prevalence of OSA in T1DM and its relationship with diabetic complications. Studies have hitherto yielded contradictory results on the occurrence of OSA in T1DM. Indeed, the risk of OSA in T1DM has ranged from 1 in 10 to more than 1 in 2 T1DM subjects. This high occurrence was confirmed by objective polysomnography as well as widely used subjective questionnaires. Multiple studies revealed the important correlation between OSA and diabetes complications. Both microvascular (nephropathy, neuropathy and retinopathy) and macrovascular complications appear to be associated with OSA occurrence, although some associations were not significant due to inadequate data. In conclusion, T1DM subjects carry a higher risk of undiagnosed OSA. Additional studies are needed to clarify the exact correlation between the two conditions.

Obstructive sleep apnea: Beyond the dogma of obesity!

Obstructive sleep apnea (OSA) has long been studied in patients with obesity and type 2 diabetes mellitus (T2DM), due to the fact that both disorders are commonly associated with an increased body mass index (BMI). However, a link between OSA and non-obese diabetic patients is still not very elaborated, nor heavily explored. In this review, we elucidate some proposed mechanisms for the link between OSA and diabetic patients both with and beyond obesity, shedding the light on the latter case. One such mechanism is oxidative stress, a phenomenon of reactive oxygen species (ROS) imbalance seen in both of the previously mentioned disorders. A plausible explanation for the OSA-induced ROS production is the repeating episodes of hypoxia and reperfusion and their effect on the mitochondrial electron transport chain. This paper explores the literature regarding ROS imbalance as the possible missing link between OSA and Diabetes Mellitus beyond obesity, while still mentioning other possible proposed mechanisms such as a dysregulated autonomic nervous system (ANS), as well as mechanical and craniofacial abnormalities. This paper also suggests a link between OSA and diabetic complications, while exploring the clinical progress made in treating the former disorder with anti-oxidant and hypo-glycemic drugs. If further investigated, these findings could help identify novel therapeutic interventions for the treatment of OSA and Diabetic patients.

Prevalence of sleep apnoea in patients with type 1 diabetes and its association with comorbidities and diabetic complications: A French nationwide prospective study

AIM

To investigate sleep apnoea prevalence, factors influencing severity, and associations between sleep apnoea severity and micro-/macrovascular complications in a large population of patients with type 1 diabetes.

MATERIALS AND METHODS

This French multicentre prospective cohort study was conducted between July 2016 and June 2020. Adults with type 1 diabetes using an insulin pump were eligible. Home care provider nurses collected demographic and clinical data and set up oximetry to determine the oxygen desaturation index (ODI). No, mild-moderate and severe sleep apnoea were defined as ODI <15 events/h, 15 to <30 events/h and ≥30 events/h, respectively. Univariate and multivariate analyses were performed to identify factors associated with sleep apnoea, and associations between sleep apnoea severity and micro-/macrovascular complications were determined using logistic regression.

RESULTS

Of 769 participants, 12.4% and 3.4% had mild-to-moderate or severe sleep apnoea, respectively. Factors significantly associated with sleep apnoea on multivariate analysis were age, sex, body mass index (BMI) and hypertension. After adjustment for age, sex and BMI, presence of severe sleep apnoea was significantly associated with macrovascular complications (odds ratio vs. no sleep apnoea: 3.96 [95% confidence interval 1.43-11.11]; P < 0.01), while mild-to-moderate sleep apnoea was significantly associated with presence of diabetic retinopathy (odds ratio 2.09 [95% confidence interval 1.10-3.74]; P < 0.01).

CONCLUSION

Sleep apnoea is a significant comorbidity in patients with type 1 diabetes, especially with respect to diabetic complications. This highlights the need for sleep apnoea screening and management in these individuals.

Screening for sleep-disordered breathing in people with type 1 diabetes by combining polysomnography with glucose variability assessment

AIMS

There are few published data on sleep-disordered breathing (SDB) in type 1 diabetes (T1DM). Here, we used a combination of polysomnography and glucose variability assessment to screen for SDB.

METHODS

In a prospective, single-centre study, adults with T1DM underwent polysomnography and continuous glucose monitoring during a single night. We measured high glucose variability and the occurrence of a low or very low glucose level. Mild and moderate-to-severe SDB were defined as an apnoea-hypopnoea index above 5/h and 15/h, respectively.

RESULTS

We studied 46 patients (25 men; median age: 42 [35-54]; diabetes duration: 18 years [13-29]; body mass index (BMI): 24.8 kg/m² [23.0-28.9]). SDB was present in 17 patients (37.0%) overall (mild SDB: n = 9; moderate-to-severe SDB; n = 8). When compared with the absence of SDB or mild SDB, moderate-to-severe SDB was associated with a higher BMI (29.8 kg/m² [27.8-31.1]) and a longer diabetes duration (26 years [18-31]) but not with above-target glucose variability or more sleep disorder symptoms. Conversely, sleep disorder symptoms were not more frequent in patients with above-target glucose variability.

CONCLUSION

SDB was highly prevalent and associated with obesity. According to the methods used here, sleep disorders were not associated with above-target glucose variability or low glucose values.

Type 1 Diabetes, Sleep, and Hypoglycemia

PURPOSE OF REVIEW

To review the relationship between sleep and hypoglycemia, sleep characteristics, and their associations with glycemic control in persons with type 1 diabetes (T1D). The effects of sleep interventions and diabetes technology on sleep are summarized.

RECENT FINDINGS

Nocturnal hypoglycemia affects objective and subjective sleep quality and is related to behavioral, psychological, and physiological factors. Sleep disturbances are common, including inadequate sleep, impaired sleep efficiency, poor subjective satisfaction, irregular timing, increased daytime sleepiness, and sleep apnea. Some have a bidirectional relationship with glycemic control. Preliminary evidence supports sleep interventions (e.g., sleep extension and sleep coach) in improving sleep and glycemic control, while diabetes technology use could potentially improve sleep. Hypoglycemia and sleep disturbances are common among persons with T1D. There is a need to develop sleep promotion programs and test their effects on sleep, glucose, and related outcomes (e.g., self-care, psychological health).

Coexistence of cardiovascular risk factors and obstructive sleep apnoea in polysomnography

OBJECTIVES

The objective of the study was to assess the relationship between the coexistence of cardiovascular risk factors (CVRFs) and the incidence and severity of obstructive sleep apnoea (OSA).

METHODS

The study involved 88 people, aged 53.76 ± 12.59 years. A questionnaire, basic anthropometric measurements, blood pressure, standard laboratory tests (total cholesterol, triglycerides and glucose) and polysomnography were performed. Each patient was assessed for the presence of CVRFs: i.e. obesity, arterial hypertension, hypercholesterolemia, hypertriglyceridemia, type 2 diabetes and smoking. OSA was diagnosed based on the apnoea and hypopnea index (AHI) in polysomnography.

RESULTS

It was documented that the mean AHI values were significantly higher in obese patients than in non-obese patients, in patients with arterial hypertension than in patients without hypertension, in patients with hypercholesterolaemia than in patients without hypercholesterolaemia and in patients declaring smoking than in non-smoking patients. The correlation analysis revealed a significant positive linear relationship between the number of CVRFs and the AHI value in polysomnography (r = 0.40, p < 0.05). Based on the regression analysis, it was documented that obesity, arterial hypertension and smoking are independent predictors of higher AHI values.

CONCLUSIONS

In the study group of patients with multiple cardiovascular risk factors, there is a directly proportional relationship between the number of cardiovascular risk factors and the AHI index in polysomnography.

Impact of sleep apnoea-hypopnoea syndrome on diabetic neuropathy. A systematic review

INTRODUCTION

Diabetes mellitus and sleep apnoea-hypopnoea syndrome appear to be related, but it is not well defined whether there is an increased risk of peripheral neuropathy in patients with both diseases. For this reason, we conducted a systematic review.

METHODS

Bibliographic search in 3 electronic databases using a predefined strategy and the PRISMA methodology. Only original studies (any type of design) published from 2000 onwards in English, French, Portuguese or Spanish were included. A study quality scale was established.

RESULTS

Twelve articles were selected, of which six studied type 2 diabetic patients. The overall prevalence of sleep apnoea-hypopnoea syndrome was 43.7% (1,559/3,564 patients). Diabetic neuropathy was more frequent in patients with sleep apnoea-hypopnoea syndrome in nine studies, although significantly only in four (60% vs 27%, P<.001; 64.5% vs 36%, P=.03; 37% vs 23.4%, P<.02; 66.6% vs 0%, P=.007). In one study, diabetic neuropathy was more frequent in patients without sleep apnoea-hypopnoea syndrome (although not statistically significant) and in 2 no comparison was made between patients with/without sleep apnoea/hypopnoea syndrome.

CONCLUSIONS

The observed results suggest a relationship between diabetes mellitus and sleep apnoea-hypopnoea syndrome in the occurrence of diabetic neuropathy.

The association between sleep and diabetes outcomes - A systematic review

AIM

This study aimed to systematically review the prevalence of diagnosed sleep disorders in people with diabetes and to determine the association between sleep disorders and blood glucose levels and diabetes outcomes.

METHODS

We conducted a literature search in the following databases: MEDLINE (Pubmed), EMBASE, CINAHL, PsychInfo and Web of Science Citation Index. Meta-analysis (random-effects models) was conducted to estimate the prevalence of sleep disorders in people with diabetes.

RESULTS

Forty-one articles measured the prevalence of sleep disorders in adults with diabetes. The estimated pooled prevalence of sleep disorders in diabetes was estimated to be 52% (95% CI 42-63%). The highest pooled prevalence was observed for unspecified sleep apnea (69%; 95% CI: 59-78%), followed by obstructive sleep apnea (60%; 95% CI 39-80%), and restless leg syndrome (27%; 95% CI 20-34%). Eleven studies examined the association between sleep disorders and diabetes control and complications. The presence of comorbid sleep disorders was associated with increased diabetes outcomes.

CONCLUSIONS

Diagnosed sleep disorders are highly prevalent in people with diabetes. Sleep disorders are associated with diabetes outcomes, though there was considerable heterogeneity across studies.

Sleep-related disorders in patients with type 1 diabetes mellitus: current insights

Type 1 diabetes mellitus (T1DM) is an autoimmune condition that results from destruction of beta cells in the pancreas. Several reviews have concluded that sleep contributes to poor glycemic control, diabetes management, and diabetes-related complications in individuals with T1DM and represents an untapped opportunity for intervention. However, at the current juncture, the American Diabetes Association's Standards of Medical Care are devoid of recommendations about how to address sleep in the management of T1DM. This article summarizes reviews of sleep in youth and adults with T1DM and empirical studies that have examined various sleep parameters ranging from sleep disturbances (general, perceived sleep quality, sleepiness, awakenings, and sleep efficiency), sleep duration, sleep consistency, sleep-disordered breathing (SDB), and sleep architecture. The data show that many individuals with T1DM sleep less than recommendations; individuals with the poorest sleep have difficulties with diabetes management; and sleep deficiency including SDB often corresponds to several disease morbidities (neuropathy, nephropathy, etc). Mixed findings exist regarding direct associations of various sleep parameters and glycemic control. SDB appears to be just as prevalent, if not more, than other conditions that have been recommended for universal screening in individuals with T1DM. The article concludes with recommendations for collaborative research efforts to further elucidate the role of sleep in diabetes-related outcomes; investigations to test behavioral strategies to increase sleep quantity and consistency; and considerations for clinical care to address sleep.

The Risk of Obstructive Sleep Apnea among Patients with Type 2 Diabetes Mellitus

CONTEXT/AIMS

Obstructive sleep apnea (OSA) and Type 2 diabetes mellitus share obesity as a common risk factor. The presence of OSA may contribute to increased morbidity and mortality of diabetes. Despite their close association, OSA is not routinely evaluated in diabetic patients. This study was conducted to determine the risk of OSA among Type 2 diabetes mellitus patients.

METHODS

Type 2 diabetic patients attending a tertiary hospital in Nigeria were evaluated for OSA risk using the Berlin Questionnaire. Other parameters measured included anthropometry and blood pressure (BP).

RESULTS

Three hundred and twenty-seven patients participated in this survey: 177 (54.1%) were female and 150 (45.9%) were male. The average age of the patients was 56.2 ± 9.3 years. Seventy-eight (44.8%) females were obese compared to 30 (20.0%) males,P < 0.001. Two hundred and one (61.5%) patients were previously known hypertensives with only 48 (23.9%; 95% confidence interval [CI]: 18.2-30.4) of them having good BP control. One hundred and sixty-two (49.5%, 95% CI; 44.0-55.1) patients had a high risk for OSA: 96 (54.2%; 95% CI: 44.6-61.7) females and 66 (44.0%; 95% CI: 35.9-52.3) males. The strongest predictor for a high risk of OSA was poorly controlled BP with an odds ratio of 2.6 (95% CI: 1.6-4.3).

CONCLUSION

This study has demonstrated that there is a high risk of OSA among Type 2 diabetic patients and that OSA risk is significantly associated with poor BP control and obesity. We recommend that diabetic patients should be assessed for OSA risk as part of their routine evaluation.

Obstructive sleep apnoea in Type 2 diabetes mellitus: increased risk for overweight as well as obese people included in a national primary care database analysis

AIMS

To determine obstructive sleep apnoea prevalence in people with Type 2 or Type 1 diabetes in a national primary care setting, stratified by BMI category, and to explore the relationship between patient characteristics and obstructive sleep apnoea.

METHODS

Using the Royal College of General Practitioners Research and Surveillance Centre database, a cross-sectional analysis was conducted. Diabetes type was identified using a seven-step algorithm and was grouped by Type 2 diabetes, Type 1 diabetes and no diabetes. The clinical characteristics of these groups were analysed, BMI-stratified obstructive sleep apnoea prevalence rates were calculated, and a multilevel logistic regression analysis was completed on the Type 2 diabetes group.

RESULTS

Analysis of 1 275 461 adult records in the Royal College of General Practitioners Research and Surveillance Centre network showed that obstructive sleep apnoea was prevalent in 0.7%. In people with Type 2 diabetes, obstructive sleep apnoea prevalence increased with each increasing BMI category, from 0.5% in those of normal weight to 9.6% in those in the highest obesity class. By comparison, obstructive sleep apnoea prevalence rates for these BMI categories in Type 1 diabetes were 0.3% and 4.3%, and in those without diabetes 1.2% and 3.9%, respectively. Obstructive sleep apnoea was more prevalent in men than women in both diabetes types. When known risk factors were adjusted for, there were increased odds ratios for obstructive sleep apnoea in people with Type 2 diabetes in the overweight and higher BMI categories.

CONCLUSIONS

Obstructive sleep apnoea was reported in people with both types of diabetes across the range of overweight categories and not simply in the highest obesity class.

Sleep Apnea and Cardiovascular Disease: An Enigmatic Risk Factor

Synchronization of molecular, metabolic, and cardiovascular circadian oscillations is fundamental to human health. Sleep-disordered breathing, which disrupts such temporal congruence, elicits hemodynamic, autonomic, chemical, and inflammatory disturbances with acute and long-term consequences for heart, brain, and circulatory and metabolic function. Sleep apnea afflicts a substantial proportion of adult men and women but is more prevalent in those with established cardiovascular diseases and especially fluid-retaining states. Despite the experimental, epidemiological, observational, and interventional evidence assembled in support of these concepts, this substantial body of work has had relatively modest pragmatic impact, thus far, on the discipline of cardiology. Contemporary estimates of cardiovascular risk still are derived typically from data acquired during wakefulness. The impact of sleep-related breathing disorders rarely is entered into such calculations or integrated into diagnostic disease-specific algorithms or therapeutic recommendations. Reasons for this include absence of apnea-related symptoms in most with cardiovascular disease, impediments to efficient diagnosis at the population level, debate as to target, suboptimal therapies, difficulties mounting large randomized trials of sleep-specific interventions, and the challenging results of those few prospective cardiovascular outcome trials that have been completed and reported. The objectives of this review are to delineate the bidirectional interrelationship between sleep-disordered breathing and cardiovascular disease, consider the findings and implications of observational and randomized trials of treatment, frame the current state of clinical equipoise, identify principal current controversies and potential paths to their resolution, and anticipate future directions.

Sleep disturbances in Wolfram syndrome

Background

Wolfram syndrome is a rare disorder associated with diabetes mellitus, diabetes insipidus, optic nerve atrophy, hearing and vision loss, and neurodegeneration. Sleep complaints are common but have not been studied with objective measures. Our goal was to assess rates of sleep apnea and objective and self-reported measures of sleep quality, and to determine the relationship of sleep pathology to other clinical variables in Wolfram syndrome patients.

Methods

Genetically confirmed Wolfram syndrome patients were evaluated at the 2015 and 2016 Washington University Wolfram Syndrome Research Clinics. Patients wore an actigraphy device and a type III ambulatory sleep study device and completed the Epworth Sleepiness Scale (ESS), the Pittsburgh Sleep Quality Index (PSQI) and/or the Pediatric Sleep Questionnaire (PSQ). PSQI and PSQ questionnaire data were compared to a previously collected group of controls. Patients were characterized clinically with the Wolfram Unified Rating Scale (WURS) and a subset underwent magnetic resonance imaging (MRI) for brain volume measurements.

Results

Twenty-one patients were evaluated ranging from age 8.9–29.7 years. Five of 17 (29%) adult patients fit the criteria for obstructive sleep apnea (OSA; apnea-hypopnea index [AHI] ≥ 5) and all 4 of 4 (100%) children aged 12 years or younger fit the criteria for obstructive sleep apnea (AHI’s ≥ 1). Higher AHI was related to greater disease severity (higher WURS Physical scores). Higher mixed apnea scores were related to lower brainstem and cerebellar volumes. Patients’ scores on the PSQ were higher than those of controls, indicating greater severity of childhood obstructive sleep-related breathing disorders.

Conclusions

Wolfram syndrome patients had a high rate of OSA. Further study would be needed to assess how these symptoms change over time. Addressing sleep disorders in Wolfram syndrome patients would likely improve their overall health and quality of life.

Sleep characteristics in young adults with type 1 diabetes

Only 14% of young adults with Type 1 Diabetes (T1D) achieve targets for glycemic control (HbA1C < 7.0%), with deterioration over time. Complex cognitive processes required to manage glycemia are vulnerable to sleep deficiency. Using Whittemore and Knafl's approach, we conducted an integrative review of research literature on sleep characteristics and glycemia in these young adults. Quality was assessed using the Mixed Methods Appraisal Tool (v. 2011). Multiple databases were searched for articles published in English in peer-reviewed journals from 2003 to 2018, using search terms 'sleep' and 'T1D' with age limiters 18-40. Of 218 studies initially retrieved, 17 original studies met the inclusion criteria. The following themes were identified in young adults with T1D: (1) They had poorer objective and subjective sleep quality, more variability, and impaired awakening response to hypoglycemia compared with controls; (2) They had poorer glycemic control that was associated with shorter sleep duration, poorer sleep quality, and less time in deep sleep; and (3) Hypoglycemia negatively impacted diabetes management, sleep quality, and next day functioning. Sleep deficiency, as indicated by short sleep duration is associated with a range of negative health outcomes for people with T1D; therefore, optimizing sleep should be a priority in practice and research.

Sympathetic Hyperactivity and Sleep Disorders in Individuals With Type 2 Diabetes

Introduction: Many studies on the impact of type 2 diabetes mellitus (T2DM) on sleep breathing have shown a higher prevalence and severity of sleep apnea-hypopnea syndrome (SAHS) in those with T2DM. Moreover, an increased activity of the sympathetic nervous system has been described in both pathologies. This cross-sectional study aimed to assess sympathetic activity in patients with T2DM, and to investigate the relationship between sympathetic activity and polysomnographic parameters. Materials and Methods: Thirty-six patients with T2DM without known clinical macrovascular nor pulmonary disease and 11 controls underwent respiratory polygraphy, and their cardiac variability and 24-h urine total metanephrines were measured. Results: SAHS was highly prevalent with a mean apnea-hypopnea index (AHI) in the range of moderate SAHS. In patients with T2DM, the nocturnal concentration of total metanephrines in urine were higher than diurnal levels [247.0 (120.0-1375.0) vs. 210.0 (92.0-670.0), p = 0.039]. The nocturnal total metanephrine concentration was positively and significantly associatedwith the percentage of sleeping time spent with oxygen saturation <90%(CT90). In the entire population and in subjects with T2DM, the multivariate regression analysis showed a direct interaction between the nocturnal concentration of urine metanephrines and the CT90. Conclusion: These findings suggest that the increase in sympathetic activity previously described in patients with T2DM could be mediated through nocturnal breathing disturbances. The diagnosis and treatment of SAHS may influence sympathetic activity disorders and may contribute to an improvement in T2DM and cardiovascular risk.

The correlation between obstructive sleep apnea and diabetic neuropathy: A meta-analysis

BACKGROUND

The aim of this study was to explore the correlation between obstructive sleep apnea (OSA) and diabetic neuropathy.

MATERIALS AND METHODS

After working out searching strategy, literatures were screened from the electronic databases: PubMed, Embase, and the Cochrane library. R 3.12 was utilized to perform meta-analysis, and odds ratio (OR) and its 95% confidence interval (CI) were used to present effect size. Heterogeneity was assessed by χ²-based Q test and I² statistics. Publication bias was estimated by Egger's test and sensitivity was evaluated by leave one out methods.

RESULTS

According to the criteria, a total of 11 studies with 1842 patients were enrolled in this study. With a significant heterogeneity (Q=31.83, I²=68.60%), the random effects model was utilized to assess the effect size of pooled data. A remarkable correlation was identified OSA and diabetic neuropathy (OR=1.84, 95% CI: 1.18-2.87) without publication bias (t=1.68, P=0.13). Meanwhile, the result of leave one out performed a well sensitivity. Moreover, the subgroup analyses presented that OSA was significantly correlated with type 1 diabetic neuropathy (OR=1.97, 95% CI: 1.19-3.25), but no remarkable correlation was identified between OSA and type 1 (OR=1.84, 95% CI: 0.86-3.93) or 1+2 (OR=1.30, 95% CI: 0.43-3.92) diabetic neuropathy.

CONCLUSION

OSA was significantly correlated with neuropathy in type 1 diabetes, but not in type 2 and type 1+2 diabetes.

Short-term metabolic control and sleep in children and adolescents with type 1 diabetes mellitus

AIMS

The aim of this study was to examine sleep in T1D children and in healthy controls by polysomnographic (PSG) examination and to determine the influence of short-term metabolic compensation on sleep quality and sleep disordered breathing (SDB).

METHODS

The prospective cross-sectional study included 44 T1D subjects and 60 healthy controls, aged 10-19 years. Subjects underwent anthropometric measurements, laboratory testing and standard overnight in-laboratory video polysomnography with continuous glucose monitoring (CGM).

RESULTS

No significant differences were found in total sleep time, sleep efficiency, percentage of sleep stages and respiratory parameters between T1D and healthy group. T1D children with more optimal short-term metabolic control (AvgSG < 10 mmol/l, n = 18) had a significantly lower apnea-hypopnea index (AHI) (0.3(0-0.5) vs. 0.6 (0.2-0.9) events/h, p < 0.05)and respiratory arousal index (0(0-0,1) vs. 0.2(0-0.3)), p < 0.01) compared to children with suboptimal short-term control(n = 26), no significant differences were found in parameters of sleep architecture. Obstructive sleep apnea (OSA) was diagnosed in only one T1D patient, nine T1D children had mild central apnea.

CONCLUSIONS

There may be an association between short-term metabolic compensation and SDB in T1D children without chronic complications, obesity or overweight and hypoglycemia. Further research is needed to confirm this result.

Cardiovascular Autonomic Neuropathy and Glucose Variability in Patients With Type 1 Diabetes: Is There an Association?

INTRODUCTION

The oxidative stress associated with glucose variability might be responsible for neuronal damage while autonomic neuropathy (AN) has a detrimental effect on metabolism. The aim of the study was to find relationship between AN and GV in type 1 diabetic patients and to identify further factors that affect GV.

PATIENTS AND METHODS

Twenty type 1 diabetic patients were involved (age: 39.5 ± 3.4 years, duration of diabetes: 17.5 ± 2.5 years; HbA1c: 8.1 ± 0.2%, mean ± SE). AN was assessed by the cardiovascular reflex tests. The interstitial glucose levels were determined following insertion of a subcutaneous electrode during the continuous glucose monitoring (CGM) method on six consecutive days. GV was characterized by calculation of four parameters.

RESULTS

SD of interstitial glucose values correlated positively with the overall AN score and the degree of the orthostatic reduction of systolic blood pressure (AN-score-SD ρ = 0.47, p < 0.05; orthostasis-SD: ρ = 0.51, p < 0.05). Mean absolute glucose (MAG) correlated with three parameters of AN (AN-score-MAG: ρ = 0.62, p < 0.01; 30/15 ratio-MAG: ρ = -0.50, p < 0.05; orthostasis-MAG: ρ = 0.59, p < 0.01). The HbA1c also correlated with two parameters of GV (HbA1c-continuous overlapping net glycemic action: ρ = 0.56, p < 0.05; HbA1c-MAG: ρ = 0.45, p < 0.05). The frequency of hypoglycemia did not exhibit any correlation with measures of GV.

CONCLUSION

Severity of glucose variability but not overall glucose load correlates with both parasympathetic and sympathetic dysfunctions in type 1 diabetes. Higher HbA1c is associated with more severe glucose variability. The observed correlation between increased glucose variability and the severity of AN necessitates the further exploration of this relationship.

Obstructive Sleep Apnea and Diabetes: A State of the Art Review

OSA is a chronic treatable sleep disorder and a frequent comorbidity in patients with type 2 diabetes. Cardinal features of OSA, including intermittent hypoxemia and sleep fragmentation, have been linked to abnormal glucose metabolism in laboratory-based experiments. OSA has also been linked to the development of incident type 2 diabetes. The relationship between OSA and type 2 diabetes may be bidirectional in nature given that diabetic neuropathy can affect central control of respiration and upper airway neural reflexes, promoting sleep-disordered breathing. Despite the strong association between OSA and type 2 diabetes, the effect of treatment with CPAP on markers of glucose metabolism has been conflicting. Variability with CPAP adherence may be one of the key factors behind these conflicting results. Finally, accumulating data suggest an association between OSA and type 1 diabetes as well as gestational diabetes. This review explores the role of OSA in the pathogenesis of type 2 diabetes, glucose metabolism dysregulation, and the impact of OSA treatment on glucose metabolism. The association between OSA and diabetic complications as well as gestational diabetes is also reviewed.

Cardiac autonomic neuropathy in patients with diabetes mellitus: current perspectives

Cardiac autonomic neuropathy (CAN) is a common and often-underdiagnosed complication of diabetes mellitus (DM). CAN is associated with increased mortality, cardiovascular disease, chronic kidney disease, and morbidity in patients with DM, but despite these significant consequences CAN often remains undiagnosed for a prolonged period. This is commonly due to the disease being asymptomatic until the later stages, as well as a lack of easily available screening strategies. In this article, we review the latest developments in the epidemiology, pathogenesis, diagnosis, consequences, and treatments of CAN in patients with DM.

Type 1 Diabetes and Sleep

IN BRIEF In people with type 1 diabetes, sleep may be disrupted as a result of both behavioral and physiological aspects of diabetes and its management. This sleep disruption may negatively affect disease progression and development of complications. This review highlights key research findings regarding sleep in people with type 1 diabetes.