Prevalence of obstructive sleep apnoea syndrome in hospitalized patients with type 2 diabetes in Beijing, China

Aneurysmal subarachnoid hemorrhage occurring during sleep: Clinical characteristics and risk factors

BACKGROUND

Aneurysmal subarachnoid hemorrhage (aSAH) is known to be triggered by several specific human activities. Sleep, by contrast, has not been considered a triggering activity for aSAH, and clinical characteristics of patients who sustain aSAH during sleep have rarely been reported in the literature.

METHODS

This is a retrospective analysis on the data acquired through a multicenter aSAH registry. Between January 2019 and December 2021, a total of 732 aSAH patients had been registered into our database. After excluding 109 patients whose activities at aSAH onset had been unidentifiable, the remaining 623 aSAH patients were dichotomized to 59 patients who sustained aSAH during sleep (Sleep group) and 564 patients who sustained aSAH during daytime activities (Awake group). Two-group comparison of demographic variables and multivariate logistic regression analysis were performed to clarify their clinical characteristics and identify potential risk factors.

RESULTS

The Sleep group exhibited significantly higher frequencies of diabetes (15.5 % vs. 6.4 %, p = 0.01) and antiplatelet use (13.8 % vs. 4.6 %, p=0.004) than the Awake group. Furthermore, multivariate logistic regression analysis showed that diabetes (OR, 3.051; 95 % CI, 1.281-7.268; p = 0.012) and antiplatelet use (OR, 3.640; 95 % CI, 1.422-9.316; p = 0.007) were correlated with aSAH occurring during sleep. There were no significant inter-group differences in the patient outcomes evaluated at discharge.

CONCLUSION

The current results indicate that risk factors may exist for aSAH occurring during sleep. Further investigations on how comorbidities such as diabetes, antiplatelet use and sleep apnea affect human hemodynamic and hemostatic parameters during sleep is warranted to better understand those relationships.

Explanatory variables of objectively measured 24-h movement behaviors in people with prediabetes and type 2 diabetes: A systematic review

AIM

Physical activity (PA), sedentary behavior (SB) and sleep (i.e. 24-h movement behaviors) are associated with health indicators in people with prediabetes and type 2 diabetes (T2D). To optimize 24-h movement behaviors, it is crucial to identify explanatory variables related to these behaviors. This review aimed to summarize the explanatory variables of 24-h movement behaviors in people with prediabetes or T2D.

METHODS

A systematic search of four databases (PubMed, Web of Science, Scopus & Embase) was performed. Only objective measurements of 24-h movement behaviors were included in the search strategy. The explanatory variables were classified according to the levels of the socio-ecological model (i.e. intrapersonal, interpersonal and environmental). The risk of bias was assessed using the Joanna Briggs Institute appraisal checklist.

RESULTS

None of the 78 included studies investigated 24-h movement behaviors. The majority of the studies investigated PA in isolation. Most studied explanatory variables were situated at the intrapersonal level. Being male was associated with more moderate to vigorous PA but less light PA in people with T2D, and more total PA in people with prediabetes. An older age was associated with a decrease in all levels of PA in people with T2D. HbA1c was positively associated with sleep and SB in both groups. No associations were found at the interpersonal or environmental level.

CONCLUSION

The results of this review underscore the lack of a socio-ecological approach toward explanatory variables of 24-h movement behaviors and the lack of focus on an integrated 24-h movement behavior approach in both populations.

[Diabetes and obstructive sleep apnoea: A case-control study]

INTRODUCTION

Obstructive sleep apnoea (OSA) and diabetes mellitus (DM) are very prevalent diseases frequently associated. Their coexistence is independently associated with an increased prevalence of cardiovascular comorbidities. As this association is underdiagnosed, it is necessary to optimise clinical suspicion by studying independent predictors of DM or prediabetes (preDM) in patients with OSA.

METHOD

A simple randomised case-control study, matched for sex, body mass index (BMI) and age, aimed to study the association of OSA with DM and preDM and to identify independent predictors for both diseases in people with OSA.

RESULTS

We included 208 cases with OSA and 208 controls without OSA. In the former, 18.8% had DM compared to only 10.1% in the latter (P=.00). Prevalence of preDM was 41.8% vs. 10.6%, respectively (P=.00). One hundred and twenty-four cases (59.6%) reported excessive daytime sleepiness (EDS) (Epworth scale, 10.5±3.1) vs. 24.5% of the control group (Epworth scale, 6.6±2.9). Apnoea-hypopnoea index (AHI) and O2 desaturation indices (IDO, CT90 and CT80) were significantly higher in the case group. The risk of MD was related to age, nocturnal hypoxaemia and EDS. The risk of pre-MD was related to BMI and AHI.

CONCLUSIONS

OSA is associated with DM and preDM. Age, nocturnal hypoxaemia and EDS are predictors of DM. BMI and AHI are predictors of pre-MD.

Scanning of obstructive sleep apnea syndrome using smartwatch: A comparison of smartwatch and polysomnography

BACKGROUND

Obstructive Sleep Apnea Syndrome (OSAS), which significantly impairs nighttime sleep quality and causes excessive daytime sleepiness, not only reduces the quality of life of patients, but also increases the social and socioeconomic burden. Wearable-noninvasive devices can provide faster OSAS screening and follow-up. Smartwatches as an objective, non-invasive, practical and relatively inexpensive method, they are attractive candidates for pre-evaluation of OSAS and referral to a physician. In this study, it was aimed to evaluate the effectiveness of a smart watch in detecting OSAS findings compared to the gold standard polysomnograhy (PSG).

METHODS

PSG data of the study group were compared with data such as SpO2, heart rate and saturation obtained by smartwatch from both sides, and the Cohen's kappa was used to measure for two methods and predictive values were evaluated.

RESULTS

A total of 115 participants [44 female (38.3%), mean age (SD): 49.24 (11.39)] were enrolled. 75 (65.22%) of the participants were diagnosed with OSAS, of which 29 (25.22%) participants have severe OSAS. The smartwatch showed good sensitivity (75% to 96%), specificity (79% to 91%), and diagnostic accuracy (AUC: 0.84 to 0.93) in predicting apnea and severe apnea, respectively. The highest agreement between PSG and smartwatch and the diagnostic ability of smartwatch were found in persons with severe OSAS.

CONCLUSION

The high PPV-NPV values in our study and the good compatibility coefficient of the smart watch with the PSG device can contribute to the expansion of the usage areas of smart watches that come into the lives of many people in daily practice.

Subclinical hypothyroidism increases insulin resistance in normoglycemic people

Objective

To investigate the effect of simple subclinical hypothyroidism (SCH) and type 2 diabetes mellitus (T2DM) combined with SCH on insulin resistance.

Design and methods

A total of 622 people with newly diagnosed T2DM were selected as the study subjects, and 621 normoglycemic people were selected as control subjects. According to the diagnostic criteria of thyroid diseases, the subjects were divided into a normal thyroid function group and a subclinical hypothyroidism group. Both groups received a physical examination, and blood samples were collected. The measurement indexes included FPG, FINS, OGTT2hPG, OGTT2hINS, HbA1c, TC, TG, HDL-C, LDL-C, TSH, FT3 and FT4. HOMA-IR, HOMA-β, and TFQI (thyroid feedback quantile index) were calculated.

Results

There was no significant difference in age or sex distribution between the T2DM group and the normoglycemic group (P>0.05). The prevalence of thyroid dysfunction in the T2DM group was significantly higher than that in the normoglycemic group (16.39% vs. 11.27%, P<0.05), and among the different types of thyroid dysfunction, the prevalence of SCH was the highest at 14.95% (P<0.05). There was no significant difference in BMI, waist-hip ratio, blood lipid profile, HOMA-β, and HOMA-IR values between the T2DM with subclinical hypothyroidism group (T2DM+SCH+ group) and the normal thyroid function group (T2DM+SCH- group) (P>0.05). The BMI, waist-hip ratio and HOMA-IR values of the normoglycemic group with subclinical hypothyroidism (T2DM-SCH+ group) were significantly higher than those of the normoglycemic group with normal thyroid function (T2DM-SCH- group) (P<0.05), and there were no significant differences between the T2DM+SCH- and T2DM+SCH+ groups (P>0.05). HOMA-β values were significantly higher in the T2DM-SCH+ group than in the T2DM-SCH-, T2DM+SCH- and T2DM+SCH+ groups (P<0.05). As the TFQI value increased, the body weight, waist-hip ratio, diastolic blood pressure, FPG, OGTT2hPG and HbA1c values gradually increased in the T2DM group and normoglycemic group (P<0.05). HDL-C, FINS, OGTT2hINS and HOMA-β values gradually decreased (P<0.05).

Conclusion

Subclinical hypothyroidism only increases insulin resistance in normoglycemic people. As the sensitivity of the central thyroid decreases, the risk of developing diabetes increases.

Pathophysiological mechanisms and therapeutic approaches in obstructive sleep apnea syndrome

Obstructive sleep apnea syndrome (OSAS) is a common breathing disorder in sleep in which the airways narrow or collapse during sleep, causing obstructive sleep apnea. The prevalence of OSAS continues to rise worldwide, particularly in middle-aged and elderly individuals. The mechanism of upper airway collapse is incompletely understood but is associated with several factors, including obesity, craniofacial changes, altered muscle function in the upper airway, pharyngeal neuropathy, and fluid shifts to the neck. The main characteristics of OSAS are recurrent pauses in respiration, which lead to intermittent hypoxia (IH) and hypercapnia, accompanied by blood oxygen desaturation and arousal during sleep, which sharply increases the risk of several diseases. This paper first briefly describes the epidemiology, incidence, and pathophysiological mechanisms of OSAS. Next, the alterations in relevant signaling pathways induced by IH are systematically reviewed and discussed. For example, IH can induce gut microbiota (GM) dysbiosis, impair the intestinal barrier, and alter intestinal metabolites. These mechanisms ultimately lead to secondary oxidative stress, systemic inflammation, and sympathetic activation. We then summarize the effects of IH on disease pathogenesis, including cardiocerebrovascular disorders, neurological disorders, metabolic diseases, cancer, reproductive disorders, and COVID-19. Finally, different therapeutic strategies for OSAS caused by different causes are proposed. Multidisciplinary approaches and shared decision-making are necessary for the successful treatment of OSAS in the future, but more randomized controlled trials are needed for further evaluation to define what treatments are best for specific OSAS patients.