Coronavirus disease 2019 (COVID-19) pandemic may exert adverse impacts on sleep among populations, which may raise awareness of the burden of sleep disturbance, and the demand of intervention strategies for different populations. We aimed to summarize the current evidence for the impacts of COVID-19 on sleep in patients with COVID-19, healthcare workers (HWs), and the general population. We searched PubMed and Embase for studies on the prevalence of sleep disturbance. Totally, 86 studies were included in the review, including 16 studies for COVID-19 patients, 34 studies for HWs, and 36 studies for the general population. The prevalence of sleep disturbance was 33.3%–84.7%, and 29.5–40% in hospitalized COVID-19 patients and discharged COVID-19 survivors, respectively. Physiologic and psychological traumatic effects of the infection may interact with environmental factors to increase the risk of sleep disturbance in COVID-19 patients. The prevalence of sleep disturbance was 18.4–84.7% in HWs, and the contributors mainly included high workloads and shift work, occupation-related factors, and psychological factors. The prevalence of sleep disturbance was 17.65–81% in the general population. Physiologic and social-psychological factors contributed to sleep disturbance of the general population during COVID-19 pandemic. In summary, the sleep disturbance was highly prevalent during COVID-19 pandemic. Specific health strategies should be implemented to tackle sleep disturbance.

ObjectiveWhether the severity of obstructive sleep apnea (OSA) contributes to clinical polycythemia is uncertain, especially in young adults. This study aimed to assess the correlation between untreated OSA and polycythemia, controlling for multiple confounders, and to observe the difference in both genders.MethodsAll participants underwent nocturnal polysomnography. Medical comorbidities, and demographic and laboratory information were also recorded. The relationship between OSA and concomitant polycythemia in both genders was analyzed.ResultsA total of 605 young participants (383 men and 222 women), aged 30.52 ± 7.21 years, were enrolled, with an average body mass index of 32.48 ± 6.06 kg/m2. Although 74.4% of patients were diagnosed with OSA, less than 10% had polycythemia. The levels of hemoglobin and hematocrit increased with the severity of OSA; only men with severe OSA had significantly higher hemoglobin, hematocrit, and polycythemia compared with those in the control group (P < 0.01). Hemoglobin and hematocrit significantly correlated with mean pulse oxygen saturation (SpO2) (P < 0.001), but the correlation coefficients were weaker in women than in men. In logistic regression analysis, mean SpO2, but not the apnea–hypopnea index (AHI), was found to be an independent predictor of polycythemia (P < 0.05). Areas under the receive operator characteristic analysis revealed that the cutoff values of hemoglobin and hematocrit were 155.5g/L and 44.6% (P < 0.001), respectively, for assessing nocturnal hypoxemia in men with OSA.ConclusionNocturnal mean SpO2 was an independent predictor of polycythemia in young adults. Mean SpO2, compared with the AHI, was more associated with polycythemia. Men were more prone to suffer from polycythemia compared with women. Hemoglobin and hematocrit values might have diagnostic utility for assessing nocturnal hypoxia severity of OSA patients, especially in men.

No abstract

Printed circuits and electronics are widely implemented in a variety of emerging areas including solar power panel, wearable devices, screen display, etc. Recently, gallium‐based alloys become promising candidates in applications ranging from flexible electronics to efficient cooling due to its high conductivity, fluidity, and nontoxicity. However, the implementation of liquid metal printing is highly restricted to its adhesion with different substrates. The adhesiveness can be enhanced by promoting the oxidation such as intensive stirring, whereas the fluidity would be severely confined. Aiming to tackle the existing challenges, here the authors propose a facile liquid metal printed electronics method through spraying a customized superhydrophobic film upon the substrate and then forming desired patterns via selective adhesion of liquid metal. The required customization can be realized via removable mask or surface energy variation. The presented strategy demonstrates excellent substrate adaptability including glass, plastic, paper, carbon fiber composite, ceramic, etc. Besides, complex 3D circuits can be created upon curved surfaces of diversified geometries. Sprayed liquid metal can be easily recycled, which is beneficial to an environmental and sustainable production. This work suggests a potential direction for liquid metal circuit fabrication and may enlighten other studies to resolve liquid metal contamination, flow friction, etc.

No abstract

Background: Mechanical ventilation (MV) with positive end-expiratory pressure (PEEP) is commonly applied in patients with severe traumatic brain injury (sTBI). However, the individual responsiveness of intracranial pressure (ICP) to PEEP varies. Thus, identifying an indicator detecting ICP responsiveness to PEEP is of great significance. As central venous pressure (CVP) could act as an intermediary to transduce pressure from PEEP to ICP, we developed a new indicator, P IC Gap, representing the gap between baseline ICP and baseline CVP. The aim of the current study was to explore the relationship between P IC Gap and ICP responsiveness to PEEP. Methods: A total of 112 patients with sTBI undergoing MV were enrolled in this prospective cohort study. ICP, CVP, cerebral perfusion pressure (CPP), static compliance of the respiratory system (Cst), and end-tidal carbon dioxide pressure (PetCO 2) were recorded at the initial (3 cmH 2 O) and adjusted (15 cmH 2 O) levels of PEEP. P IC Gap was assessed as baseline ICP-baseline CVP (when PEEP = 3 cmH 2 O). The patients were classified into the ICP responder and non-responder groups based on whether ICP increment with PEEP adjusted from 3 cmH 2 O to 15 cmH 2 O was greater than 20% of baseline ICP. The above parameters were compared between the two groups, and prediction of ICP responsiveness to PEEP adjustment was evaluated by receiver operating characteristic (ROC) curve analysis. Results: Compared with the non-responder group, the responder group had lower P IC Gap (1.63 ± 1.33 versus 6.56 ± 2.46 mmHg; p < 0.001), lower baseline ICP, and higher baseline CVP. ROC curve analysis suggested that P IC Gap was a stronger predictive indicator of ICP responsiveness to PEEP (AUC = 0.957, 95%CI 0.918-0.996; p < 0.001) compared with baseline ICP and baseline CVP, with favorable sensitivity (95.24, 95%CI 86.91-98.70%) and specificity (87.6, 95%CI 75.76-94.27%), at a cut off value of 2.5 mmHg.

ObjectivesObstructive sleep apnoea (OSA) has received much attention as a risk factor for perioperative complications and 68.5% of OSA patients remain undiagnosed before surgery. Faciocervical characteristics may screen OSA for Asians due to smaller upper airways compared with Caucasians. Thus, our study aimed to explore a machine-learning model to screen moderate to severe OSA based on faciocervical and anthropometric measurements.DesignA cross-sectional study.SettingData were collected from the Shanghai Jiao Tong University School of Medicine affiliated Ruijin Hospital between February 2019 and August 2020.ParticipantsA total of 481 Chinese participants were included in the study.Primary and secondary outcome(1) Identification of moderate to severe OSA with apnoea–hypopnoea index 15 events/hour and (2) Verification of the machine-learning model.ResultsSex-Age-Body mass index (BMI)-maximum Interincisal distance-ratio of Height to thyrosternum distance-neck Circumference-waist Circumference (SABIHC2) model was set up. The SABIHC2 model could screen moderate to severe OSA with an area under the curve (AUC)=0.832, the sensitivity of 0.916 and specificity of 0.749, and performed better than the STOP-BANG (snoring, tiredness, observed apnea, high blood pressure, BMI, age, neck circumference, and male gender) questionnaire, which showed AUC=0.631, the sensitivity of 0.487 and specificity of 0.772. Especially for asymptomatic patients (Epworth Sleepiness Scale <10), the SABIHC2 model demonstrated better predictive ability compared with the STOP-BANG questionnaire, with AUC (0.824 vs 0.530), sensitivity (0.892 vs 0.348) and specificity (0.755 vs 0.809).ConclusionThe SABIHC2 machine-learning model provides a simple and accurate assessment of moderate to severe OSA in the Chinese population, especially for those without significant daytime sleepiness.

Noxious particulate matter in the air is a primary cause of chronic obstructive pulmonary disease (COPD). The bronchial tree acts to filter these materials in the air and preserve the integrity of the bronchi. Accumulating evidence has demonstrated that smoking and air pollutants are the most prominent risk factors of COPD. Bifurcations in the airway may act as deposition sites for the retention of inhaled particles, however, little is known concerning the impacts of abnormalities of the bronchial anatomy in the pathogenesis of COPD. Studies have reported significant associations between bronchial variations and the symptoms in COPD. In particular, it has been shown that bronchial variations in the central airway tree may contribute to the development of COPD. In this review, we identified three common types of bronchial variation that were used to formulate a unifying hypothesis to explain how bronchial variations contribute to the development of COPD. We also investigated the current evidence for the involvement of specific genes including fibroblast growth factor 10 ( Fgf10 ) and bone morphogenetic protein 4 ( Bmp4 ) in the formation of bronchial variation. Finally, we highlight novel assessment strategies and opportunities for future research of bronchial variations and genetic susceptibility in COPD and comorbidities. Our data strongly highlight the role of bronchial variations in the development, complications, and acute exacerbation of COPD.