Effectiveness of Vitamin C Solution in Reducing Adverse Reactions Caused by Painless Lugol Chromoendoscopy: A Multicenter Randomized Controlled Trial.

GOAL: The purpose of this study was to evaluate the effectiveness of vitamin C solution (VCS) in reducing adverse reactions caused by painless Lugol chromoendoscopy. BACKGROUND: Lugol chromoendoscopy is an effective method for screening superficial esophageal squamous cell carcinoma, although Lugol iodine solution (LIS) causes mucosal irritation. STUDY: In 4 hospitals in China, patients were randomized and divided into a distilled water (DW) group, an sodium thiosulfate solution (STS) group and a VCS group. Patients' esophageal mucosal surfaces were stained with either 1.2% or 0.5% LIS and then sprayed with DW, STS, or VCS at various concentrations. For the current randomized study, 1610 patients were enrolled in the 1.2% LIS group and 1355 patients were enrolled in the 0.5% LIS group. In addition, 150 patients were enrolled to assess the discoloration effect. The primary outcome for evaluation was the incidence of acute or late adverse reactions after Lugol iodine staining. The secondary outcome for evaluation was the discoloration effect on esophageal iodine-stained mucosa. RESULTS: VCS significantly reduced the occurrence of acute adverse reactions due to staining from 1.2% LIS. The effect of VCS was similar to that of STS but better than that of DW ( P <0.05). Regarding 0.5% LIS staining, VCS reduced the incidence of acute adverse reactions and heartburn within 1 week ( P <0.05). Both VCS and STS had similar effects. In addition, compared with spraying NS, VCS caused rapid decolorization of iodine-stained esophageal mucosa. After 120 seconds of deiodination, the color of the esophageal mucosa faded by 90%, which is similar to the results seen in the STS group. This contrasts with the results seen in the DW group, which showed fading by only 50.97% ( P <0.05). CONCLUSION: VCS can effectively reduce adverse reactions caused by different concentrations of LIS, indicating its important clinical application in the screening of superficial esophageal squamous cell carcinoma.

Lower 24-h urinary potassium excretion is negatively associated with excessive daytime sleepiness in the general population.

OBJECTIVES: Uncertainty remains about the association of potassium (K) intake and sleepiness. Therefore, we aimed to explore the relationship between K excretion using 24-h urine samples and excessive daytime sleepiness (EDS) in the general population. METHODS: In a cross-sectional study, we used multi-stage proportional random sampling to obtain a study sample aged ≥ 18 years from Emin, China between March and June 2019. We collected timed 24-h urine specimens and conducted EDS assessments using the Epworth Sleepiness Scale (ESS) questionnaire. Subjects were divided into two groups by the median of 24-h urinary potassium (24-h UK). EDS was defined as ESS score ≥ 10. Multi-variable linear regression was used to examine the association between the 24-h UK and the odds of prevalent EDS. We performed a sensitivity analysis by excluding subjects under anti-hypertensive treatment and those with sleep disordered breathing by the NoSAS scale. RESULTS: A total of 470 participants with complete 24-h urine samples and ESS data (62% women, mean age 49.6 years, mean ESS score of 9.0 ± 5.2) were enrolled. The mean ESS score was significantly lower in the upper half of 24-h UK group than in the lower half (9.5 ± 5.3 vs 8.5 ± 5.1, P = 0.044), and accordingly, prevalent EDS was significantly greater in the lower half than in the higher half (49% vs 40%, P = 0.039). In further improving the propensity matching score, the results remained consistent with the overall results. In multiple linear regression, 24-h UK was negatively correlated with ESS score (ß = - 0.180 (- 0.276, - 0.085), < 0.001). Sensitivity analysis demonstrated augmented results in those without anti-hypertensive treatment. CONCLUSION: Lower potassium intake, as suggested by lower UK excretion, may be implicated in the presence of EDS in the general population.

Secondhand smoke is associated with poor sleep quality in self-reported never-smokers of Northwest China: a cross-sectional study.

OBJECTIVE: To investigate the relationship between secondhand smoke (SHS) exposure and sleep quality in never-smokers of Northwest China. METHODS: Never-smoking adults (≥ 15 years) from Xinjiang, Northwest China, were included in this cross-sectional survey between April and October 2019. SHS exposure in never-smokers was estimated using a structured questionnaire. Sleep quality was evaluated by Pittsburgh Sleep Quality Index (PSQI), with PSQI score > 5 classified as poor sleep quality. Association of SHS exposure and frequency and duration of SHS exposure with poor sleep quality were analyzed by using a multivariate logistic regression after adjusting for potential confounding factors, including stratification by sex. RESULTS: The mean age of participants was 48.0 years, and 77% were females. Of 21,198 never-smokers, 13% (n = 2703) reported SHS exposure and 35% (n = 7390) reported poor sleep quality. In multivariate logistic regression analysis, a significant association was observed between SHS exposure and poor sleep quality (adjusted odds ratio (OR), 1.36; 95% confidence interval (CI) 1.24-1.48). Subgroup analysis showed a negative association of SHS exposure with sleep quality in both sexes. However, a significant dose-response relationship of frequency and duration of SHS exposure per week with poor sleep quality was observed only in females. Consistent results were also observed in the aged ≥ 18 years. CONCLUSION: Exposure to SHS is associated with poor sleep quality in never-smoking adults of Northwest China. A dose-response relationship between SHS exposure and poor sleep quality is found in women. Avoiding SHS exposure may have beneficial effects on sleep quality, especially for females.

Poor sleep quality is negatively associated with low cognitive performance in general population independent of self-reported sleep disordered breathing.

BACKGROUND: Sleep disordered breathing (SDB) plays a significant role in both sleep quality and cognition and whether it has an impact on the relationship between above two factors remains to be clear. The study aimed to explore the association between sleep quality and cognitive performance in general population by considering influence of sleep disordered breathing (SDB). METHODS: In this cross-sectional study, we enrolled subjects aged ≥ 18 years using a multi-stage random sampling method. Cognitive status was assessed using Mini Mental State Examination (MMSE) questionnaire, sleep quality using Pittsburgh Sleep Quality Index (PSQI) and SDB was assessed using No-SAS scale, respectively. Multi-variable logistic regression was applied to examine the association of sleep quality and cognitive performance. Subgroup analyses were performed in different age groups, and in those with and without SDB. RESULTS: Finally, 30,872 participants aged 47.5 ± 13.8 years with 53.5% women were enrolled, of whom 32.4% had poor sleep quality and 18.6% had low cognitive performance. Compared with good sleepers, subjects with poor sleep quality exhibited significantly higher presence of low cognitive performance (23.7% vs 16.2%, P < 0.001). Poor sleepers revealed 1.26 (95%CI: 1.16,1.36), 1.26 (1.08,1.46) and 1.25 (1.14,1.37) fold odds for low cognitive performance in general population and in subjects with and without self-reported SDB respectively. Stratified by age and SDB, the association was observed in young and middle-aged group without SDB (OR = 1.44, 95%CI: 1.30,1.59) and in the elderly group with SDB (OR = 1.30, 95%CI: 1.07,1.58). CONCLUSIONS: Sleep quality is in a negative association with cognitive performance in general population independent of SDB, implying improvement of sleep disturbances is a potential objective of intervention strategies for cognitive protection at population level.

Association of Hypertension with Mild Cognitive Impairment in Population from Less-Developed Areas of Multiethnic Northwest China.

BACKGROUND: Relationship between hypertension and mild cognitive impairment (MCI) remains undetermined in population from less-developed regions. We aimed to explore whether hypertension is associated with MCI in this specific population. METHODS: In this cross-sectional study, we enrolled subjects aged ≥18 years using multistage random sampling from Emin, China, in 2019. Participants underwent questionnaires and data collection including mini-mental state examination (MMSE) and blood pressure measurement. RESULTS: Finally, 31,329 subjects were included, with 11,270 hypertensives. Compared with normotensive subjects, hypertensives were characterized by significantly older age (55.19 ± 12.25 vs. 43.26 ± 12.71), more men (52.5% vs. 42.9%), low education attainment (≤primary education: 42.4% vs. 26.3%), more abdominal obesity (39.7% vs. 19.1%), poor sleep quality (39.1% vs. 28.7%), and chronic kidney disease (6.6% vs. 3.4%, p for all <0.001). Prevalence of MCI in hypertensives was significantly higher than that of normotensive subjects (24.3% vs. 15.6%, p < 0.001). Multivariate logistic regression analysis showed in a fully adjusted model that the odds for MCI were significantly increased in hypertensives than in normotensive population (OR = 1.19, 95% CI: 1.09, 1.30, p < 0.001) and independent of all the parameters studied including age, education level, and stroke. In the age-stratified regression model, presence of hypertension significantly increased the odds of MCI by 1.17-fold (95% CI: 1.03, 1.33, p = 0.020) and by 1.22-fold (95% CI: 1.04, 1.44, p = 0.016) in middle-aged and elderly population. Sensitivity analysis of excluding those with stroke history showed that hypertension was still a risk factor for MCI in total, middle-aged, and elderly population. CONCLUSION: Hypertension is in independent negative association with MCI in middle-aged and elderly population from underdeveloped regions.

Association between 24-h urinary sodium to potassium ratio and mild cognitive impairment in community-based general population.

OBJECTIVE: To explore the relationship between parameters of Na and K excretion using 24-h urine sample and mild cognitive impairment (MCI) in general population. DESIGN: This is a cross-sectional study. SETTING: Community-based general population in Emin China. PARTICIPANTS: Totally, 1147 subjects aged ≥18 years were selected to complete the study, with a multistage proportional random sampling method. Cognitive status was assessed with Mini Mental State Examination (MMSE) questionnaire and timed 24-h urine specimens were collected. Finally, 561 participants aged ≥35 years with complete urine sample and MMSE data were included for the current analysis and divided into groups by tertiles of 24-h urinary sodium to potassium ratio (24-h UNa/K) as lowest (T1), middle (T2) and highest (T3) groups. RESULTS: The MMSE score was significantly lower in T3, compared with the T1 group (26·0 v. 25·0, P = 0·002), and the prevalent MCI was significantly higher in T3 than in T1 group (11·7 % v. 25·8 %, P < 0·001). In multiple linear regression, 24-UNa/K (ß: -0·184, 95 % CI -0·319, -0·050, P = 0·007) was negatively associated with MMSE score. In multivariable logistic regression, compared with T1 group, 24-h UNa/K in the T2 and T3 groups showed 2·01 (95 % CI 1·03, 3·93, P = 0·041) and 3·38 (95 % CI 1·77, 6·44, P < 0·001) fold odds for presence of MCI, even after adjustment for confounders. More augmented results were demonstrated in sensitivity analysis by excluding individuals taking anti-hypertensive agents. CONCLUSIONS: Higher 24-h UNa/K is in an independent association with prevalent MCI.

A systematic review and meta-analysis of effects of spironolactone on blood pressure, glucose, lipids, renal function, fibrosis and inflammation in patients with hypertension and diabetes.

PURPOSE: Hypertension commonly co-exists with diabetes mellitus (DM), and both are closely related to adverse health outcomes. The activation of aldosterone and mineralocorticoid receptor (MR) may play important roles in this process. Therefore, we aim to evaluate the efficacy of MR antagonists on cardiovascular risk factors, including blood pressure (BP), glucose, lipids, renal function, fibrosis and inflammatory and its safety in patients with both hypertension and DM. METHODS: We searched PubMed, Embase, Web of Science and Cochrane databases for clinical trials published until December 31, 2019. Studies comparing the effect of spironolactone to placebo in patients with hypertension and DM were included. Mean difference with 95% confidence intervals was used to report outcomes. RESULTS: Eleven randomised placebo-controlled trials with 640 participants were finally included with mean follow-up of 5 months. Compared to placebo, spironolactone significantly reduced office systolic (-6.57, 95%CI: -9.21, -3.93) and diastolic BP (-2.63, 95%CI: -4.25, -1.02) as well as ambulatory BP; increased glycosylated haemoglobin by 0.3 but no clear effect on fasting glucose. Spironolactone induced a significantly reduction of urinary albumin but increased serum creatinine (7.60, 95%CI: 4.94, 10.27) and decreased glomerular filtration rate (-4.28, 95%CI: -6.38, -2.18). Markers of fibrosis and inflammation, including NIIINP, PICP, hs-CRP and TNF-α were also decreased after spironolactone therapy. For lipid metabolism, there was no significant difference between groups. Spironolactone mildly increased serum potassium (0.30, 95%CI: 0.23, 0.37). 2.5% subjects treated with spironolactone experienced mild to moderate hyperkalaemia and received medication or dietary advice and another 1.6% developed severe hyperkalaemia and withdrawn from the studies. CONCLUSION: Spironolactone reduced BP and urinary albumin, improve fibrosis and inflammation, whereas slightly increases the glycosylated haemoglobin and serum creatinine in patients with hypertension and diabetes. Long-term RCTs to assess the effects of spironolactone on cardiovascular events in this population are warranted.

Study of porphyrin-modified liquid exfoliated graphene field-effect transistors for evaluating DNA methylation degree.

The applications of graphene field-effect transistors (FETs) for monitoring DNA hybridization have been widely accepted; however, for evaluating DNA methylation degree, an emerging requirement of epigenetic research, no work has been found due to the difficulties in detecting 5-methylcytosine (5mC) sites along the genomic sequence as well as counting their amount (NmC). Herein, to achieve this, a strategy for exploiting a liquid exfoliated graphene (LEG)-based FET (LEG-FET) as a sensing platform was proposed. First, LEG-FETs were prepared and activated by tetra-4-aminophenyl-porphyrin (TAPP) for anchoring single-strand DNAs (ssDNAs). Second, the 5mC sites in ssDNA were recognized by the specifically absorbed 5mC antibody (5mCab) and transduced to the changed currents (ΔIDS) by LEG-FET according to the integration of the methylation-immuno sensing principle and FET's working mechanism. Briefly, more 5mCab molecules could be captured by more 5mC sites, resulting in larger ΔIDS. The TAPP effects on LEG-FET were analyzed by SEM, Raman, AFM, and XPS characterizations as well as electronic measurements. The validity of this LEG-FET sensing platform for evaluating DNA methylation degree was proven step by step; this included the examinations of the synthesized ssDNAs with the known NmC and real ssDNA samples, whose methylation degrees were pre-determined by the gold-standard method, which is based on tedious bisulphite sequence operations and expensive mass spectrometry technology. Moreover, theoretical explanations were also provided for the sensing mechanism in the proposed DNA methylation analytical components. In conclusion, the positive and linear relations of IDS changing ratio vs. NmC as well as the detection limit of one 5mC site indicate that TAPP-modified LEG-FET can provide an alternative analytical tool to realize fast and economical DNA methylation evaluation.

Probiotics prevent Hirschsprung's disease-associated enterocolitis: a prospective multicenter randomized controlled trial.

BACKGROUND: Enterocolitis (EC) is the most common and serious postoperative complication of Hirschsprung's disease (HD). Probiotics potentially play a protective role in maintaining intestinal mucosal integrity. Based on the beneficial effects of probiotics, we hypothesized that oral probiotics could decrease the incidence and severity of Hirschsprung's disease-associated enterocolitis (HAEC). METHODS: We conducted a prospective, multicenter, randomized, and controlled trial to assess whether oral probiotics could decrease the incidence and severity of HAEC. HD patients were randomly assigned into the control group and probiotic-treated group. All children in probiotic-treated group were fed with probiotics per day for 4 weeks. In next 3 months, the incidence and severity of HAEC were analyzed. The peripheral blood T lymphocyte subsets and cytokines, including TNF-α, IFN-γ, IL-6, and IL-10, were analyzed by flow cytometry and enzyme immunoassay (EIA). RESULTS: Compared with the control group, the incidence of HAEC in the probiotic-treated group was significantly diminished. The severity of EC was also remarkably decreased. Furthermore, probiotics balanced T lymphocyte subsets. Moreover, pro-inflammatory cytokines TNF-α, IFN-γ, and IL-6 were significantly decreased and anti-inflammatory cytokine IL-10 was notably increased in probiotic-treated group. CONCLUSIONS: Probiotics not only significantly diminished the incidence but also decreased the severity of HAEC. Moreover, our study revealed that probiotics decreased pro-inflammatory cytokine and increased anti-inflammatory cytokine and furthermore balanced T lymphocytes (registered with ClinicalTrials.gov, NCT number: NCT01934959).

Co-infection of hepatitis E virus, Clonorchis sinensis, and Escherichia coli: A case report.

Hepatitis E virus (HEV) is a common cause of acute hepatitis that threatens human health worldwide. With the popularization of detection technology, the reports of hepatitis E have gradually increased. Here, we present a rare case of co-infection with hepatitis E viruses, Clonorchis sinensis and Escherichia coli. A 52-year-old man was hospitalized because of fatigue, jaundice, and nausea for more than 2 weeks. Laboratory tests showed elevated bilirubin, aminotransferase (ALT), and aspartate aminotransferase (AST); HEV-IgM was positive, and HEV-RNA could be detected. Moreover, parasites were found in the biliary drainage and the biliary culture, which suggested Escherichia coli. The patient was effectively treated with praziquantel, imipenem, and hepatoprotective drugs and his clinical symptoms were relieved after 2 months; total bilirubin decreased to 85.1 µmol/L, ALT decreased to 92.4 U/L, and AST decreased to 102 U/L.

A bidirectional thermal sensory leaky integrate-and-fire (LIF) neuron model based on bipolar NbOx volatile threshold devices with ultra-low operating current.

Brain-like artificial intelligence (AI) will become the main form and important platform in future computing. It will play an important and unique role in simulating brain functions, efficiently implementing AI algorithms, and improving computing power. Developing artificial neurons that can send facilitation/depression signals to artificial synapses, sense, and process temperature information is of great significance for achieving more efficient and compact brain-like computing systems. Herein, we have constructed a NbOx bipolar volatile threshold memristor, which could be operated by 1 µA ultra-low current and up to ∼104 switching ratios. By using a leaky integrate-and-fire (LIF) artificial neuron model, a bipolar LIF artificial neuron is constructed, which can realize the conventional threshold-driven firing, all-or-nothing spiking, refractory periods, and intensity-modulated frequency response bidirectionally at the positive/negative voltage stimulation, which will give the artificial synapse facilitation/depression signals. Furthermore, this bipolar LIF neuron can also explore different temperatures to output different signals, which could be constructed as a more compact thermal sensory neuron to avoid external harm to artificial robots. This study is of great significance for improving the computational efficiency of the system more effectively, achieving high integration density and low energy consumption artificial neural networks to meet the needs of brain-like neural computing.

Superlow Power Consumption Memristor Based on Borphyrin-Deoxyribonucleic Acid Composite Films as Artificial Synapse for Neuromorphic Computing.

Memristor synapses based on green and pollution-free organic materials are expected to facilitate biorealistic neuromorphic computing and to be an important step toward the next generation of green electronics. Metalloporphyrin is an organic compound that widely exists in nature with good biocompatibility and stable chemical properties, and has already been used to fabricate memristors. However, the application of metalloporphyrin-based memristors as synaptic devices still faces challenges, such as realizing a high switching ratio, low power consumption, and bidirectional conductance modulation. We developed a memristor that improves the resistive switching (RS) characteristics of Zn(II)meso-tetra(4-carboxyphenyl) porphine (ZnTCPP) by combining it with deoxyribonucleic acid (DNA) in a composite film. The as-fabricated ZnTCPP-DNA-based device showed excellent RS memory characteristics with a sufficiently high switching ratio of up to ∼104, super low power consumption of ∼39.56 nW, good cycling stability, and data retention capability. Moreover, bidirectional conductance modulation of the ZnTCPP-DNA-based device can be controlled by modulating the amplitudes, durations, and intervals of positive and negative pulses. The ZnTCPP-DNA-based device was used to successfully simulate a series of synaptic functions including long-term potentiation, long-term depression, spike time-dependent plasticity, paired-pulse facilitation, excitatory postsynaptic current, and human learning behavior, which demonstrates its potential applicability to neuromorphic devices. A two-layer artificial neural network was used to demonstrate the digit recognition ability of the ZnTCPP-DNA-based device, which reached 97.22% after 100 training iterations. These results create a new avenue for the research and development of green electronics and have major implications for green low-power neuromorphic computing in the future.

Memristors based on NdNiO3 nanocrystals film as sensory neurons for neuromorphic computing.

By mimicking the behavior of the human brain, artificial neural systems offer the possibility to further improve computing efficiency and solve the von Neumann bottleneck. In particular, neural systems with perceptual capability expand the application field and lay a good foundation for the construction of perceptual storage and computational systems. However, research on neurons with perceptual functions is still relatively scarce, with most works focusing on optoelectronic synapses. The neuron is important for neuromorphic computing systems because neurons output excitatory or inhibitory stimuli to regulate the weight of synapses. Therefore, the construction of sensory neurons is crucial to expand the application range of brain-like neural computing. Here, an artificial sensory neuron is proposed, which is constructed using a photosensitive bipolar threshold switching memristor based on NdNiO3 (NNO) nanocrystals. These metallic phase nanocrystals can not only enhance the local electric field, but also act as a reservoir for defects (VoS) to guide the growth of conductive filaments and stabilize the performance of the device. They present stable bipolar threshold switching behavior with a low 120 nW set power, and the operating voltages decreased in light due to photocarrier action. A leaky integrate firing (LIF) neuron has been realized, which achieved key biological neuron functions, such as all-or-nothing spiking, threshold-driven firing, refractory period, and spiking frequency modulation. The LIF neurons receiving optical inputs have the properties of an artificial sensory neuron. It could regulate the spiking output frequency at different light densities, which could be used for a ship approaching a port. This work provides a promising hardware implementation towards constructing high-performance artificial intelligence to assist ships at night in a sensory system.

TGF-ß1 Promotes Autophagy and Inhibits Apoptosis in Breast Cancer by Targeting TP63.

Background: Breast cancer (BC) is a prevalent female cancer, which has high morbidity and mortality. However, the pathogenesis of BC has not been fully elucidated. Studies have shown that TGF-ß1 plays an important role in regulating the balance between autophagy and apoptosis of tumor. We aim to clarify the specific mechanism of autophagy and apoptosis in breast cancer maintaining the tumor microenvironment. Methods: The clinical characteristics of 850 BC patients were retrieved from the TCGA database. Differentially expressed autophagy-related genes (DEARGs) between tumor and normal tissues were obtained by the Wilcox test. Through Cox proportional hazard regression analysis, the prognostic risk model was constructed and verified by the ROC curve. We used MDC staining, colony formation assay, CCK-8, flow cytometric analysis to confirm the importance of TGF-ß1 on the autophagy and apoptosis of breast cancer cells. Furthermore, western blot was performed to determine the relative expression of protein. The Kaplan-Meier Plotter database was utilized to identify the prognostic value of TP63. Results: We successfully constructed a prognostic risk model of breast cancer and screened out an autophagy-related prognostic gene -TP63. We predicted that TGF-ß1 and TP63 have a binding site in the JASPAR database as expected. Additionally, TGF-ß1 promoted autophagy and inhibited apoptosis of breast cancer cells by inhibiting the expression of TP63. Conclusion: Our study demonstrated that the molecular mechanism of TGF-ß/TP63 signaling in regulating autophagy and apoptosis of breast cancer and provided a potential prognostic marker in breast cancer.

Superlow Power Consumption Artificial Synapses Based on WSe2 Quantum Dots Memristor for Neuromorphic Computing.

As the emerging member of zero-dimension transition metal dichalcogenide, WSe2 quantum dots (QDs) have been applied to memristors and exhibited better resistance switching characteristics and miniaturization size. However, low power consumption and high reliability are still challenges for WSe2 QDs-based memristors as synaptic devices. Here, we demonstrate a high-performance, superlow power consumption memristor device with the structure of Ag/WSe2 QDs/La0.3Sr0.7MnO3/SrTiO3. The device displays excellent resistive switching memory behavior with a R OFF/R ON ratio of ~5 × 103, power consumption per switching as low as 0.16 nW, very low set, and reset voltage of ~0.52 V and~ -0.19 V with excellent cycling stability, good reproducibility, and decent data retention capability. The superlow power consumption characteristic of the device is further proved by the method of density functional theory calculation. In addition, the influence of pulse amplitude, duration, and interval was studied to gradually modulating the conductance of the device. The memristor has also been demonstrated to simulate different functions of artificial synapses, such as excitatory postsynaptic current, spike timing-dependent plasticity, long-term potentiation, long-term depression, and paired-pulse facilitation. Importantly, digit recognition ability based on the WSe2 QDs device is evaluated through a three-layer artificial neural network, and the digit recognition accuracy after 40 times of training can reach up to 94.05%. This study paves a new way for the development of memristor devices with advanced significance for future low power neuromorphic computing.

24-hour urinary potassium excretion is negatively associated with self-reported sleep quality in the general population, independently of sleep-disordered breathing.

STUDY OBJECTIVES: To investigate the association of 24-hour urinary potassium excretion with self-reported sleep quality in the general population. METHODS: In this cross-sectional study, a population of patients aged 18 years or older was randomly selected from Xinjiang, China in 2019, 24-hour urine samples collected, and Pittsburgh Sleep Quality Index (PSQI) questionnaires assessed. Participants were divided into 2 groups (upper and lower median of 24-hour urinary potassium excretion). Poor sleep quality was defined as PSQI global score ≥ 6. Associations between 24-hour urinary potassium excretion and [24.8 mmol/L] sleep quality were assessed by multiple logistic regression analysis in total participants and those stratified by sex. RESULTS: In total, 24-hour urine samples were collected from 1,147 participants, of whom data for those with complete urine samples and PSQI data were analyzed (n = 727; mean age = 48.7 years; percentage of women = 62%). Compared with the upper median group for 24-hour urinary potassium excretion, the lower median group showed a significantly higher PSQI global score (6 vs 5, P = .011), and prevalence of poor sleep quality (51.7% vs 42.2%, P = .011). In a fully-adjusted model of multivariate logistic regression, the lower median group showed 1.50-fold increased odds for presence of poor sleep quality (95% confidence interval: 1.01-2.24, P = .045). Sex-specific analyses translated these results to women, but not to men. CONCLUSIONS: These results suggest that low potassium intake, indicated by lower potassium excretion, is associated with poor sleep quality in the general population, especially among women. Therefore, additional research is necessary to clarify the effect of increasing potassium intake to improve sleep quality. CITATION: Li M, Heizhati M, Wang L, et al. 24-hour urinary potassium excretion is negatively associated with self-reported sleep quality in the general population, independently of sleep-disordered breathing. J Clin Sleep Med. 2022;18(11):2589-2596.

Association of Depression with Uncontrolled Hypertension in Primary Care Setting: A Cross-Sectional Study in Less-Developed Northwest China.

BACKGROUND: Hypertensive patients commonly experience comorbid depression, which is closely associated with adverse health outcomes. This study aimed to examine the association between depression and uncontrolled hypertension in primary care setting of Northwest China. METHODS: We used a stratified multistage random sampling method to obtain 1856 hypertensives subjects aged ≥18 years among primary care setting in Xinjiang, Northwest China, between April and October 2019. Depression was evaluated by Hospital Anxiety and Depression Scale (HADS), with a cut-off score ≥8. We related depression to uncontrolled hypertension, using multiple logistic regression, adjusting for minimally sufficient adjustment set of variables retrieved from a literature-based directed acyclic graphs (DAGs) and optimal adjustment set of variables derived from the least absolute shrinkage and selection operator (LASSO) regression. RESULTS: A total of 1,653 (89.1%) patients had uncontrolled hypertension. The prevalence of depression was 14.5% and 7.4% among patients with uncontrolled and controlled hypertension. Depression was associated with 1.12-fold increased odds of uncontrolled hypertension [odds ratio (OR) 2.12, 95% confidence interval (CI): 1.23-3.65]. The association remained significant even after adjusting for the minimal sufficient adjustment sets and the optimal adjustment set of variables. CONCLUSION: Depression is significantly associated with uncontrolled hypertension in primary care setting of northwest China. The integrated management of depression and hypertension in the setting might be warranted.

Prevalence and predictive nomogram of depression among hypertensive patients in primary care: A cross-sectional study in less developed Northwest China.

ABSTRACT: Hypertensive patients commonly co-exist persistent depressive symptoms. However, these issues are not always identified, especially in primary health care, which may worsen the prognosis of hypertension. Therefore, the aim of this study was to determine the prevalence and risk factor of depression, and to develop risk nomogram of depression in hypertensive patients from primary health care Northwest China.We used a stratified multistage random sampling method to obtain 1856 hypertensives subjects aged ≥18 years in Xinjiang between April and October 2019. The subjects were randomly divided into a training set (n = 1299) and a validation set (n = 557). Depression was evaluated by Hospital Anxiety and Depression Scale (HADS), with a cut-off score ≥8. Using the least absolute shrinkage and selection operator (LASSO) regression model, we identified optimized risk factors of depression in the training set, followed by the establishment of prediction nomogram. The discriminative ability, calibration, and clinical usefulness of nomogram were assessed. The results were verified by internal validation in validation set.13.7% hypertensive subjects displayed depression. Seven independent risk factors of depression were identified and entered into the nomogram including age, region, ethnicity, marital status, physical activity, sleep quality, and control of hypertension. The nomogram displayed robust discrimination with an AUC of 0.760 [95% confidence interval (CI): 0.724-0.797)] and 0.761 (95%CI: 0.702-0.819), and good calibration in training set and validation set, respectively. The decision curve analysis and clinical impact curve demonstrated clinical usefulness of predictive nomogram.There is a considerable prevalence of depression in patients with hypertension from primary care of Xinjiang, Northwest China. Our nomogram may help primary care providers assess the risk of depression in patients with hypertension.

Barriers to Access to Treatment for Hypertensive Patients in Primary Health Care of Less Developed Northwest China: A Predictive Nomogram.

BACKGROUND: This study aims to evaluate the risk factors associated with untreated hypertension and develop and internally validate untreated risk nomograms in patients with hypertension among primary health care of less developed Northwest China. METHODS: A total of 895 eligible patients with hypertension in primary health care of less developed Northwest China were divided into a training set (n = 626) and a validation set (n = 269). Untreated hypertension was defined as not taking antihypertensive medication during the past two weeks. Using least absolute shrinkage and selection operator (LASSO) regression model, we identified the optimized risk factors of nontreatment, followed by establishment of a prediction nomogram. The discriminative ability, calibration, and clinical usefulness were determined using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision analysis. The results were assessed by internal validation in the validation set. RESULTS: Five independent risk factors were derived from LASSO regression model and entered into the nomogram: age, herdsman, family income per member, altitude of habitation, and comorbidity. The nomogram displayed a robust discrimination with an AUC of 0.859 (95% confidence interval: 0.812-0.906) and good calibration. The nomogram was clinically useful when the intervention was decided at the untreated possibility threshold of 7% to 91% in the decision curve analysis. Results were confirmed by internal validation. CONCLUSIONS: Our nomogram showed favorable predictive accuracy for untreated hypertension in primary health care of less developed Northwest China and might help primary health care assess the risk of nontreatment in patients with hypertension.

Subjective Poor Sleep Quality is Associated with Higher Blood Pressure and Prevalent Hypertension in General Population Independent of Sleep Disordered Breathing.

OBJECTIVE: To explore the relationship of subjective sleep quality with blood pressure (BP) and hypertension by considering the influence of sleep disordered breathing (SDB) and age in the general population. METHODS: We evaluated sleep quality using the Pittsburgh sleep quality index (PSQI) and SDB using NoSAS score and measured BP in randomly selected adults in China in 2019. Sleep quality is categorized into four groups as very good, fairly good, fairly bad and very bad. SDB is defined as NoSAS score ≥8. Hypertension is defined as systolic BP ≥140 mmHg and/or diastolic BP ≥90 mmHg, and/or use of antihypertensive medicine within previous 2 weeks. Multi-variable linear and logistic regression analyses were used to assess the association of global PSQI score and sleep quality with BP and prevalent hypertension. RESULTS: In the 33,341 participants (53.4% women, median age: 48 years), prevalence of hypertension significantly increased from very good to very bad sleepers in total (34.3 vs 42.6 vs 50.3 vs 58.5%), SDB (61.2 vs 68.3 vs 73.3 vs 75.5%) and non-SDB participants (26.8 vs 33.1 vs 40.1 vs 50.9%). In multiple linear regression, PSQI global score showed significant positive association with BP levels in total, SDB and non-SDB participants, consistent in sensitivity analysis by excluding participants who were taking antihypertensives, and in participants aged <60 years in age-stratified analysis. In multivariable logistic regression, odds ratio for presence of hypertension significantly increased from very good to very bad sleepers in total (1 vs 1.08 vs 1.22 vs 1.48), SDB (1 vs 1.17 vs 1.35 vs 1.28) and non-SDB participants (1 vs 1.05 vs 1.14 vs 1.53), consistent in participants aged <60 years. CONCLUSION: Poor subjective sleep quality is significantly associated with higher BP and prevalent hypertension, independent of SDB in the young- and middle-aged general population, indicating potential of improving sleep quality to lower BP and optimize hypertension management at population level.