Associations of prediabetes and sleep duration, and inflammation as a mediator in the China Health and Retirement Longitudinal Study.

OBJECTIVE: The objective of this study was to examine the relationship between sleep duration and prediabetes, as well as to evaluate the influence of inflammation in mediating this association. METHODS: A total of 4632 participants from the China Health and Retirement Longitudinal Study (CHARLS) were included in this study, comprising both baseline and 4-year follow-up data. The prospective relationship between sleep duration and the risk of prediabetes was examined using logistic regression models. We used multinomial logistic regression to evaluate the impact of prediabetes on sleep duration changes over follow-up, assessing the role of C-reactive protein in the association using mediation analysis. RESULTS: Participants with short sleep duration (<5 hours) had a higher risk of prediabetes (odds ratios=1.381 [95% CI: 1.028-1.857]) compared to those with normal sleep durations (7-8 hours). However, excessive sleep durations (≥9 hours) did not show a statistically significant association with prediabetes risk. Moreover, individuals at least 60years old who experienced short sleep durations exhibited a higher risk of prediabetes. Individuals with prediabetes were more likely to have shorter sleep duration than excessive sleep duration (relative risk ratios=1.280 [95% CI: 1.059-1.547]). The mediation analysis revealed a mediating effect of C-reactive protein on the association between prediabetes and reduced sleep duration. CONCLUSIONS: Short sleep duration was identified as a risk factor for the incidence of prediabetes. Conversely, prediabetes was found to contribute to shorter sleep duration rather than excessive sleep duration. Moreover, elevated levels of C-reactive protein may serve as a potential underlying mechanism that links prediabetes with shorter sleep.

Trends in parkinson's disease mortality in China from 2004 to 2021: a joinpoint analysis.

BACKGROUND: This study aimed to analyze the trends of Parkinson's disease (PD) mortality rates among Chinese residents from 2004 to 2021, provide evidence for the formulation of PD prevention and control strategies to improve the quality of life among PD residents. METHODS: Demographic and sociological data such as gender, urban or rural residency and age were obtained from the National Cause of Death Surveillance Dataset from 2004 to 2021. We then analyzed the trends of PD mortality rates by Joinpoint regression. RESULTS: The PD mortality and standardized mortality rates in China showed an overall increasing trend during 2004-2021 (average annual percentage change [AAPC] = 7.14%, AAPCASMR=3.21%, P < 0.001). The mortality and standardized mortality rate in male (AAPC = 7.65%, AAPCASMR=3.18%, P < 0.001) were higher than that of female (AAPC = 7.03%, AAPCASMR=3.09%, P < 0.001). The PD standardized mortality rates of urban (AAPC = 5.13%, AAPCASMR=1.76%, P < 0.001) and rural (AAPC = 8.40%, AAPCASMR=4.29%, P < 0.001) residents both increased gradually. In the age analysis, the mortality rate increased with age. And the mortality rates of those aged > 85 years was the highest. Considering gender, female aged > 85 years had the fastest mortality trend (annual percentage change [APC] = 5.69%, P < 0.001). Considering urban/rural, rural aged 80-84 years had the fastest mortality trend (APC = 6.68%, P < 0.001). CONCLUSIONS: The mortality rate of PD among Chinese residents increased from 2004 to 2021. Male sex, urban residence and age > 85 years were risk factors for PD-related death and should be the primary focus for PD prevention.

Association between PM10 pollution and the hospitalization of chronic obstructive pulmonary disease with comorbidity: evidence in 17 cities of Henan, Central China.

Particulate matter (PM10) changes have been confirmed as one of the contributory factors affecting human health, the association between PM10 pollution and the hospitalization of chronic obstructive pulmonary disease (COPD) with comorbidity diseases was rarely reported. The same inpatient more than twice times admissions with COPD illness from January 1, 2016 to December 31, 2021 were identified from hospitals in the 17 cities of Henan, Central China. City-specific associations were firstly estimated using the case time series (CTS) model and then combined to obtain the regional average association. The multivariate meta-analytic model produces pooled estimates of the set of coefficients representing the PM10-COPD hospitalizations association across the 17 cities. Cause-specific hospitalization analyses were performed by COPD patients with different comorbidity combinations. A total of 34,348 elderly (age ≥ 65) subjects were analyzed and with a total of 35,122.35 person-years. These coefficients can be used to compute the linear exposure-response curve expressed as relative risk (RR) in per 10 µg/m3 increase in PM10 at lag03, which was 1.0091 (95% CI 1.0070-1.0112) for COPD with comorbidity, 1.0089 (95% CI 1.0067-1.0110) for COPD with circulatory system diseases, 1.0079 (95% CI 1.0052-1.0105) for COPD with respiratory system diseases, 1.0076 (95% CI 1.0032-1.0121) for COPD with endocrine system diseases, and 1.0087 (95% CI 1.0013-1.0162) for COPD with genitourinary system diseases, respectively. Some heterogeneity was found across cities, with estimates ranging from 1.0227 in the Puyang and Jiaozuo to 1.0053 in Henan Provance, China. The effect of higher PM10, on average, was higher in studies for northern cities, with a steeper raise in risk: per 10 µg/m3 increase in PM10, the RR from 1.0062 (95% CI 1.0030-1.0093) for the 10th percentile of latitude to 1.0124 (95% CI 1.0089-1.0160) for the 90th percentile. Our findings indicated that PM10 exposure may increase the risk of hospitalizations for COPD with comorbidity. Moreover, there might be a higher morbidity risk associated with PM10 in northern latitudes, indicating that stricter air quality standards could potentially reduce PM10-related morbidity among individuals with COPD. These findings have implications for the implementation of effective clean air interventions aligned with national climate policies.

Association of social isolation and cognitive performance: a longitudinal study using a four-wave nationwide survey.

BACKGROUND: This study aimed to examine the bidirectional relationship between social isolation and cognitive performance among Chinese middle-aged and older adults. METHODS: We used four waves of data from the China Health and Retirement Longitudinal Study. A latent growth model (LGM) was applied to examine the association between social isolation and cognitive performance across different characteristics. RESULTS: In the analysis, we ultimately included 9,367 participants after excluding respondents with missing key variables. Social isolation and cognitive performance showed significant differences across time. After adjusting for the confounders, there was a significant association between higher social isolation and poor cognitive performance (ß = -1.38, p < 0.001), and higher levels of social isolation resulted in a more pronounced decline in cognition over time (ß = 0.17, p < 0.001). Additionally, the path coefficient between the initial level of cognition at baseline and the slope of social isolation was - 0.07 (p < 0.001) and 0.01 (p = 0.021), respectively. For the correlation between slopes, our study found that females' cognition scores were more susceptible to social isolation (ß = - 2.78, p < 0.001). Similarly, regarding cognition scores, the influence of social isolation was greater among people with education below the primary level (ß = - 2.89, p = 0.002) or a greater number of chronic diseases (ß = - 2.56, p = 0.001). CONCLUSION: Our findings support the bidirectional association between social isolation and cognition. Specifically, higher baseline social isolation and its rate of increase over time contribute to an intensification of cognitive decline at follow-up. Besides, poorer cognitive performance predicted higher social isolation.

Effect of prior anticoagulation therapy on stroke severity and in-hospital outcomes in patients with acute ischemic stroke and atrial fibrillation.

BACKGROUND: We aimed to assess the prevalence of prior anticoagulation therapy (warfarin or non-vitamin K antagonist oral anticoagulants [NOACs]) among patients with acute ischemic stroke (AIS) and atrial fibrillation (AF) in China and investigate the associations between prior anticoagulation therapy and initial stroke severity and in-hospital outcomes. METHODS: We included consecutive patients with AIS and known history of AF admitted to hospitals in the China Stroke Center Alliance (CSCA) program from January 2019 to July 2019. Multivariate logistic regression analyses were performed to determine the associations between prior anticoagulation therapy and initial stroke severity and in-hospital outcomes. RESULTS: Of 7181 patients (median [IQR] age, 75.0 [68.0-81.0] years; 48.7% men), 700 (9.7%), 129 (1.8%), and 255 (3.6%) patients received prior subtherapeutic warfarin (international normalized ratio [INR] <2.0), therapeutic warfarin (INR ≥2.0), and NOACs therapy, respectively. A total of 6499 patients had a preadmission CHA2DS2-VASc score ≥ 2, among whom 94.6% were not adequately anticoagulated. Compared with no prior anticoagulation therapy, prior NOACs therapy was associated with reduced risk of moderate or severe stroke at admission (odds ratio [95% CI], 0.64 [0.43-0.94], P = 0.023) and in-hospital mortality or discharge against medical advice (DAMA) (0.46 [0.24-0.86], P = 0.015). However, no significant association was observed between prior therapeutic warfarin therapy and stroke severity or in-hospital mortality or DAMA. CONCLUSIONS: Among patients with AIS and AF in China, the proportion of patients with inadequate anticoagulation prior to stroke remained substantially high. Prior NOACs therapy was associated with reduced stroke severity and less in-hospital mortality or DAMA.

Electro-microenvironment modulated inhibition of endogenous biofilms by piezo implants for ultrasound-localized intestinal perforation disinfection.

Endogenous bacterial infections from damaged gastrointestinal (GI) organs have high potential to cause systemic inflammatory responses and life-threatening sepsis. Current treatments, including systemic antibiotic administration and surgical suturing, are difficult in preventing bacterial translocation and further infection. Here, we report a wireless localized stimulator composed of a piezo implant with high piezoelectric output serving as an anti-infective therapy patch, which aims at modulating the electro-microenvironment of biofilm around GI wounds for effective inhibition of bacterial infection if combined with ultrasound (US) treatment from outside the body. The pulsed charges generated by the piezo implant in response to US stimulation transfer into bacterial biofilms, effectively destroying their macromolecular components (e.g., membrane proteins), disrupting the electron transport chain of biofilms, and inhibiting bacterial proliferation, as proven by experimental studies and theoretical calculations. The piezo implant, in combination with US stimulation, also exhibits successful in vivo anti-infection efficacy in a rat cecal ligation and puncture (CLP) model. The proposed strategy, combining piezo implants with controllable US activation, creates a promising pathway for inhibiting endogenous bacterial infection caused by GI perforation.

Differentiation of malignant from benign pleural effusions based on artificial intelligence.

INTRODUCTION: This study aimed to construct artificial intelligence models based on thoracic CT images to perform segmentation and classification of benign pleural effusion (BPE) and malignant pleural effusion (MPE). METHODS: A total of 918 patients with pleural effusion were initially included, with 607 randomly selected cases used as the training cohort and the other 311 as the internal testing cohort; another independent external testing cohort with 362 cases was used. We developed a pleural effusion segmentation model (M1) by combining 3D spatially weighted U-Net with 2D classical U-Net. Then, a classification model (M2) was built to identify BPE and MPE using a CT volume and its 3D pleural effusion mask as inputs. RESULTS: The average Dice similarity coefficient, Jaccard coefficient, precision, sensitivity, Hausdorff distance 95% (HD95) and average surface distance indicators in M1 were 87.6±5.0%, 82.2±6.2%, 99.0±1.0%, 83.0±6.6%, 6.9±3.8 and 1.6±1.1, respectively, which were better than those of the 3D U-Net and 3D spatially weighted U-Net. Regarding M2, the area under the receiver operating characteristic curve, sensitivity and specificity obtained with volume concat masks as input were 0.842 (95% CI 0.801 to 0.878), 89.4% (95% CI 84.4% to 93.2%) and 65.1% (95% CI 57.3% to 72.3%) in the external testing cohort. These performance metrics were significantly improved compared with those for the other input patterns. CONCLUSIONS: We applied a deep learning model to the segmentation of pleural effusions, and the model showed encouraging performance in the differential diagnosis of BPE and MPE.

The Relationship Between Sleep Duration and Blood Lipids Among Chinese Middle-Aged and Older Adults: Cross-Lagged Path Analysis From CHARLS.

This study used data from the China Health and Retirement Longitudinal Study to investigate the temporal relationship between blood lipids and sleep duration in Chinese middle-aged and older adults. We used medical examinations and questionnaire data of 5,016 Chinese middle-aged and older adults (age 45+) in 2011 and 2015. Cross-lagged path analysis was performed to examine the bidirectional relationships between blood lipids and sleep duration. Sleep duration and lipids data were analyzed as continuous variables. Temporal relationships between sleep duration and HDL-cholesterol, LDL-cholesterol, total cholesterol, and triglycerides were different. Sleep duration was negatively associated with HDL-cholesterol 4 year later (ß1 = -0.171, P = 0.005), and HDL-cholesterol was negatively associated with sleep duration 4 year later (ß2 = -0.006, P = 0.002). Longer sleep duration was associated lower levels of LDL-cholesterol (ß1 = -0.275, P = 0.097) and total cholesterol (ß1 = -0.329, P = 0.096) 4 year later. There was a positive correlation between triglycerides and sleep duration. The path coefficient from triglycerides to sleep duration 4 year later (ß2 = 0.001, P = 0.018) was greater than that from sleep duration to triglycerides 4 year later (ß1 = 0.109, P = 0.847), with P = 0.030 for the difference between ß1 and ß2. In stratified analysis, we found that the strength and direction of the relationships may be related to age and BMI. Effects of sleep duration on blood lipids were only observed among participants aged <60 years, while the effect in the opposite direction was observed in older adults (age 60+), and the cross-lagged path coefficients were more significant in adults with BMI > 25.

Evaluating the predictive ability of temperature-related indices on the stroke morbidity in Shenzhen, China: Under cross-validation methods framework.

BACKGROUND: Composite temperature-related indices have been utilized to comprehensively reflect the impact of multiple meteorological factors on health. We aimed to evaluate the predictive ability of temperature-related indices, choose the best predictor of stroke morbidity, and explore the association between them. METHODS: We built distributed lag nonlinear models to estimate the associations between temperature-related indices and stroke morbidity and then applied two types of cross-validation (CV) methods to choose the best predictor. The effects of this index on overall stroke, intracerebral hemorrhage (ICH), and ischemic stroke (IS) morbidity were explored and we explained how this index worked using heatmaps. Stratified analyses were conducted to identify vulnerable populations. RESULTS: Among 12 temperature-related indices, the alternative temperature-humidity index (THIa) had the best overall performance in terms of root mean square error when combining the results from two CVs. With the median value of THIa (25.70 °C) as the reference, the relative risks (RRs) of low THIa (10th percentile) reached a maximum at lag 0-10, with RRs of 1.20 (95%CI:1.10-1.31), 1.49 (95%CI:1.29-1.73) and 1.12 (95%CI:1.03-1.23) for total stroke, ICH and IS, respectively. According to the THIa formula, we matched the effects of THIa on stroke under various combinations of temperature and relative humidity. We found that, although the low temperature (<20 °C) had the greatest adverse effect, the modification effect of humidity on it was not evident. In contrast, lower humidity could reverse the protective effect of temperature into a harmful effect at the moderate-high temperature (24 °C-27 °C). Stratification analyses showed that the female was more vulnerable to low THIa in IS. CONCLUSIONS: THIa is the best temperature-related predictor of stroke morbidity. In addition to the most dangerous cold weather, the government should pay more attention to days with moderate-high temperature and low humidity, which have been overlooked in the past.

Modification effects of seasonal and temperature variation on the association between exposure to nitrogen dioxide and ischemic stroke onset in Shenzhen, China.

The independent associations of extreme temperature and ambient air pollutant with the admission to hospital and mortality of ischemic stroke have been widely investigated. However, knowledge about the modification effects of variation in season and temperature on the association between exposure to nitrogen dioxide (NO2) and ischemic stroke onset is still limited. This study purposed to explore the effect of NO2 on daily ischemic stroke onset modified by season and ambient temperature, and identify the potential population that susceptible to ischemic stroke onset connected with NO2 and ambient temperature. Data on daily ischemic stroke counts, weather conditions, and ambient air pollutant concentrations in Shenzhen were collected between January 1, 2008, and December 31, 2014. The seasonal effect on the NO2-associated onset was measured by a distributed-lag linear model. Furthermore, a generalized additive model that incorporated with stratification analyses was used to calculate the interactive effects between NO2 and ambient temperature. During the winter, the average percentage increase in daily ischemic stroke onset for each 10 µg/m3 increment in NO2 concentration on lagged 2 days was 3.05% (95% CI: 1.31-4.82%), while there was no statistically significant effect of NO2 during summer. And the low-temperature days ([Formula: see text] mean temperature), with a 2.23% increase in incidence (95% CI: 1.18-3.29%) for the same concentration increase in NO2, were significant higher than high temperature days ([Formula: see text] mean temperature). The modification effects of temperature on the study association were more pronounced in individuals aged 65 years or more and in males. The adverse health effects of NO2 on ischemic stroke are more pronounced during winter or low temperature periods. Elderly adults or males presented higher risks with these exposures.

Predicting EGFR mutation, ALK rearrangement, and uncommon EGFR mutation in NSCLC patients by driverless artificial intelligence: a cohort study.

BACKGROUND: Timely identification of epidermal growth factor receptor (EGFR) mutation and anaplastic lymphoma kinase (ALK) rearrangement status in patients with non-small cell lung cancer (NSCLC) is essential for tyrosine kinase inhibitors (TKIs) administration. We aimed to use artificial intelligence (AI) models to predict EGFR mutations and ALK rearrangement status using common demographic features, pathology and serum tumor markers (STMs). METHODS: In this single-center study, demographic features, pathology, EGFR mutation status, ALK rearrangement, and levels of STMs were collected from Wuhan Union Hospital. One retrospective set (N = 1089) was used to train diagnostic performance using one deep learning model and five machine learning models, as well as the stacked ensemble model for predicting EGFR mutations, uncommon EGFR mutations, and ALK rearrangement status. A consecutive testing cohort (n = 1464) was used to validate the predictive models. RESULTS: The final AI model using the stacked ensemble yielded optimal diagnostic performance with areas under the curve (AUC) of 0.897 and 0.883 for predicting EGFR mutation status and 0.995 and 0.921 for predicting ALK rearrangement in the training and testing cohorts, respectively. Furthermore, an overall accuracy of 0.93 and 0.83 in the training and testing cohorts, respectively, were achieved in distinguishing common and uncommon EGFR mutations, which were key evidence in guiding TKI selection. CONCLUSIONS: In this study, driverless AI based on robust variables could help clinicians identify EGFR mutations and ALK rearrangement status and provide vital guidance in TKI selection for targeted therapy in NSCLC patients.

Gustave Roussy Immune Score as a Novel Prognostic Scoring System for Colorectal Cancer Patients: A Propensity Score Matching Analysis.

AIM: The Gustave Roussy Immune Score (GRIm-Score) was originally designed to select cancer patients for immunotherapy, and later was reported to be a novel prognostic scoring system in lung cancer and esophageal cancer. This study was aimed to determine the prognostic role and predictive performance of GRIm-Score in colorectal cancer (CRC) CRC patients. METHODS: We conducted a single-institution study of 1,579 adult CRC patients receiving surgical removal, and those patients were divided into low GRIm-Score group (scores 0, 1) and high GRIm-Score group (scores 2, 3). Propensity score matching (PSM) was executed to balance the potential confounding factors between the two groups. Survival and time-dependent receiver operating characteristic (Td-ROC) analyses were applied to depict the prognostic role and predictive significance of GRIm-Score in CRC patients. RESULTS: There were 200 cases CRC patients in high GRIm-Score group and 1,379 cases in low GRIm-Score group. CRC patients with high GRIm-Score correspond with higher level of CEA, CA125, and inflammatory indexes, such as NLR, PLR, SII, PNI, and ALRI. Correlation analysis exhibited that GRIm-Score correlated well with the established inflammatory indexes. Survival analysis revealed that CRC patients in high GRIm-Score group showed worse overall survival (OS, P <0.0001) and disease-free survival (DFS, P <0.0001) compared with those in low GRIm-Score group. Results from multivariate Cox regression implicated that high GRIm-Score was not only a potent prognostic index for unfavorable OS (HR = 1.622, 95%CI: 1.118-2.355, P = 0.0109), but also a potent risk factor for worse DFS (HR = 1.743, 95%CI: 1.188-2.558, P = 0.0045). Td-ROC analysis demonstrated that GRIm-Score exhibited the superior discriminatory power in the prediction of OS and DFS when compared to SII, PNI, and ALRI. Such strong associations between high levels of preoperative GRIm-Score and unfavorable survival outcomes remained robust after PSM analysis. CONCLUSION: GRIm-Score, a novel inflammatory and nutritional risk scoring system, is a potent prognostic index in CRC patients receiving surgical removal. GRIm-Score can be used as an effective and simplified risk stratification tool for postoperative survival prediction of CRC patients.

Sociodemographic Factors Associated With HIV/HCV High-Risk Behaviors Among People Who Use Drugs on Methadone Maintenance Treatment: A 10-Year Observational Study.

Background: Sociodemographic factors have an impact worldwide on the behavior of people who use drugs (PWUD). This study attempts to clarify the sociodemographic factors related to HIV/HCV high-risk behaviors (injection drug use, syringe sharing, and multiple sex partners) among PWUD on methadone maintenance treatment (MMT) in the long term. Methods: The 13,300 PWUD recruited into the MMT program were followed during 2006-2015. Generalized estimating equations were used to examine the relationship between sociodemographic characteristics and HIV/HCV high-risk behaviors. Results: We found that male (vs. female), living alone (vs. living with family or relatives), temporary income, financial support from family/friends, and financial support from social welfare (vs. regular salary) were positively associated with injection drug use. Age of initial drug use was negatively associated with injection drug use and syringe sharing. For both genders, being unmarried (vs. married or in cohabitation), living with friends, living alone (vs. living with family or relatives), temporary income, financial supports from family/friends (vs. regular salary), being employed (vs. unemployed/between jobs) was positively associated. In contrast, age at baseline was negatively associated with having multiple sexual partners for both genders. Ethnic of non-Han (vs. Han) was positively associated with having multiple sexual partners simply for males. Being divorced or widowed (vs. married or cohabitated) was positively associated with having multiple sexual partners merely for females. Conclusion: HIV/HCV high-risk behaviors correlated with certain sociodemographic factors of PWUD receiving MMT. There is a need for improving the well-being, employment, and housing status of PWUD on MMT to reduce their HIV/HCV risk behaviors.

Plasma Metabolomic Profiles in Recovered COVID-19 Patients without Previous Underlying Diseases 3 Months After Discharge.

BACKGROUND: It remains unclear whether discharged COVID-19 patients have fully recovered from severe complications, including the differences in the post-infection metabolomic profiles of patients with different disease severities. METHODS: COVID-19-recovered patients, who had no previous underlying diseases and were discharged from Wuhan Union Hospital for 3 months, and matched healthy controls (HCs) were recruited in this prospective cohort study. We examined the blood biochemical indicators, cytokines, lung computed tomography scans, including 39 HCs, 18 recovered asymptomatic (RAs), 34 recovered moderate (RMs), and 44 recovered severe/ critical patients (RCs). A liquid chromatography-mass spectrometry-based metabolomics approach was employed to profile the global metabolites of fasting plasma of these participants. RESULTS: Clinical data and metabolomic profiles suggested that RAs recovered well, but some clinical indicators and plasma metabolites in RMs and RCs were still abnormal as compared with HCs, such as decreased taurine, succinic acid, hippuric acid, some indoles, and lipid species. The disturbed metabolic pathway mainly involved the tricarboxylic cycle, purine, and glycerophospholipid metabolism. Moreover, metabolite alterations differ between RMs and RCs when compared with HCs. Correlation analysis revealed that many differential metabolites were closely associated with inflammation and the renal, pulmonary, heart, hepatic, and coagulation system functions. CONCLUSION: We uncovered metabolite clusters pathologically relevant to the recovery state in discharged COVID-19 patients which may provide new insights into the pathogenesis of potential organ damage in recovered patients.

Short-Term Effect of Temperature Change on Non-Accidental Mortality in Shenzhen, China.

Temperature change is an important meteorological indicator reflecting weather stability. This study aimed to examine the effects of ambient temperature change on non-accidental mortality using diurnal temperature change (DTR) and temperature change between neighboring days (TCN) from two perspectives, intra-day and inter-day temperature change, and further, to explore seasonal variations of mortality, identify the susceptible population and investigate the interaction between temperature change and apparent temperature (AT). We collected daily data on cause-specific mortality, air pollutants and meteorological indicators in Shenzhen, China, from 1 January 2013 to 29 December 2017. A Quasi-Poisson generalized linear regression combined with distributed lag non-linear models (DLNMs) were conducted to estimate the effects of season on temperature change-related mortality. In addition, a non-parametric bivariate response surface model was used to explore the interaction between temperature change and AT. The cumulative effect of DTR was a U-shaped curve for non-accidental mortality, whereas the curve for TCN was nearly monotonic. The overall relative risks (RRs) of non-accidental, cardiovascular and respiratory mortality were 1.407 (95% CI: 1.233-1.606), 1.470 (95% CI: 1.220-1.771) and 1.741 (95% CI: 1.157-2.620) from exposure to extreme large DTR (99th) in cold seasons. However, no statistically significant effects were observed in warm seasons. As for TCN, the effects were higher in cold seasons than warm seasons, with the largest RR of 1.611 (95% CI: 1.384-1.876). The elderly and females were more sensitive, and low apparent temperature had a higher effect on temperature change-related non-accidental mortality. Temperature change was positively correlated with an increased risk of non-accidental mortality in Shenzhen. Both female and elderly people are more vulnerable to the potential adverse effects, especially in cold seasons. Low AT may enhance the effects of temperature change.

Exenatide Twice Daily Plus Glargine Versus Aspart 70/30 Twice Daily in Patients With Type 2 Diabetes With Inadequate Glycemic Control on Premixed Human Insulin and Metformin.

OBJECTIVE: Many patients with type 2 diabetes treated with premixed insulin gradually have inadequate glycemic control and switch to a basal-bolus regimen, which raises some concerns for weight gain and increased hypoglycemic risk. Switching to combination use of glp-1 agonist and basal insulin may be an alternative option. METHODS: After a 12-week premixed human insulin 70/30 dosage optimization period, 200 patients with HbA1c of 7.0% to 10.0% were randomized into 24-week treatment groups with exenatide twice a day plus glargine or with aspart 70/30 twice a day. RESULTS: After 24 weeks, the patients receiving exenatide plus glargine (n = 90) had improved HbA1c control compared with those receiving aspart 70/30 (n = 90) (least squares mean change: ‒0.59 vs ‒0.13%; difference [95% CI]: ‒0.45 [‒0.74 to ‒0.17]) in the full analysis set population. Weight decreased 3.5 kg with exenatide and decreased 0.4 kg with aspart 70/30 (P < .001). The insulin dose was reduced 10.7 units/day (95% CI, ‒12.2 to ‒9.2 units; P < .001) with exenatide, and increased 9.7 units/day (95% CI, 8.2 to 11.2 units; P < .001) with aspart 70/30. The most common adverse events were gastrointestinal adverse effects in the exenatide group (nausea [21%], vomiting [16%], diarrhea [13%]). The incidence of hypoglycemia was similar in 2 groups (27% for exenatide and 38% for aspart 70/30; P = .1). CONCLUSION: In premixed human insulin‒treated patients with type 2 diabetes with inadequate glycemic control, switching to exenatide twice a day plus glargine was superior to aspart 70/30 twice a day for glycemic and weight control.

Effect of ambient temperature on stroke onset: a time-series analysis between 2003 and 2014 in Shenzhen, China.

OBJECTIVE: Evidence on the relationship between ambient temperature and morbidity of different stroke subtypes in China is limited. This study aimed to assess the influence of ambient temperature on stroke risk in Shenzhen, China. METHODS: From 1 January 2003 to 31 December 2014, 114 552 stroke cases in Shenzhen were collected. A generalised additive model with quasi-Poisson regression combined with a distributed lag non-linear model was applied to evaluate the temperature effects on stroke subtypes. Furthermore, this study explored the variability of the effects across sex, age and education. RESULTS: The immediate heat effects on ischaemic stroke (IS) and the persistent effects of ambient temperature on intracerebral haemorrhage (ICH) were significant. Overall, the cold-related relative risks (RRs) of IS, ICH and subarachnoid haemorrhage (SAH) were 1.02 (0.97-1.07), 1.16 (1.04-1.30) and 1.12 (0.61-2.04), whereas the heat-related RRs were 1.00 (0.97-1.04), 0.80 (0.73-0.88) and 1.05 (0.63-1.78), respectively. For IS, a weakly beneficial cold effect was found among men while a detrimental heat effect among both men and women, the elderly and higher-educated population at lag0. However, regarding ICH, the temperature effects in men, the young and higher-educated population are stronger at lag0-4, lag0-7 as cold reveals threat and heat reveals protection. CONCLUSION: Responses of diverse stroke subtypes to ambient temperature varied. Effective measures should be taken to increase public awareness about the effects of ambient temperature on stroke attack and to educate the public about self-protection.

Effect of Cold Spells and Their Different Definitions on Mortality in Shenzhen, China.

A high premium has been put on researching the effects of cold spells because of their adverse influence on people's daily lives and health. The study aimed to find the most appropriate definition of the cold spell in Shenzhen and quantify the impact of cold spells on mortality. Based on the daily mortality data in Shenzhen from 2013 to 2017 and the meteorological and pollutant data from the same period, we quantified the effect of cold spells using eight different definitions in the framework of a distributed lag non-linear model with a quasi-Poisson distribution. In Shenzhen, low temperatures increase the risk of death more significantly than high temperatures (using the optimal temperature as the cut-off value). Comparing the quasi-Akaike information criterion value, attribution fraction (b-AF), and attribution number (b-AN) for all causes of deaths and non-accidental deaths, the optimal definition of the cold spell was defined as the threshold was 3rd percentile of the daily average temperature and duration for 3 or more consecutive days (all causes: b-AF = 2.31% [1.01-3.50%], b-AN = 650; non-accidental: b-AF = 1.92% [0.57-3.17%], b-AN = 471). For cardiovascular deaths, the best definition was the temperature threshold as the 3rd percentile of the daily average temperature with a duration of 4 consecutive days (cardiovascular: b-AF = 1.37% [0.05-2.51%], b-AN = 142). Based on the best definition in the model, mortality risk increased in cold spells, with a statistically significant lag effect occurring as early as the 4th day and the effect of a single day lasting for 6 days. The maximum cumulative effect occurred on the 14th day (all-cause: RR = 1.54 [95% CI, 1.20-1.98]; non-accidental: RR = 1.43 [95% CI, 1.11-1.84]; cardiovascular: RR = 1.58 [95% CI, 1.00-2.48]). The elderly and females were more susceptible to cold spells. Cold spells and their definitions were associated with an increased risk of death. The findings of this research provide information for establishing an early warning system, developing preventive measures, and protecting susceptible populations.

Years of life lost and mortality risk attributable to non-optimum temperature in Shenzhen: a time-series study.

To assess YLL and mortality burden attributable to non-optimum ambient temperature, we collected mortality and environmental data from June 1, 2012 to December 30, 2017 in Shenzhen. We applied distributed lag nonlinear models with 21 days of lag to examine temperature-YLL and temperature-mortality associations, and calculated the attributable fractions of YLL and deaths for non-optimum temperature, including four subranges, mild cold, mild heat, extreme cold, and extreme heat. Cold and heat were distinguished by the optimum temperature, and each was separated into extreme and mild by cutoffs at 2.5th (12.2 °C) and 97.5th (30.4 °C) temperature percentile further. The optimum temperature was defined as the temperature that had minimum effect on YLL or mortality risk. The optimum temperature for non-accidental YLL was 24.5 °C, and for mortality it was 25.4 °C. Except for the population older than 65 years, the optimum temperature was generally lower in the YLL model than the mortality model. Of the total 61,576 non-accidental deaths and 1,350,835.7 YLL within the study period, 17.28% (95% empirical CI 9.42-25.14%) of YLL and 17.27% (12.70-21.34%) of mortality were attributable to non-optimum temperature. More YLL was caused by cold (10.14%, 3.94-16.36%) than by heat (7.14%, 0.47-13.88%). Mild cold (12.2-24.5 °C) was responsible for far more YLL (8.78%, 3.00-14.61%) than extreme cold (3.5-12.2 °C). As for cardiovascular deaths, only the fractions attributable to overall and cold temperature were significant, with mild cold contributing the largest fraction to YLL (16.31%, 6.85-25.82%) and mortality (16.08%, 9.77-21.22%). Most of the temperature-related YLL and mortality was attributable to mild but non-optimum weather, especially mild cold, while the YLL model implied a more prominent heat effect on premature death. Our findings can supply additional evidence from multiperspectives for health planners to define priorities and make targeted policies for mitigating the burden of adverse temperatures.

Estimation of the Outbreak Severity and Evaluation of Epidemic Prevention Ability of COVID-19 by Province in China.

Objectives. To compare the epidemic prevention ability of COVID-19 of each province in China and to evaluate the existing prevention and control capacity of each province.Methods. We established a quasi-Poisson linear mixed-effects model using the case data in cities outside Wuhan in Hubei Province, China. We adapted this model to estimate the number of potential cases in Wuhan and obtained epidemiological parameters. We estimated the initial number of cases in each province by using passenger flowrate data and constructed the extended susceptible-exposed-infectious-recovered model to predict the future disease transmission trends.Results. The estimated potential cases in Wuhan were about 3 times the reported cases. The basic reproductive number was 3.30 during the initial outbreak. Provinces with more estimated imported cases than reported cases were those in the surrounding provinces of Hubei, including Henan and Shaanxi. The regions where the number of reported cases was closer to the predicted value were most the developed areas, including Beijing and Shanghai.Conclusions. The number of confirmed cases in Wuhan was underestimated in the initial period of the outbreak. Provincial surveillance and emergency response capabilities vary across the country.