BACKGROUND: Spicy food consumption has been reported to be inversely associated with mortality from multiple diseases. However, the effect of spicy food intake on the incidence of vascular diseases in the Chinese population remains unclear. This study was conducted to explore this association. METHODS: This study was performed using the large-scale China Kadoorie Biobank (CKB) prospective cohort of 486,335 participants. The primary outcomes were vascular disease, ischemic heart disease (IHD), major coronary events (MCEs), cerebrovascular disease, stroke, and non-stroke cerebrovascular disease. A Cox proportional hazards regression model was used to assess the association between spicy food consumption and incident vascular diseases. Subgroup analysis was also performed to evaluate the heterogeneity of the association between spicy food consumption and the risk of vascular disease stratified by several basic characteristics. In addition, the joint effects of spicy food consumption and the healthy lifestyle score on the risk of vascular disease were also evaluated, and sensitivity analyses were performed to assess the reliability of the association results. RESULTS: During a median follow-up time of 12.1 years, a total of 136,125 patients with vascular disease, 46,689 patients with IHD, 10,097 patients with MCEs, 80,114 patients with cerebrovascular disease, 56,726 patients with stroke, and 40,098 patients with non-stroke cerebrovascular disease were identified. Participants who consumed spicy food 1-2 days/week (hazard ratio [HR] = 0.95, 95% confidence interval [95% CI] = [0.93, 0.97], P <0.001), 3-5 days/week (HR = 0.96, 95% CI = [0.94, 0.99], P = 0.003), and 6-7 days/week (HR = 0.97, 95% CI = [0.95, 0.99], P = 0.002) had a significantly lower risk of vascular disease than those who consumed spicy food less than once a week ( Ptrend <0.001), especially in those who were younger and living in rural areas. Notably, the disease-based subgroup analysis indicated that the inverse associations remained in IHD ( Ptrend = 0.011) and MCEs ( Ptrend = 0.002) risk. Intriguingly, there was an interaction effect between spicy food consumption and the healthy lifestyle score on the risk of IHD ( Pinteraction = 0.037). CONCLUSIONS Our findings support an inverse association between spicy food consumption and vascular disease in the Chinese population, which may provide additional dietary guidance for the prevention of vascular diseases.
Humans ; Male ; Female ; Prospective Studies ; Middle Aged ; Aged ; Vascular Diseases/etiology* ; Risk Factors ; China/epidemiology* ; Adult ; Proportional Hazards Models ; Cerebrovascular Disorders/epidemiology* ; East Asian People

The disease risk prediction model is the basis of precision prevention and an essential reference for clinical treatment decisions. The development of risk prediction models requires the support of a large amount of high-quality data. A large population cohort study is an important basis for this study. The United Kingdom Biobank (UKB), as a mega-population cohort and biobank, has played an essential role in the exploration of disease etiology and research related to disease prevention and control, with its rich baseline and follow-up data and concepts and mechanisms shared globally. This study followed PRISMA guidelines and included 210 articles with corresponding authors from 18 countries, of which 58 (27.62%) were from the UKB. A total of 491 disease risk prediction models were extracted for cancer, cardiovascular and cerebrovascular diseases, endocrine and metabolic diseases, respiratory diseases, and other diseases and their subgroups, of which 132 were developed by UKB without validation, 183 were developed by UKB with internal validation, 17 were developed by UKB with external validation, and 159 were developed by external development with UKB validation. A total of 188 models used only macro variables (38.29%), and 303 models combined macro and micro variables (61.71%). Model construction methods included survival outcome models, logistic regression, and machine learning. Survival outcome models were dominated by Cox proportional risk regression models and a few models considering competitive risk, accelerated failure models, or different baseline risk functions. Machine learning models included random forest, XGBoost, CatBoost, support vector machine, convolutional neural network, and other methods. The UKB is an essential resource for multiple disease risk prediction modeling studies.

Extremely unbalanced data here refers to datasets where the values of independent or dependent variables exhibit severe unbalance in proportions, such as extremely unbalanced case-control ratio, very low incidence rate of disease, heavily censored time-to-event data, and low-frequency or rare variants. In such scenarios, the statistic derived from hypothesis test using the classical statistical method, e.g., logistic regression model and Cox proportional hazard regression model, might deviate from theoretical asymptotic distribution, resulting in inflation or deflation of type I error. With the increased availability and exploration of resources from large-scale population cohorts in genome-wide association study (GWAS), there is a growing demand for effective and accurate statistical approaches to handle extremely unbalanced data in independent and non-independent samples. Our study introduces classical statistical methods in genetic statistics firstly, then, summarizes the failure of classical statistical methods in dealing with extremely unbalanced data through simulation experiments to draw researchers' attention to the extremely unbalanced data in GWAS.

As an important means of data visualization, statistical graphics can potentially convey scientific findings and key points. However, authoritative graphic guidelines are lacking currently, and medical researchers still have shortcomings in mastering graphic design principles and drawing skills, which may obscure some key research findings and even misinterpret the research findings. Based on statistical examples, we summarized the essential elements and design principles of statistical graphics to address these challenges and to provide a reference for medical researchers.

Objective:To understand the infection status and characteristics of 2019-nCoV infection in different areas in China after the adjustment of the national prevention and control strategy of 2019-nCoV infection.Methods:The online questionnaire survey was conducted among staff and students of 39 public health schools in 23 provinces (municipalities) in China from 12: 00 on December 20 to 9: 00 on December 23, 2022. The infection rates in staff and students in all the provinces were estimated. The risk factors, demographic and clinical characteristics of 2019-nCoV infections were explored.Results:A total of 28 901 valid questionnaires were obtained (26 355 from students and 2 546 from staff) with a qualified rate of 94.3%. The infection rates varied greatly among provinces and cities; the infection rates in students and staff in Beijing reached 78.55% and 76.40%, respectively. Infection rates in students and staff in Tianjin and Hebei also exceeded 65.00%, and 96.76% of infections occurred on and after December 1, 2022. Students had lower risk for the infection compared with staff ( OR=0.72, 95% CI: 0.60-0.86). Compared with age group ≤20 years, the OR of age groups 21-30, 31-40, 41-50, 51-60 and > 60 years were 1.22 (95% CI: 1.14-1.30), 1.54 (95% CI: 1.30-1.84), 1.25 (95% CI: 0.99-1.58), 1.29 (95% CI: 0.94-1.78) and 1.19 (95% CI: 0.51-2.80), respectively. The longer the period after the last vaccination, the higher the risk for the infection. Compared with those who received the last vaccination in the past 3 months, the OR of those who received the last vaccination in the past 4-6 months, 7-9 months, 10-12 months, 13-15 months and ≥16 months were 1.56 (95% CI: 1.34-1.82), 1.59 (95% CI: 1.36-1.86), 1.67 (95% CI: 1.45-1.93), 1.86 (95% CI:1.58-2.19) and 2.46 (95% CI: 2.09-2.90), respectively. Compared with those living alone, the OR of those living with 1-2, 3-4 and ≥5 roommates were 17.55 (95% CI: 15.91-19.39), 20.22 (95% CI: 18.25-22.43) and 11.78 (95% CI: 10.40-13.36), respectively. Only 5.94% of the staff and 7.19% of the students reported asymptomatic infections. Among those with symptoms, 88.18% of students and 85.65% of staff reported symptom of fever. Conclusions:The transmission dynamics of 2019-nCoV infection varied significantly across the country. The speed of transmission of 2019-nCoV and clinical severity of the infection were far beyond our knowledge. Organized epidemiological survey should be regularly carried out to provide reliable data support for more accurate prediction of the epidemic and medical resource allocation.

Objective:To observe heart rate circadian rhythm in patients with chronic kidney disease (CKD) stage 5 and to analyze the effects of parathyroidectomy (PTX) on heart rate circadian rhythm in severe secondary hyperparathyroidism (SHPT) patients.Methods:A cross-sectional observation was performed in 213 patients with CKD stage 5 and 96 controls, and the patients were divided into those with severe SHPT (PTX group, n=70) and without severe SHPT (non-PTX group, n=143). Forty-six PTX patients were followed up prospectively. The baseline data were compared among these groups. Holter electrocardiogram was performed for each participant. Non-dipping heart rate was defined as night/day heart rate ratio greater than 0.9. Multiple linear regression analysis was used to analyze the related factors of heart rate circadian rhythm in patients with CKD stage 5. Results:The 24-hour, daytime and nighttime mean heart rate in patients with CKD stage 5 were all higher than those in controls, especially in PTX group (all P<0.05). The night/day heart rate ratios of controls and CKD stage 5 patients were (0.81±0.08) and (0.91±0.08) respectively ( P<0.01). Correlation analysis showed 24-hour and daytime or nighttime mean heart rate in patients with CKD stage 5 were positively correlated with serum levels of phosphorus and ln(alkaline phosphatase), while nighttime mean heart rate and night/day heart rate ratio were positively related with serum intact parathyroid hormone level. After adjusting with postoperative follow-up period (median time: 10.9 months), 24-hour and nighttime mean heart rate, and night/day heart rate ratio in PTX patients all decreased significantly (all P<0.01). Conclusions:Heart rate is increased and circadian rhythm is abnormal in patients with CKD stage 5, which are related with mineral and bone disorder. PTX significantly decreases 24-hour and nighttime mean heart rate in severe SHPT patients, and improves the heart rate circadian rhythm.

Objective:To investigate the predictive value of abnormal heart rate circadian rhythm for all-cause mortality in stage 5 chronic kidney disease (CKD 5) patients.Methods:The retrospective study was performed in CKD 5 patients enrolled from the First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital) and the Affiliated BenQ Hospital of Nanjing Medical University from February, 2011 to December, 2019. A total of 159 healthy volunteers were enrolled as the healthy control group during the same period. The circadian rhythm of heart rate was monitored by 24-hour Holter. Related indices (including 24-hour, daytime and nighttime mean heart rate, night/day heart rate ratio, 24-hour maximum heart rate, 24-hour minimum heart rate and difference between maximum and minimum of 24-hour heart rate) were calculated. Non-dipping heart rate was defined as night/day heart rate ratio greater than 0.9. Cox regression model was used to analyze the risk factors of all-cause mortality in CKD 5 patients. Kaplan-Meier survival curve and Log-rank test were used to compare the differences of cumulative mortality between high ratio group (night/day heart rate ratio>0.91) and low ratio group (night/day heart rate ratio≤0.91). The nonlinear relationship between night/day heart rate ratio and all-cause mortality was analyzed by restricted cubic spline plot. Time-dependent receiver operating characteristic (ROC) curve was used to analyze the predictive value of night/day heart rate ratio for all-cause mortality in CKD 5 patients.Results:A total of 159 healthy volunteers and 221 CKD 5 patients were included in this study. There were 123 males (55.66%) and the age was (52.72±13.13) years old in CKD 5 patients. The total median follow-up time was 50.0 months. Compared with controls, 24-hour, nighttime mean heart rate, 24-hour minimum heart rate in CKD 5 patients were increased (all P<0.05), furthermore, the night/day heart rate ratio was higher [(0.91±0.09) vs (0.81±0.08), P<0.001], showing "non-dipping heart rate". However, the 24-hour maximum heart rate and the difference between maximum and minimum of 24-hour heart rate in CKD 5 patients were lower than controls (both P<0.05). Multivariate Cox regression analysis showed that the increased night/day heart rate ratio (per 0.1 increase, HR=1.557, 95% CI 1.073-2.258, P=0.020) was an independent influencing factor for all-cause mortality in CKD 5 patients. Kaplan-Meier survival curve analysis showed that the cumulative mortality of the high ratio group was significantly increased than that of the low ratio group (Log-rank test χ 2=7.232, P=0.007). From the restricted cubic spline plot, there was a linear effect between night/day heart rate ratio and all-cause mortality ( P=0.141), and when night/day heart rate ratio was above 0.91, the risk of all-cause mortality was significantly increased in CKD 5 patients. According to time-dependent ROC curve, the accuracy of night/day heart rate ratio in predicting all-cause mortality was 70.90% even when the survival time was up to 70.0 months. Conclusions:The circadian rhythm of heart rate in CKD 5 patients displays "non-dipping" state. High night/day heart rate ratio is an independent influencing factor for all-cause mortality in CKD 5 patients.

Objective:To explore the consistency of peripheral whole blood and venous serum procalcitonin (PCT) levels, and the value of peripheral whole blood PCT in evaluating pediatric bacterial infection.Methods:This multicenter cross-sectional parallel control study was conducted in 11 children′s hospital. All the 1 898 patients older than 28 days admitted to these hospitals from March 2018 to February 2019 had their peripheral whole blood and venous serum PCT detected simultaneously with unified equipment, reagent and method. According to the venous serum PCT level, the patients were stratified to subgroups. Analysis of variance and chi-square test were used to compare the demographic characteristics among groups. And the correlation between the peripheral blood and venous serum PCT level was investigated by quantitative Pearson correlation analysis.The PCT resultes were also converted into ranked data to further test the consistency between the two sampling methods by Spearman′s rank correlation test. Furthermore, the ranked data were converted into binary data to evaluate the consistency and investigate the best cut-off of peripheral blood PCT level in predicting bacterial infection.Results:A total of 1 898 valid samples were included (1 098 males, 800 females),age 27.4(12.2,56.7) months. There was a good correlation between PCT values of peripheral whole blood and venous serum ( r=0.97 , P<0.01). The linear regression equation was PCT?venous serum=0.135+0.929×PCT peripheral whole blood. However, when stratified to 5 levels, PCT results showed diverse and unsatisfied consistency between the two sampling methods ( r=0.51-0.92, all P<0.01). But after PCT was converted to ordinal categorical variables, the stratified analysis showed that the coincidence rate of the measured values by the two sampling methods in each boundary area was 84.9%-97.1%. The dichotomous variables also showed a good consistency (coincidence rate 96.8%-99.3%, Youden index 0.82-0.89). According to the severity of disease, the serum PCT value was classified into 4 intervals（<0.5、0.5-<2.0、2.0-<10.0、≥10.0 μg/L）, and the peripheral blood PCT value also showed a good predictive value (AUC value was 0.991 2-0.997 9). The optimal cut points of peripheral whole blood PCT value 0.5、1.0、2.0、10.0 μg/L corresponding to venous serum PCT values were 0.395, 0.595, 1.175 and 3.545 μg/L, respectively. Conclusions:There is a good correlation between peripheral whole blood PCT value and the venous serum PCT value, which means that the peripheral whole blood PCT could facilitate the identification of infection and clinical severity. Besides, the sampling of peripheral whole blood is simple and easy to repeat.

During the epidemics of COVID-19 in domestic China and recently continuing rapid spread worldwide, a bunch of studies fitted the epidemics by transmission dynamics model to nowcast and forecast the trend of epidemics of COVID-19. However, due to little known of the new virus in early stage and much uncertainty in the comprehensive strategies of prevention and control for epidemics, majority of models, not surprisingly, predict in less accuracy, although the dynamics model has its great value in better understanding of transmission. This comment discusses the principle assumptions and limitations of the dynamics model in forecasting the epidemic trend, as well as its great potential role in evaluation the efforts of prevention and control strategies.

Objective: To evaluate the current status of the prevention and control of coronavirus disease (COVID-19) outbreak in China, establish a predictive model to evaluate the effects of the current prevention and control strategies, and provide scientific information for decision- making departments. Methods: Based on the epidemic data of COVID-19 openly accessed from national health authorities, we estimated the dynamic basic reproduction number R₀(t) to evaluate the effects of the current COVID-19 prevention and control strategies in all the provinces (municipalities and autonomous regions) as well as in Wuhan and the changes in infectivity of COVID-19 over time. Results: For the stability of the results, 24 provinces (municipality) with more than 100 confirmed COVID-19 cases were included in the analysis. At the beginning of the outbreak, the R₀(t) showed unstable trend with big variances. As the strengthening of the prevention and control strategies, R₀(t) began to show a downward trend in late January, and became stable in February. By the time of data analysis, 18 provinces (municipality) (75%) had the R₀(t)s less than 1. The results could be used for the decision making to free population floating conditionally. Conclusions Dynamic R₀(t) is useful in the evaluation of the change in infectivity of COVID-19, the prevention and control strategies for the COVID-19 outbreak have shown preliminary effects, if continues, it is expected to control the COVID-19 outbreak in China in near future.