Objective: To analyze the trend of the incidence of pulmonary tuberculosis in Yecheng County of Xinjiang from 2011 to 2022 and the influence of age, period and birth cohort effect on the incidence of pulmonary tuberculosis, so as to provide a new theoretical reference for the prevention and control of local pulmonary tuberculosis. Methods : Based on the registration data of new pulmonary tuberculosis cases in Yecheng County, Xinjiang from 2011 to 2022, the connection point regression model was used to calculate the crude incidence rate, age-standardized incidence rate, annual percentage change(APC), and average annual percentage change(AAPC) to describe the epidemic trend of pulmonary tuberculosis. The age-period-cohort model was used to explore the influence of age, period and birth cohort effect on the trend of pulmonary tuberculosis incidence. Results : From 2011 to 2022, a total of 17 057 new cases of pulmonary tuberculosis were registered in Yecheng County, Xinjiang. The crude incidence and standardized incidence were 416.07/100 000 and 496.01/100 000, respectively. The incidence of pulmonary tuberculosis increased first and then decreased during the 12 years, with an upward trend from 2011 to 2018. The APC values of the standardized incidence of pulmonary tuberculosis in the total population, males and females were 24.42%(95%CI: 11.55-38.78), 27.24%(95%CI: 12.35-44.10) and 21.79%(95%CI: 9.81-35.09), respectively. From 2018 to 2022, there was a downward trend. The APC values of the standardized incidence of tuberculosis in the total population, males and females were-38.51%(95%CI:-53.27--19.09),-38.18%(95%CI:-54.59--15.85) and-38.73%(95%CI:-52.96--20.19), respectively. With the increase of age, the incidence of pulmonary tuberculosis showed a trend of rising first and then fluctuating steadily. The risk of the population increased first and then decreased over time, and the later the birth, the lower the risk of the cohort. Conclusion The incidence of pulmonary tuberculosis in Yecheng County of Xinjiang showed a trend of increasing first and then decreasing in the past 12 years, and gradually increased with age. The earlier the birth, the higher the risk of the disease. Men and the elderly are the key targets of tuberculosis prevention and control in Yecheng County, Xinjiang. It is recommended to strengthen the screening of key populations.

Objective : To explore the feasibility of machine learning methods in the discrimination of tuberculosis patients. Methods : The data of 15 observation indicators of 860 patients were obtained from a tertiary hospital. Through in-depth mining and analysis of the data, support vector machine, random forest and neural network model methods were used to discriminate the diseases of patients. Results : The accuracies of the TB suspected patient discrimination models based on support vector machine, random forest and neural network were 90%, 91% and 88%, respectively. Conclusion All three machine learning methods can be used for discriminative analysis of suspected tuberculosis patients. In comparison, random forest performs better in discriminating patients with tuberculosis from those with pneumonia.

Objective: To investigate the characteristics of temporal and spatial distribution of tuberculosis epidemics in Shache County, Kashgar Region, Xinjiang. Methods: Information on the incidence of tuberculosis in Sacha County from 2019—2021 was collected and spatiotemporally analyzed by applying the circular distribution method, local spatial autocorrelation analysis, hot and cold spot analysis, directional distribution and spatial center of gravity methods. Results : The total number of tuberculosis cases in Shache County in 2019—2021 was 8 345, of which 52.03%were male and 47.97% were female, and the patients were predominantly 60-75 years old. The number of reported incidences of TB in Tagarqi Township, Shache Township, and Chajek Township ranked among the top three in the county. Spring and summer were the disease-prone seasons for TB, and mid-March to mid-July was the period of high disease incidence. Misha Township and Ishkuli Township are the “high and high” gathering areas, while the “low and low” gathering areas are mainly concentrated in Khoshrav Township and Karasu Township. The hotspots of TB incidence in Shache county were Tagarqi township, Misha township, and Ishkuli township. During the study period, the center of gravity of TB incidence in Shache county of Kashgar area gradually shifted from the southwest to the northeast. Conclusion In Shache county, there is a certain degree of aggregation of tuberculosis outbreaks, with more men than women reporting illnesses, a larger proportion of older people, and a strong seasonal incidence of the disease, with Mixia township and Ishikuli township being the key areas of incidence. Relevant departments should continue to strengthen the disease surveillance of key populations and regions during the high incidence of tuberculosis, and take appropriate intervention measures to reduce the risk of tuberculosis transmission.

Background The effects of meteorological factors and air pollutants on ischemic heart disease (IHD) hospitalizations in Urumqi have not been fully understood. Objective To investigate the effects of meteorological conditions (temperature, relative humidity) and common air pollutants [fine particulate matter (PM_2.5), inhalable particulate matter (PM₁₀), ozone (O₃), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon monoxide (CO)] on the daily hospitalization volume of IHD, and to provide a scientific basis for the development of targeted prevention and management strategies. Methods Basic information of 90622 IHD hospitalized patients in Urumqi City was collected from January 1, 2014 to December 31, 2022, and daily air pollutant concentration data and meteorological data were collected during the same period. The meteorological data included daily mean temperature, daily maximum temperature, daily minimum temperature, and daily mean relative humidity, and the common air pollutants included PM_2.5, PM₁₀, daily maximum 8-h average concentration of O₃ (O₃_8 h), SO₂, NO₂, and CO. Descriptive statistical analyses (mean, standard deviation, and quartiles) were performed on the collected data. A distribution lag nonlinear model (DLNM) based on time-stratified case-crossover design was established to estimate the lagged effects (RR) as well as the cumulative lagged effects (RR_cum) of daily mean temperature, relative humidity, and different air pollutants on the number of IHD admissions, stratified by gender and age (<60 and ≥60 years). Subsequently, a generalized additive model (GAM) was used to explore the effects of cold waves (≤ P₅ of the daily minimum temperature and lasting ≥3 d) versus heat waves (≥ P₉₅ of the daily maximum temperature and lasting ≥3 d) on IHD hospitalizations and the potential interactions between temperature and the more influential air pollutants [particulate matter (PM) and O₃_8 h] on IHD hospitalizations. Results The maximum number of IHD hospitalizations in a single day in Urumqi from January 1, 2014 to December 31, 2022 was 100, and the average daily number of hospitalized IHD patients was 27. Daily mean temperature, relative humidity, and air pollutants had different nonlinear relationships and hysteresis with IHD hospitalizations. Extremely low temperatures (<P₁: −18 °C) showed the greatest risk to admission for the total IHD population at a cumulative lag of 31 d (lag0-31) (RR_cum=2.092, 95%CI: 1.261,3.471). Female [lag0-31, RR_cum and 95%CI: 3.416 (2.296,5.082)] and people ≥60 years old [lag0-31, RR_cum and 95%CI: 2.356 (1.681,3.303)] were more sensitive to extremely low temperatures. The risk of IHD hospitalization was greatest on lag20 for cold waves (RR=1.242, 95%CI: 1.053, 1.465), and no lagged effect of heat waves on the number of IHD hospitalizations was found. There was a positive interaction (SI >1, P<0.001) between temperature, PM, and O₃_8 h on the risk of IHD hospitalization, especially for low temperature-high PM and O₃_8 h. Conclusion Both low temperature and high pollutant concentrations associate with an increase in IHD hospitalizations with lagged effects in Urumqi from 2014 to 2022, while cold waves associate with a higher risk of IHD admissions. Females and people aged 60 years and older are at high risk.

Objective To analyze the incidence characteristics and trends in pulmonary tuberculosis in the Hotan prefecture,before and after the epidemic,and to provide a reference basis for the formulation and evaluation of tu-berculosis prevention and control measures in the Hotan prefecture.Methods The Hotan prefecture's pulmonary tuberculosis incidence data was collected between 2015 and 2021.Joinpoint regression(JPR)model and Interrupt-ed Time Series(ITS)model were established to explore the incidence trend of pulmonary tuberculosis,as well as the impact of COVID-19 prevention and control measures in Xinjiang on the incidence trend in Hotan,respectively.Furthermore,an analysis of variations in incidence among different age and gender subgroups was carried out.Re-sults The results of the JPR model showed that from 2015 to 2021,the reported incidence rate of pulmonary tuber-culosis in the Hotan prefecture initially increased and then decreased,with a turning point appearing in December 2018.The incidence rate in males was slightly higher than that in females,and the turning point and incidence trend were consistent with the overall trend.Among all age subgroups,those≥60 age group had the highest inci-dence rate,with the trend also showing an initial increase followed by a decrease.A turning point in the incidence rate for the under 18 age group appeared in June 2021,yet the trend was not statistically significant(P>0.05).The turning points in the 19-59 age group and in those aged≥60 were consistent with the overall trend.The re-sults of the ITS model showed that the incidence rate of pulmonary tuberculosis in the Hotan prefecture significantly decreased since January 2020,dropping from 319.28 per 100 000 in 2019 to 155.88 per 100 000 in 2021,a de-crease of 51.16%year-on-year,with a monthly average reduction of 0.049 per 100 000.Conclusion In 2018,Xinjiang province integrated tuberculosis screening into the universal health checkup for the entire population,which led to the identification of numerous cases of tuberculosis.In the Hotan prefecture,the reported incidence of pulmonary tuberculosis peaked in December 2018 and then started to decline.Under the impact of COVID-19 isola-tion measures in Xinjiang,the reported incidence rate showed a notable decrease starting in January 2020.Reitera-ting preventive measures and remaining watchful for the possible appearance of latent tuberculosis patients is crucial as the pandemic fades.

BACKGROUND:Early identification of patients requiring ventilator support will be beneficial for the outcomes of botulism.The present study aimed to establish a new scoring system to predict mechanical ventilation(MV)for botulism patients. METHODS:A single-center retrospective study was conducted to identify risk factors associated with MV in botulism patients from 2007 to 2022.Univariate analysis and multivariate logistic regression analysis were used to screen out risk factors for constructing a prognostic scoring system.The area under the receiver operating characteristic(ROC)curve was calculated. RESULTS:A total of 153 patients with botulism(66 males and 87 females,with an average age of 43 years)were included.Of these,49 patients(32.0%)required MV,including 21(13.7%)with invasive ventilation and 28(18.3%)with non-invasive ventilation.Multivariate analysis revealed that botulinum toxin type,pneumonia,incubation period,degree of hypoxia,and severity of muscle involvement were independent risk factors for MV.These risk factors were incorporated into a multivariate logistic regression analysis to establish a prognostic scoring system.Each risk factor was scored by allocating a weight based on its regression coefficient and rounded to whole numbers for practical utilization([botulinum toxin type A:1],[pneumonia:2],[incubation period≤1 day:2],[hypoxia<90%:2],[severity of muscle involvement:grade II,3;grade III,7;grade IV,11]).The scoring system achieved an area under the ROC curve of 0.82(95%CI 0.75-0.89,P<0.001).At the optimal threshold of 9,the scoring system achieved a sensitivity of 83.7%and a specificity of 70.2%. CONCLUSION:Our study identified botulinum toxin type,pneumonia,incubation period,degree of hypoxia,and severity of muscle involvement as independent risk factors for MV in botulism patients.A score≥9 in our scoring system is associated with a higher likelihood of requiring MV in botulism patients.This scoring system needs to be validated externally before it can be applied in clinical settings.

Objective: To analyze the spatio-temporal distribution characteristics of pulmonary tuberculosis incidence in Xinjiang, and to provide reference for the prevention and control of pulmonary tuberculosis. Methods: The reported incidence numbers of tuberculosis and population data from various counties, cities(prefectures), and districts in Xinjiang from 2010 to 2022 were collected. Based on spatial-temporal scan statistics, standard deviational ellipse analysis, and centroid migration models, the clustering and migration trends of tuberculosis incidence were evaluated. Utilizing Kriging interpolation techniques, an interpolation analysis of the 2022 incidence rate was conducted on an annual scale, with the reported incidence rate in 2018 serving as a temporal control, to identify hotspots of the spatio-temporal distribution. ArcGIS software was employed to visualize the continuous spatial trends of incidence rate changes. Results: The annual reported incidence rate of tuberculosis in Xinjiang from 2010 to 2022 varied year by year, with fluctuations and increases prior to 2018, peaking in 2018, and then declining annually thereafter. The spatial distribution of the incidence rate exhibited a trend of initial clustering followed by diffusion, with the centroid of incidence shifting towards the northeast, yet the epicenter of the epidemic remained in Aksu Prefecture. The results of spatiotemporal scan statistics analysis revealed that the three-level aggregated areas of the epidemic encompassed a total of 41 prefectures, counties, and cities, with the tuberculosis incidence risk in the primary and secondary aggregated areas being significantly higher than that in other regions(P<0.01). The Kriging interpolation prediction map suggested that the four prefectures in southern Xinjiang continued to be high-risk regions for tuberculosis(incidence rate>300/100 000). The overall incidence rate in the northern region was relatively low, with the lowest rate observed in Urumqi, radiating outwards. Conclusion The incidence rate of tuberculosis in Xinjiang shows an upward trend before 2018, followed by a year-on-year decrease. The centroid of the incidence rate shifts towards the northeast. From 2010 to 2022, the tuberculosis epidemic in Xinjiang exhibits a notable spatiotemporal clustering, particularly prominent in the southwestern region, where the four prefectures constitute high-risk areas for tuberculosis. The prevention and control efforts of tuberculosis in Xinjiang should prioritize the regions with high tuberculosis incidence, intensifying prevention and control measures as well as policy support.

Objective:To investigate the intelligence status of children aged 10 - 12 in rural areas of Linxia Hui Autonomous Prefecture (referred to as Linxia) in Gansu Province.Methods:From September to November 2019, a cross-sectional study was carried out to investigate the intelligence status of children aged 10 to 12 in 8 counties (cities) of Linxia. Chinese Raven's Progressive Matrices (rural version) was used for intelligence test and children's intelligence quotient (IQ) was calculated by regular mold to evaluate children's intelligence level.Results:A total of 1 721 children in Linxia were tested for intelligence, with an average IQ of 103.2. Among them, low intelligence (≤69) accounted for 1.0% (18/1 721), borderline (70 - 79) accounted for 3.0% (52/1 721), middle and lower (80 - 89) accounted for 8.4% (144/1 721), moderate (90 - 109) accounted for 56.6% (974/1 721), middle and upper (110 - 119) accounted for 21.9% (377/1 721), excellent (120 - 129) accounted for 7.8% (135/1 721), extremely excellent (≥130) accounted for 1.2% (21/1 721). There were 635, 598 and 488 children aged 10, 11 and 12, respectively, with an average IQ of 106.1, 103.3 and 99.2. There were 919 males and 802 females, with an average IQ of 102.9 and 103.4, respectively.Conclusion:In 2019, the intelligence of children aged 10 to 12 in rural areas of Linxia has reached the moderate level.

In March 2020, the outflow of age limited videos from ICU in Spain inspired us to rethink whether there is age discrimination in the allocation of scarce medical resources. This paper frist reflected on the problem of age discrimination caused by this phenomenon from four moral intuitions: the sacred view of life, the quality of life and values, public health ethics and Chinese culture, and then examined whether it is illegal from the legal level, finally pointed out the negative impact on the society, and put forward that taking age as the standard for the allocation of scarce medical resources is not suitable for China’s national conditions.

Background Air quality health index (AQHI) is derived from exposure-response coefficients calculated from air pollution and morbidity/mortality time series, which helps to understand the overall short-term health impacts of air pollution. Objective To study the effects of common air pollutants on respiratory diseases in Urumqi and to develop an AQHI for the risk of respiratory diseases in the city. Methods The daily outpatient volume data of respiratory diseases from The First Affiliated Hospital of Xinjiang Medical University, meteorological data (daily mean temperature and daily mean relative humidity), and air pollutants [fine particulate matter (PM_2.5), inhalable particulate matter (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon dioxide (CO), and ozone (O₃)] in Urumqi City, Xinjiang, China were collected from January 1, 2017 to December 31, 2021. A distributed lag nonlinear model based on quasi-Poisson distribution was constructed by time-stratified case crossover design. Adopting zero concentration of air pollutants as reference, the exposure-response coefficient (β value) was used to quantify the impact of included air pollutants on the risk of seeking medical treatment for respiratory diseases, and the AQHI was established. The association of between AQHI and the incidence of respiratory diseases and between air quality index (AQI) and the incidence of respiratory diseases was compared to evaluate the prediction effect of AQHI. Results Each 10 µg·m⁻³ increase in PM₁₀, SO₂, NO₂, and O₃ concentrations presented the highest excess risk of seeking outpatient services at 3 d cumulative lag (Lag03) and 2d cumulative lag (Lag02), with increased risks of morbidity of 0.687% (95%CI: 0.101%, 1.276%), 17.609% (95%CI: 3.253%, 33.961%), 13.344% (95%CI: 8.619%, 18.275%), and 4.921% (95%CI: 1.401%, 8.502%), respectively. There was no statistically significant PM_2.5 or CO lag effect. An AQHI was constructed based on a model containing PM₁₀, SO₂, NO₂, and O₃, and the results showed that the excess risk of respiratory disease consultation for the whole population, different genders, ages, or seasons for each inter-quartile range increase in the AQHI was higher than the corresponding value of AQI. Conclusion PM₁₀, SO₂, NO₂, and O₃ impact the number of outpatient visits for respiratory diseases in Urumqi, and the constructed AQHI for the risk of respiratory diseases in Urumqi outperforms the AQI in predicting the effect of air pollution on respiratory health.