Background Air pollution remains a critical public health issue, with persistent exposure to air pollutants continuing to pose significant health risks. Currently, research investigating the association between air pollution and myocardial infarction mortality in Shenzhen remains inadequate. Objective To quantitatively assess the association between air pollutants and myocardial infarction mortality in residents. Methods Based on the mortality surveillance system of Shenzhen Center for Disease Control and Prevention, we conducted a time-stratified case-crossover study of 10089 permanent residents who died from myocardial infarction in Shenzhen between 2013 and 2022. Using residential address information, we obtained individual-level exposure data for air pollutants from the China High Air Pollutants dataset and meteorological factors from the China Meteorological Administration Land Data Assimilation System. A time-stratified case-crossover study design was employed to construct a conditional logistic regression model to assess the association between short-term exposure to air pollutants and myocardial infarction mortality. The exposure-response relationship was visualized, and a comprehensive health risk assessment was performed. Results This study included a total of 10 089 cases of myocardial infarction deaths in Shenzhen. The median [interquartile range (IQR)] concentrations of fine particulate matter (PM_2.5), inhalable particulate matter (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ozone (O₃) in Shenzhen from 2013 to 2022 were 24.59 (20.19) μg·m⁻³, 42.85 (28.42) μg·m⁻³, 8.53 (3.39) μg·m⁻³, 29.47 (13.56) μg·m⁻³, 0.77 (0.27) mg·m⁻³, and 86.53 (51.39) μg·m⁻³, respectively. The moving average concentrations of PM_2.5 and PM₁₀ over the current day and the previous 2 days (lag02) showed the highest risk of myocardial infarction mortality, with an odds ratio (OR) and 95% confidence interval (95%CI) of 1.004 (1.001, 1.007) and 1.004 (1.002, 1.006), respectively. At lag05, SO₂ demonstrated the strongest association with the risk of myocardial infarction mortality, with an OR (95%CI) of 1.042 (1.019, 1.065). The exposure-response relationships of PM_2.5, PM₁₀, and SO₂ with myocardial infarction mortality were approximately linear, whereas NO₂ exhibited a nonlinear relationship. At lag05, the highest risk of myocardial infarction mortality associated with NO₂ exposure was observed when the NO₂ concentration was ≤21.92 μg·m⁻³, with an OR (95% CI) of 1.024 (1.003, 1.046). The health risk assessment indicated that, using the WHO Air Quality Guidelines as the reference, the local PM_2.5 and NO₂ exposure led to an excess mortality of 398 and 298 cases, respectively. The sensitivity analysis revealed that after adjusting for O₃ and restricting the study period to 2013—2019, the effect estimates for PM_2.5, PM₁₀, NO₂, and SO₂ on myocardial infarction mortality slightly increased. Conclusion Short-term exposure to air pollutants, including PM_2.5, PM₁₀, NO₂, and SO₂, could increase the risk of myocardial infarction mortality. This study provides important scientific evidence for environmental health risk assessment and environmental management in Shenzhen.

Objective To quantitatively assess the association of short-term exposure to polycyclic aromatic hydrocarbons (PAHs) in ambient fine particulate matter (PM2.5) with residents mortality. Methods A time-stratified case-crossover study was conducted from 2020 to 2022 among 10606 non-accidental residents by using the Guangzhou Cause of Death Surveillance System in Conghua District, Guangzhou. Exposure levels of PAHs in PM_2.5 and meteorological data during the study period were obtained from the Center for Disease Control and Prevention in Conghua District and the China Meteorological Administration Land Data Assimilation System (CLDAS-V2.0), respectively. Conditional Poisson regression model was used to estimate the exposure-response association between PAHs and the mortality risk. Results Fluoranthene, chrysene, benzo[k]fluoranthene, benzo[a]pyrene, and indeno[1,2,3-cd]pyrene were significantly associated with an increased risk of mortality. For every one interquartile range increase in exposure levels, the non-accidental mortality risks increased by 8.33% (95% CI: 1.80%, 15.27%), 4.67% (95% CI: 1.86%, 7.57%), 6.07% (95% CI: 2.08%, 10.21%), 4.62% (95% CI: 1.85%, 7.47%), and 4.70% (95% CI: 0.53%, 9.03%), respectively. The estimated non accidental deaths attributable to exposure to fluoranthene, chrysene, benzo[k]fluorine, benzo[a]pyrene and indine[1,2,3-cd]pyrene were 5.91%, 6.08%, 6.51%, 6.46%, and 4.21%, respectively. Conclusions Short-term exposure to PAHs in PM_2.5, including fluoranthene, chrysene, benzo[k]fluoranthene, benzo[a]pyrene and indine[1,2,3-cd]pyrene, was significantly associated with an increased risk of mortality among residents.

Background Exposure to air pollutants increases the risk of diseases in multiple systems, including respiratory and cardiovascular systems, yet its association with neurological diseases remains unclear. Objective To quantitatively evaluate the association between short-term exposure to air pollutants and outpatient and emergency visits for neurological diseases, identify potential susceptible populations, and quantify associated disease burden. Methods Daily 24-hour average concentrations of fine particulate matter (PM_2.5), inhalable particulate matter (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon monoxide (CO), daily maximum 8-hour average concentration of ozone (O₃), daily meteorological data (24-hour average temperature, 24-hour average relative humidity), and data on daily outpatient and emergency department visits for neurological diseases from two hospitals in Conghua District, Guangzhou, China, were collected from 2015 to 2022. A time-stratified case-crossover design was adopted, and a conditional Poisson regression model was constructed to analyze the association between air pollution exposure and neurological disease visits. Two-pollutant models and sensitivity analysis were used to validate model stability. Stratified analyses by season (cold season: from November to March; warm season: from April to October), sex (male, female), and age (≤45 years, 46–60 years, ≥61 years) were performed to identify vulnerable group. Additionally, the number and proportion of neurological disease visits attributable to short-term air pollutant exposure were calculated. Results A total of 72 673 outpatient and emergency department visits for neurological diseases were included during the study period. Most of the patients were middle-aged and elderly individuals (69.89% were over 45 years old) and females (60.25%). The results of single-pollutant models showed that for each interquartile range (IQR) increase in exposure to PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃, the risk of outpatient and emergency department visits for neurological diseases increased by 7.54% (95%CI: 4.69%, 10.46%), 6.66% (95%CI: 3.92%, 9.46%), 16.72% (95%CI: 10.58%, 23.19%), 8.12% (95%CI: 4.82%, 11.53%), 5.60% (95%CI: 2.34%, 8.97%), and 6.11% (95%CI: 2.91%, 9.40%), respectively. The results of the two-pollutant model showed that the association between PM_2.5 and SO₂ exposure and outpatient and emergency department visits for neurological diseases were relatively stable. The stratified analyses showed that the effect of SO₂ was stronger in the cold season. It was estimated that 8.32% (95%CI: 5.55%, 10.96%) and 6.65% (95%CI: 4.27%, 8.96%) of the outpatient and emergency department visits were attributable to short-term exposure to SO₂ and PM_2.5, respectively. Conclusion Exposure to PM_2.5 and SO₂ is associated with increased risks of outpatient and emergency visits for neurological diseases. SO₂ shows stronger effects during the cold season, and exposure to air pollution contributes to up to 8.32% of neurological disease visits.

Objective To quantitatively evaluate the association of short-term exposure to ambient submicron particulate matter (PM₁) with hospital admissions for angina in older adults. Methods A case-crossover study was conducted among 46 687 older adults hospitalized for angina from 2016 to 2019 in Guangzhou medical institutions. Grid data on ambient PM₁ concentrations in Guangzhou were obtained from the ChinaHighAirPollutants (CHAP) dataset. Exposure to PM₁ was assessed according to each subject's residential addresses. Conditional logistic regression model was used to analyze the the exposure-response association between PM₁ and hospital admissions for angina. Results From 2016 to 2019, the average exposure level of PM₁ on the same day of hospital admissions (lag 0) for angina was 21.0 ± 11.5 μg/m³. The results of main model analysis showed that lag 0 day exposure to ambient PM₁ was significantly associated with a higher odds of hospital admissions for angina in older adults. Each 10 μg/m³ increase of PM₁ exposure level was significantly associated with a 1.31% (95% CI: 0.05%, 2.59%) increased odds of angina admissions. Results from a two-pollutant model adjusting for O₃ showed that the association between short-term exposure to PM₁ and odds of hospitalization for angina remained stable. According to the results of the above model, it was estimated that the excess hospitalization attributable to ambient PM₁ exposure accounted for 2.46% (95% CI: 0.09%, 4.76%) of the total admissions in Guangzhou during 2016-2019, corresponding to 1539 (95% CI: 54, 2976) admissions. No significant effect modification on the associations was observed by sex, age, or season. Conclusion Short-term exposure to ambient PM₁ was significantly associated with an increased odds of hospital admissions for angina in older adults.

Objective To explore the automated identification and diameter measurement methods for inferior vena cava (IVC) based on clinical ultrasound images of IVC. Methods An automated identification and localization method based on topology and automatic tracking algorithm was proposed. Tracking algorithm was used for identifying and continuously locating to improve the efficiency and accuracy of measurement. Tests were conducted on 18 sets of ultrasound data collected from 18 patients in intensive care unit (ICU),with clinicians' measurements as the gold standard. Results The recognition accuracy of the automated method was 94.44％ (17/18),and the measurement error of IVC diameter was within the range of±1.96s (s was the standard deviation). The automated method could replace the manual method. Conclusion The proposed IVC automated identification and localization algorithm based on topology and automatic tracking algorithm has high recognition success rate and IVC diameter measurement accuracy. It can assist clinicians in identifying and locating IVC,so as to improve the accuracy of IVC measurement.

Objective:To construct an operation efficiency evaluation model of rehabilitation medical equipment based on equipment status information,and to improve the operation efficiency of rehabilitation medical equipment.Methods:The operating efficiency evaluation model of medical equipment in rehabilitation department was constructed based on the state information modeling of medical equipment.A total of 35 medical devices in clinical use in the Rehabilitation Department of Shanxi Bethune Hospital from 2021 to 2023 were selected.During the operation period of the equipment from January 2021 to June 2022,the conventional management mode was adopted,and during the operation period of the equipment from July 2022 to December 2023,the operation efficiency evaluation model of medical equipment in the rehabilitation department based on equipment status information was adopted.The timeliness of equipment management,management index score,equipment failure rate and management recognition score of the two management methods were analyzed and compared.Results:The repair time,maintenance time,automatic fault response time and equipment fault information push time of the medical equipment in the rehabilitation department managed by the efficiency evaluation model were(2.36±1.35)min,(3.36±1.56)d,(4.15±2.34)min and(4.36±1.36)min,respectively,which were all less than those of conventional management,the difference was statistically significant(t=13.294,11.931,15.534,18.829,P＜0.05).The average scores of equipment resource allocation,information support,environmental protection and management performance were(89.14±6.58)points,(90.69±8.45)points,(90.69±4.39)points and(91.01±5.45)points,respectively,which were higher than those of conventional management,the difference was statistically significant(t=13.982,13.246,16.251,16.422,P＜0.05).The failure rates of monitoring equipment,ultrasonic equipment,orthodontic equipment and other rehabilitation equipment were(0.98±0.20)%,(0.99±0.22)%,(0.90±0.18)%and(1.01±0.22)%,respectively,which were lower than those of conventional management,the difference was statistically significant(t=18.627,20.941,19.715,19.505,P＜0.05).The recognition scores of engineering designers,operators and doctors involved in the use and management of medical equipment in the rehabilitation department with the equipment management using the efficiency evaluation model were(89.36±6.39),(91.57±5.36)and(92.36±4.21),respectively,which were higher than those of conventional management,the difference was statistically significant(t=9.119,11.812,13.469,P＜0.05).Conclusion:The operation efficiency evaluation model of medical equipment in rehabilitation department based on equipment status information can effectively improve the accuracy of risk management of equipment in rehabilitation department,reduce the risk coefficient of equipment operation,reduce potential safety risks,and improve the operation quality and efficiency of equipment.

OBJECTIVE: Evidence that long-term exposure to ambient air pollution increases mortality among older adults, particularly those residing in low-level air pollution locations, remains scarce. This study investigated the potential links between long-term low-level air pollution exposure and mortality among Chinese older adults. METHODS: A population-based study with 317,464 individuals aged ≥ 65 years was conducted in Shenzhen, China during 2018 and 2020. Logistic regression models were used to analyze the associations between long-term exposure to air pollution and all-cause mortality, as the primary outcome, as well as non-accidental, cancer and cardiovascular mortality. RESULTS: Significant associations of PM ₁, PM _2.5, PM ₁₀, SO ₂, CO, and O ₃ exposures with a higher risk of all-cause mortality were found. Adjusted odds ratio ( OR) for each 1 µg/m ³ increment was 1.49 [95% confidence interval ( CI): 1.46, 1.53] for PM ₁, 1.30 (1.27, 1.32) for PM _2.5, 1.05 (1.04, 1.06) for PM ₁₀, 5.84 (5.39, 6.32) for SO ₂, 1.04 (1.04, 1.05) for CO, and 1.02 (1.00, 1.03) for O ₃, respectively. Long-term PM ₁, PM _2.5, PM ₁₀, SO ₂, and CO exposures also elevated the risks of non-accidental, cancer and cardiovascular mortality. CONCLUSION Long-term low-level air pollution exposure was associated with an increased mortality risk among Chinese older adults.
Humans ; Aged ; China/epidemiology* ; Male ; Female ; Air Pollution/adverse effects* ; Environmental Exposure/adverse effects* ; Air Pollutants/analysis* ; Aged, 80 and over ; Particulate Matter/adverse effects* ; Cardiovascular Diseases/mortality* ; Mortality ; Neoplasms/mortality* ; East Asian People

Virtual reality (VR) is a technology that interacts computer-generated three-dimensional scenes with the user′s senses and has been gradually applied in the real medical field. Since the first time of successful attempt in 3D laparoscopic gastrointestinal surgery VR living video broadcast in 2016, the authors have experienced the exploration of the application of this technology (2016-2017) as well as the in-depth research phase (2018-2019). Nowadays, the VR application in our center has entered into the application practice phase (2020 to present). With the technology iteration and more and more application experience acquisition, our current VR application mainly focuses on two practice settings, including the clinical teaching scenarios for early exposure to acute appendicitis for medical undergraduate students and the preoperative communication to give pati-ents an early sense of the process in the operating theatre, and has achieved good application results. With continuous breakthroughs and innovations in software and hardware, we believe that more clinical VR scenarios and the course audience will be expanded to a wider group. The integration of some new hotspots such as Meta-Universe and ChatGPT will make up for the shortcomings in VR content scenarios and interactivity, and its application prospects are infinite.

Objective:To analyze and summarize the implementation effect of basic essential surgical training (BEST) course of laparoscopic skills over the past 10 years and the practical experience in updating course content and models.Methods:The pre-class assessment questionnaires, basic laparoscopic operation assessment results, and post-class assessment questionnaires of the students who participated in the BEST course of laparoscopic skills were collected. According to the period of the course construction, the students were divided into two groups, namely students who used the course of single training system in the early stage (traditional group) and students who used the course integrating a variety of training systems after the course model was updated in the later stage (test group). The two groups were compared for the scores of track circle moving, tunnel crossing, and high and low columns, as well as their subjective evaluation of course setting and implementation effect. The t-test, Wilcoxon test, or chi-square test was conducted according to the data type using SPSS 13.0. Results:The time for 150 traditional group students to complete track circle moving, tunnel crossing, and high and low columns was 1.08 min (0.81 min, 1.60 min), 2.20 min (1.60 min, 3.27 min), and 4.86 min (3.28 min, 6.36 min), respectively, while the time for 75 test group students to complete the three operations was 1.27 min (0.87 min, 1.83 min), 2.57 min (1.58 min, 4.07 min), and 4.35 min (2.90 min, 6.42 min), respectively, with no significant difference between the two groups ( P>0.05). In terms of students' subjective evaluation of the course, a higher percentage of the test group students were satisfied with classroom environment, teaching method arrangement, training equipment, training opportunities, helping clinical work, and meeting pre-class expectations than those in the traditional group. Conclusion:The constantly updated BEST course can ensure the training quality of trainees and obtain their higher satisfaction. The benefits of this course in clinical practice can be further verified through long-term follow-up of these trainees.

Objective:Continuous glucose monitoring (CGM) technology is used to compare the advantages of insulin degludec (IDeg) as a basal insulin regimen compared with insulin glargine (IGlar) in the treatment of adult type 1 diabetes mellitus.Methods:30 adult patients with T1DM admitted to Heji Hospital Affiliated to Changzhi Medical College from September 2019 to December 2020 were screened. According to the random number table method, the patients were randomly divided into two groups (insulin degludec group and insulin glargine group) at a ratio of 1∶1, respectively treated with IDeg, IGlar and aspartate insulin for 12 weeks. The main outcome measures were the coefficient of variation of blood glucose (CV), mean amplitude of glycemic excursions (MAGE), time in range (TIR), time above range (TAR) and time below range (TBR). The secondary outcome measures were mean blood glucose (MBG), standard deviation of blood glucose (SD), fasting blood glucose (FPG), 2 h postprandial blood glucose (2 h BG), hemoglobin A1c (HbA 1c), means of daily differences (MOOD), and the frequency of hypoglycemic events. Results:At 12 weeks of treatment, the HbA 1c, FPG, 2 h BG, MBG, SD, CV and MAGE of insulin degludec group were lower than those of insulin glargine group, with statistically significant difference (all P<0.05). The TIR in the insulin degludec group was significantly higher than that in the insulin glargine group [73(63, 75)% vs 43(28, 63)%, P<0.001], and the TAR was lower than that in the glycerine group [25(17, 23)% vs 35(33, 64)%, P=0.003]. From the curve spectrum of blood glucose level of the two groups, the stability of blood glucose in the insulin degludec group was better than that in the insulin glargine group. After 12 weeks of treatment, 8 cases (8/15) in insulin degludec group had HbA 1c<7.0%, and 4 cases (4/15) in insulin glargine group had HbA 1c<7.0%, without statistically significant difference ( P=0.264). There were 7 cases (7/15) in the insulin degludec group and 1 case (1/15) in the insulin glargine group who achieved high quality blood glucose control, with statistically significant difference ( P=0.035). At the 12th week of outpatient follow-up, the incidence of nocturnal hypoglycemic events in insulin degludec group was significantly lower than that in insulin glargine group (4/15 vs 11/15, P=0.027). Conclusions:Compared with insulin glargine, insulin degludec can achieve higher blood glucose compliance rate, lower blood glucose level and reduce blood glucose fluctuations in patients with type 1 diabetes.