1.Epidemiological characteristics and influencing factors of severe fever with thrombocytopenia syndrome in Zhejiang Province
LÜ ; Jing ; XU Xinying ; QIAO Yingyi ; SHI Xinglong ; YUE Fang ; LIU Ying ; CHENG Chuanlong ; ZHANG Yuqi ; SUN Jimin ; LI Xiujun
Journal of Preventive Medicine 2026;38(1):10-14
Objective:
To analyze the epidemiological characteristics and influencing factors of severe fever with thrombocytopenia syndrome (SFTS) in Zhejiang Province from 2019 to 2023, so as to provide the reference for strengthening SFTS prevention and control.
Methods:
Data on laboratory-confirmed SFTS cases in Zhejiang Province from 2019 to 2023 were collected through the Infectious Disease Reporting Information System of Chinese Disease Prevention and Control Information System. Meteorological data, geographic environment and socioeconomic factors during the same period were collected from the fifth-generation European Centre for Medium-Range Weather Forecasts, Geospatial Data Cloud, and Zhejiang Statistical Yearbook, respectively. Descriptive epidemiological methods were used to analyze the epidemiological characteristics of SFTS from 2019 to 2023, and a Bayesian spatio-temporal model was constructed to analyze the influencing factors of SFTS incidence.
Results:
A total of 578 SFTS cases were reported in Zhejiang Province from 2019 to 2023, with an annual average incidence of 0.23/105. The peak period was from May to July, accounting for 52.60%. There were 309 males and 269 females, with a male-to-female ratio of 1.15∶1. The cases were mainly aged 50-<80 years, farmers, and in rural areas, accounting for 82.53%, 77.34%, and 75.43%, respectively. Taizhou City and Shaoxing City reported more SFTS cases, while Shaoxing City and Zhoushan City had higher annual average incidences of SFTS. The Bayesian spatio-temporal interaction model showed good goodness of fit. The results showed that mean temperature (RR=1.626, 95%CI: 1.111-2.378) and mean wind speed (RR=1.814, 95%CI: 1.321-2.492) were positively correlated with SFTS risk, while altitude (RR=0.432, 95%CI: 0.230-0.829) and population density (RR=0.443, 95%CI: 0.207-0.964) were negatively correlated with SFTS risk.
Conclusions
SFTS in Zhejiang Province peaks from May to July. Middle-aged and elderly people and farmers are high-risk populations. Taizhou City, Shaoxing City, and Zhoushan City are high-incidence areas. Mean temperature, mean wind speed, altitude, and population density can all affect the risk of SFTS incidence.
2.Construction and validation of a risk prediction model for oral frailty in the elderly community population
Min WANG ; Wenjuan YANG ; Ting LIAO ; Jinmei ZOU ; Dongxia LIAO ; Cuicui ZHANG ; Yingyi DENG ; Xiyan GONG ; Changju LIAO
Chinese Journal of Nursing 2025;60(3):274-280
Objective This study examines the factors influencing oral frailty in the elderly community,develops a risk prediction model,and validates its efficacy,so as to provide references for identifying and preventing oral weakness in the elderly.Methods 556 elderly individuals from 4 communities were selected by convenience sampling from June to August 2024 in Zigong City Sichuan Province.They were randomly divided into a training group(383 cases)and a validation group(165 cases).Data were collected by a general information questionnaire,Social Frailty Scale,Geriatric Depression Scale,and the Oral Frailty Index-8 screening tool.Logistic regression was used to determine the influencing factors,and R software was used to establish a nomogram model for predicting the risk of oral frailty.Bootstrap method and the validation group were used for internally validation of the model.Calibration curve was used to evaluate the prediction performance of the model.Results 548 valid questionnaires were collected.The final model variables included whether the age ≥80 years,wearing removable dentures,reduced frequency of going out,brushing teeth less than twice a day,frequent dry mouth,increased difficulty in eating hard foods,and choking.The area under the receiver operating characteristic curve of the training group was 0.95(95%CI:0.93~0.97),and the best cutoff value was 0.687.The model achieved an accuracy of 87%,sensitivity of 91%,specificity of 85%,positive predictive value of 0.75,and negative predictive value of 0.95.The Hosmer-Lemeshow fitting test show that x2=3.036,P=0.932,indicating a good model fit.Conclusion The oral frailty prediction model demonstrated a good discrimination,calibration,and clinical utility,which can provide a scientific basis for the prevention and early screening of oral frailty in the elderly.
3.Teaching practice of oncology internship for eight-year clinical medicine program students
Zhiyang ZHANG ; Yifei YAN ; Yingyi WANG ; Nan JIA
Basic & Clinical Medicine 2025;45(10):1396-1400
Objective To investigate the needs and gains of eight-year clinical medicine program students during their oncology internships,and provide reference for the reform of clinical teaching in oncology.Methods A ques-tionnaire survey was conducted among 52 students from Peking Union Medical College,Tsinghua University School of Medicine,and Peking Union Medical College"4+4"medical doctor program who underwent internships in the Department of Oncology at Peking Union Medical College from July 2023 to June 2024 in order to examine their basic knowledge of oncology,the courses they are interested in,their preference for teaching methods and the gains from the internships.The exam was conducted before and after the internship.Results All 52 students participated in the survey and examination.Most students were interested in clinical diagnosis and treatment,new drug develop-ment and progress in basic research.All students acknowledged that their ability to solve actual clinical problems had been improved after the internship in oncology,51(98.08%)recognized that their capacity of literature searching and reviewing,integrating the information and reasoning had improved,while 50(96.15%)believed that their capacity to read Computed Tomography(CT)images or perform imaging diagnosis had improved.The number of students who were interested in oncology increased from 41(78.85%)before the internship and up to 47(90.38%)after the training.The average score of the students before internship was 63.88±8.90,and then signif-icantly increased up to 82.94±9.12 afterwards.Conclusions Eight-year program students of clinical medicine are quite interested in oncology,their learning and training outcomes have been further improved through the clinical training during internship.
4.Construction and validation of a risk prediction model for oral frailty in the elderly community population
Min WANG ; Wenjuan YANG ; Ting LIAO ; Jinmei ZOU ; Dongxia LIAO ; Cuicui ZHANG ; Yingyi DENG ; Xiyan GONG ; Changju LIAO
Chinese Journal of Nursing 2025;60(3):274-280
Objective This study examines the factors influencing oral frailty in the elderly community,develops a risk prediction model,and validates its efficacy,so as to provide references for identifying and preventing oral weakness in the elderly.Methods 556 elderly individuals from 4 communities were selected by convenience sampling from June to August 2024 in Zigong City Sichuan Province.They were randomly divided into a training group(383 cases)and a validation group(165 cases).Data were collected by a general information questionnaire,Social Frailty Scale,Geriatric Depression Scale,and the Oral Frailty Index-8 screening tool.Logistic regression was used to determine the influencing factors,and R software was used to establish a nomogram model for predicting the risk of oral frailty.Bootstrap method and the validation group were used for internally validation of the model.Calibration curve was used to evaluate the prediction performance of the model.Results 548 valid questionnaires were collected.The final model variables included whether the age ≥80 years,wearing removable dentures,reduced frequency of going out,brushing teeth less than twice a day,frequent dry mouth,increased difficulty in eating hard foods,and choking.The area under the receiver operating characteristic curve of the training group was 0.95(95%CI:0.93~0.97),and the best cutoff value was 0.687.The model achieved an accuracy of 87%,sensitivity of 91%,specificity of 85%,positive predictive value of 0.75,and negative predictive value of 0.95.The Hosmer-Lemeshow fitting test show that x2=3.036,P=0.932,indicating a good model fit.Conclusion The oral frailty prediction model demonstrated a good discrimination,calibration,and clinical utility,which can provide a scientific basis for the prevention and early screening of oral frailty in the elderly.
5.Associations of systemic immune-inflammation index and systemic inflammation response index with maternal gestational diabetes mellitus: Evidence from a prospective birth cohort study.
Shuanghua XIE ; Enjie ZHANG ; Shen GAO ; Shaofei SU ; Jianhui LIU ; Yue ZHANG ; Yingyi LUAN ; Kaikun HUANG ; Minhui HU ; Xueran WANG ; Hao XING ; Ruixia LIU ; Wentao YUE ; Chenghong YIN
Chinese Medical Journal 2025;138(6):729-737
BACKGROUND:
The role of inflammation in the development of gestational diabetes mellitus (GDM) has recently become a focus of research. The systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI), novel indices, reflect the body's chronic immune-inflammatory state. This study aimed to investigate the associations between the SII or SIRI and GDM.
METHODS:
A prospective birth cohort study was conducted at Beijing Obstetrics and Gynecology Hospital from February 2018 to December 2020, recruiting participants in their first trimester of pregnancy. Baseline SII and SIRI values were derived from routine clinical blood results, calculated as follows: SII = neutrophil (Neut) count × platelet (PLT) count/lymphocyte (Lymph) count, SIRI = Neut count × monocyte (Mono) count/Lymph count, with participants being grouped by quartiles of their SII or SIRI values. Participants were followed up for GDM with a 75-g, 2-h oral glucose tolerance test (OGTT) at 24-28 weeks of gestation using the glucose thresholds of the International Association of Diabetes and Pregnancy Study Groups (IADPSG). Logistic regression was used to analyze the odds ratios (ORs) (95% confidence intervals [CIs]) for the the associations between SII, SIRI, and the risk of GDM.
RESULTS:
Among the 28,124 women included in the study, the average age was 31.8 ± 3.8 years, and 15.76% (4432/28,124) developed GDM. Higher SII and SIRI quartiles were correlated with increased GDM rates, with rates ranging from 12.26% (862/7031) in the lowest quartile to 20.10% (1413/7031) in the highest quartile for the SII ( Ptrend <0.001) and 11.92-19.31% for the SIRI ( Ptrend <0.001). The ORs (95% CIs) of the second, third, and fourth SII quartiles were 1.09 (0.98-1.21), 1.21 (1.09-1.34), and 1.39 (1.26-1.54), respectively. The SIRI findings paralleled the SII outcomes. For the second through fourth quartiles, the ORs (95% CIs) were 1.24 (1.12-1.38), 1.41 (1.27-1.57), and 1.64 (1.48-1.82), respectively. These associations were maintained in subgroup and sensitivity analyses.
CONCLUSION
The SII and SIRI are potential independent risk factors contributing to the onset of GDM.
Humans
;
Female
;
Pregnancy
;
Diabetes, Gestational/immunology*
;
Prospective Studies
;
Adult
;
Inflammation/immunology*
;
Glucose Tolerance Test
;
Birth Cohort
6.Relationship between school bullying and non-suicidal self-injury behaviors in adolescents with depressive disorders: the pathways of self-esteem and alexithymia
Liping LIU ; Min ZHANG ; Yingyi CHEN ; Binglan XU ; Lei DU ; Zhaoyuan XU
Sichuan Mental Health 2025;38(4):327-332
BackgroundNon-suicidal self-injury (NSSI) behaviors are common among adolescents with depressive disorders, and school bullying is recognized as a major risk factor. Previous research has shown that self-esteem and alexithymia are closely associated with both school bullying and NSSI. However, the mediating roles of self-esteem and alexithymia in the link between school bullying and NSSI are unclear. ObjectiveTo explore the mediating roles of alexithymia and self-esteem in the relationship between school bullying and NSSI behaviors in adolescents with depressive disorders, in order to inform intervention strategies targeting NSSI in this population. MethodsA total of 335 adolescents diagnosed with depressive disorders and treated at the First Psychiatric Hospital of Harbin from July 2023 to October 2024 were enrolled. Assessments included a self-developed demographic questionnaire, Adolescent Non-suicidal Self-injury Assessment Questionnaire-Behavior (ANSAQ-B), Delaware Bullying Victimization Scale-Student (DBVS-S), Rosenberg Self-Esteem Scale (RSES), and 26-item Toronto Alexithymia Scale (TAS-26). Pearson correlation analysis was used to examine the relationship among variables. Controlling for gender and age at onset of depressive symptoms, mediation analysis was performed using the “mediation” package in R 4.4.2. ResultsScores on DBVS-S and TAS-26 were positively correlated with ANSAQ-B score (r=0.408, 0.417, P<0.01), while RSES scores were negatively correlated(r=-0.300, P<0.01). Regression analysis showed that school bullying and alexithymia significantly positively predicted NSSI behaviors (B=0.212, 0.333, P<0.01), while self-esteem negatively predicted NSSI behaviors (B=-0.368, P<0.01). Alexithymia was found to mediate the relationship between school bullying and NSSI behaviors, with an indirect effect of 0.040 (95% CI: 0.018~0.069) ,account for 17.17% of the total effect. The indirect effect through self-esteem was not statistically significant (95% CI: -0.004~0.069). ConclusionExposure to school bullying and high levels of alexithymia are important predictors of NSSI behavior in adolescents with depressive disorders, and school bullying may indirectly influence NSSI behavior through alexithymia. [Funded by Scientific Research Project of Health Commition of Heilongjiang Province,(number, 20230303090154]
7.Application of AI software for chromosomal aberration analysis in occupational health surveillance and radiation biological dose estimation
Yingyi PENG ; Qiuying LIU ; Zhifang LIU ; Zongjun ZHANG ; Xiaoyan CHEN ; Kunjie HUANG ; Qiying NONG ; Na ZHAO
China Occupational Medicine 2025;52(2):171-175
Objective To explore the feasibility of applying artificial intelligence (AI) technology in chromosomal aberration (CA) analysis for occupational health surveillance of radiation workers and in biological dose estimation during nuclear emergency responses. Methods Peripheral blood samples from healthy volunteers were irradiated in vitro with X-rays and cobalt-60 (⁶⁰Co) γ rays. Chromosome slides were prepared using an automated harvesting and dropping device. The data training and outcome evaluation of CA analysis was performed on the AI software using chromosome images from occupational medical examination of radiation workers from the current lab or chromosome slides from blood samples irradiated with X-rays. The trained AI software was then used to assist in CA analysis and biological dose estimation among occupational medical examination of radiation workers, with results compared with manual reading and actual exposure doses. Results The trained AI software achieved a CA recognition accuracy of 95.11%. In the occupational health examination of radiation workers, the positive CA detection rate using AI + manual review was 2.25% higher than that in manual reviewing alone. The errors in biological dose estimation for ⁶⁰Co γ rays and X-rays using AI + manual review analysis were 11.86% and 7.33%, respectively, both within the acceptable 20.00% error margin. Conclusion AI + manual review can be effectively applied in CA analysis for occupational health examination and biological dose estimation during nuclear emergencies, significantly improving analysis efficiency.
8.First overseas imported case of schistosomiasis haematobia in Xihu District, Hangzhou City
Huami ZHANG ; Xing SU ; Jianfeng ZHANG ; Yingyi ZHANG
Chinese Journal of Schistosomiasis Control 2024;36(5):548-550
This paper reports the diagnosis and treatment of the first imported case of schistosomiasis haematobia in Xihu District of Hangzhou. The patient was an international student from Zimbabwe, and experienced repeated gross hematuria without obvious motivation. Cystoscopy displayed bladder masses, and a large number of fresh or calcified parasite eggs were found in pathological sections. In addition, urine microscopy identified Schistosoma haematobium eggs. The case was therefore definitively diagnosed as overseas imported case of imported schistosomiasis haematobia. Another case of schistosomiasis mansoni was identified among international students in the same school with the patient above by indirect haemagglutination test and urine and stool etiology examination. It is recommended to intensify health education and monitoring among overseas floating populations and improve the diagnostic skills of overseas imported schistosomiasis among professionals working in medical and disease control and prevention institutions, in order to prevent misdiagnosis and mistreatment.
9.Application of Allograft Endometriosis Rat Model in Pharmaco-dynamic Evaluation of GnRH Agonists
Ruihua ZHONG ; Guoting LI ; Wenjie YANG ; Xiangjie GUO ; Jieyun ZHOU ; Yingyi HU ; Qicheng NI ; Ye YANG ; Min ZHANG ; Yan ZHU
Laboratory Animal and Comparative Medicine 2024;44(2):127-138
Objective To establish an allogeneic rat model of endometriosis and to evaluate the effects of gonadotropin-releasing hormone (GnRH) agonist GenSci006 on experimental rat endometriosis. Methods Endometrium from SPF grade donor female SD rats were transplanted onto the abdominal wall of recipient female rats to construct an allogeneic endometriosis model. The rats undergoing sham surgery were divided into the sham group. Three weeks later, the length, width and height of the ectopic endometrium were measured, and the volume of the endometrium (V1) was calculated before drug administration. The modeling rats were randomly divided into four groups: model group, triptorelin group (0.25 mg/kg), GenSci006-1 group (0.125 mg/kg) and GenSci006-2 group (0.25 mg/kg). Each group had 16 rats and received a single dose of the corresponding drug. The sham group and model group were administered an equal volume of solvent. Three weeks after administration, ectopic endometrium was measured to calculate the volume V2 and inhibition rate. The effect of GenSci006 on rat uterus and ovarian tissues was assessed by comparing organ coefficients and changes in pathological sections. Enzyme-linked immunosorbent assay (ELISA) was used to measure the levels of serum estradiol (E2), progesterone (P4), follicle stimulating hormone (FSH), and luteinizing hormone (LH). Real-time fluorescent quantitative PCR was used to detect the expression of GnRH receptor (GnRHR) mRNA in the hypothalamus and pituitary. Western blot was used to detect the expression of estradiol receptor alpha (ERα), beta (ERβ) and progesterone receptor (PR) in ectopic endometrium. Results Three weeks after administration, compared with the model group, the body weight of rats in the triptorelin and GenSci006-2 groups significantly increased (P < 0.05), while the volume of ectopic endometrium significantly decreased (P < 0.05). Compared with the sham group, the model group showed no significant changes in uterine and ovarian organ coefficients or endometrial thickness (P > 0.05). Compared with the model group, the uterine organ coefficients and endometrial thickness were significantly reduced in the triptorelin and GenSci006-2 groups (P < 0.05). Compared with the sham group, the serum levels of E2, P4, FSH and LH in the model group showed no significant changes (P > 0.05). Compared with the model group, the ovarian organ coefficient and serum P4 levels of rats in the Triptorelin, GenSci006-1, and GenSci006-2 groups were significantly reduced (P < 0.05), while the serum LH levels of rats in the GenSci006-1 group were significantly increased (P < 0.05). However, there were no significant changes in serum E2 and FSH levels in each group (P > 0.05). Compared with the model group, the expression levels of GnRHR mRNA in the pituitary tissue of rats in the triptorelin and GenSci006-2 groups were significantly downregulated (P < 0.05), with no significantly changes in the hypothalamus (P > 0.05). There were no significant changes in the expression level of GnRHR mRNA in the hypothalamus or the protein levels of ERα, ERβ and PR in the ectopic endometrial tissue in any group (P > 0.05). Conclusion The allogeneic endometriosis rat model is a suitable animal model for screening and evaluating drugs for treating endometriosis. The volume of ectopic endometrium, inhibition rate, uterine and ovarian organ coefficients, and serum E2 levels may serve as indicators for detecting drug efficacy.
10.Relationship between plasma SP-A expression level and disease stage in silicosis patients
Kengkeng CHEN ; Bizhu ZHANG ; Yingyi PENG ; Zhifang LIU ; Xiaoyan CHEN ; Jiachun JIN
Shanghai Journal of Preventive Medicine 2024;36(2):203-206
ObjectiveTo investigate the relationship between plasma surfactant protein⁃A (SP⁃A) expression level and silicosis progression, and to provide early evidence for exploring whether SP⁃A can be used as a biomarker for clinical monitoring of silicosis disease progression. MethodsWe recruited 187 silicosis patients in Guangdong Province hospital for occupational disease prevention and treatment between November, 2019 and November,2020. Their peripheral venous blood samples were collected for the plasma isolation. The level of pulmonary SP⁃A was detected by enzyme-linked immunosorbent assay. ResultsThere was a statistically significant difference in the level of SP⁃A among the silicosis groups (P<0.05), and the plasma SP-A level of the silicosis patients in stage Ⅲ was higher than that in stage Ⅰ and stage Ⅱ (P<0.05). Smoking had effect on plasma SP⁃A levels, Age, working years and drinking had no effect on plasma SP⁃A levels. ConclusionThe expression level of SP⁃A in the plasma of silicosis patients is increased, which has a certain correlation with the disease stage, and plays a certain early warning role in the occurrence and development of silicosis, and may be a potential biomarker for the diagnosis and prognosis of silicosis.


Result Analysis
Print
Save
E-mail