1.Comparison of the predictive performance of SARIMA, Prophet, and BSTS models in forecasting the incidence of hand, foot, and mouth disease
LU Wenhai ; KONG Xiaojie ; SONG Lixia ; LU Chunru ; YU Bikun ; XIE Yan
Journal of Preventive Medicine 2026;38(1):79-84
Objective:
To compare the predictive performance of the seasonal autoregressive integrated moving average (SARIMA) model, the Prophet model, and the Bayesian structural time series (BSTS) model in forecasting the incidence of hand, foot, and mouth disease (HFMD) , so as to provide a basis for optimizing the early warning system of this disease.
Methods:
Weekly incidence data of HFMD in Longgang District, Shenzhen City from 2014 to 2024 were collected. The HFMD incidence data from 2014-2019 and 2023 were used as the training set to construct SARIMA, Prophet, and BSTS models, while the data from 2024 were used as the test set to compare and evaluate the predictive performance of the three models. The technique for order preference by similarity to ideal solution (TOPSIS) method was employed to calculate the C-value. This approach integrates multiple evaluation metrics, such as the mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), and symmetric mean absolute percentage error (SMAPE), to comprehensively assess model performance.
Results:
A total of 150 111 cases of HFMD were reported in Longgang District from 2014 to 2024, with an average annual incidence of 400.72/105. The weekly incidence fluctuated between 0 and 63.78/105, exhibiting a bimodal seasonal pattern characterized by a primary peak from May to July and a secondary peak from September to October. In the training set, all three models demonstrated a good fit to the bimodal epidemic trend of HFMD, with the BSTS model achieving the best fit. The BSTS model yielded performance metrics as follows: MAE=0.124, MSE=0.050, RMSE=0.223, SMAPE=0.021, and a C-value of 1.000. In the test set, all three models, including SARIMA, Prophet, and BSTS, performed well for short-term predictions (≤16 weeks), with the Prophet model showing relatively superior predictive performance. However, the prediction accuracy of all models declined as the forecast horizon extended. During the primary peak period (May-July), the Prophet model exhibited better predictive performance, whereas the BSTS model performed relatively better during the secondary peak period (September-October).
Conclusions
For the short-term forecasting of weekly HFMD incidence, the Prophet model outperformed both the SARIMA and BSTS models. During the primary peak period, the Prophet model demonstrated superior predictive performance, whereas the BSTS model exhibited better accuracy in forecasting the secondary peak period.
2.Explainable Machine Learning Model for Predicting Prognosis in Patients with Malignant Tumors Complicated by Acute Respiratory Failure: Based on the eICU Collaborative Research Database in the United States
Zihan NAN ; Linan HAN ; Suwei LI ; Ziyi ZHU ; Qinqin ZHU ; Yan DUAN ; Xiaoting WANG ; Lixia LIU
Medical Journal of Peking Union Medical College Hospital 2026;17(1):98-108
To develop and validate a model for predicting intensive care unit (ICU) mortality risk in patients with malignant tumors complicated by acute respiratory failure (ARF) based on an explainable machine learning framework. Clinical data of patients with malignant tumors and ARF were extracted from the eICU Collaborative Research Database in the United States, including demographic characteristics, comorbidities, vital signs, laboratory test indicators, and major interventions within the first 24 hours after ICU admission.The study outcome was ICU death.Enrolled patients were randomly divided into a training set and a validation set at a ratio of 7:3.Predictor variables were selected using least absolute shrinkage and selection operator (LASSO) regression.Five machine learning algorithms-extreme gradient boosting (XGBoost), support vector machine (SVM), Logistic regression, multilayer perceptron (MLP), and C5.0 Decision Tree-were employed to construct predictive models.Model performance was evaluated based on the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and other metrics.The optimal model was further interpreted using the Shapley additive explanations (SHAP) algorithm. A total of 3196 patients with malignant tumors complicated by ARF were included.The training set comprised 2, 261 patients and the validation set 935 patients; 683 patients died during ICU stay, while 2513 survived.LASSO regression ultimately selected 12 variables closely associated with patient ICU outcomes, including sepsis comorbidity, use of vasoactive drugs, and within the first 24 hours after ICU admission: minimum mean arterial pressure, maximum heart rate, maximum respiratory rate, minimum oxygen saturation, minimum serum bicarbonate, minimum blood urea nitrogen, maximum white blood cell count, maximum mean corpuscular volume, maximum serum potassium, and maximum blood glucose.After model evaluation, the XGBoost model demonstrated the best performance.The AUCs for predicting ICU mortality risk in the training and validation sets were 0.940 and 0.763, respectively; accuracy was 88.3% and 81.2%;sensitivity was 98.5% and 95.9%.Its predictive performance also remained optimal in sensitivity analyses.SHAP analysis indicated that the top five variables contributing to the model's predictions were minimum oxygen saturation, minimum serum bicarbonate, minimum mean arterial pressure, use of vasoactive drugs, and maximum white blood cell count. This study successfully developed a mortality risk prediction model for ICU patients with malignant tumors complicated by ARF based on a large-scale dataset and performed explainability analysis.The model aids clinicians in early identification of high-risk patients and implementing individualized interventions.
3.A cross-sectional study of anxiety disorders in adults in Inner Mongolia Autonomous Region
Xin WANG ; Lixia CHEN ; Tingting ZHANG ; Ping LYU ; Dongsheng LYU ; Zhaorui LIU ; Jie YAN ; Ruiqi WANG ; Hua DING ; Yinxia BAI ; Yueqin HUANG ; Xiaojie SUI
Chinese Mental Health Journal 2025;39(5):385-391
Objective:To describe the prevalence of anxiety disorders and its distribution in Inner Mongolia Autonomous Region,and to explore the relevant factors of anxiety disorders.Methods:From June 2019 to Decem-ber 2019,representative multi-stage disproportionate stratified sampling procedure was used to sample in residents aged 18 and over in the Inner Mongolia Autonomous Region.All respondents were face-to-face interviewed by trained interviewers.Composite International Diagnostic Interview-3.0(CIDI-3.0)was used to diagnose anxiety disorders according to the criteria and definition of the Diagnostic and Statistical Manual of Mental Disorders,Fourth Edition(DSM-Ⅳ).Chi-square test and multivariate logistic regression analysis were used for statistical anal-ysis.Results:Totally 12 315 people were interviewed in the survey.The weighted 12-mouth prevalence rate of any anxiety disorder was 4.64%,and the lifetime prevalence rate was 6.25%.The weighted 12-month prevalence rate of anxiety disorders was higher in female than that in male(5.38%vs.3.92%).The rate was higher in rural resi-dents than that in urban residents(5.67%vs.3.95%).The rate was higher in people with chronic diseases than that in people without chronic diseases(6.81%vs.2.29%).Logistic regression analysis showed that unmarried(OR=2.32,95%CI:1.31-4.10),separated/divorced(OR=2.49,95%CI:1.33-4.67),in debt(OR=1.55,95%CI:1.04-2.32),chronic disease(OR=2.22,95%CI:1.39-3.53),family history of anxiety disorders(OR=12.05,95%CI:8.78-16.53),poor sleep(OR=2.64,95%CI:1.97-3.54)were risk factors of occurrence of anxiety disorders,while junior high school(OR=0.65,95%CI:0.44-0.96)was protective factor of anxiety disor-ders.Conclusion:Adults with chronic diseases,poor sleep,unmarried or separated/divorced,family history of anxi-ety disorders,and financial debt are at higher risk groups of anxiety disorder in Inner Mongolia Autonomous Re-gion.
4.Changing antimicrobial resistance profiles of Burkholderia cepacia in hospitals across China:results from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chunyue GE ; Yunjian HU ; Xiaoman AI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(5):557-562
Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1%(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5%,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3%(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1%)were isolated from sputum and respiratory secretions,followed by urine(10.7%)and blood samples(8.1%).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1%.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4%in the patients<18 years old to 20.6%in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.
5.Development and application of intensive care unit digital intelligence multimodal shift handover system.
Xue BAI ; Lixia CHANG ; Wei FANG ; Zhengang WEI ; Yan CHEN ; Zhenfeng ZHOU ; Min DING ; Hongli LIU ; Jicheng ZHANG
Chinese Critical Care Medicine 2025;37(10):950-955
OBJECTIVE:
To develop a digital intelligent multimodal shift handover system for the intensive care unit (ICU) and evaluate its application effect in ICU shift handovers.
METHODS:
A research and development team was established, consisting of 1 department director, 1 head nurse, 3 information technology engineers, 3 nurses, and 2 doctors. Team members were assigned responsibilities including overall coordination and planning, platform design and maintenance, pre-application training, collection and organization of clinical feedback, and research investigation respectively. A digital intelligent multimodal shift handover system was developed for ICU based on the Shannon-Weaver linear transmission model. This innovative system integrated automated data collection, intelligent dynamic monitoring, multidimensional condition analysis and visual reporting functions. A cloud platform was used to gather data from multi-parameter vital signs monitors, infusion pumps, ventilators and other devices. Artificial intelligence algorithms were employed to standardize and analyze the data, providing personalized recommendations for healthcare professionals. A self-controlled before-after method was adopted. Before the application of the ICU digital intelligent multimodal shift handover system (from December 2023 to March 2024), the traditional verbal bedside handover was used; from June 2024 to March 2025, the ICU digital intelligent multimodal shift handover system was applied for shift handovers. Questionnaires before the application of the shift handover system were collected in April 2024, and those after the application were collected in April 2025. The shift handover time, handover quality (scored by the nursing handover evaluation scale), satisfaction with doctor-nurse communication (scored by the ICU doctor-nurse scale) before and after the application of the handover system were compared, and nurses' satisfaction with the shift handover system (scored by the clinical nursing information system effectiveness evaluation scale) was investigated.
RESULTS:
After the application of the ICU digital intelligent multimodal shift handover system, the shift handover time was significantly shorter than that before the application [minutes: 20 (15, 25) vs. 30 (22, 40)], the handover quality was significantly higher than that before the application [score: 84.0 (78.0, 88.5) vs. 71.0 (55.0, 79.0)], and the satisfaction with doctor-nurse communication was also significantly higher than that before the application (score: 84.58±6.79 vs. 74.50±11.30). All differences were statistically significant (all P < 0.05). In addition, the nurses' system effectiveness evaluation scale score was 102.30±10.56, which indicated that nurses had a very high level of satisfaction with the ICU digital intelligent multimodal shift handover system.
CONCLUSIONS
The application of the ICU digital intelligent multimodal shift handover system can shorten the shift handover time, improve the handover quality, and enhance the satisfaction with doctor-nurse communication. Nurses have a high level of satisfaction with this system.
Intensive Care Units
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Humans
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Patient Handoff
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Artificial Intelligence
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Algorithms
6.Clinical value analysis of different MRI measurement methods in evaluating the efficacy of neoadjuvant therapy for breast cancer
Yuling DUAN ; Xuezhi ZHOU ; Yongyi LI ; Lixia MA ; Desheng YANG ; Jiao CHENG ; Yan WU ; Tao LIU ; Guoyuan JIANG ; Mei WANG
The Journal of Practical Medicine 2025;41(14):2152-2159
Objective To compare the diagnostic performance of three breast MRI measurement methods—RECIST 1.1,the optimal method,and three-dimensional(3D)volumetric assessment—in assessing the efficacy of neoadjuvant chemotherapy(NAC)in breast cancer patients,with the objective of identifying the most clinically practical approach.Methods A total of 110 breast cancer patients who underwent NAC followed by surgical treatment between 2019 and 2023 were included in the study.Breast magnetic resonance imaging(MRI)was conducted within one week before and after the completion of NAC.Tumor response was evaluated using RECIST 1.1 criteria,widely recognized as the optimal method,as well as 3D volume measurement.Pathological response was determined according to the Miller-Payne grading system.Sensitivity,specificity,accuracy,and the area under the receiver operating characteristic curve(AUC)were computed and compared using the DeLong test.Results The AUC values for RECIST 1.1,the optimal method,and 3D volumetric assessment were 0.768,0.795,and 0.883,respectively.The 3D volumetric assessment exhibited significantly better discriminative performance(P<0.05),with the highest sensitivity(98.9%),specificity(77.8%),and accuracy(95.5%).Additionally,the optimal method demonstrated superior performance over RECIST 1.1 across multiple parameters.Conclusions 3D volumetric mea-surement demonstrates superior performance compared to RECIST 1.1 and the optimal method in evaluating the response to NAC,offering a more accurate and comprehensive assessment tool.Additionally,the optimal method shows advantages over RECIST 1.1 and may serve as a practical alternative in settings where 3D software is not available.
7.Research progresses in imaging evaluation on changes of body composition in prostate cancer patients after androgen deprivation treatment
Na JIANG ; Junrong YAN ; Tao LIU ; Lixia QIAN
Chinese Journal of Interventional Imaging and Therapy 2025;22(5):355-359
Prostate cancer is a common malignant tumor in males.Androgen deprivation treatment(ADT)is the main therapeutic method for prostate cancer,which often leads to changes of body composition(BC)characterized by sarcopenia,centripetal fat redistribution and osteoporosis.Imaging techniques can accurately and conveniently assess changes of BC.The research progresses of imaging evaluation on BC changes in prostate cancer patients after ADT were reviewed in this article.
8.Sinicization and reliability and validity the European organization for research and treatment of cancer quality of life questionnaire-head and neck 43
Qing LYU ; Junqiu LI ; Fa ZHANG ; Cuimin KOU ; Yan LI ; Shuxiang ZHANG ; Yanxin ZHANG ; Lixia NIU ; Yiming ZHU ; Xin YUAN ; Linan QIN ; Shaoyan LIU
Chinese Journal of Otorhinolaryngology Head and Neck Surgery 2025;60(6):617-623
Objective:To translate the European organization for research and treatment of cancer quality of life questionnaire-head and neck 43(EORTC QLQ-H&N43) and to conduct cultural debugging and reliability and validity testing for the Chinese version of the scale.Methods:The Chinese version of EORTC QLQ-H&N43 was formed through literal translation, integration, back translation, group discussion, cultural adjustment, and pre-investigation of the English version of the scale. From March 2023 to December 2023, convenience sampling was used to investigate 254 patients with head and neck tumors at the Cancer Hospital of the Chinese Academy of Medical Sciences, including 197 males and 57 females, aged (55.6±13.6) years. SPSS 25.0 statistical software was used to analyze the performance of the scale.Results:The Chinese version of EORTC QLQ-H&N43 retained all 43 items. After evaluation by 5 experts, the content validity index (I-CVI) at the item level of the scale ranged from 0.80 to 1.00, and the average content validity index (S-CVI/Ave) at the scale level was 0.991. Through exploratory factor analysis, a total of 9 common factors were extracted, with a cumulative variance contribution rate of 68.158%; Cronbach′s α coefficient of the total scale was 0.943, and the half reliability was 0.896.Conclusion:The Chinese version of EORTC QLQ-H&N43 has good reliability and validity, which can be used as an effective tool to evaluate the quality of life of head and neck cancer patients in China.
9.Factors influencing occupational burnout and career choice among resident physicians during standardized training
Yan ZHAN ; Li ZHANG ; Miao JIA ; Jianyu QUE ; Haifei GAO ; Xiaomin GUO ; Lixia CHEN
Chinese Mental Health Journal 2025;39(6):547-554
Objective:To investigate the prevalence,related factors,and career implications of occupational burnout among resident physicians during standardized training in Inner Mongolia.Methods:This cross-sectional study used convenience sampling to enroll 2 891 resident physicians,assessing them with a self-developed general information questionnaire,socio-psychological scales,and a universal burnout inventory.Latent profile analysis clas-sified participants based on burnout dimensions,while logistic regression models examined the factors influencing burnout and their relationship with career choices.Results:Resident physicians were divided into low(59.0%),moderate(28.9%),and high(12.1%)burnout subgroups.Logistic regression showed that,compared to the low burnout group,significant risk factors included professional master's students(OR=0.44),working>70 hours weekly(OR=0.63),>4 night shifts monthly(OR=0.66),anxiety(mild OR=0.49;moderate OR=0.26;se-vere OR=0.14),depression(mild OR=0.38;moderate OR=0.24;severe OR=0.11),insomnia(mild OR=0.51;moderate OR=0.44;severe OR=0.38),low social support(OR=0.23),and low happiness index(OR=0.42).Male residents(OR=1.25)were less likely to experience burnout.High burnout residents were 5.11 times more likely to quit the medical profession.Conclusion:Training intensity and socio-psychological factors signifi-cantly contribute resident physicians' burnout levels,with severe burnout increase career attrition.
10.Analysis of the genetic characteristics of varicella-zoster virus prevalent in Qinghai province from 2020 to 2024
Lixia FAN ; Jinyuan GUO ; Qianlan LI ; Yan ZHANG ; Xiaotong WANG ; Zhijian TANG ; Chunxiang WANG
Chinese Journal of Experimental and Clinical Virology 2025;39(4):468-473
Objective:To understand the genetic characteristics of varicella-zoster virus(VZV)prevalent in Qinghai province,China since 2020.Methods:A total of 54 pharyngeal swab specimens were collected from sporadic suspected varicella cases in Qinghai province in 2020,2023,and 2024. Real-time fluorescence quantitative polymerase chain reaction was used for etiological screening of the specimens. Sequencing of three genes,namely ORF22,ORF38,and ORF62,and single-nucleotide polymorphism(SNP)analysis were performed on VZV nucleic acid-positive specimens.Results:All 54 suspected varicella cases were diagnosed with VZV infection,and three gene sequences were successfully obtained from 53 specimens. The results of genotype identification showed that all VZV infection case specimens obtained in this study in Qinghai province were wild strains. Among them,4 specimens in 2020 were of clade 2 type;among 14 specimens in 2023,7 were of clade 2 type and the remaining 7 were of clade 5 type;among 35 specimens in 2024,27 were of clade5 type,5 were of clade 2 type,and 3 were of clade 4 type. The SNP results showed that in 2023 and 2024,one specimen each had an A→G base mutation at position 37 990,and in 2024,3 specimens had a T→C base mutation at position 37946. Among them,the sequences containing the former mutation have been prevalent and spread in multiple regions of China,and the latter has not been reported in other regions of China.Conclusion:From 2020 to 2024 in Qinghai province,at least three genotypes of VZV,namely clade 2 type,clade 5 type,and clade 4 type,co-prevailed,and the clade 5 genotype of VZV may become the dominant prevalent strain.


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