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.

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.

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 ; Humans ; Patient Handoff ; Artificial Intelligence ; Algorithms

OBJECTIVE To investigate the suspected outbreak of one incident of carbapenem-resistant Acinetobacter baumannii(CRAB)infection in an intensive care unit(ICU)so as to provide experience and reference for preven-tion and control of multidrug-resistant organisms(MDROs)infections in a grass-root hospital.METHODS The epidemiological survey and environmental hygiene surveillance were performed for 8 patients with CRAB infection who were detected in ICU of Qingbaijiang District People's Hospital from Jul.21,2022 to Aug.6,2022 so as to find out the infection sources and transmission routes and take targeted intervention measures.RESULTS Totally 8 patients had CRAB infection in the ICU in a short time period,the drug resistance spectrum was basically the same;the CRAB infection/colonization rate was 12.50％(8/64),the incidence rate of CRAB infection was 7.81％(5/64),which was higher during this period than that during the same period in 2020 and 2021(P＜0.05).The environmental hygiene surveillance showed that the isolation rate of CRAB was 6.00％(3/50).The strains isolated from the hand washing sink between bed 2 and bed 3,the hanging tower of bed 13 and the countertops of treat-ment rooms showed the basically same result of drug susceptibility testing with CRAB strains isolated from the patients.This incident had been effectively under control through targeted prevention and control strategies such as the control and separation of the patients,subgrouping treatment and nursing,repeated deep cleaning and disinfec-tion as well as strict implementation of hand hygiene.CONCLUSION The overloaded enrollment of patients,insuf-ficient between-bed interval,poor and delayed cleaning and disinfection of environmental object surfaces,extensive contamination of instrument and facilities,spare supplies and hand washing sink are probably the leading causes of outbreak and prevalence of CRAB.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

Objective To understand the nursing practice of prone position ventilation for patients with moderate to severe acute respiratory distress syndrome(ARDS)in intensive care unit(ICU)in Shandong province,so as to provide basis for standardizing the nursing practice process of prone position ventilation and carrying out training for hospitals.Methods A self-made questionnaire was used,and convenience sampling was adopted.From September 15th to November 5th,2023,ICU nurses were selected from various hospital levels in Shandong province to investigate the obstructive factors of prone ventilation implementation,the weak links in nursing practice and status,and the occurrence of complications.Results A total of 1 188 questionnaires were collected,of which 991 were valid.92.8%(920/991)of nurses had performed prone position ventilation.The biggest obstacle to the implementation of prone position ventilation was the complexity of patient treatments and multiple devices involved[74.6%(686/920)].Regarding the status of training,90.5%(897/991)of nurses had received training on prone position ventilation and 77.0%(763/991)of nurses felt that training was needed.As for pre-operation assessment,more than 80.0%of nurses evaluated patients'vital signs,airway and secretions and so on,among which the evaluation awareness of analgesia was the worst[81.6%(751/920)].As for the main points of implementation,only 14.0%(129/920)of nurses chose the opposite side of the most important pipeline as the turning direction;48.6%(447/920)of nurses chose the anti-Trendelenburg position;36.3%(334/920)of nurses chose to ventilate≥12 hours.Facial edema[81.7%(752/920)],skin pressure injury[78.9%(726/920)]and eye complication[75.8%(697/920)]were the top 3 most frequent complications.Conclusions ICU nurses'prone position ventilation practices were generally line with the nursing team standard for prone position of adult mechanically ventilated patients and the best evidence recommendation,and needs to be further standardized in aspects of turning direction,position management,ventilation duration,and enteral nutrition management.It is recommended that nursing managers at all levels of hospitals further improve the quality of nursing practice of prone position ventilation according to relevant evidence-based evidence and the actual situation of hospitals.

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.

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.

Objective:To analyze the temporal distribution of other infectious diarrhea (OID) in Shenzhen and provide evidence for the prevention and control of OID.Methods:The incidence data of OID in Shenzhen from 2011 to 2023 were collected. The seasonal and trend decomposition using loess (STL), seasonal index method, concentration degree and circular distribution method were used to analyze the incidence trend and temporal distribution of OID.Results:A total of 477 611 cases of OID were reported in Shenzhen from 2011 to 2023, with an average annual incidence rate of 260.19/100 000 showing a fluctuating upward trend. The seasonal index method indicated that October-January was period with high incidence of OID in Shenzhen and the seasonal intensity began to decrease in 2020. STL revealed an obvious incidence peak in winter. The concentration method showed that OID had a certain seasonality before 2018 except 2016, but the seasonality was not obvious after 2018. The circular distribution results showed that r was 0.05, mean angle ā was 1.92° and angular standard deviation s was 141.93° ( Z=1 033.37, P<0.001), with the peak on January 1 st and the high incidence period from August 11 th to May 25 th. Conclusions:OID had a certain degree of seasonality in Shenzhen, with an obvious incidence peak in winter. Since the seasonal intensity of OID decreased after 2018, the surveillance, early warning and risk assessment of OID should be continued, and prevention and control measures should be adjusted timely according to the change in the characteristics of the epidemic.