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 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.

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.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Objective:To evaluate the effect of fiberoptic endoscopic evaluation of swallowing (FEES) on clinical functional outcomes of patients with intensive care unit-acquired swallowing disorders (ICU-ASD).Methods:This retrospective cohort study analyzed clinical data of patients diagnosed with post-extubation dysphagia (PED) in the intensive care unit (ICU) and respiratory intensive care unit (RICU) of the Affiliated Hospital of Inner Mongolia Medical University from February 2020 to February 2025. Patients were categorized into a FEES group of 60 cases [34 males, 26 females, aged 37-80 years (median age 62 years)] and a control group without FEES of 58 cases [32 males, 26 females, aged 39-77 years (median age 61 years)].The patients in two groups received swallowing function and feeding training based on the results of the FEES assessment and the Volume-Viscosity Swallow Test-Clinical Version (VVST-CV), respectively. Clinical functional outcome measures included pneumonia incidence, clinical pulmonary infection score (CPIS), pneumonia severity index (PSI), Functional Oral Intake Scale (FOIS), and dietary method at discharge. χ2 test, Mann-Whitney U test, and Wilcoxon signed-rank test, were employed for statistical analysis of the outcome measures. Results:Compared with the control group, the FEES group had significantly lower aspiration pneumonia incidence at discharge [3.3% (2/60) vs 15.5% (9/58), χ2=5.179, P=0.023]. Regarding dietary methods,a significantly higher proportion of patients in the FEES group achieved complete oral feeding compared with the control group [75.0% (45/60) vs 67.3% (39/58), χ2=8.065, P<0.05]. After training, the FEES group had higher median FOIS scores than the control group (7.00 vs 6.00, Z=-2.370, P=0.018), and lower CPIS scores (2.50 vs 5.00, Z=-2.216, P=0.027) and PSI scores (59.00 vs 73.00, Z=-2.251, P=0.024). Within-group comparisons revealed that FOIS scores significantly improved post-training in both groups (both P<0.001). Conclusion:Early FEES examination for ICU patients with acquired swallowing disorders is associated with a lower incidence of pneumonia, improved swallowing function, and superior clinical functional outcomes.

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 investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.