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 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.

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 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 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 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.

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.

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.