Objective Against the backdrop of rapid advancements in artificial intelligence(AI)technology,generative AI such as DeepSeek and Manus is integrating into and reshaping the healthcare industry with disruptive force.AI and related technologies are increasingly being applied in hospital management.Based on the mature application of Robotic Process Automa-tion(RPA)technology,this study aims to explore the potential of AI technology in the automatic collection,processing,and dis-tribution of daily hospital information statistics reports.By constructing an automated daily report generation system,it seeks to address issues in traditional hospital management such as high labor costs and low efficiency,thereby providing technical support for the construction of smart hospitals.Methods This study took a tertiary hospital in Shenzhen as an empirical research sub-ject,developing a specific workflow plan for automatically generating daily hospital information statistics reports based on AI+RPA technology to empower smart hospital management.To tackle data missing issues,an innovative 30-minute silent period manual review mechanism was established,creating a dual-guarantee system of"automatic machine processing+manual seconda-ry verification."The study focused on achieving technical breakthroughs in key links including data acquisition,storage and pro-cessing,daily report generation,and scheduled push notifications,ensuring the automation and accuracy of the daily hospital in-formation statistics reporting process.Results The AI+RPA technology demonstrated excellent implementation outcomes in key aspects and specific application scenarios such as data acquisition,storage,automated daily report generation,and automated sending to designated locations for hospital information statistics.The efficiency of daily report generation was significantly im-proved,labor costs were reduced,and data accuracy was enhanced.The human-machine collaboration mechanism effectively re-solved low-level errors caused by missing data and optimized the overall daily report generation process.Conclusion By recon-structing the workflow for daily hospital information statistics reports,AI+RPA technology significantly enhanced management ef-ficiency and data quality,meeting the data needs of hospital management departments.Compared to the daily consumption of hu-man resources previously,the"Statistics Robot"not only substantially reduces labor costs but can also be scheduled to run auto-matically during idle periods for both personnel and information systems.It breaks down departmental barriers and data silos,a-chieving higher resource allocation efficiency and laying a data foundation for smart hospital development.In the future,the deep integration of AI with RPA technology and the targeted development of software robots for other specialized purposes will bring more innovation and transformation to smart hospitals,further enhancing hospital management efficiency and service quality.

Objective Against the backdrop of rapid advancements in artificial intelligence(AI)technology,generative AI such as DeepSeek and Manus is integrating into and reshaping the healthcare industry with disruptive force.AI and related technologies are increasingly being applied in hospital management.Based on the mature application of Robotic Process Automa-tion(RPA)technology,this study aims to explore the potential of AI technology in the automatic collection,processing,and dis-tribution of daily hospital information statistics reports.By constructing an automated daily report generation system,it seeks to address issues in traditional hospital management such as high labor costs and low efficiency,thereby providing technical support for the construction of smart hospitals.Methods This study took a tertiary hospital in Shenzhen as an empirical research sub-ject,developing a specific workflow plan for automatically generating daily hospital information statistics reports based on AI+RPA technology to empower smart hospital management.To tackle data missing issues,an innovative 30-minute silent period manual review mechanism was established,creating a dual-guarantee system of"automatic machine processing+manual seconda-ry verification."The study focused on achieving technical breakthroughs in key links including data acquisition,storage and pro-cessing,daily report generation,and scheduled push notifications,ensuring the automation and accuracy of the daily hospital in-formation statistics reporting process.Results The AI+RPA technology demonstrated excellent implementation outcomes in key aspects and specific application scenarios such as data acquisition,storage,automated daily report generation,and automated sending to designated locations for hospital information statistics.The efficiency of daily report generation was significantly im-proved,labor costs were reduced,and data accuracy was enhanced.The human-machine collaboration mechanism effectively re-solved low-level errors caused by missing data and optimized the overall daily report generation process.Conclusion By recon-structing the workflow for daily hospital information statistics reports,AI+RPA technology significantly enhanced management ef-ficiency and data quality,meeting the data needs of hospital management departments.Compared to the daily consumption of hu-man resources previously,the"Statistics Robot"not only substantially reduces labor costs but can also be scheduled to run auto-matically during idle periods for both personnel and information systems.It breaks down departmental barriers and data silos,a-chieving higher resource allocation efficiency and laying a data foundation for smart hospital development.In the future,the deep integration of AI with RPA technology and the targeted development of software robots for other specialized purposes will bring more innovation and transformation to smart hospitals,further enhancing hospital management efficiency and service quality.

Objective:To evaluate the relationship between postoperative delirium(POD) and preoperative frailty in elderly patients undergoing spinal surgery.Methods:Two hundred and twenty patients of both sexes, aged ≥65 yr, of American Society of Anesthesiologists Physical Status classification Ⅱ-Ⅳ, undergoing elective posterior lumbar decompression, bone grafting and internal fixation under general anesthesia, were selected. Frailty was measured using the FRAIL (fatigue, resistance, ambulation, illness, and loss of weight) scale on 1 day before surgery. POD was assessed twice a day within 3 days by Confusion Assessment Method. Patients were divided into POD group and non-POD group according to whether POD occurred within 3 days after surgery. Multivariate logistic regression analysis was used to identify the risk factors for POD in elderly patients undergoing spinal surgery, and the value of preoperative frailty in predicting POD was analyzed using the receiver operating characteristic curve.Results:A total of 190 patients were finally enrolled, among which 55 patients presented with frailty before surgery, and the incidence was 29.0%. Forty-six patients developed POD, and the incidence was 24.2%. Multivariate logistic regression analysis showed that aging ( OR=1.15, 95% confidence interval [ CI] 1.03-1.29, P=0.017), preoperative frailty ( OR=2.35, 95% CI 1.24-4.43, P=0.009), increase in surgical segments ( OR=4.14, 95% CI 1.71-10.05, P=0.002) and increase in postoperative 24-h pain VAS score ( OR=1.38, 95% CI 1.07-1.78, P=0.013) were independent risk factors for POD in elderly patients undergoing spinal surgery. The area under receiver operating characteristic curve of preoperative frailty in predicting POD was 0.702 (95% CI 0.608-0.796, P<0.001). Conclusions:Preoperative frailty is an independent risk factor for POD in elderly patients undergoing spinal surgery. Preoperative frailty can predict the occurrence of POD in elderly patients undergoing spinal surgery to some extent.

Objective To investigate the clinical characteristics of chronic invasive fungal rhinosinusitis.Methods Clinical features and outcomes of 46 proven cases of chronic invasive fungal rhinosinusitis admitted in Huashan Hospital,Fudan University from January 2009 to December 2016 were retrospectively reviewed.Results Of the 46 patients enrolled,left sphenoid sinus,ethmoid sinus and maxillary sinus were affected in 24,23 and 20 cases,respectively,while right maxillary sinus,ethmoid sinus and sphenoid sinus were affected in 18,16 and 15 eases,respectively.Left and right frontal sinus were affected in 9 and 6 cases,respectively.The central nervous system and orbit were the most commonly affected sites in external nasal involvements,noted in 22 cases respectively.Left sphenoid (17 cases) and ethmoid sinus (15 cases) involvements were most common in central nervous system affected patients.Left sphenoid (14 cases) and ethmoid sinus (13 cases) involvements were most common in orbit affected patients.Aspergillus species were the primary pathogens observed in 42 eases.Zygomycete,candida and dark filamentous fungus were observed in two,one and one case,respectively.Pathologically,37 of the cases were chronic nongranulomatous type and the left 9 were chronic granulomatous type who were all immunocompetent hosts.The initial symptoms usually included headache,dizziness and nasal discomforts including nasal obstruction and purulent secretion.The chief complaints usually included headache,dizziness,and visual disturbances including blurred vision,vision loss or even blindness.Antifungal treatment combined with surgical interventions for removal or drainage focus lesions achieved significant effect,and 42 patients were cured.Conclusions Chronic invasive fungal rhinosinusitis should be taken into consideration in the presence of nasal discomforts or nonspecific symptoms such as headache and dizziness.The possibility of chronic invasive fungal rhinosinusitis should be cautious after the emergence of vision abnormalities.