Objective To develop and validate a deep learning model for automatic identification of liver CT contrast-enhanced phases.Methods A total of 766 patients with liver CT contrast-enhanced images were retrospectively collected.A three-phase classification model and an arterial phase(AP)classification model were developed,so as to automatically identify liver CT contrast-enhanced phases as early arterial phase(EAP)or late arterial phase(LAP),portal venous phase(PVP),and equilibrium phase(EP).In addition,221 patients with liver CT contrast-enhanced images in 5 different hospitals were used for external validation.The annotation results of radiologists were used as a reference standard to evaluate the model performances.Results In the external validation datasets,the accuracy in identifying each enhanced phase reached to 90.50%-99.70%.Conclusion The automatic identification model of liver CT contrast-enhanced phases based on residual network may provide an efficient,objective,and unified image quality control tool.

Zhejiang University School of Medicine's affiliated Sir Run Run Shaw Hospital has responded to innovative rehabilitation healthcare policy by implementing enhanced recovery after surgery(ERAS)wards based on healing concepts during the development of new wards in its multi-campus integration.By integrating 5G communication technology with the hospital's various information systems and leveraging the hospital's locational advantages,the hospital has upgraded its software and hardware configurations,promoting a multidisciplinary collaborative bedside management model in the context of new technologies.In terms of overall environment construction,the hospital uses best healing theories in physical design,organizational conditions,and interpersonal relationships to facilitate and support patients'healing experiences,effectively improving medical and nursing services.

Zhejiang University School of Medicine's affiliated Sir Run Run Shaw Hospital has responded to innovative rehabilitation healthcare policy by implementing enhanced recovery after surgery(ERAS)wards based on healing concepts during the development of new wards in its multi-campus integration.By integrating 5G communication technology with the hospital's various information systems and leveraging the hospital's locational advantages,the hospital has upgraded its software and hardware configurations,promoting a multidisciplinary collaborative bedside management model in the context of new technologies.In terms of overall environment construction,the hospital uses best healing theories in physical design,organizational conditions,and interpersonal relationships to facilitate and support patients'healing experiences,effectively improving medical and nursing services.

Zhejiang University School of Medicine's affiliated Sir Run Run Shaw Hospital has responded to innovative rehabilitation healthcare policy by implementing enhanced recovery after surgery(ERAS)wards based on healing concepts during the development of new wards in its multi-campus integration.By integrating 5G communication technology with the hospital's various information systems and leveraging the hospital's locational advantages,the hospital has upgraded its software and hardware configurations,promoting a multidisciplinary collaborative bedside management model in the context of new technologies.In terms of overall environment construction,the hospital uses best healing theories in physical design,organizational conditions,and interpersonal relationships to facilitate and support patients'healing experiences,effectively improving medical and nursing services.

Zhejiang University School of Medicine's affiliated Sir Run Run Shaw Hospital has responded to innovative rehabilitation healthcare policy by implementing enhanced recovery after surgery(ERAS)wards based on healing concepts during the development of new wards in its multi-campus integration.By integrating 5G communication technology with the hospital's various information systems and leveraging the hospital's locational advantages,the hospital has upgraded its software and hardware configurations,promoting a multidisciplinary collaborative bedside management model in the context of new technologies.In terms of overall environment construction,the hospital uses best healing theories in physical design,organizational conditions,and interpersonal relationships to facilitate and support patients'healing experiences,effectively improving medical and nursing services.

Zhejiang University School of Medicine's affiliated Sir Run Run Shaw Hospital has responded to innovative rehabilitation healthcare policy by implementing enhanced recovery after surgery(ERAS)wards based on healing concepts during the development of new wards in its multi-campus integration.By integrating 5G communication technology with the hospital's various information systems and leveraging the hospital's locational advantages,the hospital has upgraded its software and hardware configurations,promoting a multidisciplinary collaborative bedside management model in the context of new technologies.In terms of overall environment construction,the hospital uses best healing theories in physical design,organizational conditions,and interpersonal relationships to facilitate and support patients'healing experiences,effectively improving medical and nursing services.

Zhejiang University School of Medicine's affiliated Sir Run Run Shaw Hospital has responded to innovative rehabilitation healthcare policy by implementing enhanced recovery after surgery(ERAS)wards based on healing concepts during the development of new wards in its multi-campus integration.By integrating 5G communication technology with the hospital's various information systems and leveraging the hospital's locational advantages,the hospital has upgraded its software and hardware configurations,promoting a multidisciplinary collaborative bedside management model in the context of new technologies.In terms of overall environment construction,the hospital uses best healing theories in physical design,organizational conditions,and interpersonal relationships to facilitate and support patients'healing experiences,effectively improving medical and nursing services.

Zhejiang University School of Medicine's affiliated Sir Run Run Shaw Hospital has responded to innovative rehabilitation healthcare policy by implementing enhanced recovery after surgery(ERAS)wards based on healing concepts during the development of new wards in its multi-campus integration.By integrating 5G communication technology with the hospital's various information systems and leveraging the hospital's locational advantages,the hospital has upgraded its software and hardware configurations,promoting a multidisciplinary collaborative bedside management model in the context of new technologies.In terms of overall environment construction,the hospital uses best healing theories in physical design,organizational conditions,and interpersonal relationships to facilitate and support patients'healing experiences,effectively improving medical and nursing services.

Zhejiang University School of Medicine's affiliated Sir Run Run Shaw Hospital has responded to innovative rehabilitation healthcare policy by implementing enhanced recovery after surgery(ERAS)wards based on healing concepts during the development of new wards in its multi-campus integration.By integrating 5G communication technology with the hospital's various information systems and leveraging the hospital's locational advantages,the hospital has upgraded its software and hardware configurations,promoting a multidisciplinary collaborative bedside management model in the context of new technologies.In terms of overall environment construction,the hospital uses best healing theories in physical design,organizational conditions,and interpersonal relationships to facilitate and support patients'healing experiences,effectively improving medical and nursing services.

Objective:To analyze the difference of clinical characteristics and outcomes of infants with moderate and severe pediatric acute respiratory distress syndrome(PARDS)diagnosed according to baseline oxygenation index(OI) in pediatric intensive care unit(PICU).Methods:Second analysis of the data collected from the "Efficacy of pulmonary surfactant (PS) in the treatment of children with moderate and severe ARDS" program.Retrospectively compare of the differences in clinical data such as general condition, underlying diseases, OI, mechanical ventilation, PS administration and outcomes among infants with moderate and severe PARDS divided by baseline OI who admitted to PICUs at 14 participating tertiary hospitals from 2016 to December 2021.Results:Among the 101 cases, 55 cases (54.5%) were moderate and 46 cases (45.5%) were severe PARDS.The proportion of male in the severe group (50.0% vs.72.7%, P=0.019) and the pediatric critical illness score(PCIS)[72 (68, 78) vs.76 (70, 80), P=0.019] were significantly lower than those in the moderate group, while there was no significant difference regarding age, body weight, etiology of PARDS and underlying diseases.The utilization rate of high-frequency ventilator in the severe group was significantly higher than that in the moderate group (34.8% vs.10.9%, P=0.004), but there was no significant difference in PS use, fluid load and pulmonary complications.The 24 h OI improvement (0.26±0.33 vs.0.04±0.34, P=0.001) and the 72 h OI improvement[0.34 (-0.04, 0.62) vs.0.15 (-0.14, 0.42), P=0.029)]in the severe group were significantly better than those in the moderate group, but there was no significant difference regarding mortality, length of hospital stay and intubation duration after diagnosis of PARDS between the two groups. Conclusion:In moderate and severe(divided by baseline OI) PARDS infants with invasive mechanical ventilation, children in severe group have better oxygenation improvement in the early stage after PARDS identified and are more likely to receive high frequency ventilation compared to those in moderate group.Baseline OI can not sensitively distinguish the outcomes and is not an ideal index for PARDS grading of this kind of patient.