Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To explore the policy synergy of 71 Diagnosis-Intervention Packet(DIP)pilot cities from the perspective of policy synergy at both the national and provincial levels.Methods:Policy evaluation dimensions were constructed by text mining method,and the surface plots of policy consistency were drawn by the Policy Modeling Consistency Index(PMC),and the degree of policy synergy between each city and national policies and with cities in the province were calculated by correlation analysis.Results:Different levels of policy in pilot cities and the policy differences among pilot cities mainly focus on policy disclosure,core elements,and infrastructure,at the central level,most cities maintain a high degree of consistency with the state in terms of policy nature,management measures,infrastructure,and policy evaluation,and the policy timeliness,policy perspective,and core elements still need to be improved;at the provincial level,cities within the 20 provinces show characteristics in low level of complete synergy,high level of close synergy and differentiated partial synergy.Conclusion:The 71 DIP pilot cities have established a preliminary policy system,but there are still more cities with missing policies and a lack of coordination.In the future,efforts should be made to advance the policy development process,promote the improvement of the policy system,and promote coordination among pilot cities in policy implementation.

Objective:To investigate respiratory virus infection in children with septic shock in pediatric care units (PICU) in China and its influence on clinical outcomes.Methods:The clinical data of children with septic shock in children′s PICU from January 2018 to December 2019 in 10 Chinese hospitals were retrospectively collected. They were divided into the pre-COVID-19 and post-COVID-19 groups according to the onset of disease, and the characteristics and composition of respiratory virus in the 2 groups were compared. Matching age, malignant underlying diseases, bacteria, fungi and other viruses, a new database was generated using 1∶1 propensity score matching method. The children were divided into the respiratory virus group and non-respiratory virus group according to the presence or absence of respiratory virus infection; their clinical characteristics, diagnosis, and treatment were compared by t-test, rank sum test and Chi-square test. The correlation between respiratory virus infection and the clinical outcomes was analyzed by logistic regression. Results:A total of 1 247 children with septic shock were included in the study, of them 748 were male; the age was 37 (11, 105) months. In the pre-and post-COVID-19 groups, there were 530 and 717 cases of septic shock, respectively; the positive rate of respiratory virus was 14.9% (79 cases) and 9.8% (70 cases); the seasonal distribution of septic shock was 28.9% (153/530) and 25.9% (185/717) in autumn, and 30.3% (161/530) and 28.3% (203/717) in winter, respectively, and the corresponding positive rates of respiratory viruses were 19.6% (30/153) and 15.7% (29/185) in autumn, and 21.1% (34/161) and 15.3% (31/203) in winter, respectively. The positive rates of influenza virus and adenovirus in the post-COVID-19 group were lower than those in the pre-COVID-19 group (2.1% (15/717) vs. 7.5% (40/530), and 0.7% (5/717) vs. 3.2% (17/530), χ2=21.51 and 11.08, respectively; all P<0.05). Rhinovirus virus were higher than those in the pre-Covid-19 group (1.7% (12/717) vs. 0.2% (1/530), χ2=6.51, P=0.011). After propensity score matching, there were 147 cases in both the respiratory virus group and the non-respiratory virus group. Rate of respiratory failure, acute respiratory distress, rate of disseminated coagulation dysfunction, and immunoglobulin usage of the respiratory virus group were higher than those of non-respiratory virus group (77.6% (114/147) vs. 59.2% (87/147), 17.7% (26/147) vs. 4.1% (6/147), 15.6% (25/147) vs. 4.1% (7/147), and 35.4% (52/147) vs. 21.4% (32/147); χ2=11.07, 14.02, 11.06 and 6.67, all P<0.05); and PICU hospitalization of the former was longer than that of the later (7 (3, 16) vs. 3 (1, 7)d, Z=5.01, P<0.001). Univariate logistic regression analysis showed that the presence of respiratory viral infection was associated with respiratory failure, disseminated coagulation dysfunction, the use of mechanical ventilation, and the use of immunoglobulin and anti-respiratory viral drugs ( OR=2.42, 0.22, 0.25, 0.56 and 1.12, all P<0.05). Conclusions:The composition of respiratory virus infection in children with septic shock is different between pre and post-COVID-19. Respiratory viral infection is associated with organ dysfunction in children with septic shock. Decreasing respiratory viral infection through respiratory protection may improve the clinical outcome of these children.

Objective:To explore the factors affecting the prognosis of severe pediatric acute respiratory distress syndrome (ARDS) after receiving extracorporeal membrane oxygenation (ECMO) support.Methods:It was a multicenter prospective observational study. A total of 95 children with severe ARDS who were treated with ECMO salvage therapy from January 2018 to December 2022 in 9 pediatric ECMO centers in China were enrolled in the study. The general data, disease severity, organ function, comprehensive treatment and prognosis were recorded, and they were divided into survival group and death group according to the outcome at discharge. T test, chi-square test, multivariate Logistic regression and mixed linear model were used to analyze the relationship among baseline before ECMO treatment, some important indicators (pediatric critical scores, platelet count, albumin, fibrinogen, etc) during ECMO treatment and prognosis. Results:Among the 95 children with severe ARDS who received ECMO, 55 (58%) were males and 40 (42%) were females, aged 36.9 (0.5, 72.0) months. Twelve children (13%) were immunodeficient. Sixty-eight (72%) children were treated with venous artery (VA) mode and 27 (28%) with venous vein (VV) mode. The discharge survival rates of overall, VA, and VV mode children were 51% (48/95), 47% (32/68), and 59% (16/27), respectively. The number of immunodeficient children in the death group was higher, and there were lower pediatric critical scores, platelet count, albumin, fibrinogen and arterial oxygen partial pressure/fraction of inspired oxygen (PaO 2/FiO 2), higher ventilator driving pressure (ΔP), oxygenaion index (OI), and longer ARDS duration before ECMO (all P<0.05). There were no statistically significant differences in other indicators, including age, gender, weight, and ECMO mode among different prognostic groups (all P>0.05). High ΔP, high OI, low P/F, and low albumin were high-risk factors affecting prognosis(all P<0.05). After further grouping, it was found that ΔP≥25 cmH 2O (1 cmH 2O=0.098 kPa), P/F≤67 mmHg (1 mmHg=0.133 kPa) and OI≥35 were the thresholds for predicting poor prognosis ( P<0.05). From 24 h after ECMO, there were significant differences in ΔP, P/F and OI between the dead group and the survival group (all P<0.05), and the differences gradually increased with the ECMO process. The platelet level was significant from 7 days after ECMO ( P<0.05) and gradually expanded. Blood lactate levels showed a significant difference between the 2 groups on before and after ECMO ( P<0.05) and gradually increased from 24 h after ECMO. Conclusions:The risk factors affecting the prognosis of severe ARDS in ECMO include high ΔP, high OI, low P/F and low albumin purification therapy before ECMO. The gradual decrease of ΔP, OI and increase of P/F from 24 h of ECMO predicted a good prognosis, while the gradual increase of lactate after ECMO application showed a poor prognosis.

Objective:To investigate the clinical features, pathogen composition, and prognosis of septic shock in pediatric intensive care units (PICU) in China.Methods:A multicenter retrospective cohort study. A retrospective analysis was conducted on the clinical data of children with septic shock from 10 hospitals in China between January 2018 and December 2021. The clinical features, pathogen composition, and outcomes were collected. Patients were categorized into malignant tumor and non-malignant tumor groups, as well as survival and mortality groups. T test, Mann Whitney U test or Chi square test were used respectively for comparing clinical characteristics and prognosis between 2 groups. Multiple Logistic regression was used to identify risk factors for mortality. Results:A total of 1 247 children with septic shock were included, with 748 males (59.9%) and the age of 3.1 (0.9, 8.8) years. The in-patient mortality rate was 23.2% (289 cases). The overall pathogen positive rate was 68.2% (851 cases), with 1 229 pathogens identified. Bacterial accounted for 61.4% (754 strains) and virus for 24.8% (305 strains). Among all bacterium, Gram negative bacteria constituted 64.2% (484 strains), with Pseudomonas aeruginosa and Enterobacter being the most common; Gram positive bacteria comprised 35.8% (270 strains), primarily Streptococcus and Staphylococcus species. Influenza virus (86 strains (28.2%)), Epstein-Barr virus (53 strains (17.4%)), and respiratory syncytial virus (46 strains (17.1%)) were the top three viruses. Children with malignant tumors were older and had higher pediatric risk of mortality (PRISM) Ⅲ score, paediatric sequential organ failure assessment (pSOFA) score (7.9 (4.3, 11.8) vs. 2.3 (0.8, 7.5) years old, 22 (16, 26) vs. 16 (10, 24) points, 10 (5, 14) vs. 8 (4, 12) points, Z=11.32, 0.87, 4.00, all P<0.05), and higher pathogen positive rate, and in-hospital mortality (77.7% (240/309) vs. 65.1% (611/938), 29.7% (92/309) vs. 21.0% (197/938), χ2=16.84, 10.04, both P<0.05) compared to the non-tumor group. In the death group, the score of PRISM Ⅲ, pSOFA (16 (22, 29) vs. 14 (10, 20) points, 8 (12, 15) vs. 6 (3, 9) points, Z=4.92, 11.88, both P<0.05) were all higher, and presence of neoplastic disease, positive rate of pathogen and proportion of invasive mechanical ventilation in death group were also all higher than those in survival group (29.7% (87/289) vs. 23.2% (222/958), 77.8% (225/289) vs. 65.4% (626/958), 73.7% (213/289) vs. 50.6% (485/958), χ2=5.72, 16.03, 49.98, all P<0.05). Multiple Logistic regression showed that PRISM Ⅲ, pSOFA, and malignant tumor were the independent risk factors for mortality ( OR=1.04, 1.09, 0.67, 95% CI 1.01-1.05, 1.04-1.12, 0.47-0.94, all P<0.05). Conclusions:Bacterial infection are predominant in pediatric septic shock, but viral infection are also significant. Children with malignancies are more severe and resource consumptive. The overall mortality rate for pediatric septic shock remains high, and mortality are associated with malignant tumor, PRISM Ⅲ and pSOFA scores.