Objective:To utilize routinely available clinical parameters to uncover the clinical features of different clusters in patients with chronic rhinosinusitis with nasal polyp (CRSwNP) through unsupervised clustering analysis.Methods:The clinical data from 155 CRSwNP patients undergoing nasal endoscopic surgery at Renmin Hospital of Wuhan University from 2021 to 2023 were prospectively collected, including 112 males and 43 females, aged from 7 to 87 years. Unsupervised clustering analysis was conducted using various clinical parameters, including age, gender, smoking and drinking history, local eosinophil (EOS) and neutrophil (NEU) counts, comorbid allergic rhinitis (AR), comorbid asthma, recurrence status, serum-specific IgE, total IgE, cytokine levels, peripheral blood EOS count and percentage, Lund-Mackay CT score, the ratio of CT scores for the maxillary sinus and ethmoid sinus (E/M ratio), visual analogue scale (VAS) score, Lund-Kennedy endoscopic score, and other common clinical indicators to elucidate the clinical characteristics of each cluster. Statistical analysis was conducted using GraphPad Prism 9.5 software.Results:Hierarchical clustering analysis identified four main clusters (Cluster A1-A4), showcasing distinct characteristics such as mild nasal polyps with higher peripheral blood cytokines levels, nasal polyps accompanied by allergies and asthma, a subtype of nasal polyps with high recurrence rates dominated by neutrophils, and nasal polyps with high eosinophil levels. Further subset clustering revealed two clusters of mild polyps (Cluster B1-B2) featuring high cytokine expression and comorbid AR; and two clusters of severe polyps (Cluster B3-B4) presented with severe symptoms, high Lund-Mackay CT score, and high Lund-Kennedy endoscopic score. Variations between Cluster B3 and B4 included symptom complexity, the degree of eosinophil infiltration, and the probability of comorbid asthma. Further clustering analysis for eosinophilic nasal polyps revealed a cluster characterized by highly neutrophilic infiltration and recurrent nasal polyps. The comprehensive analysis of multi-index correlations demonstrated valuable insights into the relationships between common clinical parameters of nasal polyps, providing valuable information for a deeper understanding of the pathogenesis of CRSwNP.Conclusion:The clustering analysis in this study categorizes CRSwNP patients into different clusters based on clinical features and disease outcomes, providing a new perspective for more precise clinical treatment strategies.

ObjectiveTo investigate the value of baseline red cell distribution width （RDW） and alkaline phosphatase （ALP） level after ursodeoxycholic acid （UDCA） treatment for one month in predicting the response to UDCA treatment in patients with primary biliary cholangitis （PBC）. MethodsA retrospective analysis was performed for the data of 127 patients with PBC who were diagnosed in Department of Hepatology， The Third People’s Hospital of Jiangsu University， from January 2015 to July 2022， with data collected at baseline， after one month of treatment， and after one year of follow-up. Based on the Paris-I criteria， the patients were divided into good response group and poor response group， and the two groups were analyzed in terms of clinical and laboratory features and their association with response to UDCA. The Logistic regression method was used to investigate the independent risk factors for response to UDCA treatment. The area under the ROC curve （AUC） was used to determine the optimal cut-off values of related indicators； the patients were divided into two groups based on such values， and the two groups were compared in terms of baseline indicators and response. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between two groups. ResultsCompared with the good response group， the poor response group had significantly higher levels of total bilirubin， aspartate aminotransferase/alanine aminotransferase， ALP， RDW， and RDW-CV at baseline and a significantly higher level of ALP after one month of UDCA treatment （Z=-4.792， -3.697， -2.399， -4.102， -3.220， and -4.236， all P<0.05）. Compared with the good response group， the poor response group had significantly lower levels of albumin， hemoglobin， lymphocytes， hematocrit， and body mass index at baseline （Z=-3.592， -3.603， -2.602， -3.829， -2.432， all P<0.05）， as well as significantly lower levels of prealbumin， albumin/globulin ratio， apolipoprotein A， and free triiodothyronine at baseline （t=4.530， 3.402， 3.485， and 3.639， all P<0.001）. Compared with the poor response group， the good response group had a significantly lower proportion of patients with liver cirrhosis， gallstones/cholecystitis， or anemia （χ²=20.815， 3.892， and 12.283， all P<0.05）. Baseline RDW （odds ratio ［OR］=1.157， 95% confidence interval ［CI］： 1.028‍ — ‍1.301， P=0.015） and ALP level after one month of treatment （OR=1.012， 95%CI： 1.005‍ — ‍1.020， P=0.002） were independent risk factors for response to UDCA， with an AUC of 0.713 and 0.720， respectively. The patients with baseline RDW≥upper limit of normal （ULN） and ALP≥2.2×ULN after one month of UDCA treatment had a lower UDCA response rate （42.6% vs 8.2%， χ²=20.813， P<0.001）. ConclusionPatients with baseline RDW≥ULN and ALP≥2.2×ULN after one month of UDCA treatment tend to have a low biochemical response rate to UDCA.

Objective:To explore the current situation of synergistic allocation of factors of production in China's medical research institutes,sort out the focuses and deficiencies of the existing policies,so as to provide references for the optimization of production factor and the new quality productivity formation in medical institutions.Methods:Based on the two-factor productivity theory,the index evaluation system is constructed,and the composite system synergy model is used to analyze the degree of order of production factors and the degree of synergy of the composite system,and explore the change of synergy degree of each sequential covariate;and the macro model of the health system is used in conjunction with the content analysis method to carry out the frequency counting of the policies to promote the enhancement of the capacity of each production factor of the main body of innovation of the medical scientific research institutes.Results:The synergistic degree of the production factors and the composite system of medical research institutions showed a non-synergistic development trend,with the worst synergistic level in 2021;number of personnel,number of institutions,building floor space,production factors and sequential coefficients were weakly synergized and in a state of non-synergistic development.Among the 43 policy texts,the internal submodular policy tools were used more,the external submodular policy tools were used less,and the use of internal and external policy tools is unbalanced.Conclusion:The number of personnel,institutions and building area of medical research institutions are constraints on the synergistic development of innovative entities.It is recommended to increase the training of innovative talents in medical research institutions,improve the construction of new institutions,coordinate the layout of large scientific devices and functional housing,introduce targeted systematic planning,improve the market of factors of production,and consolidate the technological foundation for future development.

Objective:To explore the current situation of synergistic allocation of factors of production in China's medical research institutes,sort out the focuses and deficiencies of the existing policies,so as to provide references for the optimization of production factor and the new quality productivity formation in medical institutions.Methods:Based on the two-factor productivity theory,the index evaluation system is constructed,and the composite system synergy model is used to analyze the degree of order of production factors and the degree of synergy of the composite system,and explore the change of synergy degree of each sequential covariate;and the macro model of the health system is used in conjunction with the content analysis method to carry out the frequency counting of the policies to promote the enhancement of the capacity of each production factor of the main body of innovation of the medical scientific research institutes.Results:The synergistic degree of the production factors and the composite system of medical research institutions showed a non-synergistic development trend,with the worst synergistic level in 2021;number of personnel,number of institutions,building floor space,production factors and sequential coefficients were weakly synergized and in a state of non-synergistic development.Among the 43 policy texts,the internal submodular policy tools were used more,the external submodular policy tools were used less,and the use of internal and external policy tools is unbalanced.Conclusion:The number of personnel,institutions and building area of medical research institutions are constraints on the synergistic development of innovative entities.It is recommended to increase the training of innovative talents in medical research institutions,improve the construction of new institutions,coordinate the layout of large scientific devices and functional housing,introduce targeted systematic planning,improve the market of factors of production,and consolidate the technological foundation for future development.

Objective:To explore the current situation of synergistic allocation of factors of production in China's medical research institutes,sort out the focuses and deficiencies of the existing policies,so as to provide references for the optimization of production factor and the new quality productivity formation in medical institutions.Methods:Based on the two-factor productivity theory,the index evaluation system is constructed,and the composite system synergy model is used to analyze the degree of order of production factors and the degree of synergy of the composite system,and explore the change of synergy degree of each sequential covariate;and the macro model of the health system is used in conjunction with the content analysis method to carry out the frequency counting of the policies to promote the enhancement of the capacity of each production factor of the main body of innovation of the medical scientific research institutes.Results:The synergistic degree of the production factors and the composite system of medical research institutions showed a non-synergistic development trend,with the worst synergistic level in 2021;number of personnel,number of institutions,building floor space,production factors and sequential coefficients were weakly synergized and in a state of non-synergistic development.Among the 43 policy texts,the internal submodular policy tools were used more,the external submodular policy tools were used less,and the use of internal and external policy tools is unbalanced.Conclusion:The number of personnel,institutions and building area of medical research institutions are constraints on the synergistic development of innovative entities.It is recommended to increase the training of innovative talents in medical research institutions,improve the construction of new institutions,coordinate the layout of large scientific devices and functional housing,introduce targeted systematic planning,improve the market of factors of production,and consolidate the technological foundation for future development.

Objective:To explore the current situation of synergistic allocation of factors of production in China's medical research institutes,sort out the focuses and deficiencies of the existing policies,so as to provide references for the optimization of production factor and the new quality productivity formation in medical institutions.Methods:Based on the two-factor productivity theory,the index evaluation system is constructed,and the composite system synergy model is used to analyze the degree of order of production factors and the degree of synergy of the composite system,and explore the change of synergy degree of each sequential covariate;and the macro model of the health system is used in conjunction with the content analysis method to carry out the frequency counting of the policies to promote the enhancement of the capacity of each production factor of the main body of innovation of the medical scientific research institutes.Results:The synergistic degree of the production factors and the composite system of medical research institutions showed a non-synergistic development trend,with the worst synergistic level in 2021;number of personnel,number of institutions,building floor space,production factors and sequential coefficients were weakly synergized and in a state of non-synergistic development.Among the 43 policy texts,the internal submodular policy tools were used more,the external submodular policy tools were used less,and the use of internal and external policy tools is unbalanced.Conclusion:The number of personnel,institutions and building area of medical research institutions are constraints on the synergistic development of innovative entities.It is recommended to increase the training of innovative talents in medical research institutions,improve the construction of new institutions,coordinate the layout of large scientific devices and functional housing,introduce targeted systematic planning,improve the market of factors of production,and consolidate the technological foundation for future development.

Objective:To explore the current situation of synergistic allocation of factors of production in China's medical research institutes,sort out the focuses and deficiencies of the existing policies,so as to provide references for the optimization of production factor and the new quality productivity formation in medical institutions.Methods:Based on the two-factor productivity theory,the index evaluation system is constructed,and the composite system synergy model is used to analyze the degree of order of production factors and the degree of synergy of the composite system,and explore the change of synergy degree of each sequential covariate;and the macro model of the health system is used in conjunction with the content analysis method to carry out the frequency counting of the policies to promote the enhancement of the capacity of each production factor of the main body of innovation of the medical scientific research institutes.Results:The synergistic degree of the production factors and the composite system of medical research institutions showed a non-synergistic development trend,with the worst synergistic level in 2021;number of personnel,number of institutions,building floor space,production factors and sequential coefficients were weakly synergized and in a state of non-synergistic development.Among the 43 policy texts,the internal submodular policy tools were used more,the external submodular policy tools were used less,and the use of internal and external policy tools is unbalanced.Conclusion:The number of personnel,institutions and building area of medical research institutions are constraints on the synergistic development of innovative entities.It is recommended to increase the training of innovative talents in medical research institutions,improve the construction of new institutions,coordinate the layout of large scientific devices and functional housing,introduce targeted systematic planning,improve the market of factors of production,and consolidate the technological foundation for future development.

Objective:To explore the current situation of synergistic allocation of factors of production in China's medical research institutes,sort out the focuses and deficiencies of the existing policies,so as to provide references for the optimization of production factor and the new quality productivity formation in medical institutions.Methods:Based on the two-factor productivity theory,the index evaluation system is constructed,and the composite system synergy model is used to analyze the degree of order of production factors and the degree of synergy of the composite system,and explore the change of synergy degree of each sequential covariate;and the macro model of the health system is used in conjunction with the content analysis method to carry out the frequency counting of the policies to promote the enhancement of the capacity of each production factor of the main body of innovation of the medical scientific research institutes.Results:The synergistic degree of the production factors and the composite system of medical research institutions showed a non-synergistic development trend,with the worst synergistic level in 2021;number of personnel,number of institutions,building floor space,production factors and sequential coefficients were weakly synergized and in a state of non-synergistic development.Among the 43 policy texts,the internal submodular policy tools were used more,the external submodular policy tools were used less,and the use of internal and external policy tools is unbalanced.Conclusion:The number of personnel,institutions and building area of medical research institutions are constraints on the synergistic development of innovative entities.It is recommended to increase the training of innovative talents in medical research institutions,improve the construction of new institutions,coordinate the layout of large scientific devices and functional housing,introduce targeted systematic planning,improve the market of factors of production,and consolidate the technological foundation for future development.

Objective:To explore the current situation of synergistic allocation of factors of production in China's medical research institutes,sort out the focuses and deficiencies of the existing policies,so as to provide references for the optimization of production factor and the new quality productivity formation in medical institutions.Methods:Based on the two-factor productivity theory,the index evaluation system is constructed,and the composite system synergy model is used to analyze the degree of order of production factors and the degree of synergy of the composite system,and explore the change of synergy degree of each sequential covariate;and the macro model of the health system is used in conjunction with the content analysis method to carry out the frequency counting of the policies to promote the enhancement of the capacity of each production factor of the main body of innovation of the medical scientific research institutes.Results:The synergistic degree of the production factors and the composite system of medical research institutions showed a non-synergistic development trend,with the worst synergistic level in 2021;number of personnel,number of institutions,building floor space,production factors and sequential coefficients were weakly synergized and in a state of non-synergistic development.Among the 43 policy texts,the internal submodular policy tools were used more,the external submodular policy tools were used less,and the use of internal and external policy tools is unbalanced.Conclusion:The number of personnel,institutions and building area of medical research institutions are constraints on the synergistic development of innovative entities.It is recommended to increase the training of innovative talents in medical research institutions,improve the construction of new institutions,coordinate the layout of large scientific devices and functional housing,introduce targeted systematic planning,improve the market of factors of production,and consolidate the technological foundation for future development.

Objective:To explore the current situation of synergistic allocation of factors of production in China's medical research institutes,sort out the focuses and deficiencies of the existing policies,so as to provide references for the optimization of production factor and the new quality productivity formation in medical institutions.Methods:Based on the two-factor productivity theory,the index evaluation system is constructed,and the composite system synergy model is used to analyze the degree of order of production factors and the degree of synergy of the composite system,and explore the change of synergy degree of each sequential covariate;and the macro model of the health system is used in conjunction with the content analysis method to carry out the frequency counting of the policies to promote the enhancement of the capacity of each production factor of the main body of innovation of the medical scientific research institutes.Results:The synergistic degree of the production factors and the composite system of medical research institutions showed a non-synergistic development trend,with the worst synergistic level in 2021;number of personnel,number of institutions,building floor space,production factors and sequential coefficients were weakly synergized and in a state of non-synergistic development.Among the 43 policy texts,the internal submodular policy tools were used more,the external submodular policy tools were used less,and the use of internal and external policy tools is unbalanced.Conclusion:The number of personnel,institutions and building area of medical research institutions are constraints on the synergistic development of innovative entities.It is recommended to increase the training of innovative talents in medical research institutions,improve the construction of new institutions,coordinate the layout of large scientific devices and functional housing,introduce targeted systematic planning,improve the market of factors of production,and consolidate the technological foundation for future development.