Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective:To compare the patient-reported outcomes and short-term clinical outcomes between robotic-assisted and laparoscopic-assisted radical gastrectomy for locally advanced gastric cancer.Methods:This single-center prospective randomized controlled trial was conducted in the Department of Gastrointestinal Surgery, Affiliated Hospital of Qingdao University from October 2020 to August 2022. Patients with locally advanced gastric cancer who were to undergo radical gastrectomy were selected and randomly divided into two groups according to 1∶1, and received robotic surgery and laparoscopic surgery, respectively. Patient-reported outcomes and short-term clinical outcomes (including postoperative complications, surgical quality and postoperative short-term recovery) were compared between the two groups by independent sample t test, Mann-Whitney U test, repeated ANOVA, generalized estimating equation, χ2 test and Fisher′s exact test. Results:A total of 237 patients were enrolled for modified intention-to-treat analysis (120 patients in the robotic group, 117 patients in the laparoscopic group). There were 180 males and 59 females, aged (63.0±10.2) years (range: 30 to 85 years). The incidence of postoperative complications was similar between the robotic group and laparoscopic group (16.7% (20/120) vs. 15.4% (18/117), χ2=0.072, P=0.788). The robotic group had higher patient-reported outcomes scores in general health status, emotional, and social domains compared to the laparoscopic group, differences in time effect, intervention effect, and interaction effect were statistically significant (general health status: χ2 value were 275.68, 3.91, 6.38, P value were <0.01, 0.048, 0.041; emotional: χ2 value were 77.79, 6.04, 6.15, P value were <0.01, 0.014, 0.046; social: χ2 value were 148.00, 7.57, 5.98, P value were <0.01, 0.006, 0.048). However, the financial burden of the robotic group was higher, the differences in time effect, intervention effect and interaction effect were statistically significant ( χ2 value were 156.24, 4.08, 36.56, P value were <0.01, 0.043,<0.01). Conclusion:Compared to the laparoscopic group, the robotic group could more effectively relieve postoperative negative emotions and improve recovery of social function in patients.

Objective:To compare the patient-reported outcomes and short-term clinical outcomes between robotic-assisted and laparoscopic-assisted radical gastrectomy for locally advanced gastric cancer.Methods:This single-center prospective randomized controlled trial was conducted in the Department of Gastrointestinal Surgery, Affiliated Hospital of Qingdao University from October 2020 to August 2022. Patients with locally advanced gastric cancer who were to undergo radical gastrectomy were selected and randomly divided into two groups according to 1∶1, and received robotic surgery and laparoscopic surgery, respectively. Patient-reported outcomes and short-term clinical outcomes (including postoperative complications, surgical quality and postoperative short-term recovery) were compared between the two groups by independent sample t test, Mann-Whitney U test, repeated ANOVA, generalized estimating equation, χ2 test and Fisher′s exact test. Results:A total of 237 patients were enrolled for modified intention-to-treat analysis (120 patients in the robotic group, 117 patients in the laparoscopic group). There were 180 males and 59 females, aged (63.0±10.2) years (range: 30 to 85 years). The incidence of postoperative complications was similar between the robotic group and laparoscopic group (16.7% (20/120) vs. 15.4% (18/117), χ2=0.072, P=0.788). The robotic group had higher patient-reported outcomes scores in general health status, emotional, and social domains compared to the laparoscopic group, differences in time effect, intervention effect, and interaction effect were statistically significant (general health status: χ2 value were 275.68, 3.91, 6.38, P value were <0.01, 0.048, 0.041; emotional: χ2 value were 77.79, 6.04, 6.15, P value were <0.01, 0.014, 0.046; social: χ2 value were 148.00, 7.57, 5.98, P value were <0.01, 0.006, 0.048). However, the financial burden of the robotic group was higher, the differences in time effect, intervention effect and interaction effect were statistically significant ( χ2 value were 156.24, 4.08, 36.56, P value were <0.01, 0.043,<0.01). Conclusion:Compared to the laparoscopic group, the robotic group could more effectively relieve postoperative negative emotions and improve recovery of social function in patients.