Objective:To systematically analyze the incidence and influencing factors of frailty in elderly patients with hematologic malignancies.Methods:Research on frailty in elderly patients with hematologic malignancies was retrieved from Chinese and English databases such as China National Knowledge Infrastructure, Wanfang Data, PubMed, and Web of Science. The search period was from database establishment to August 23, 2024. Two researchers screened the included studies, conducted quality assessment, and extracted data. Meta-analysis was conducted using Stata 18 and RevMan 5.4.Results:A total of seven studies were included, encompassing 19 076 elderly hematologic malignancy patients, with a frailty incidence of 59% [95% CI (0.48, 0.69) ]. Meta-analysis revealed that age [ MD=4.31, 95% CI (3.67, 4.96) ], gender [ OR=0.88, 95% CI (0.83, 0.93) ], alcohol consumption [ OR=1.67, 95% CI (1.15, 2.44) ], self-care ability [ MD=-1.79, 95% CI (-3.17, -0.41) ], anemia [ OR=6.67, 95% CI (2.94, 15.14) ], infection [ OR=1.81, 95% CI (1.16, 2.84) ], and neuropathy [ OR=2.52, 95% CI (1.38, 4.61) ] were the influencing factors of frailty in elderly patients with hematologic malignancies. Conclusions:The incidence of frailty is high in elderly patients with hematologic malignancies. Elderly patients with hematologic malignancies who are older, female, consume alcohol, have low self-care ability, anemia, infections, and neuropathy are prone to frailty. Healthcare providers can conduct early screening and intervention for high-risk populations of frailty based on risk factors to improve the quality of life for elderly hematologic malignancy patients.

Objective:To systematically analyze the incidence and influencing factors of frailty in elderly patients with hematologic malignancies.Methods:Research on frailty in elderly patients with hematologic malignancies was retrieved from Chinese and English databases such as China National Knowledge Infrastructure, Wanfang Data, PubMed, and Web of Science. The search period was from database establishment to August 23, 2024. Two researchers screened the included studies, conducted quality assessment, and extracted data. Meta-analysis was conducted using Stata 18 and RevMan 5.4.Results:A total of seven studies were included, encompassing 19 076 elderly hematologic malignancy patients, with a frailty incidence of 59% [95% CI (0.48, 0.69) ]. Meta-analysis revealed that age [ MD=4.31, 95% CI (3.67, 4.96) ], gender [ OR=0.88, 95% CI (0.83, 0.93) ], alcohol consumption [ OR=1.67, 95% CI (1.15, 2.44) ], self-care ability [ MD=-1.79, 95% CI (-3.17, -0.41) ], anemia [ OR=6.67, 95% CI (2.94, 15.14) ], infection [ OR=1.81, 95% CI (1.16, 2.84) ], and neuropathy [ OR=2.52, 95% CI (1.38, 4.61) ] were the influencing factors of frailty in elderly patients with hematologic malignancies. Conclusions:The incidence of frailty is high in elderly patients with hematologic malignancies. Elderly patients with hematologic malignancies who are older, female, consume alcohol, have low self-care ability, anemia, infections, and neuropathy are prone to frailty. Healthcare providers can conduct early screening and intervention for high-risk populations of frailty based on risk factors to improve the quality of life for elderly hematologic malignancy patients.

Objective:To construct medical students' employment quality evaluation index system based on analytic hierarchy process (AHP), for providing basis to scientific and objective evaluation of medical students' employment quality.Methods:Two rounds of consultation with 21 experts were conducted to construct medical students' employment quality index and evaluation standard by Delphi method, and the weight of each index and evaluation standard determined by AHP. Excel 2007 and SPSS 21.0 were used to analyze the results of expert consultation. The enumeration data were expressed as frequency and percentage. The mean and coefficient of variation were used to describe the importance scores of experts on indicators at all levels. The positive coefficient, authority coefficient and coordination degree of experts were calculated, and the Kendall coordination coefficient ( W) test was carried out. Yaahp 6.0 is used to analyze the pairwise comparison matrix in the analytic hierarchy process to calculate the weight of the indicator. Results:The authority of expert consultation was ranged from 0.77 to 0.94, and the positive coefficient of experts was 100.00%. The evaluation system of medical students' employment quality was determined, which involved 3 first-class indexes, 9 second-class indexes and 35 third-class indexes, and the weight coefficients of each index were calculated by AHP.Conclusion:The evaluation index system of medical students' employment quality is reasonable, which can be used to provide reference standard for medical students' employment quality evaluation, and has certain application value.