1.Summary of the best evidence for nonpharmacological interventions in patients with post-stroke depression
Qiqi NI ; Xinrui WAN ; Jiaoni SHEN ; Jia WU ; Guijuan HE
Chinese Journal of Modern Nursing 2022;28(17):2296-2302
Objective:To summarize and evaluate the best evidence for nonpharmacological interventions in patients with post-stroke depression.Methods:Based on the "6S" pyramid model of evidence resources, the Chinese and English databases and websites of relevant professional associations were systematically searched for evidence on nonpharmacological interventions in patients with post-stroke depression, including guidelines, evidence summaries, systematic reviews, and expert consensus. The retrieval time limit was from the establishment of the database to July 31, 2021. The quality of the article was independently evaluated by two researchers, and evidence was extracted and summarized for the article that met the quality standards.Results:A total of 15 articles were included, including 4 guidelines, 1 evidence summary, 9 systematic reviews, and 1 expert consensus. A total of 25 pieces of the best evidence were compiled from five aspects, namely, health education, exercise intervention, psychological intervention, physical intervention and traditional Chinese medicine techniques.Conclusions:Medical and nursing staff should formulate nonpharmacological interventions for post-stroke depression patients according to the specific clinical conditions and patient characteristics, and apply the evidence in clinical practice.
2.Construction and validation of a risk assessment model for frailty in elderly patients with lower extremity osteoarthritis
Jiaoni SHEN ; Hangting LI ; Jia WU ; Qiqi NI ; Xinrui WAN ; Guijuan HE
Chinese Journal of Nursing 2024;59(18):2206-2213
Objective To analyze the influencing factors of frailty in elderly patients with lower extremity osteoarthritis,and to construct and validate the risk assessment model.Methods Convenient sampling method was used to select 535 elderly patients with lower extremity osteoarthritis from tertiary hospitals and community health service centers in Hangzhou from January to September 2022 as the survey subjects including 357 in the modeling group and 178 in the validation group.Univariate and multivariate logistic regression analysis were used to determine the risk factors of frailty,construct a risk assessment model and draw a nomogram.The discrimination and calibration of the model were evaluated by the area under the receiver operating characteristic curve and the Hosmer-Lemeshow test.The Bootstrap method was used for intemal validation of the model,and the time verification method was used for external validation.Results The model variables included the number of affected joints,age-adjusted Charlson comorbidity index,pain,nutritional status,sedentary time,activity of daily living,osteoarthritis index,lower limb muscle strength,and Social Support Rating Scale score.The Hosmer-Lemeshow test results of the model showed that P=0.202,the area under the receiver operating characteristic curve was 0.942,the optimal critical value was 0.392,the sensitivity was 0.914,the specificity was 0.893,and the accuracy rate was 0.902.The internal and external validation showed that the C-statistics were 0.935 and 0.919,respectively,and the calibration curve showed good fitting.Conclusion The risk assessment model has a good degree of discrimination and calibration,which can more intuitively and easily screen elderly patients with lower extremity osteoarthritis at high risk of frailty,and provide references for early monitoring,identification,prevention and control.