Objective] To explore the treatment of Lanshi Micang disease with tumors related diagnosis and treatment method, in order to have a more comprehensive understanding of anal fistula, so as to broaden the mind, improve the clinical efficacy. [Method] FromLanshi Micang-Anal Fistulaof eight prescriptions for treatment of hemorrhoids and analysis, on the basis of combining the characteristics of compatibility with tumors inDongyuan effect testand the specific prescription, made analysis of anal fistula, diagnosis and treatment of anal fistula for the study of LI Dongyuan thought. [Results] LI Dongyuan from dampness, heat, wind, dryness four on the treatment of anal fistula, with angelica, Gentiana and blood dryness of medicine, to Shufeng pain, Xinrun and blood on regulation of syndrome treatment, paid attention to diet to restore the anal fistula. [Conclusion] LI DongyuanLanshi Micangis rich in content, the treatment of anal fistula has experience, as of today, the diagnosis and treatment on anorectal diseases of clinical thought still has important guiding significance.

Objective The research was to achieve Shanghai resident satisfaction of primary health service after new health reform.Methods During self-compiled questionnaire survey,the research adapted stratified random sampling to select 9 community health centers in Shanghai urban,rural and suburb areas.Results Shanghai resident satisfaction rate of new health reform was 85.2％.Satisfaction rate of basic medical security system was 85.0％.Satisfaction rate of basic medical service was 96.5％.Satisfaction rate of basic public health service was 95.1％.Age,region,job,education and income were main factors to satisfaction of primary health service.Conclusion From an overall point of view,Shanghai resident satisfaction of primary health service after new health reform was high.However,the level of basic medical security and convenience of reimbursement were not high.Medical expenses of primary health care institution had not been effectively controlled.Basic medicine could not fully meet the medication needs of primary health care institutions.

Objective: To conduct a scoping review on prognostic prediction models for patients with comorbidity of chronic diseases, and understand modeling methods, predictive factors and predictive effect of the models, so as to provide the reference for prognostic evaluation on patients with comorbidity of chronic diseases. Methods: Literature on prognostic prediction models for patients with comorbidity of chronic diseases was collected through SinoMed, CNKI, Wanfang Data, VIP, PubMed, Embase, Cochrane Library and Web of Science published from the time of their establishment to November 1, 2023. The quality of literature was assessed using prediction model risk of bias assessment tool (PROBAST), then modeling methods, predictive factors and predictive effects were reviewed. Results: Totally 2 130 publications were retrieved, and nine publications were finally enrolled, with an overall high risk of bias. Thirteen models were involved, with three established using machine learning methods and ten established using logistic regression. The prediction results of four models were death, with main predictive factors being age, gender, body mass index (BMI), Barthel index and pressure ulcers; the prediction results of nine models were rehospitalization, with main predictive factors being age, BMI, hospitalization frequency, duration of hospital stay and hospitalization costs. Eleven models reported the area under the receiver operating characteristic curve (AUC), ranging from 0.663 to 0.991 6; two models reported the C-index, ranging from 0.64 to 0.70. Eight models performed internal validation, one model performed external validation, and four models did not reported verification methods. Conclusions The prognostic prediction models for patients with comorbidity of chronic diseases are established by logistic regression and machine learning methods with common nursing evaluation indicators, and perform well. Laboratory indicators should be considered to add in the models to further improve the predictive effects.

Objective: To systematically evaluate the influencing factors for medication compliance in patients with comorbidities of chronic diseases, so as to provide the evidence for improving medication compliance. Methods: Literature on influencing factors for medication compliance in patients with comorbidities of chronic diseases were retrived from CNKI, Wanfang Data, VIP, SinoMed, PubMed, Web of Science, Cochrane Library and Embase from inception to January 20, 2024. After independent literature screening, data extraction, and quality assessment by two researchers, a meta-analysis was performed using RevMan 5.4 and Stata 16.0 softwares. Literature were excluded one by one for sensitivity analysis. Publication bias was assessed using Egger's test. Results: Initially, 7 365 relevant articles were retrieved, and 35 of them were finally included, with a total sample size of about 150 000 individuals. There were 30 cross-sectional studies and 5 cohort studies; and 11 high-quality studies and 24 medium-quality studies. The meta-analysis showed that the demographic factors of lower level of education (OR=2.148, 95%CI: 1.711-2.696), lower economic income (OR=1.897, 95%CI: 1.589-2.264), male (OR=0.877, 95%CI: 0.782-0.985), living alone (OR=2.833, 95%CI: 1.756-4.569) and unmarried (OR=2.784, 95%CI: 1.251-6.196); the medication treatment factors of polypharmacy (OR=1.794, 95%CI: 1.190-2.706), potentially inappropriate medication (OR=2.988, 95%CI: 1.527-5.847), low frequency of daily medication (OR=0.533, 95%CI: 0.376-0.754) and adverse drug reactions (OR=3.319, 95%CI: 1.967-5.602); the disease factors of long course of disease (OR=2.118, 95%CI: 1.643-2.730), more comorbidities (OR=1.667, 95%CI: 1.143-2.431) and cognitive impairment (OR=2.007, 95%CI: 1.401-2.874); and the psychosocial factors of poor belief in taking medication (OR=1.251, 95%CI: 1.011-1.547), poor self-rated health (OR=1.990, 95%CI: 1.571-2.522) and being guided by healthcare professionals (OR=0.151, 95%CI: 0.062-0.368) were the influencing factors for medication compliance in patients with chronic comorbidities. Conclusion The medication compliance in patients with comorbidities of chronic diseases is associated with demographic factors, pharmacological factors, disease factors and psychosocial factors, mainly including living alone, adverse drug reactions, course of disease, number of comorbidities and medication beliefs.

Objective:To study the CT features for solitary fibrous tumor (SFT) in the abdomen and pelvis and to improve the diagnostic accuracy.Methods:Fourteen patients with SFT were collected in our hospital from January,2011 to December,2015.Characteristic of images were analyzed and compared for 10 SFT,which located outside the abdominal organs with extragastrointestinal stromal tumors (EGIST),leiomyosarcoma,and schwannoma.Results:Necrosis and cystic formation were frequently present in SFT in the abdomen and pelvis.CE-CT showed serpentine vessels along the periphery,while pattern of enhancement was maplike inhomogeneous progressive.Comparing with the EGIST or schwannoma,the difference of CT value in non-contrast and the arterial phase were statistically significant (P＜0.05).The numbers of peritumoral circuity vessel were significantly different between SFT and EGIST (~=18.27,P＜0.008) or between SFT and schwannoma (x2=19.25,P＜0.008).Comparing with the leiomyosarcoma or schwannoma,SFT located outside the abdominal organs.We found that tumor necrosis rate was significantly different between SFT and leiomyoscarcoma (x2=8.00,P＜0.008).Conclusion:SFT in the abdomen and pelvis show certain CT characteristics.The CT value in noncontrast and at the arterial phase,tumor necrosis rate,and serpentine vessels along the periphery were pivotal in differentiating SFT from leiomyosarcoma,EGIST and schwannoma.

Objective:To summarize the best evidence of medication adherence interventions for patients with multiple chronic conditions.Methods:According to the "6S" evidence model, literature on medication adherence in patients with multiple chronic conditions was retrieved from BMJ Best Clinical Practice, UpToDate, Medlive, National Institute for Health and Clinical Excellence, Cochrane Library, Embase, PubMed, Web of Science, China Biology Medicine disc, China National Knowledge Infrastructure, WanFang data and so on. The search period was from establishing the database to August 30, 2023.Results:A total of 16 articles were included, including three guidelines, four expert consensus, seven systematic reviews, and two meta-analyses. Twenty-seven pieces of evidence were summarized from six aspects of compliance assessment, educational intervention, behavioral intervention, optimized treatment program, technical reminder intervention, and social-psychological-emotional intervention.Conclusions:The best evidence of medication adherence interventions for patients with multiple chronic conditions summarized provides a reference for medical and nursing staff to develop medication adherence interventions.