Conectar
Shame has an important impact on the mental health and quality of life of patients. The shame in patients with ureterostomy after cystectomy remains unclear. This survey aimed to evaluate the status quo and influencing factors of shame in patients with ureterostomy after cystectomy, to provide support for the clinical care. Patients with ureterostomy after cystectomy treated in the wound stomy clinic of a third-class hospital from 1 June 2022 to 31 July 2023 were included. General data questionnaire and social impact scale (SIS) were used for data collection. Univariate and multiple linear regression analysis were performed to evaluate the influencing factors of shame in patients with ureterostomy after cystectomy. One hundred and sixty four patients with ureterostomy after cystectomy were included. The total score of shame in patients with ureterostomy was (60.75 ± 6.31), which was in the high level. Age (r = 0.442), home place (r = 0.427), per capita monthly household income (r = 0.605), self-care ability (r = 0.597) and complications of stoma (r = 0.542) were correlated with the SIS score in patients with ureterostomy after cystectomy (all p < 0.05). Multiple linear regression analyses indicated that age, home place, per capita monthly household income, self-care ability and complications of stoma were the influencing factors of SIS score in patients with ureterostomy after cystectomy (all p < 0.05). The five variables explained 64.5% of the patients' sense of shame variation. Patients with ureterostomy after cystectomy have a serious sense of shame in the early stage after operation and there are many influencing factors. Health care providers should take early nursing interventions targeted on those influencing factors to reduce the patients' sense of shame.
This study systematically evaluates the effect of body mass index on the occurrence of wound infections and complications in patients undergoing liver cancer surgery through a meta-analysis. A computerized search was conducted, from database inception to October 2023, in PubMed, Embase, Google Scholar, Cochrane Library, China National Knowledge Infrastructure and Wanfang databases for studies related to the impact of body mass index on patients undergoing liver cancer surgery. Two researchers independently selected studies based on inclusion and exclusion criteria, extracted data, and assessed the quality. Data analysis was performed using Stata 17.0 software. A total of 8 studies, encompassing 21 030 liver cancer surgery patients, were included. The analysis revealed that patients with a higher body mass index had a significantly higher incidence of wound infection (odds ratio [OR] = 2.36, 95% confidence interval [CI]: 1.21–4.60, p = 0.012) and complications (OR = 1.58, 95% CI: 1.11–2.24, p = 0.011) compared to the control group. Additionally, the hospital stay for higher body mass index patients was longer than that for the control group (standard mean difference [SMD] = −1.09, 95% CI: −4.71 to 2.53, p = 0.556), although this difference was not statistically significant. The study indicates that liver cancer surgery patients with higher body mass index were at an increased risk of postoperative wound infection and complications. This finding highlights the importance of considering body mass index as a factor in the management and care of patients undergoing liver cancer surgery.
Postoperative Surgical Site Infections (SSIs) pose significant challenges to recovery after joint arthroplasty. This systematic review and meta-analysis aim to compare the incidence of SSIs after knee or hip arthroplasty under Spinal Anaesthesia (SA) versus general anaesthesia (GA). We conducted the systematic review and meta-analysis following the PRISMA guidelines, analysing data from 15 studies selected from PubMed, Embase, Web of Science, and Cochrane Library up to May 16, 2023. The analysis included studies comparing SSIs incidence in patients aged 18 years and above who underwent knee or hip arthroplasty under SA or GA. Quality assessment was performed using the Cochrane Collaboration's risk of bias tool. The effect size was calculated using random or fixed-effects models based on the observed heterogeneity. We assessed the heterogeneity between studies and conducted a sensitivity analysis. Of 1651 initially identified studies, 15 articles encompassing 353 169 patients were included in the final analysis. A total of 156 405 patients were under SA, while 196 764 received GA. The studies demonstrated substantial heterogeneity (p = 0.007, I 2 = 53.7%), resulting in a random-effects model being employed. Patients receiving SA showed a 23% lower likelihood of developing SSIs postoperatively compared to GA patients (OR: 0.77, 95% CI: 0.70–0.86, p < 0.001). Sub-group analysis further confirmed these findings regardless of the type of joint arthroplasty. This meta-analysis indicated a significantly lower incidence of SSIs following knee or hip arthroplasty under SA compared to GA. Despite observed heterogeneity, the results underscore the potential benefit of SA over GA in orthopaedic surgeries to reduce the risk of SSIs.
The current methods for the prediction of mortality and amputation for inpatients with diabetic foot (DF) use only conventional, simple variables, which limits their performance. Here, we used a random survival forest (RSF) model and multicomponent variables to improve the prediction of mortality and amputation for these patients. We performed a retrospective cohort study of 175 inpatients with DF who were recruited between 2014 and 2021. Thirty-one predictors in six categories were considered as potential covariates. Seventy percent (n = 122) of the participants were randomly selected to constitute a training set, and 30% (n = 53) were assigned to a testing set. The RSF model was used to screen appropriate variables for their value as predictors of 2-year all-cause mortality and amputation, and a multicomponent prediction model was established. Model performance was evaluated using the area under the curve (AUC) and the Hosmer–Lemeshow test. The AUCs were compared using the Delong test. Seventeen variables were selected to predict mortality and 23 were selected to predict amputation. Uric acid and alanine transaminase were the top two most useful variables for the prediction of mortality, whereas urine protein and platelet were the top variables for the prediction of amputation. The AUCs were 0.913 and 0.851 for the prediction of mortality for the training and testing sets, respectively; and the equivalent AUCs were 0.963 and 0.893 for the prediction of amputation. There were no significant differences between the AUCs for the training and testing sets for both the mortality and amputation models. These models showed a good degree of fit. Thus, the RSF model can predict mortality and amputation in inpatients with DF. This multicomponent prediction model could help clinicians consider predictors of different dimensions to effectively prevent DF from clinical outcomes .
FreshRSS 