Search

To investigate the preventive effect of different dressings on pressure injuries related to non‐invasive ventilation equipment and to screen the efficacy of dressings. Systematic review and network meta‐analysis. PubMed, the Cochrane Library, Web of Science, EMBASE, Cumulative Index to Nursing & Allied Health Literature (CINAHL), China Knowledge Resource Integrated Database (CNKI), Wanfang Database, Chinese Biomedical Database (CBM) and Weipu Database (VIP) were used for the search from the date of inception of each database to 15 October 2023. The quality of the data was assessed using the Cochrane Risk of Bias tool. Stata 16.0 Software was used to analysis and ranking of different types of dressings. A total of 23 randomized controlled trials on 7 interventions were included in the final analysis. The effectiveness of these in preventing the overall incidence of pressure injuries is ranked from best to worst as follows: hydrogel dressing > foam dressing > petroleum jelly gauze dressing > hydrocolloid dressing > film dressing > clean gauze dressing > sterile gauze. Sixteen studies reported the incidence of Stage I pressure injuries, the effectiveness in preventing the incidence of Stage I pressure injuries was ranked from best to least effective: foam dressing > hydrogel dressing > petroleum jelly gauze dressing > hydrocolloid dressing > film dressing > clean gauze dressing > sterile gauze dressing. Fourteen studies reported the incidence of Stages I/II pressure injuries, the effective in preventing the incidence of Stages I and II pressure injuries was ranked from best to least effective: foam dressing > hydrogel dressing > petroleum jelly gauze dressing > hydrocolloid dressing > clean gauze dressing > sterile gauze dressing. Considering the advantages and disadvantages of different dressings, both hydrogel and foam dressings are effective in preventing pressure injuries related to non‐invasive ventilation equipment. [ABSTRACT FROM AUTHOR]

Despite the fact that machine learning (ML) algorithms to construct predictive models for pressure injury development are widely reported, the performance of the model remains unknown. The goal of the review was to systematically appraise the performance of ML models in predicting pressure injury. PubMed, Embase, Cochrane Library, Web of Science, CINAHL, Grey literature and other databases were systematically searched. Original journal papers were included which met the inclusion criteria. The methodological quality was assessed independently by two reviewers using the Prediction Model Risk of Bias Assessment Tool (PROBAST). Meta‐analysis was performed with Metadisc software, with the area under the receiver operating characteristic curve, sensitivity and specificity as effect measures. Chi‐squared and I2 tests were used to assess the heterogeneity. A total of 18 studies were included for the narrative review, and 14 of them were eligible for meta‐analysis. The models achieved excellent pooled AUC of 0.94, sensitivity of 0.79 (95% CI [0.78–0.80]) and specificity of 0.87 (95% CI [0.88–0.87]). Meta‐regressions did not provide evidence that model performance varied by data or model types. The present findings indicate that ML models show an outstanding performance in predicting pressure injury. However, good‐quality studies should be conducted to verify our results and confirm the clinical value of ML in pressure injury development. [ABSTRACT FROM AUTHOR]

Total knee arthroplasty (TKA) is considered a common surgical option in patients with end-stage osteoarthritis of the knee. This systematic review and meta-analysis aimed to determine the effectiveness of cognitive behavioral therapy (CBT) for patients after TKA. PubMed, EMBASE, the Cochrane Library, Web of Science and CINAHL were searched for randomized controlled trials (RCTs) from inception to 20 August 2021. Included studies were evaluated with the Cochrane risk-of-bias tool. Six RCTs were included. Our study results demonstrated that a significant reduction in pain catastrophing was seen in patients receiving CBT at post-intervention (SMD −0.48, 95% CI = −0.72 to −0.23, I2 17.2%, p = 0.00) but not in 3-month or 12-month follow-up. There were no significant differences between CBT and usual-care patients regarding pain intensity or knee function at different time-points. This is the first time that meta-analysis has been conducted to determine the effectiveness of CBT for patients after TKA. It is necessary to conduct longer follow-ups, include larger samples and conduct rigorous RCTs to further explore this issue. [ABSTRACT FROM AUTHOR]

To systematically assess the prevalence of facial pressure injuries related to adult non‐invasive ventilation equipment, and risk factors of facial pressure injuries. PubMed, Cochrane Library, Web of Science, Embase, China Knowledge Resource Integrated Database, Wanfang Database, Chinese Biomedical Database and Weipu Database were comprehensively searched for observational studies investigating the prevalence and risk factors of facial pressure injuries related to adult non‐invasive ventilation equipment from inception to May 16th, 2022. Filter articles based on inclusion and exclusion criteria. The quality of the included studies was evaluated independently by two investigators. Meta‐analysis was conducted using Stata 16.0 software package. In total, 2835 articles were screened and data from 12 studies were used in meta‐analysis. The prevalence of facial pressure injuries related to adult non‐invasive ventilation equipment was 25% (95% confidence interval, CI:15% to 37%, I2 = 97.34%, P < 0.0001). After controlling for confounding variables, the following risk factors of facial pressure injuries: use equipment form, with diabetes, fever, cumulative time of using equipment, facial skin oedema and Glasgow score. Understanding the risk factors of facial pressure injuries can provide the healthcare personnel with the theoretical basis for the management and treatment of the patients. [ABSTRACT FROM AUTHOR]

To examine the association between cognitive frailty and the risk of future falls among older adults. Systematic review and meta-analysis. Older people aged ≥60 years with cognitive frailty from community, hospital, or both. PubMed, EMBASE, Web of Science, the Cochrane Library, Wanfang Database, China Knowledge Resource Integrated Database (CNKI), Weipu Database (VIP), and Chinese Biomedical Database (CBM) were searched for relevant studies published from the inception of the database until June 14, 2022. Stata 16.0 software was used to perform the meta-analysis. A random effects model was used to pool the prevalence of falls in older adults over age 60 years with cognitive frailty and the strength of the association between cognitive frailty and falls [odds ratios (ORs) and 95% CIs]. Quality assessment, heterogeneity, and sensitivity analyses were also conducted. A study protocol was registered in PROSPERO (CRD42022331323). The review included 18 studies in qualitative synthesis, 14 of which were in meta-analysis. Eleven sets of cross-sectional data involving 23,025 participants and 5 sets of longitudinal data involving 11,924 participants were used in the meta-analysis. The results showed that the overall prevalence of falls in 1742 people with cognitive frailty was 36.3% (95% CI 27.9-44.8, I 2 = 93.4%). Longitudinal study results showed that cognitively frail individuals had a higher risk of falls (OR 3.02, 95% CI 2.11-4.32, I 2 = 0.0%, P =.406), compared to robust participants without cognitive impairment; physically frail people (alone) had a moderate risk of falls (OR 2.16, 95% CI 1.42-3.30, I 2 = 9.7%, P =.351); cognitively impaired people (alone) had a lower risk of falls (OR 1.36, 95% CI 1.03-1.79, I 2 = 0.0%, P =.440). Among cross-sectional studies, cognitive frailty was associated with the risk of falls (OR 2.74, 95% CI 2.20-3.40, I 2 = 53.1%, P =.019). Although high heterogeneity was noted among 11 cross-sectional studies reporting ORs, the sensitivity analysis showed that no single study significantly affected the final pooled results. This systematic review and meta-analysis confirms the findings that cognitive frailty was demonstrated to be a significant predictor of future falls in older adults. However, further prospective investigations are warranted. [ABSTRACT FROM AUTHOR]

• This study provides the latest evidence on the level of life space mobility of community elderly people. • The life space mobility of community elderly people is at a moderate level globally, with 42% of them living in a state of restricted life space. • The level of life space mobility among community elderly people gradually achieved stability after 2017. • South America, females and earlier survey years have a lower level of LSM. Multiple countries have conducted surveys on the level of life space mobility for community-dwelling elderly through the Life-Space Assessment, the results vary greatly, from 41.7 to 88.6. However, there is no meta-analysis on the current situation of community-dwelling elderly life space mobility. To systematically assess the global level of life space mobility for community-dwelling elderly, to identify potential covariates such as geographical regions, survey years, gender, and age that contribute to the heterogeneity between the studies, and to identify the dynamic trend based on survey years. Systematic review and meta-analysis. Two reviewers searched the following 8 electronic bibliographic databases from inception until May 28, 2023: PubMed, The Cochrane Library, Web of Science, Embase, Chinese Biomedical Database, China Knowledge Resource Integrated Database, WanFang, and Weipu Database. This review was conducted using the Stata 14.1 and R 4.3.1. The Cochrane's Q statistical and I2 index were used to test for heterogenicity and assess the degree of heterogenicity, respectively. Studies were appraised using the Agency for Healthcare Research and Quality tool, the Newcastle-Ottawa Scale for the quality of cross-sectional studies, cohort studies, respectively. A total of 29 studies were selected from databases and reference lists. The pooled score of Life-Space Assessment was 66.84 (95% CI: 63.30–70.39) and the prevalence of restricted life space was 42% (95% CI: 0.27–0.57). The geographical regions, survey years, gender were found to be a significant covariate of the pooled score of life space mobility estimate in the subgroup analysis. The mean score of Life-Space Assessment gradually achieved stability after 2017. The life space mobility of community-dwelling elderly in the global is at a moderate level, with 42% of them experiencing restricted life space. South America, females and earlier survey years have a lower level of life space mobility. In the future, the government should identify vulnerable groups for targeted intervention to promote the level of LSM in the community-dwelling elderly. PROSPERO [CRD42023443054]. [ABSTRACT FROM AUTHOR]

To critically appraise and quantify the performance studies by employing machine learning (ML) to predict delirium. A systematic review and meta-analysis. Articles reporting the use of ML to predict delirium in adult patients were included. Studies were excluded if (1) the primary goal was only the identification of various risk factors for delirium; (2) the full-text article was not found; and (3) the article was published in a language other than English/Chinese. PubMed, Embase, Cochrane Library database, Web of Science, Grey literature, and other relevant databases for the related publications were searched (from inception to December 15, 2021). The data were extracted using a standard checklist, and the risk of bias was assessed through the prediction model risk of bias assessment tool. Meta-analysis with the area under the receiver operating characteristic curve, sensitivity, and specificity as effect measures, was performed with Metadisc software. Cochran Q and I 2 statistics were used to assess the heterogeneity. Meta-regression was performed to determine the potential effect of adjustment for the key covariates. A total of 22 studies were included. Only 4 of 22 studies were quantitatively analyzed. The studies varied widely in reporting about the study participants, features and selection, handling of missing data, sample size calculations, and the intended clinical application of the model. For ML models, the overall pooled area under the receiver operating characteristic curve for predicting delirium was 0.89, sensitivity 0.85 (95% confidence interval 0.84‒0.85), and specificity 0.80 (95% confidence interval 0.81–0.80). We found that the ML model showed excellent performance in predicting delirium. This review highlights the potential shortcomings of the current approaches, including low comparability and reproducibility. Finally, we present the various recommendations on how these challenges can be effectively addressed before deploying these models in prospective analyses. [ABSTRACT FROM AUTHOR]