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(1) To describe existing tools to assess the burden of informal caregivers of people with cancer, (2) to describe how these tools have been validated and (3) to describe the areas of interest of existing assessment tool entries.
The caregiver burden of informal caregivers of people with cancer greatly affects their lives. There is a wide variety of relevant assessment tools available, but there are no studies to help researchers to select tools.
A search was conducted using the keywords ‘cancer’, ‘caregiver’, ‘burden’ and ‘scale’ in Medline (PubMed), CINAHL and EMBASE to include articles that developed or applied tools to assess the burden on informal caregivers of cancer patients. Once eligible tools were identified, we searched their ‘primary reference’ studies. If the original scale was assessed in a population other than informal caregivers of cancer patients, we again searched for psychometric measures in the population of caregivers of cancer patients.
This study retrieved 938 articles on developing or applying the informal caregiver burden instrument for cancer patients, including 42 scales. Internal consistency of the original scales ranged from 0.53 to 0.96. Nineteen scales initially developed to assess caregiver burden for patients with dementia, stroke and other disorders were later used for caregivers of cancer patients, eight of which have not yet been validated. Reclassifying all scale domains of concern revealed that scale assessments focused more on caregivers' physical health, emotional state and caregiving tasks.
This review identifies many scales for assessing informal caregiver burden in cancer patients and gives scales recommended. However, a portion still needs to be validated. The development of a new scale proposes to be based on a theoretical framework and to consider dimensions for assessing support resources.
What problem did the study address?: This paper collates assessment tools on the burden of informal carers of people with cancer. It also provides information on the applicable population, reliability and validity.
What were the main findings?: 41 scales could be considered for use, eight of which have not been validated. The scales focus more on assessing caregivers' physical health, emotional state and caregiving tasks, and less on the dimension of support resources.
Where and on whom will the research have an impact?: There are implications for informal carers of cancer patients in hospitals or in the community, as well as for relevant researchers.
Retrieved with reference to systematic evaluation.
No patient or public contribution.
A meta-analysis was conducted to comprehensively evaluate the impact of cluster nursing interventions on the prevention of pressure ulcers (PUs) in intensive care unit (ICU) patients. Computer searches were performed in databases including Embase, Google Scholar, Cochrane Library, PubMed, Wanfang and China National Knowledge Infrastructure for randomized controlled trials (RCTs) implementing cluster nursing interventions for PUs prevention in ICU patients, with the search period covering the database inception to November 2023. Two researchers independently screened the literature, extracted data and conducted quality assessments. Stata 17.0 software was employed for data analysis. Overall, 17 RCTs involving 1463 ICU patients were included. The analysis showed that compared with conventional nursing, cluster nursing interventions significantly reduced the incidence of PUs (odds ratio: 0.24, 95% confidence intervals [CI]: 0.17–0.34, p < 0.001) and also significantly improved the levels of anxiety (standardized mean difference [SMD]: −1.39, 95% CI: −1.57 to 1.22, p < 0.001) and depression (SMD: −1.64, 95% CI: −2.02 to 1.26, p < 0.001) in ICU patients. This study indicates that the application of cluster nursing interventions in ICU patients can effectively reduce the incidence of PUs, as well as improve patients' anxiety and depression levels, thereby enhancing their quality of life, which is worth clinical promotion and application.
A meta-analysis was conducted to evaluate the impact of transconjunctival sutureless vitrectomy (TSV) over 20 G vitrectomy on wound healing, as well as the requirements for closing the wound in order to treat vitreoretinal diseases. Among the 500 cases who had been treated with vitrectomy to September 2023, 250 were treated by transconjunctiva without vitrectomy and 250 were treated with 20 G vitrectomy. The odds ratio (OR) and mean difference (MD) of 95% confidence interval (CI) were computed to evaluate the influence of wound opening and closing on vitrectomy diseases. The evaluation of vitreoretinal diseases was performed with either a random-or fixed-effect model, which involved TSV compared to 20 G vitrectomy. Compared to 20 G vitrectomy, the opening time of the wound in TSV was less (MD, −2.03; 95% CI, −2.87, −1.19; p < 0.0001); Compared to 20 G vitrectomy, the closing time of the wound was less (MD, −4.84; 95% CI, −6.38, −3.03; p < 0.0001); Nevertheless, there were no statistically significant differences in the incidence of vitreous haemorrhage after TSV surgery compared with 20 G vitrectomy (OR, 0.74; 95% CI, 0.25, 2.18; p = 0.59). TSV vitrectomy can shorten the duration of the operation and speed up the healing of the wound. It is suggested that additional studies be carried out with a larger sample size in order to verify this conclusion.
In this study, we explored the use of thermal imaging technology combined with computer vision techniques for assessing surgical incision healing. We processed 1189 thermal images, annotated by experts to define incision boundaries and healing statuses. Using these images, we developed a machine learning model based on YOLOV8, which automates the recognition of incision areas, lesion segmentation and healing classification. The dataset was divided into training, testing and validation sets in a 7:2:1 ratio. Our results show high accuracy rates in incision location recognition, lesion segmentation and healing classification, indicating the model's effectiveness as a precise and automated diagnostic tool for surgical incision healing assessment. Conclusively, our thermal image-based machine learning model demonstrates excellent performance in wound assessment, paving the way for its clinical application in intelligent and standardized wound management.
Colorectal endoscopic mucosal resection (EMR) is associated with the risk of postoperative wound infections, prompting investigations into effective prophylactic measures. This meta-analysis aimed to evaluate the efficacy of various prophylactic interventions in reducing the incidence of wound infections following EMR. Adhering to PRISMA guidelines, we conducted a comprehensive search across multiple databases for randomized controlled trials (RCTs) and cohort studies from 2015 to 2022. We included studies that compared the efficacy of antibiotic prophylaxis and antiseptic measures, with clear data on post-procedure infection rates. Eight studies met our inclusion criteria, and data were extracted for meta-analysis. The risk of bias was assessed using the Cochrane Collaboration tool and the Newcastle-Ottawa Scale. The meta-analysis included 3765 patients from eight RCTs. Prophylactic antibiotics (cefixime and cefuroxime) showed moderate to high efficacy, with infection rates as low as 0% and 0.76%. Prophylactic endoscopic closure and clipping showed the highest efficacy, with zero reported infections. The standardized surgical site infection prevention bundle had lower effectiveness, with an infection incidence of 3.83%. The risk of bias assessment indicated potential performance bias due to lack of blinding, but overall evidence quality was upheld by proper random sequence generation and diligent outcome data monitoring. The effectiveness of specific prophylactic measures, notably prophylactic antibiotics and mechanical closure techniques, has been shown in significantly reducing the risk of wound infections following colorectal EMR.
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