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To construct and evaluate a novel nomogram for predicting the risk of dual dimensional frailty (comorbidity between physical frailty and social frailty) in older maintenance haemodialysis.
A cross-sectional investigation was conducted. A total of 386 older MHD patients were recruited between September and December 2024 from four haemodialysis centres in four tertiary hospitals in Sichuan Province, China. LASSO regression and binary logistic regression were employed to determine the predictors of dual dimensional frailty. The prediction performance of the model was evaluated by discrimination and calibration. The decision curve was utilised to estimate the clinical utility. Internal validation with 1000 bootstrap samples was conducted to minimise overfitting.
In the overall sample (386 cases), a total of 92 (23.8%) of patients exhibited dual dimensional frailty. Five relevant predictors, including physical activity, self-perceived health status, ADL impairment, malnutrition, and self-perceptions of aging, were identified for constructing the nomogram. Internal validation indicated excellent discriminatory power and calibration of the model, while the clinical decision curve demonstrated its remarkable clinical utility.
The novel nomogram constructed in this study holds promise for aiding healthcare professionals in identifying physical and social frailty risks among older patients on maintenance haemodialysis, potentially informing early and targeted interventions.
This nomogram enables nurses to efficiently stratify dual-dimensional frailty risk during routine assessments, facilitating early identification of high-risk patients. Its visual output can guide tailored interventions, such as exercise programmes, nutritional support, and counselling, while optimising resource allocation.
Data were collected from self-reported conditions and patients' clinical information.
STROBE checklist was employed.
To develop a deep learning-based smart assessment model for pressure injury surface.
Exploratory analysis study.
Pressure injury images from four Guangzhou hospitals were labelled and used to train a neural network model. Evaluation metrics included mean intersection over union (MIoU), pixel accuracy (PA), and accuracy. Model performance was tested by comparing wound number, maximum dimensions and area extent.
From 1063 images, the model achieved 74% IoU, 88% PA and 83% accuracy for wound bed segmentation. Cohen's kappa coefficient for wound number was 0.810. Correlation coefficients were 0.900 for maximum length (mean difference 0.068 cm), 0.814 for maximum width (mean difference 0.108 cm) and 0.930 for regional extent (mean difference 0.527 cm2).
The model demonstrated exceptional automated estimation capabilities, potentially serving as a crucial tool for informed decision-making in wound assessment.
This study promotes precision nursing and equitable resource use. The AI-based assessment model serves clinical work by assisting healthcare professionals in decision-making and facilitating wound assessment resource sharing.
The STROBE checklist guided study reporting.
Patients provided image resources for model training.
This meta-analysis investigates the effect of dexmedetomidine on postoperative wound healing in neurosurgical patients. A thorough literature search resulted in the selection of seven studies from an initial pool of 1546 records. The analysis focused on wound healing outcomes, evaluated by the Redness, Oedema, Ecchymosis, Discharge, Approximation (REEDA) scale and the Manchester Scar Scale (MSS). Results indicated significant improvements in the dexmedetomidine group: the REEDA scale scores at day seven post-surgery showed a Standardized Mean Difference group (SMD = −16.18, 95% CI: [−22.30, −10.06], p < 0.01), and the MSS scores at 3 months post-operation demonstrated an (SMD = −8.95, 95% CI: [−14.27, −3.62], p < 0.01). These findings suggest that dexmedetomidine may enhance wound healing and reduce scar formation in neurosurgical patients. Bias assessment indicated a low risk of bias across the studies.
It is still a matter of controversy whether percutaneous endoscopic gastrostomy(PEG) should be used prior to the operation for the purpose of feeding the patient with resectable oesophageal carcinoma (EC). Comparison was made between EC and preoperatively treated PEG and non-preoperative PEG. An extensive literature review has been conducted to determine the results about PEG and No-PEG trials. In this paper, we chose 4 papers out of 407 of them through a strict selection process. In this trial, there were 1027 surgical cases of oesophagus carcinoma, 152 with PEG pre-surgery and 875 without PEG. The total sample size ranged from 14 to 657. Two studies showed that there was no statistically significant difference in the occurrence of postoperative wound infection among PEG and No-PEG(OR, 1.03; 95% CI, 0.38, 2.80 p = 0.96), there was no statistical significance in the likelihood of anastomotic leak among PEG after surgery compared to No-PEG in 4 trials (OR, 1.13; 95% CI, 0.62–2.07 p = 0.69), and there were no statistical differences between PEG and No-PEG before operation on anastomotic stricture for esophagectomy(OR, 0.70; 95% CI, 0.31–1.56 p = 0.38). No wound or anastomosis complications were observed in the PEG group. Thus, PEG preoperatively is an effective and safe procedure without any harmful influence on gastrointestinal structure or anastomosing. It can be applied to patients with oesophagus carcinoma who have a high risk of undernutrition. Nevertheless, because of the limited number of randomized controlled trials in this meta-analysis, caution should be exercised in their treatment. More high-quality research involving a large sample is required to confirm the findings.
Tracheostomy is one of the most common operations. The two main methods of tracheostomy are open surgical tracheostomy (OST) and percutaneous dilatational tracheostomy (PDT). In critical cases, the combination of these two approaches is especially crucial, with the possibility of successful outcomes and low complications. Thus, the purpose of this system is to analyse the effects of both methods on the outcome of postoperative wound. In this research, we performed a systematic review of Cochrane Library, PubMed, Web of Science and Embase, to determine all randomized controlled trials (RCTs) that are comparable in terms of postoperative injury outcomes. Eleven RCTs were found after screening. This study will take the necessary data from the selected trials and evaluate the documentation for RCTs. PDT was associated with a lower incidence of infection at the wound site than OST (OR, 4.46; 95% CI: 2.84–7.02 p < 0.0001), and PDT decreased blood loss (OR, 2.88; 95% CI: 1.62–5.12 p = 0.0003). But the operation time did not differ significantly in both PDT to OST (MD, 4.65; 95% CI: −1.19–10.48 p = 0.12). The meta-analyses will assist physicians in selecting the best operative procedure for critical cases of tracheostomy. These data can serve as guidelines for clinical management and in the design of future randomized, controlled studies.
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