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This study aims to investigate the current situation of needlestick injuries (NSIs) of clinical nurses and identify associated factors by using the theoretical framework of the human factors analysis and classification system (HFACS).
A nationwide cross-sectional survey was conducted.
Multi-stage sampling was used to investigate 3336 nurses in 14 Chinese hospitals. Descriptive statistics and univariate and multivariate logistic regression were employed to reveal the rate of NSIs and their associated factors.
A total of 970 nurses (29.1%) reported having experienced at least one NSI in the past year. The multivariate logistic regression analysis showed that good hospital safety climate and clinical nurses in intensive care unit (ICU) and emergency department had protective effects against NSIs compared with nurses in internal medicine department. The nurse, senior nurse, and nurse in charge have significantly increased the risk for NSIs compared with the associate chief nurse or above. Patients with poor vision but wearing glasses and poor vision but not wearing glasses were more prone to have NSIs. Working in the operating room compared with internal medicine, average weekly working time of >45 h compared with ≤40 h and poor general health led to increased risk of NSIs.
The rate of NSIs in clinical nurses was high in China. Individual factors including professional title, department, visual acuity and general mental health and organisational factors including weekly working hours and hospital safety atmosphere were significantly correlated with the occurrence of NSIs.
Nursing managers should focused on physical and psychological conditions of clinical nurses, and organisational support is required to enhance the hospital safety atmosphere.
Contributions from patients or the public are irrelevant because this study aims to explore current situation and factors associated with NSIs in clinical nurses.
This study aims to investigate the role of anoikis-related genes in diabetic foot (DF) by utilizing bioinformatics analysis to identify key genes associated with anoikis in DF. We selected the GEO datasets GSE7014, GSE80178 and GSE68183 for the extraction and analysis of differentially expressed anoikis-related genes (DE-ARGs). GO analysis and KEGG analysis indicated that DE-ARGs in DF were primarily enriched in apoptosis, positive regulation of MAPK cascade, anoikis, focal adhesion and the PI3K-Akt signalling pathway. Based on the LASSO and SVM-RFE algorithms, we identified six characteristic genes. ROC curve analysis revealed that these six characteristic genes had an area under the curve (AUC) greater than 0.7, indicating good diagnostic efficacy. Expression analysis in the validation set revealed downregulation of CALR in DF, consistent with the training set results. GSEA results demonstrated that CALR was mainly enriched in blood vessel morphogenesis, endothelial cell migration, ECM-receptor interaction and focal adhesion. The HPA database revealed that CALR was moderately enriched in endothelial cells, and CALR was found to interact with 63 protein-coding genes. Functional analysis with DAVID suggested that CALR and associated genes were enriched in the phagosome component. CALR shows promise as a potential marker for the development and treatment of DF.
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