Conectar
by Chi Su, Yilong Hua, Yi Liu, Shu Tao, Fei Jia, Wenhui Zhao, Wangyang Lin
Mining wastewater with heavy metals poses a serious threat to the ecological environment. However, the acute single and combined ecological effects of heavy metals, such as chromium (Cr) and nickel (Ni), on freshwater ostracods, and the development of relevant prediction models, remain poorly understood. In this study, Heterocypris sp. was chosen to investigate the single and combined acute toxicity of Cr and Ni. Then, the quantitative structure-activity relationship (QSAR) model was used to predict the combined toxicity of Cr and Ni. The single acute toxicity experiments revealed high toxicity for both Cr and Ni. In addition, Cr exhibited greater toxicity compared to Ni, as evidenced by its lower 96-hour half-lethal concentration (LC50) of 1.07 mg/L compared to 4.7 mg/L for Ni. Furthermore, the combined acute toxicity experiments showed that the toxicity of Cr-Ni was higher than Ni but lower than Cr. Compared with the concentration addition (CA) and independent action (IA) models, the predicted results of the QSAR model were more consistent with the experimental results for the Cr-Ni combined acute toxicity. So, the high accuracy of QSAR model identified its feasibility to predict the toxicity of heavy metal pollutants in mining wastewater.Peripheral artery disease (PAD) is a major risk factor for cardiovascular morbidity and mortality, despite surgical and endovascular treatments. Emerging evidence supports the use of immediate antithrombotic medications after endovascular intervention for PAD, however, there is a lack of consensus regarding choice and duration of antithrombotic therapy. Prescriber decision-making is a complex process, with prior studies demonstrating patient factors can influence variability in antithrombotic therapy for PAD. However, it remains unclear the relative contribution of these factors. This paper describes a planned study that aims to (1) determine the influence of patient factors on clinician preference for antithrombotic therapy following endovascular intervention and (2) compare differences in prescribing preferences between consultant vascular surgeons and trainees.
This cross-sectional survey will evaluate antithrombotic prescribing choices using a discrete choice experiment (DCE) that has been developed and piloted for this study. A list of attributes and levels was generated using a mixed-methods approach. This included an extensive literature review and semistructured interviews with prescribing clinicians. Following final selection of included attributes, specialised software was used to construct a D-efficient design for the DCE questionnaire. The electronic questionnaire will be administered to vascular trainees and consultant surgeons across Australia. These data will be analysed using multinomial logistic regression, treating the decision to prescribe antithrombotic therapy as a function of both the attributes of the two alternatives, as well as characteristics of the respondent. Latent class analysis will be used to explore heterogeneity of responses.
Ethics approval was obtained from the University of Sydney Human Ethics committee (2023/474). The results of this study will be published in peer-reviewed journals and presented at national vascular surgical conferences. These results will be used to improve understanding how clinicians make prescribing decisions and to inform future strategy to enhance guideline-directed prescribing.
To develop an interpretable deep learning model of lupus nephritis (LN) relapse prediction based on dynamic multivariable time-series data.
A single-centre, retrospective cohort study in China.
A Chinese central tertiary hospital.
The cohort study consisted of 1694 LN patients who had been registered in the Nanjing Glomerulonephritis Registry at the National Clinical Research Center of Kidney Diseases, Jinling Hospital from January 1985 to December 2010.
We developed a deep learning algorithm to predict LN relapse that consists of 59 features, including demographic, clinical, immunological, pathological and therapeutic characteristics that were collected for baseline analysis. A total of 32 227 data points were collected by the sliding window method and randomly divided into training (80%), validation (10%) and testing sets (10%). We developed a deep learning algorithm-based interpretable multivariable long short-term memory model for LN relapse risk prediction considering censored time-series data based on a cohort of 1694 LN patients. A mixture attention mechanism was deployed to capture variable interactions at different time points for estimating the temporal importance of the variables. Model performance was assessed according to C-index (concordance index).
The median follow-up time since remission was 4.1 (IQR, 1.7–6.7) years. The interpretable deep learning model based on dynamic multivariable time-series data achieved the best performance, with a C-index of 0.897, among models using only variables at the point of remission or time-variant variables. The importance of urinary protein, serum albumin and serum C3 showed time dependency in the model, that is, their contributions to the risk prediction increased over time.
Deep learning algorithms can effectively learn through time-series data to develop a predictive model for LN relapse. The model provides accurate predictions of LN relapse for different renal disease stages, which could be used in clinical practice to guide physicians on the management of LN patients.
To characterise subphenotypes of self-reported symptoms and outcomes (SRSOs) in postacute sequelae of COVID-19 (PASC).
Prospective, observational cohort study of subjects with PASC.
Academic tertiary centre from five clinical referral sources.
Adults with COVID-19 ≥20 days before enrolment and presence of any new self-reported symptoms following COVID-19.
We collected data on clinical variables and SRSOs via structured telephone interviews and performed standardised assessments with validated clinical numerical scales to capture psychological symptoms, neurocognitive functioning and cardiopulmonary function. We collected saliva and stool samples for quantification of SARS-CoV-2 RNA via quantitative PCR.
Description of PASC SRSOs burden and duration, derivation of distinct PASC subphenotypes via latent class analysis (LCA) and relationship with viral load.
We analysed baseline data for 214 individuals with a study visit at a median of 197.5 days after COVID-19 diagnosis. Participants reported ever having a median of 9/16 symptoms (IQR 6–11) after acute COVID-19, with muscle-aches, dyspnoea and headache being the most common. Fatigue, cognitive impairment and dyspnoea were experienced for a longer time. Participants had a lower burden of active symptoms (median 3 (1–6)) than those ever experienced (p
We identified three distinct PASC subphenotypes. We highlight that although most symptoms progressively resolve, specific PASC subpopulations are impacted by either high burden of constitutional symptoms or persistent olfactory/gustatory dysfunction, requiring prospective identification and targeted preventive or therapeutic interventions.
With the growing emphasis on swift recovery, minimally invasive thoracic surgery has advanced significantly. Video-assisted thoracoscopic surgery (VATS) has seen rapid development, and the double-lumen tube (DLT) remains the most dependable method for tracheal intubation in VATS. However, hypoxaemia during DLT intubation poses a threat to the perioperative safety of thoracic surgery patients. Recently, transnasal high-flow nasal oxygen (HFNO) has shown promise in anaesthesia, particularly in handling short-duration hypoxic airway emergencies. Yet, its application in the perioperative period for patients undergoing pulmonary surgery with compromised cardiopulmonary function lacks evidence, and there are limited reliable clinical data.
A prospective, randomised, controlled, single-blind design will be employed in this study. 112 patients aged 18–60 years undergoing elective VATS-assisted pulmonary surgery will be enrolled and randomly divided into two groups: the nasal high-flow oxygen group (H group) and the traditional mask transnasal oxygen group (M group) in a 1:1 ratio. HFNO will be used during DLT intubation for the prevention of asphyxia in group H, while conventional intubation procedures will be followed by group M. Comparison will be made between the two groups in terms of minimum oxygen saturation during intubation, hypoxaemia incidence during intubation, perioperative complications and postoperative hospital days.
Approval for this study has been granted by the local ethics committee at Shenzhen Second People’s Hospital. The trial results will be disseminated through peer-reviewed journals and scientific conferences.
To qualitatively explore the factors that enhance resilience among emergency nurses (ENs).
This study is an exploratory qualitative investigation. Semistructured in-depth interviews were used for data collection, while qualitative content analysis was applied for data analysis.
A grade A tertiary hospital in Shanghai, China.
The study subjects comprised 17 ENs, who were selected using a purposive sampling method.
Three main themes and the nine subthemes emerged from the study, that is, individual resources, including competency, personality traits and occupational benefits; family resources, including close parent–child attachment and supportive family dynamics; social resources, including peer support, organisational support, resilient leadership and popular support.
This qualitative study explored the factors promoting resilience among ENs and provided a reference for managers to formulate future management strategies. From the perspective of positive psychology, nurses should receive comprehensive support, focusing on improving their professional accomplishment and role ability while prioritising the development of resilient leadership. These efforts are expected to drive progress and growth across the emergency care team.
This study aimed to evaluate the effectiveness of the Trauma Rating Index in Age, Glasgow Coma Scale, Respiratory rate and Systolic blood pressure score (TRIAGES) in predicting 24-hour in-hospital mortality among patients aged 65 years and older with isolated traumatic brain injury (TBI).
A retrospective, single-centre cohort study.
This study was conducted at a government-run tertiary comprehensive hospital.
This study included 982 patients aged 65 years or older with isolated TBI, who were admitted to the emergency department between 1 January 2020 and 31 December 2021.
None.
24-hour in-hospital mortality was the primary outcome.
Among the 982 patients, 8.75% died within 24 hours of admission. The non-survivors typically had higher TRIAGES and lower GCS scores. Logistic regression showed significant associations of both TRIAGES and GCS with mortality; the adjusted ORs were 1.98 (95% CI 1.74 to 2.25) for TRIAGES and 0.72 (95% CI 0.68 to 0.77) for GCS. Receiver operating characteristic (ROC) analysis indicated an area under the ROC curve of 0.86 for GCS and 0.88 for TRIAGES, with a significant difference (p=0.012). However, precision–recall curve (PRC) analysis revealed an area under the PRC of 0.38 for GCS and 0.47 for TRIAGES, without a significant difference (p=0.107).
The TRIAGES system is a promising tool for predicting 24-hour in-hospital mortality in older patients with TBI, demonstrating comparable or slightly superior efficacy to the GCS. Further multicentre studies are recommended for validation.
Lateral violence is a global social problem that has attracted considerable attention in the field of public health. This has seriously affected the quality of care, the safety of patients' lives and the career development of nurses.
To systematically evaluate the factors influencing of nursing lateral violence and provide evidence for preventing and reducing inter-nursing lateral violence.
A systematic review of qualitative study was performed in accordance with the Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ) guidelines. We collected qualitative studies on the factors influencing of inter-nursing lateral violence by searching PubMed, EMbase, The Cochrane Library, Web of Science, CINAHL, Science Direct, WanFang Data, China National Knowledge Infrastructure (CNKI), Chinese Scientific Journal Database (VIP) and Chinese Biomedical Literature Database (CBM). Data from inception to September 2023. Literature screening and data extraction were independently conducted by two reviewers. The Critical Appraisal Skills Program (CASP) scale was employed to assess the quality of the studies, including objectives, methodologies, designs, results and contributions.
A total of 25 studies involving 882 participants were included. The results of the thematic analysis indicated that inter-nursing lateral violence was influenced by hospital management, perpetrators, victims and sociodemographic factors.
Inter-nursing lateral violence was influenced by multidimensional factors. To reduce the occurrence of horizontal violence among nurses, hospitals need to explore the establishment and improvement of a horizontal violence resolution mechanism, and schools should pay attention to the joint support and education of nursing students, create a good working environment and harmonious nursing culture, and promote mutual respect among nurses.
This review emphasises the importance of the influencing factors of horizontal violence among nurses, analyses the importance of influencing factors from different perspectives, and proposes corresponding measures to reduce inter-nursing lateral violence.
This study was mostly a literature review; neither patients nor pertinent staff were involved in either the design or conduct of the investigation.
To identify and appraise the quality of evidence of transitional care interventions on quality of life in lung cancer patients.
Quality of life is a strong predictor of survival. The transition from hospital to home is a high-risk period for patients' readmission and death, which seriously affect their quality of life.
Systematic review and meta-analysis.
The PubMed, Embase, Cochrane Library, Web of Science and CINAHL databases were searched from inception to 22 October 2022. The primary outcome was quality of life. Statistical analysis was conducted using Review Manager 5.4, results were expressed as standard mean difference (SMD) with a 95% confidence interval (CI). The risk of bias of the included studies was assessed using the Cochrane risk of bias assessment tool. This study was complied with PRISMA guidelines and previously registered in PROSPERO (CRD42023429464).
Fourteen randomized controlled trials were included consisting of a total of 1700 participants, and 12 studies were included in the meta-analysis. It was found that transitional care interventions significantly improved quality of life (SMD = 0.21, 95% CI: 0.02 to 0.40, p = .03) and helped reduce symptoms (SMD = −0.65, 95% CI: −1.13 to −0.18, p = .007) in lung cancer patients, but did not significantly reduce anxiety and depression, and the effect on self-efficacy was unclear.
This study shows that transitional care interventions can improve quality of life and reduce symptoms in patients, and that primarily educational interventions based on symptom management theory appeared to be more effective. But, there was no statistically significant effect on anxiety and depression.
This study provides references for the application of transitional care interventions in the field of lung cancer care, and encourages nurses and physicians to apply transitional care plans to facilitate patients' safe transition from hospital to home.
No Patient or Public Contribution.
Efficient discharge for stroke patients is crucial but challenging. The study aimed to develop early predictive models to explore which patient characteristics and variables significantly influence the discharge planning of patients, based on the data available within 24 h of admission.
Prospective observational study.
A prospective cohort was conducted at a university hospital with 523 patients hospitalised for stroke. We built and trained six different machine learning (ML) models, followed by testing and tuning those models to find the best-suited predictor for discharge disposition, dichotomized into home and non-home. To evaluate the accuracy, reliability and interpretability of the best-performing models, we identified and analysed the features that had the greatest impact on the predictions.
In total, 523 patients met the inclusion criteria, with a mean age of 61 years. Of the patients with stroke, 30.01% had non-home discharge. Our model predicting non-home discharge achieved an area under the receiver operating characteristic curve of 0.95 and a precision of 0.776. After threshold was moved, the model had a recall of 0.809. Top 10 variables by importance were National Institutes of Health Stroke Scale (NIHSS) score, family income, Barthel index (BI) score, FRAIL score, fall risk, pressure injury risk, feeding method, depression, age and dysphagia.
The ML model identified higher NIHSS, BI, and FRAIL, family income, higher fall risk, pressure injury risk, older age, tube feeding, depression and dysphagia as the top 10 strongest risk predictors in identifying patients who required non-home discharge to higher levels of care. Modern ML techniques can support timely and appropriate clinical decision-making.
This study illustrates the characteristics and risk factors of non-home discharge in patients with stroke, potentially contributing to the improvement of the discharge process.
STROBE guidelines.
A meta-analysis was conducted to evaluate the effects of loose combined cutting seton surgery on wound healing and pain in patients with high anal fistula, aiming to provide evidence-based medical evidence for surgical method selection for these patients. A comprehensive computerized search of PubMed, Cochrane Library, EMBASE, Wanfang and China National Knowledge Infrastructure databases was conducted to collect all relevant studies published up to November 2023, evaluating the effects of loose combined cutting seton surgery in treating patients with high anal fistulas. Two researchers independently screened, extracted data, and assessed the quality of the identified studies. RevMan 5.4 software was employed for data analysis. Overall, 16 articles were included, comprising 1124 patients, with 567 undergoing loose combined cutting seton surgery and 557 undergoing simple cutting seton surgery. The analysis revealed patients undergoing loose combined cutting seton surgery had a higher rate of postoperative wound healing (97.44% vs. 81.69%, odds ratio [OR]: 7.49, 95% confidence interval [CI]: 4.29–13.10, p < 0.00001), shorter wound healing time (standardized mean differences [SMD]: −1.48, 95% CI: −1.89 to −1.08, p < 0.00001), lower postoperative wound pain scores (SMD: −2.51, 95% CI: −3.51 to −1.51, p < 0.00001), and a lower rate of postoperative complications (3.43% vs. 20.83%, OR: 0.13, 95% CI: 0.05–0.31, p < 0.00001). The current evidence suggests that compared to simple cutting seton surgery, loose combined cutting seton surgery in treating high anal fistulas can promote postoperative wound healing, shorten wound healing time, alleviate pain, and reduce the incidence of postoperative complications, making it a worthy clinical practice for widespread application.
Diabetic foot ulcers (DFUs) are a serious chronic complication of diabetes mellitus and a leading cause of disability and death in diabetic patients. However, current treatments remain unsatisfactory. Although macrophages are associated with DFU, their exact role in this disease remains uncertain. This study sought to detect macrophage-related genes in DFU and identify possible therapeutic targets. Single-cell datasets (GSE223964) and RNA-seq datasets (GSM68183, GSE80178, GSE134431 and GSE147890) associated with DFU were retrieved from the gene expression omnibus (GEO) database for this study. Analysis of the provided single-cell data revealed the distribution of macrophage subpopulations in the DFU. Four independent RNA-seq datasets were merged into a single DFU cohort and further analysed using bioinformatics. This included differential expression (DEG) analysis, multiple machine learning algorithms to identify biomarkers and enrichment analysis. Finally, key results were validated using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and Western bolt. Finally, the findings were validated using RT-qPCR and western blot. We obtained 802 macrophage-related genes in single-cell analysis. Differential expression analysis yielded 743 DEGs. Thirty-seven macrophage-associated DEGs were identified by cross-analysis of marker genes with macrophage-associated DEGs. Thirty-seven intersections were screened and cross-analysed using four machine learning algorithms. Finally, HMOX1 was identified as a potentially valuable biomarker. HMOX1 was significantly associated with biological pathways such as the insulin signalling pathway. The results showed that HMOX1 was significantly overexpressed in DFU samples. In conclusion, the analytical results of this study identified HMOX1 as a potentially valuable biomarker associated with macrophages in DFU. The results of our analysis improve our understanding of the mechanism of macrophage action in this disease and may be useful in developing targeted therapies for DFU.
The resilience education of intern nursing students has significant implications for the development and improvement of the nursing workforce. The clinical internship period is a critical time for enhancing resilience.
To evaluate the resilience level of Chinese nursing interns and explore the effects of factors affecting resilience early in their careers, focusing on the mediating roles of career adaptability between clinical learning environment and resilience.
The cross-sectional study design was adopted. From March 2022 to May 2023, 512 nursing interns in tertiary care hospitals were surveyed online with the Connor-Davidson Resilience Scale, the Clinical Learning Environment Scale for Nurse and the Career Adapt-Abilities Scale. Structural equation modelling was used to clarify the relationships among these factors. Indirect effects were tested using bootstrapped confidence intervals.
The nursing interns showed a moderately high level of resilience [M (SD) = 70.15 (19.90)]. Gender, scholastic attainment, scholarship, career adaptability and clinical learning environment were influencing factors of nursing interns' resilience. Male interns with good academic performance showed higher levels of resilience. Career adaptability and clinical learning environment positively and directly affected their resilience level (β = 0.62, 0.18, respectively, p < .01). Career adaptability was also positively affected by the clinical learning environment (β = 0.36, p < .01), and mediated the effect of clinical learning environment on resilience (β = 0.22, p < .01).
Clinical learning environment can positively affect the resilience level of nursing interns. Career adaptability can affect resilience directly and also play a mediating role between clinical learning environment and resilience. Thus, promotion of career adaptability and clinical teaching environment should be the potential strategies for nursing interns to improve their resilience, especially for female nursing interns with low academic performance.
Complex fractures present significant challenges in orthopaedic surgery, particularly in terms of postoperative wound healing. Nutritional status plays a crucial role in the recovery process, with early nutritional support potentially influencing wound healing outcomes. This meta-analysis aimed to assess the impact of early nutritional interventions on postoperative wound healing and scar formation in patients with complex fractures. From an initial pool of 1742 articles, 7 studies were selected for analysis. The results revealed that preoperative nutritional support significantly improved early wound healing, as indicated by lower REEDA scores (SMD = −14.06, 95% CI: [−16.79, −11.32], p < 0.01) 1 week post-surgery. Furthermore, there was a notable reduction in scar formation, as demonstrated by lower Manchester Scar Scale scores (SMD = −25.03, 95% CI: [−30.32, −19.74], p < 0.01) 3 months post-surgery. These findings highlight the importance of incorporating nutritional strategies into the management of complex fractures to optimize postoperative recovery.
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.
Following pancreatic resection, there may be a variety of complications, including wound infection, haemorrhage, and abdominal infection. The placement of drainage channels during operation may decrease the chances of postoperative complications. However, what kind of drainage can decrease the rate of postoperative complications is still a matter of debate. The purpose of this research is to evaluate the efficacy of both active and passive drainage for post-operation wound complications. From the beginning of the database until November 2023, EMBASE, the Cochrane Library and the Pubmed database have been searched. The two authors collected 2524 related studies from 3 data bases for importation into Endnote software, and 8 finished trials were screened against the exclusion criteria. Passive drainage can decrease the incidence of superficial wound infection in postoperative patients with pancreas operation (Odds Ratio [OR], 1.30; 95% CI, 1.06–1.60 p = 0.01); No statistically significant difference was found in the incidence of deep infections among the two groups (OR, 1.51; 95% CI, 0.68–3.36 p = 0.31); No statistical significance was found for the rate of haemorrhage after active drainage on the pancreas compared with that of passive drainage (OR, 0.72; 95% CI, 0.29–1.77 p = 0.47); No statistically significant difference was found in the rate of death after operation for patients who had received a pancreas operation in active or passive drainage (OR, 0.90; 95% CI, 0.57–1.42 p = 0.65); On the basis of existing evidence, the use of passive abdominal drainage reduces postoperative surface wound infections in patients. But there were no statistically significant differences in the risk of severe complications, haemorrhage after surgery, or mortality. However, because of the limited sample size of this meta-analysis, it is necessary to have more high-quality research with a large sample size to confirm the findings.
Foot infections, sores or deep tissue damage from diabetes can be a serious psychological and physical injury. This paper aims at making meta-analyses on the therapeutic effects of traditional Chinese medicine (TCM) on diabetic foot ulcers. The Chinese National Knowledge Infrastructure, VIP Database, Wanfang Database and so on, has conducted a randomized controlled trial to evaluate the clinical effect of TCM soaking method for diabetes patients with diabetes. Literature has been determined to be included by computer search and by hand rough checks. The search period was from the creation of the database to October 2023. Review Manager 5.3 was used to analyse the meta data and evaluate it systematically. Altogether, 479 research was conducted in China's data base and 20 of them were eventually collected for the final statistical analysis. In all, 1361 patients were enrolled in the trials. The results indicated that TCM immersion in diabetic foot resulted in significantly improved obvious wound healing (OR, 3.2; 95% CI, 2.5, 4.09, p < 0.0001); results showed that TCM immersion therapy significantly increased the efficiency of effective wound healing (OR, 4.55; 95% CI, 3.25, 6.37, p < 0.001). Statistical significance was found. Using Egger's approach to detect publishing bias suggests that there is no risk of publishing bias in terms of marked wound healing and effective healing. Traditional Chinese drug immersion can increase obviously the recovery ratio and the effective recovery ratio of diabetic foot.
The aim of this study is to develop a nomogram to assess the risk of surgical site infection in elderly patients undergoing open lumbar spine surgery and explore related risk factors. We reviewed the records of 578 elderly patients who had undergone open lumbar spine surgery. The clinical parameters were subjected to lasso regression and logistic regression analyses. Subsequently, a nomogram was constructed to predict the risk of postoperative surgical site infection and validated using bootstrap resampling. A total of 578 patients were included in the analysis, of which 17 were diagnosed as postoperative surgical site infection. Following the final logistic regression analysis, obesity, hypoalbuminemia and drinking history were identified as independent risk factors and subsequently incorporated into the nomogram. The nomogram demonstrated excellent discrimination, with an area under the receiver-operating characteristic curve of 0.879 (95% CI 0.769 ~ 0.989) after internal validation. The calibration curve exhibited a high level of consistency. Decision curve analysis revealed that this nomogram had greater clinical value when the risk threshold for surgical site infection occurrence was >1% and <89%. We had developed a nomogram for predicting the risk of postoperative surgical site infection in elderly patients who had undergone open lumbar spine surgery. Validation using bootstrap resampling demonstrated excellent discrimination and calibration, indicating that the nomogram may hold potential clinical utility as a simple predictive tool for healthcare professionals.
Kawasaki disease (KD) is one of the most challenging diseases that is defined as an acute vasculitis that affects the coronary arteries primarily in children. It causes complications if left untreated at early stages, ultimately leading to death. Corticosteroids have been recognized to treat and cause great impact on the patients with KD. Glucocorticoid is one of the main corticosteroids that are being used to treat KD and cutaneous wounds. However, ineffectiveness of a few glucocorticoids can limit the efficacy of this treatment. This study particularly aimed to elucidate the impact of glucocorticoids on cutaneous wounds in KD. To perform the meta-analysis, a comprehensive literature survey was conducted to unveil the studies and research conducted on Kawasaki patients that revealed different glucocorticoids in the form of specific interventions influencing KD. The literature was searched using numerous keywords, screened and data was extracted to perform the meta-analysis and then it was conducted using the metabin function of R package meta. A total of 2000 patients from both intervention and control groups were employed to carry out the meta-analysis to analyse and evaluate the impact of glucocorticoids on curing KD and cutaneous wounds in patients. The results disclosed that glucocorticoids along with other steroids, mainly IVIG (intravenous immunoglobulin), was an effective intervention to patients suffering from Kawasaki. The results depicted significant outcomes with the values (risk ratio [RR]: 1.08, 95% confidence interval [CI]: 0.58–2.00, p < 0.01) and enlightened the fact that adopting different glucocorticoids may significantly improve the efficacy of skin lesions along with KD. Hence, interventions of glucocorticoids must be utilized in the clinical practice to reduce the incidence of skin wounds and adverse effects caused due to KD.
We investigated the contamination of the operator and the surrounding environment during wound debridement through simulated operations using fluorescent labelling. On-site simulated operation assessment was performed before and after the training. Oranges and square towels were used to simulate wounds and the inpatient units, respectively. Fluorescent powder was applied to the surfaces. Operations on oranges simulated bedside debridement, and the postoperative distribution of the fluorescent powder was employed to reflect the contamination of the operator and the surrounding environment. During the pre-training assessment, contamination was observed in 28 of the 29 trainees. The commonly contaminated parts were the extensor side of the forearm, middle abdomen, upper abdomen, and hands. The right side of the operating area was contaminated in 24 trainees. During the post-training assessment, contamination was observed in 13 of the 15 trainees. The commonly parts were the hands, extensor side of the forearm, and the lower abdomen. The front, back, left, and right sides of the operating area were contaminated in 12, 9, 11, and 14 trainees, respectively. Contamination of the treatment cart was observed in 5 trainees. Operator and the surrounding environment can be contaminated during wound debridement. Attention should be paid to hand hygiene, wearing and changing of work clothes, and disinfection of the surrounding environment. Moreover, regular training is recommended.
FreshRSS 