Guiyuan Ma’s research while affiliated with Central South University and other places

Catheter-related thrombosis (CRT) poses serious risks for cancer patients. Identifying risk factors and implementing targeted interventions can prevent CRT. To explore thromboelastogram parameters and clinical risk factors for CRT in elderly lung cancer patients. A total of 663 elderly lung cancer patients were selected from three hospitals in Hunan, Hainan, and Qinghai provinces in China from January 1, 2022, to June 30, 2024. The patients were divided into two groups: a CRT group (221 patients) and a non-CRT group (442 patients), with a ratio of 1:2. A between-group comparison and binary logistic regression were used to analyze risk factors for CRT in elderly lung cancer patients. Binary logistic regression analysis showed that decreased R (odds ratio [OR]: 0.849, 95% confidence interval [CI]: 0.763–0.945, p = 0.003), decreased K (0.571, 95% CI: 0.404–0.807, p = 0.001), advanced age (OR: 1.073, 95% CI: 1.033–1.113, p < 0.001), elevated platelet count (OR: 1.006, 95% CI: 1.004–1.009, p < 0.001), increased hemoglobin level (OR: 1.020, 95% CI: 1.009–1.031, p < 0.001), shortened PT (OR: 0.904, 95% CI: 0.830–0.985, p = 0.022), surgery ≤ 1 month (OR: 2.258, 95% CI: 1.420–3.590, p = 0.001), male sex (OR: 4.534, 95% CI: 2.815–7.304, p < 0.001), diabetes (OR: 2.478, 95% CI: 1.373–4.472, p = 0.003), hypertension (OR: 2.386, 95% CI: 1.505–3.784, p < 0.001), physical activity disorders (OR: 9.038, 95% CI: 4.462–18.309, p < 0.001) were independent risk factors for CRT in elderly lung cancer patients. Independent risk factors for CRT in elderly lung cancer patients include decreased K-values and decreased R-values, shortened PT, advanced age, elevated platelet count, increased hemoglobin level, surgery ≤ 1 month, male sex, diabetes, hypertension, and physical activity disorders.

Evaluating Master of Nursing Specialist (MNS) students' knowledge, attitudes, and practice regarding catheter‐related thrombosis (CRT) prevention and treatment is beneficial in developing effective CRT training for them. This study thus aimed to explore their knowledge, attitudes, and practice toward CRT. This was a cross‐sectional study that included 1046 MNS students in China. The results revealed that the median scores for the participants' knowledge, attitudes, and practice were 12 (interquartile range: 9–14), 55 (interquartile range: 50–65), and 62 (interquartile range: 51–71), respectively. There was a positive correlation between knowledge and attitudes, as well as attitudes and practice. Age, school level, proactively learning CRT knowledge, gender, enrolment method, participation in clinical practice time, and attendance at CRT training were related to knowledge (p < 0.05). Attendance at CRT training and experience using thrombosis risk assessment forms were related to attitude and practice (p < 0.05). Gender and experience caring for CRT patients were associated with practice (p < 0.05). MNS students have insufficient knowledge of CRT prevention and treatment, and the practice needs to be improved. However, their attitudes are positive.

Central venous access devices (CVADs) are integral to cancer treatment. However, catheter-related thrombosis (CRT) poses a considerable risk to patient safety. It interrupts treatment; delays therapy; prolongs hospitalisation; and increases the physical, psychological and financial burden of patients. Our study aims to construct and validate a predictive model for CRT risk in patients with cancer. It offers the possibility to identify independent risk factors for CRT and prevent CRT in patients with cancer. We prospectively followed patients with cancer and CVAD at Xiangya Hospital of Central South University from January 2021 to December 2022 until catheter removal. Patients with CRT who met the criteria were taken as the case group. Two patients with cancer but without CRT diagnosed in the same month that a patient with cancer and CRT was diagnosed were selected by using a random number table to form a control group. Data from patients with CVAD placement in Qinghai University Affiliated Hospital and Hainan Provincial People’s Hospital (January 2023 to June 2023) were used for the external validation of the optimal model. The incidence rate of CRT in patients with cancer was 5.02% (539/10 736). Amongst different malignant tumour types, head and neck (9.66%), haematological (6.97%) and respiratory (6.58%) tumours had the highest risks. Amongst catheter types, haemodialysis (13.91%), central venous (8.39%) and peripherally inserted central (4.68%) catheters were associated with the highest risks. A total of 500 patients with CRT and 1000 without CRT participated in model construction and were randomly assigned to the training (n = 1050) or testing (n = 450) groups. We identified 11 independent risk factors, including age, catheterisation method, catheter valve, catheter material, infection, insertion history, D-dimer concentration, operation history, anaemia, diabetes and targeted drugs. The logistic regression model had the best discriminative ability amongst the three models. It had an area under the curve (AUC) of 0.868 (0.846–0.890) for the training group. The external validation AUC was 0.708 (0.618–0.797). The calibration curve of the nomogram model was consistent with the ideal curve. Moreover, the Hosmer–Lemeshow test showed a good fit (P > 0.05) and high net benefit value for the clinical decision curve. The nomogram model constructed in this study can predict the risk of CRT in patients with cancer. It can help in the early identification and screening of patients at high risk of cancer CRT.

Background Ventilator‐associated pneumonia (VAP) is the most common nosocomial infection in intensive care units (ICUs) and is a common cause of morbidity and mortality in intensive care patients. Previous studies show that insufficient knowledge and compliance barriers among nurses affect pneumonia. There have been no investigations into intensive care nurses' knowledge and compliance barriers to evidence‐based guidelines (EBGs) for VAP prevention in county‐level hospitals in China. Aim To explore adult ICU nurses' knowledge and compliance barriers to EBGs for preventing VAP in county‐level hospitals in Hunan Province, China, examine the correlation between knowledge and compliance barriers, and analyse associated factors. Study Design A cross‐sectional electronic survey was conducted to focus on nurses' knowledge of and compliance barriers to EBGs for preventing VAP. Results A total of 386 valid questionnaires were collected, with a response rate of 97.47% (386/396 = 97.47%). The median scores for nurses' knowledge (out of 9) and compliance barriers (out of 8) to EBGs for preventing VAP were 7 (interquartile range: 5–8) and 3 (interquartile range: 2–4), respectively. Knowledge was negatively associated with compliance barriers (r = −0.437, p < .01). The results of the multiple linear regression analysis showed that hospital level, age, nurses' attendance at VAP training and years of experience in ICUs were related to the level of knowledge. Nurses' attendance at VAP training, age and years of experience in ICUs were associated with the level of compliance barriers. Conclusions Intensive care nurses have satisfactory knowledge of EBGs for preventing VAP, but compliance barriers can be reduced. Better knowledge helps reduce the barriers to compliance among nurses. Relevance to Clinical Practice Nurse managers and nurse educators are suggested to examine nurses' knowledge and compliance barriers to EBGs for preventing VAP, develop personalized training plans, promote continuous education based on the latest EBGs and raise the nurse–patient ratio reasonably.

Background Medical personnel contact with the patient closely, and their knowledge of vascular catheter-associated infections (VCAIs) is closely related to the prevention of VCAIs. Researchers mainly pay attention to the VCAIs knowledge of doctors and nurses but rarely pay attention to the nursing students in the hospital internship stage. Purpose To investigate the current situation of knowledge of intern-nursing students in VCAIs, and analyze its influencing factors. Patients and Methods 843 intern-nursing students were selected from 10 hospitals in five regions of eastern, western, southern, northern, and central China from June 26 to July 31, 2023, using a two-stage random sampling method. A self-designed questionnaire with good reliability and validity was used to investigate their knowledge of VCAIs, and t-test, multiple linear regression analysis, and Welch t-test were used to analyze the collected data by using SPSS Statistics 26.0 (IBM Corp., Armonk, NY). Results Intern nursing students’ mean score of VCAIs knowledge was 48.66 (SD=15.77), with a score below 60 (unqualified) accounting for 75.4%, a score of 60–79 (qualified) accounting for 19.7%, a score of 80–89 (good) accounting for 3.6%, and a score of above 90 accounting for 1.3%. Students who attended VCAIs training three or more times had higher scores than those who did not attend training (B: 4.706, p=0.001), knowledge scores of students with a bachelor’s degree or above were higher than those with junior college degree or below (B: 8.479, p<0.001), students who interned in tertiary hospitals had higher scores than those practicing in secondary hospitals (B:12.381, p<0.001) and scores of students in hospital training were significantly higher than study independently (B:4.116, p=0.007). Conclusion Intern-nursing students have a relatively low level of knowledge about VCAIs. It is recommended to strengthen clinical systematic and standardized training, improve the knowledge mastery level of intern-nursing students, and enhance their ability to handle VCAIs.

BACKGROUND Central venous access devices (CVADs) play a crucial role in providing treatment and supportive care for cancer patients. However, catheter-related thrombosis (CRT) poses a significant risk to patient safety., which will interrupt patient treatment, delay the patient's therapeutic period, prolong hospitalization, and increase the patient’s physical, mental, and economic burden. Identifying independent risk factors for CRT in cancer patients, proactively utilizing high-quality risk assessment tools in high-risk groups, and implementing precise prevention and treatment can effectively reduce the occurrence of CRT. OBJECTIVE Construction and validation of a prediction model for predicting the risk of catheter-related thrombosis (CRT) in cancer patients’ central venous access devices (CVADs). METHODS Using a prospective study design, cancer patients with CVADs in Xiangya Hospital of Central South University were followed up from January 2021 to December 2022 until catheter removal and 539 cases of CVADs-CRT occurred. Five hundred patients who met the inclusion and exclusion criteria were taken as the case group. Two cases of cancer patients without CRT were taken according to the number of CRTs/number of non-CRTs (1:2) in the same month in which a case of cancer patient with CRT was diagnosed by using the random number table method, for a total of 1,000 cases of cancer patients without CRT as the control group. Patient data were randomly divided into a training group (n=1050) and a testing group (n=450) according to the ratio of 7:3. Univariate and Least Absolute Shrinkage and Selection Operator (LASSO) algorithm was used to determine the risk factors for CRT formation. Risk prediction models were constructed based on Logistic Regression, Random Forest, and Support Vector Machine and evaluated by area under the curve (AUC). Data from patients with CVADs placement in Qinghai University Affiliated Hospital and Hainan Provincial People's Hospital (January 2023 to June 2023) were applied to externally validate the optimal model's differentiation, calibration, and clinical applicability. RESULTS The incidence of CVADs-CRT in cancer patients was 5.02%. There was a difference in the occurrence of CRT in patients with different cancers (P<.05), and the top three highest risks of occurrence were in patients with head and neck tumors (9.66%), haematological tumors (6.97%) and respiratory tumors (6.58%). There was a difference in the occurrence of CRT in patients with different catheters placed (P<.05), with the top three highest risks occurring in hemodialysis catheters (13.91%), CVC (8.39%), and PICC (4.68%). Eleven independent risk factors were screened for age, catheter method, catheter valve, catheter material, infection, catheter history, D-Dimer, operation history, anemia, diabetes, and targeted drugs. The Logistic prediction model had the best discriminative ability among the three machine learning-constructed models, with AUCs of 0.868 (0.846-0.890) for the training group. The externally validated AUC was 0.708 (0.618-0.797), the Nomogram model calibration curve was consistent with the ideal curve, and the Hosmer-Lemeshow test showed a good fit (P > .05) and a high net benefit value for the clinical decision curve. CONCLUSIONS The Nomogram constructed in this study can be personalised to predict the risk of developing CVADs-CRT in cancer patients, which can help in the early identification and screening of patients at high risk of cancer CVADs-CRT.

Background Cancer indeed represents a significant public health challenge, and unplanned extubation of peripherally inserted central catheter (PICC-UE) is a critical concern in patient safety. Identifying independent risk factors and implementing high-quality assessment tools for early detection in high-risk populations can play a crucial role in reducing the incidence of PICC-UE among patients with cancer. Precise prevention and treatment strategies are essential to improve patient outcomes and safety in clinical settings. Objective This study aims to identify the independent risk factors associated with PICC-UE in patients with cancer and to construct a predictive model tailored to this group, offering a theoretical framework for anticipating and preventing PICC-UE in these patients. Methods Prospective data were gathered from January to December 2022, encompassing patients with cancer with PICC at Xiangya Hospital, Central South University. Each patient underwent continuous monitoring until the catheter’s removal. The patients were categorized into 2 groups: the UE group (n=3107) and the non-UE group (n=284). Independent risk factors were identified through univariate analysis, the least absolute shrinkage and selection operator (LASSO) algorithm, and multivariate analysis. Subsequently, the 3391 patients were classified into a train set and a test set in a 7:3 ratio. Utilizing the identified predictors, 3 predictive models were constructed using the logistic regression, support vector machine, and random forest algorithms. The ultimate model was selected based on the receiver operating characteristic (ROC) curve and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) synthesis analysis. To further validate the model, we gathered prospective data from 600 patients with cancer at the Affiliated Hospital of Qinghai University and Hainan Provincial People’s Hospital from June to December 2022. We assessed the model’s performance using the area under the curve of the ROC to evaluate differentiation, the calibration curve for calibration capability, and decision curve analysis (DCA) to gauge the model’s clinical applicability. Results Independent risk factors for PICC-UE in patients with cancer were identified, including impaired physical mobility (odds ratio [OR] 2.775, 95% CI 1.951-3.946), diabetes (OR 1.754, 95% CI 1.134-2.712), surgical history (OR 1.734, 95% CI 1.313-2.290), elevated D-dimer concentration (OR 2.376, 95% CI 1.778-3.176), targeted therapy (OR 1.441, 95% CI 1.104-1.881), surgical treatment (OR 1.543, 95% CI 1.152-2.066), and more than 1 catheter puncture (OR 1.715, 95% CI 1.121-2.624). Protective factors were normal BMI (OR 0.449, 95% CI 0.342-0.590), polyurethane catheter material (OR 0.305, 95% CI 0.228-0.408), and valved catheter (OR 0.639, 95% CI 0.480-0.851). The TOPSIS synthesis analysis results showed that in the train set, the composite index (Ci) values were 0.00 for the logistic model, 0.82 for the support vector machine model, and 0.85 for the random forest model. In the test set, the Ci values were 0.00 for the logistic model, 1.00 for the support vector machine model, and 0.81 for the random forest model. The optimal model, constructed based on the support vector machine, was obtained and validated externally. The ROC curve, calibration curve, and DCA curve demonstrated that the model exhibited excellent accuracy, stability, generalizability, and clinical applicability. Conclusions In summary, this study identified 10 independent risk factors for PICC-UE in patients with cancer. The predictive model developed using the support vector machine algorithm demonstrated excellent clinical applicability and was validated externally, providing valuable support for the early prediction of PICC-UE in patients with cancer.

BACKGROUND Cancer is a major public health problem and poses a health threat to the population, and Peripherally Inserted Central Catheters-Unplanned Extubation (PICC-UE) is considered the most adverse event for patient safety. Identifying independent risk factors for PICC-UE, applying high-quality assessment tool early in high-risk population, and adopting precise prevention and treatment can effectively reduce the occurrence of PICC-UE. OBJECTIVE The objective is to identify the independent risk factors for PICC-UE in cancer patients, and to develop a predictive model for PICC-UE for cancer patients, providing a theoretical basis for the prevention and prediction of PICC-UE in cancer patients. METHODS Prospective data were collected from January to December 2022 from cancer patients with PICC at Xiangya Hospital, Central South University, and each patient was followed up until the catheter removal. The patients were divided into UE group (n=3107) and non-UE group (n=284), and independent risk factors were determined by univariate, LASSO algorithm and multivariate analysis. The 3391 patients were then divided into a trainset and a testset according to the ratio of 7:3. The screened predictors were used to build three predictive models using Logistic Regression, Support Vector Machine and Random Forest algorithms, and the optimal model was screened by ROC curve and TOPSIS synthesis analysis. We collected prospective data of 600 cancer patients with PICC from June to December 2022 at the Affiliated Hospital of Qinghai University and Hainan Provincial People's Hospital for external validation. The Area Under the Curve (AUC) of the ROC was used to test the differentiation of the model, and the Calibration Curve to assess the calibration capability and Decision Curve Analysis (DCA) to evaluate the clinical applicability of the model. RESULTS Independent risk factors for PICC-UE in cancer patients included impaired physical mobility (OR=2.775), diabetes (OR=1.754), surgical history (OR=1.734), elevated D-dimer concentration (OR=2.376), targeted therapy (OR=1.441), surgical protocol (OR=1.543), and more than one catheter puncture (OR=1.715); protective factors included normal BMI (OR=0.449), polyurethane catheter material (OR=0.305), and valved catheter (OR=0.639). The results of the TOPSIS synthesis analysis: the Ci values were 0.00, 0.82 and 0.85 in the trainset, and the Ci values were 0.00, 1.00 and 0.81 in the testset for the Logistic, Support Vector Machine and Random Forest models, respectively. The optimal model constructed based on Support Vector Machine was obtained and validated externally, the ROC curve, Calibration curve and DCA curve showed that the model had excellent accuracy, stability, generalizability and clinical applicability. CONCLUSIONS Ten independent predictors of PICC-UE in cancer patients were obtained in this study. The predictive model was constructed based on Support Vector Machine, which has clinical application value through external validation, and provides significant support for the early prediction of PICC-UE in cancer patients.

Objectives: As the coronavirus disease 2019 (COVID-19) pandemic continues to spread worldwide, nucleic acid detection is a key step in controlling it. Psychological issues and job burnout of nurses working in nucleic acid sampling roles for long periods have become apparent. This study aimed to explore the effects of mindfulness decompression therapy on mental health and job burnout in front-line nurses working in nucleic acid sampling during the pandemic. Methods: Nucleic acid sampling frontline nurses who were positive for burnout on both the Symptom Checklist-90 (SCL-90) and the Maslach Burnout Inventory-General Scale (MBI-GS) were selected as the participants. Frontline nurses in the nucleic acid testing area who received routine psychological nursing intervention from June 2020 to April 2021 were used as the control group. Nurses who received both routine psychological nursing and mindfulness decompression therapy from May 2021 to December 2021 formed the "mindfulness" subject group. We compared the two groups' primary outcome measures of SCL-90 and MBI-GS scores. Results: Before the intervention, there were no significant differences between the two groups in general data, SCL-90 scores, and MBI-GS scores. After the mindfulness decompression therapy, according to SCL-90 and MBI-GS scales, psychological distress and job burnout of nurses in the mindfulness group were significantly better than those in the control group. Conclusion: Mindfulness decompression therapy can effectively improve mental health and relieve job burnout in frontline nurses in nucleic acid sampling areas, which is worthy of clinical application. Randomized controlled trials are still needed, however, to fully confirm the effects of mindfulness decompression therapy.

BACKGROUND Population aging is an important problem in the world. Family nursing has become an effective way to deal with population aging. China's Internet + home care is in its infancy, and there are few studies on the willingness and demand of clinical nurses in municipal hospitals for Internet + home care. OBJECTIVE The study aims to investigate the willingness and demand of clinical nurses in municipal hospitals in China for Internet + home care services, and analyze the factors affecting the participation of clinical nurses in municipal hospitals in Internet + home care services, and promote the development of Internet + home care. METHODS In this study, we recruited 9405 nurses from 10 hospitals in 5 regions of China by multi-stage sampling method. We use a self-designed reliability and validity questionnaire to measure nurses' willingness and demand for Internet + home care services. Data analysis adopts: χ 2 test, Welch t-test, Binary logistic regression analysis and Multiple linear regression analysis. RESULTS Nurses were highly willing to provide Internet +home care services. Statistical differences were found in the willingness to provide Internet +home care services and the preference for service distance, service period, service times and number of service between nurses in municipal hospitals (both P<.05). Binary Logistic regression analysis showed that job title, educational title, marital status and monthly income are risk facors towards nurses’ willingness for Internet +home care services (both OR＞1) but gender is protective factor (OR＜1). Multiple linear regression showed that job title, monthly family income,educational level influence nurses’ demand for Internet +home care services. CONCLUSIONS The clinical nurses in municipal hospitals have a high willingness and demand for Internet + home care services, which suggests that managers need to strengthen knowledge publicity, and education, reasonably arrange the service period, duration, and frequency, improve various policies, regulations and service processes, improve the service salary of home nurses, and pay attention to the needs and willingness of nurses for Internet + home care services to improve the enthusiasm of nurses to participate in Internet + home care services.