Third-class Hospital Research Articles

Structural equation modeling analysis of factors influencing decisional conflict between dialysis modality among end-stage kidney disease patients in Wuhan

ObjectivesTo explore the influencing factors and relationships associated with decisional conflict of dialysis modality in End-stage kidney disease (ESKD) patients.MethodsThis study was a survey-based cross-sectional investigation conducted on 150 ESKD patients in a third-class hospital in Wuhan. The general information questionnaire, decisional conflict scale, Montreal cognitive assessment, frail scale, perceived social support scale, and brief health literacy screen were used for investigation. SPSS 25.0 was used to compare the differences between the decisional and non-decisional conflict groups, and AMOS 23.0 was used to construct a structural equation model to explore the influencing factors.ResultsThe incidence of decisional conflict in 150 ESKD patients was 33.3% (50/150). Binary logistic regression analysis showed that the independent risk factors for decisional conflict of dialysis modality in ESKD patients included monthly household income (OR = 0.184), cognitive function (OR = 7.0), social support (OR = 0.891), health literacy (OR = 0.608), the level of eGFR (OR = 1.488), and the level of cTnI (OR = 9.558). The constructed path analysis model had a good fit (x2/df = 1.499, GFI = 0.957, AGFI = 0.911, NFI = 0.906, CFI = 0.967, RMSEA = 0.055). The path analysis showed that health literacy (0.577) had the greatest impact on the decisional conflict, with a direct effect of 0.480 and an indirect effect of 0.097 through cognitive function and monthly household income. Next was social support, with an effect value of 0.434.ConclusionsIn clinical practice, it is important to enhance the health literacy of patients and their families and to provide advanced education on dialysis plans. Additionally, in managing and planning chronic kidney disease progression and dialysis, it is recommended to regularly and systematically assess cognitive function, particularly before the patient’s cognitive impairment worsens or the severity of the disease progresses. Advanced care planning can be established through collaboration between healthcare professionals and patients to ensure appropriate decision-making and management.Implications for the profession and patient careThis paper finds that the factors that influence and relate to dialysis methods in end-stage renal disease patients help nurses exercise autonomy better, assist patients in reducing their decisional conflict, and improve clinical outcomes.Patient or public contributionPatients received a relevant questionnaire survey, and caregivers assisted in conducting the study.

Malnutrition is associated with severe outcome in elderly patients hospitalised with COVID-19

Some studies have identified influencing factors of COVID-19 illness in elderly, such as underlying diseases, but research on the effect of nutritional status is still lacking. This study retrospectively examined the influence of nutritional status on the outcome of elderly COVID-19 inpatients. A retrospective analysis of the clinical data of 4241 COVID-19 patients who were admitted to a third-class hospital of Nanchang between November 1, 2022 and January 31, 2023 was conducted. Nutritional status was assessed using the prognostic nutritional index (PNI) and controlling nutritional status score (CONUT). The influence of nutritional status on the outcome of COVID-19 patients was determined through multivariate adjustment analysis, restrictive cubic spline, and receiver operating characteristic curve (ROC). Compared with mild/no malnutrition, severe malnutrition substantially increased the critical outcome of COVID-19. A linear relationship was observed between the odds ratio (OR) and PNI and CONUT (P > 0.05). The area under the ROC curve indicated that PNI was the better predictor. The optimal cutoff value of PNI was 38.04 (95%CI: 0.797 ~ 0.836, AUC = 0.817), with a sensitivity of 70.7% and a specificity of 79.6%. The critical illness of elderly COVID-19 patients shows a linear relationship with malnutrition at admission. The use of PNI to assess the prognosis of COVID-19 eldeely patients is reliable, highlighting the importance for doctors to closely pay attention to the nutritional status of COVID-19 patients. Focusing on nutritional status in clinical practice can effectively reduce the critical illness of elderly COVID-19 patients.

Improve disaster literacy in nurses: a qualitative descriptive study.

The enhancement of nurses' disaster literacy is crucial for effective disaster emergency management, especially for clinical nurses with no prior experience in disaster rescue. This study aims to explore the perspectives of nurses who have been involved in disaster rescue operations on strategies to advance nurses' disaster literacy. A qualitative descriptive study, which follows unified qualitative study reporting guidelines. Thirty disaster rescue nurses were recruited to participate in this study, who came from 30 third-class hospitals in China. From October to December 2021, information was acquired by conducting semi-structured telephone interviews with participants. Qualitative content analysis was used to examine the data. Six categories and eleven subcategories were created. Strengthening disaster education and training was the main focus, and its subcategories included continuing education, nursing curriculum development, and disaster rescue experience guide. The second focus, which included scene simulation, actual combat/military simulation, and virtual reality simulation, was strengthening disaster simulation and drill. The third focus was on providing psychosocial support, which included improving self-psychological adjustment, developing resilience, and engaging in active coping. The fourth category was to strengthen nurse/hospital managers roles and leadership, which included enhancing professional identity and policies/leadership support. The fifth category was disaster preparedness, and the sixth was enhancing knowledge transformation. Government agencies or healthcare organizations should actively promote the formation of nurses' disaster literacy from multiple viewpoints. Disaster education and training, simulation exercises, and psychosocial support should be prioritized.

Symptom clusters and network analysis of patients with intermediate and advanced liver cancer treated with targeted immunotherapy.

This study aims to identify symptom clusters in patients with intermediate and advanced liver cancer receiving targeted immunotherapy, focusing on core and bridge symptoms to establish a foundation for precise symptom management. This study used a cross-sectional survey and utilized convenience sampling from May 2023 to January 2024 at a third-class hospital in Shanghai, China. The severity of symptoms in liver cancer patients during treatment was evaluated using the Memorial Symptom Assessment Scale. Network analysis was employed to depict the interrelation of symptom clusters and identify core and bridge symptoms. The symptoms were classified by severity into five clusters: oral, gastrointestinal, fatigue-related, body image, and pain-sleep. Within the symptom network, the core symptoms were pain, "I don't look like myself," and nausea, while the critical bridge symptoms included pain, itching, and feeling bloated. The strongest connections were observed between nausea and vomiting, followed by taste changes and dry mouth, as well as weight loss and "I don't look like myself." In patients receiving targeted immunotherapy for intermediate and advanced liver cancer, multiple symptoms can emerge simultaneously, forming interconnected clusters. By identifying and intervening in core and bridge symptoms, personalized management strategies can be developed to relieve other symptoms and disrupt connections between symptom clusters, thereby enhancing symptom management efficacy. This study has significant clinical and research implications, offering new insights to improve patients' quality of life and treatment outcomes.

Vitamin D deficiency and the risk of diabetic retinopathy in patients with type 2 diabetes in Tibet: a cross-sectional analysis

BackgroundDiabetic retinopathy (DR) is one of the most common complications of diabetes worldwide. The aim of this study was to assess the prevalence of DR in hospitalized patients with type 2 diabetes (T2DM) in Tibet and to identify risk factors that may influence the occurrence of DR.MethodsThis was a cross-sectional study conducted in a third-class hospital in the Tibet Autonomous Region. The prevalence of DR in hospitalized patients with T2DM was measured. Univariate and multivariate logistic regression, restricted cubic spline (RCS) analysis and receiver-operating characteristic curve analysis were used to investigate the risk factors for DR.ResultsThe prevalence of DR was 29.3%. The duration of diabetes; concentrations of 25-OH-VitD3, hemoglobin, fasting insulin, alanine aminotransferase, total bilirubin, and creatinine; and HOMA-IR were significantly different between DR patients and non-DR patients (all P < 0.05). Univariate and multivariate logistic regression revealed that a longer duration of diabetes and lower 25-OH-VitD3 levels were associated with increased DR risk. RCS analysis suggested overall positive associations of the duration of diabetes and 25-OH-VitD3 concentrations with DR risk (P nonlinearity < 0.05). The turning points for the duration of diabetes and 25-OH-VitD3 concentrations were 5.1 years and 10.6 ng/mL, respectively. The sensitivity, specificity, and area under the receiver-operating characteristic curve for the combination of the duration of diabetes and 25-OH-VitD3 levels were 79.4%, 69.4% and 0.764, respectively.ConclusionsGiven the high prevalence of DR in hospitalized patients with T2DM in Tibet, vitamin D supplementation seems to be important in the prevention of DR to some degree.

Development and Validation of a Machine Learning Algorithm to Predict the Risk of Blood Transfusion after Total Hip Replacement in Patients with Femoral Neck Fractures: A Multicenter Retrospective Cohort Study.

Total hip arthroplasty (THA) remains the primary treatment option for femoral neck fractures in elderly patients. This study aims to explore the risk factors associated with allogeneic blood transfusion after surgery and to develop a dynamic prediction model to predict post-operative blood transfusion requirements. This will provide more accurate guidance for perioperative humoral management and rational allocation of medical resources. We retrospectively analyzed data from 829 patients who underwent total hip arthroplasty for femoral neck fractures at three third-class hospitals between January 2017 and August 2023. Patient data from one hospital were used for model development, whereas data from the other two hospitals were used for external validation. Logistic regression analysis was used to screen the characteristic subsets related to blood transfusion. Various machine learning algorithms, including logistic regression, SVA (support vector machine), K-NN (k-nearest neighbors), MLP (multilayer perceptron), naive Bayes, decision tree, random forest, and gradient boosting, were used to process the data and construct prediction models. A 10-fold cross-validation algorithm facilitated the comparison of the predictive performance of the models, resulting in the selection of the best-performing model for the development of an open-source computing program. BMI (body mass index), surgical duration, IBL (intraoperative blood loss), anticoagulant history, utilization rate of tranexamic acid, Pre-Hb, and Pre-ALB were included in the model as well as independent risk factors. The average area under curve (AUC) values for each model were as follows: logistic regression (0.98); SVA (0.91); k-NN (0.87) MLP, (0.96); naive Bayes (0.97); decision tree (0.87); random forest (0.96); and gradient boosting (0.97). A web calculator based on the best model is available at: (https://nomo99.shinyapps.io/dynnomapp/). Utilizing a computer algorithm, a prediction model with a high discrimination accuracy (AUC > 0.5) was developed. The logistic regression model demonstrated superior differentiation and reliability, thereby successfully passing external validation. The model's strong generalizability and applicability have significant implications for clinicians, aiding in the identification of patients at high risk for postoperative blood transfusion.

Multi-trajectories of symptoms and their associations with unplanned 30-day hospital readmission among patients with heart failure: a longitudinal study.

This study aimed to uncover hidden patterns and predictors of symptom multi-trajectories within 30 days after discharge in patients with heart failure and assess the risk of unplanned 30-day hospital readmission in different patterns. The study was conducted from September 2022 to September 2023 in four third-class hospitals in Tianjin, China. A total of 301 patients with heart failure were enrolled in the cohort, and 248 patients completed a 30-day follow-up after discharge. Three multi-trajectory groups were identified: mild symptom status (24.19%), moderate symptom status (57.26%), and severe symptom status (18.55%). With the mild symptom status group as a reference, physical frailty, psychological frailty, and comorbid renal dysfunction were predictors of the moderate symptom status group. Physical frailty, psychological frailty, resilience, taking diuretics, and comorbid renal dysfunction were predictors of the severe symptom status group. Compared with the mild symptom status group, the severe symptom status group was significantly associated with high unplanned 30-day hospital readmission risks. This study identified three distinct multi-trajectory groups among patients with heart failure within 30 days after discharge. The severe symptom status group was associated with a significantly increased risk of unplanned 30-day hospital readmission. Common and different factors predicted different symptom multi-trajectories. Healthcare providers should assess the physical and psychological frailty and renal dysfunction of patients with heart failure before discharge. Inpatient care aimed at alleviating physical and psychological frailty and enhancing resilience may be important to improve patients' symptom development post-discharge.

Shame in patients undergoing ureterostomy: A cross-sectional survey.

Shame has an important impact on the mental health and quality of life of patients. The shame in patients with ureterostomy after cystectomy remains unclear. This survey aimed to evaluate the status quo and influencing factors of shame in patients with ureterostomy after cystectomy, to provide support for the clinical care. Patients with ureterostomy after cystectomy treated in the wound stomy clinic of a third-class hospital from 1 June 2022 to 31 July 2023 were included. General data questionnaire and social impact scale (SIS) were used for data collection. Univariate and multiple linear regression analysis were performed to evaluate the influencing factors of shame in patients with ureterostomy after cystectomy. One hundred and sixty four patients with ureterostomy after cystectomy were included. The total score of shame in patients with ureterostomy was (60.75 ± 6.31), which was in the high level. Age (r = 0.442), home place (r = 0.427), per capita monthly household income (r = 0.605), self-care ability (r = 0.597) and complications of stoma (r = 0.542) were correlated with the SIS score in patients with ureterostomy after cystectomy (all p < 0.05). Multiple linear regression analyses indicated that age, home place, per capita monthly household income, self-care ability and complications of stoma were the influencing factors of SIS score in patients with ureterostomy after cystectomy (all p < 0.05). The five variables explained 64.5% of the patients' sense of shame variation. Patients with ureterostomy after cystectomy have a serious sense of shame in the early stage after operation and there are many influencing factors. Health care providers should take early nursing interventions targeted on those influencing factors to reduce the patients' sense of shame.

Influencing Factors of Constipation in Elderly Patients With Intracerebral Hemorrhage: Implication for Clinical Care.

Background: Constipation is common in elderly inpatients with intracerebral hemorrhage. This study aimed to construct a model for predicting the risk of constipation in elderly inpatients with intracerebral hemorrhage and to provide reference for formulating targeted intervention measures. Methods: Elderly patients with intracerebral hemorrhage who were treated in the department of Neurosurgery of a third-class hospital in Suzhou from January 2018 to September 2023 were included. Clinical data of patients with and without constipation were compared. Logistic regression analysis was used to explore the influencing factors of constipation in elderly patients with intracerebral hemorrhage, and R software was used to construct a line chart model to verify its predictive effect. Results: A total of 504 elderly patients with intracerebral hemorrhage were included. The incidence of constipation in elderly patients with cerebral hemorrhage was 63.9%. Logistic regression analysis showed that GCS score (OR = 1.094, 95%CI: 1.019∼1.174), hypertension (OR = 2.911, 95%CI: 1.797∼4.715), use of dehydrating agent (OR = 3.794, 95%CI: 2.337∼6.158), surgical treatment (OR = 3.986, 95%CI: 2.339∼6.793), use of sedative drugs (OR = 4.212, 95%CI:2.386-7.435), and limb paralysis (OR = 6.313, 95%CI:3.689∼10.803) were the independent risk factors for constipation in elderly patients with intracerebral hemorrhage. The area under the ROC curve of the prediction model was 0.872 (95%CI: 0.8401∼0.9033), the best critical value was 0.705, the sensitivity was 0.748, and the specificity was 0.857. Conclusion: The constipation risk prediction model of elderly patients with cerebral hemorrhage has good differentiation and calibration, which is helpful for health care providers to identify the risk of constipation in elderly patients with intracerebral hemorrhage.

Core and bridge symptoms of demoralization in Chinese female cancer patients: a network analysis.

In this study, we explore the core and bridge symptoms of demoralization in female cancer patients in China, and provide a basis for precise psychological intervention among female cancer patients. This study used a cross-sectional survey. Participants were recruited from three third-class hospitals in Jiangsu Province from June 2022 to June 2023 using the convenience sampling method. The severity of each symptom of demoralization was investigated in female cancer patients using the Demoralization Scale (DS). Network analysis was performed using the R language to identify core and bridge symptoms in the network and further explore some characteristic edge connections in the network. The network structure model of demoralization had strong accuracy and stability. In the network, the symptoms with the highest strength centrality were "Discouragement" (C3, strength=2.19), "No self-worth" (A3, strength=1.21), "Don't want to live" (A5, strength=1.20), "Hopeless" (D4, strength=0.81), and "Vulnerability" (B3, strength=0.74), respectively. The bridge strength analysis identified "Hopeless" (D4, bridge strength=0.92), "Discouragement" (C3, bridge strength=0.85), "No self-worth" (A3, bridge strength=0.75), "Poor spirits" (E2, bridge strength=0.71), and "Vulnerability" (B3, bridge strength=0.69) as the bridge symptoms. The strongest edge connections of all dimensions were "No self-worth" and "Worthless" (A3-E6, edge weighting=0.27), "Poor spirits" and "Loss of emotional control" (E2-D1, edge weighting=0.22), "Discouragement" and "Vulnerability" (C3-B3, edge weighting=0.14), and "Hopeless" and "No meaning of survival" (D4-A4, edge weighting=0.12). "Discouragement (C3)", "No self-worth (A3)", "Hopeless (D4)", and "Vulnerability (B3)" are both core symptoms and bridge symptoms. These symptoms can not only trigger a patient's demoralization but also stimulate more severe symptom clusters through interactions. The early recognition of and intervention regarding these symptoms could be important for the prevention and treatment of demoralization among female cancer patients.

Validation and psychometric testing of the Chinese version of the prenatal body image questionnaire

BackgroundThe body image during pregnancy potentially affects both short- and long-term maternal and child health outcomes, including pregnancy mood, postpartum weight recovery, and the quality of mother–child interactions. However, research on the impact of body changes during pregnancy in the Chinese population is scarce. A comprehensive, practical, and reliable tool for assessing pregnant women is needed to detect, intervene in, and implement the reduction of physical dissatisfaction risk. This study translated the Prenatal Body Image Questionnaire (PBIQ) into the Chinese version (PBIQ-C) to assess the body image of pregnant women and evaluated its reliability and validity.MethodsAn improved Brislin translation model was used for the translation. A panel of experts determined the content validity. A convenience sample of 429 pregnant women was chosen from three third-class hospitals in different regions of Fujian Province, China. Factor analysis, Pearson’s correlation, retest reliability, and Cronbach’s alpha were employed to evaluate structural validity and reliability.ResultsThe final PBIQ-C had five dimensions with 21 items. Exploratory factor analysis obtained a five-factor solution, which accounted for a total of 60.34%. Confirmatory factor analysis showed that the model fit of the five-factor model also reached a satisfactory model fit after modifying: The Comparative Fit Index was 0.93, and the Tucker-Lewis Index was 0.92; the Root Mean Square Error of Approximation was 0.079. The content validity index of the scale ranged from 0.63 ~ 1.00. The Cronbach’s alpha coefficient was 0.95 for the total scale, and the test–retest reliability was 0.80.ConclusionsThe findings indicated that the PBIQ-C is a valid and reliable instrument for assessing women’s body image during pregnancy, which helps in the early identification of body dissatisfaction during pregnancy and enables the early prevention of postpartum depression.

Development and validation of a prediction model for self-reported hypoglycemia risk in patients with type 2 diabetes: A longitudinal cohort study.

To develop and validate a simple prediction model for hypoglycemia risk in patients with type 2 diabetes. We prospectively analyzed the data of 1,303 subjects in a third-class hospital in Tianjin and followed up their hypoglycemia events at 3 and 6 months. The hypoglycemia risk prediction models for 3 and 6 months were developed and the model performance was evaluated. A total of 340 (28.4%) patients experienced hypoglycemia within 3 months and 462 (37.2%) within 6 months during the follow-up period. Age, central obesity, intensive insulin therapy, frequency of hypoglycemia in the past year, and hypoglycemia prevention education entered both model3month and model6month. The area under the receiver operating characteristic curve of model3month and model6month were 0.711 and 0.723, respectively. The Youden index was 0.315 and 0.361, while the sensitivities were 0.615 and 0.714, and the specificities were 0.717 and 0.631. The calibration curves showed that the models were similar to reality. The decision curves implied that the clinical net benefit of the model was clear. The study developed 3 and 6 month hypoglycemia risk prediction models for patients with type 2 diabetes. The discrimination and calibration of the two prediction models were good, and might help to improve clinical decision-making and guide patients to more reasonable self-care and hypoglycemia prevention at home.

Comparison of the performance of four screening tools for sarcopenia in patients with chronic liver disease

ObjectivesEarly identification of sarcopenia in patients with chronic liver disease is crucial for patient management and prevention of severe complications. We aimed to assess the effectiveness of Ishii score, Strength, Assistance with Walking, Rise from a Chair, Climb Stairs and Falls (SARC-F), SARC-F and Calf Circumference (SARC-CalF), and Mini Sarcopenia Risk Assessment-7 (MSRA-7) to screen sarcopenia in patients with chronic liver disease. MethodsThis prospective study included patients with chronic liver disease in the infectious department of a tertiary hospital in Sichuan, China. Ishii score, SARC-F, SARC-CalF, and MSRA-7 were used to screen for sarcopenia risk. Sarcopenia was diagnosed according to the Asian Myometriosis Working Group (AWGS) 2019, which was used as the gold standard to compare the performance of the four screening tools. We completed clinical registration on the Chinese Clinical Trial Registration website (ChiCTR2100043910). ResultsA total of 366 patients with chronic liver disease (22.4% women, mean age 48.96 ± 11.88 years) were evaluated. Based on the AWGS 2019 standard, the prevalence of sarcopenia in patients with chronic liver disease was 17.5%. Among all participants, receiver operating characteristic (ROC) produced an area under the curve (AUC) of 0.82 for Ishii score (sensitivity 85.94%, specificity 78.15%), 0.53 for SARC-F (sensitivity 6.25%, specificity 99.34%), 0.64 for SARC-CalF (sensitivity 45.31%, specificity 83.11%), and 0.55 for MSRA-7 (sensitivity 87.50%, specificity 22.85%). Based on AUC, decision curve analysis, and calibration curves, we concluded that Ishii score was the most accurate screening tool and was superior to the other tools. ConclusionsIshii score is more suitable for screening sarcopenia in patients with chronic liver disease than the SARC-F, SARC-CalF, and MSRA-7, based on the AWGS 2019 criteria. Nursing professionals can use Ishii score as a clinical tool to screen for sarcopenia in patients with chronic liver disease, providing an indication cue for the final diagnosis of sarcopenia, improving diagnostic efficiency, and enabling early identification and prevention of complications resulting from sarcopenia.

Comparison of LASSO and random forest models for predicting the risk of premature coronary artery disease

PurposeWith the change of lifestyle, the occurrence of coronary artery disease presents a younger trend, increasing the medical and economic burden on the family and society. To reduce the burden caused by this disease, this study applied LASSO Logistic Regression and Random Forest to establish a risk prediction model for premature coronary artery disease(PCAD) separately and compared the predictive performance of the two models.MethodsThe data are obtained from 1004 patients with coronary artery disease admitted to a third-class hospital in Liaoning Province from September 2019 to December 2021. The data from 797 patients were ultimately evaluated. The dataset of 797 patients was randomly divided into the training set (569 persons) and the validation set (228 persons) scale by 7:3. The risk prediction model was established and compared by LASSO Logistic and Random Forest.ResultThe two models in this study showed that hyperuricemia, chronic renal disease, carotid artery atherosclerosis were important predictors of premature coronary artery disease. A result of the AUC between the two models showed statistical difference (Z = 3.47, P < 0.05).ConclusionsRandom Forest has better prediction performance for PCAD and is suitable for clinical practice. It can provide an objective reference for the early screening and diagnosis of premature coronary artery disease, guide clinical decision-making and promote disease prevention.

Application of exponential smoothing method and SARIMA model in predicting the number of admissions in a third-class hospital in Zhejiang Province

ObjectiveTo establish the exponential smoothing prediction model and SARIMA model to predict the number of inpatients in a third-class hospital in Zhejiang Province, and evaluate the prediction effect of the two models, and select the best number prediction model.MethodsThe data of hospital admissions from January 2019 to September 2022 were selected to establish the exponential smoothing prediction model and the SARIMA model respectively. Then compare the fitting parameters of different models: R2_adjusted, R2, Root Mean Square Error (RMSE)、Mean Absolute Percentage Error (MAPE)、Mean Absolute Error(MAE) and standardized BIC to select the best model. Finally, the established model was used to predict the number of hospital admissions from October to December 2022, and the prediction effect of the average relative error judgment model was compared.ResultsThe best fitting exponential smoothing prediction model was Winters Addition model, whose R2_adjusted was 0.533, R2 was 0.817, MAPE was 6.133, MAE was 447.341. The best SARIMA model is SARIMA(2,2,2)(0,1,1)12 model, whose R2_adjusted is 0.449, R2 is 0.199, MAPE is 8.240, MAE is 718.965. The Winters addition model and SARIMA(2,2,2)(0,1,1)12 model were used to predict the number of hospital admissions in October-December 2022, respectively. The results showed that the average relative error was 0.038 and 0.015, respectively. The SARIMA(2,2,2)(0,1,1)12 model had a good prediction effect.ConclusionBoth models can better fit the number of admissions, and SARIMA model has better prediction effect.

Pain catastrophising in Chinese patients with breast cancer during postoperative chemotherapy: a qualitative study

ObjectiveTo investigate the pain catastrophising in patients with breast cancer during postoperative chemotherapy.MethodsObjective sampling method was used to select patients with breast cancer who underwent breast surgery and received chemotherapy...

Transhepatectomy combined with arterial chemoembolization and transcatheter arterial chemoembolization in the treatment of hepatocellular carcinoma: a clinical prognostic analysis

BackgroundThe prognosis of patients undergoing hepatectomy combined with transarterial chemoembolization (TACE) and TACE alone was examined in order to better understand the role of hepatectomy in the treatment of hepatocellular carcinoma (HCC). In this work, we also created a model and investigated the variables influencing overall survival (OS) in HCC patients.MethodsRetrospective analysis of 1083 patients who received TACE alone as the control group and 188 patients who received TACE after surgery in a total of 1271 HCC patients treated with LR + TACE or TACE at three third-class hospitals in China. It was done using the Propensity Score Matching (PSM) technique. The differences in OS between the two groups were compared, and OS-influencing factors were looked at. The main endpoint is overall survival. In this study, the COX regression model was used to establish the nomogram.ResultsThe median OS of the LR + TACE group was not attained after PSM. The median OS for the TACE group was 28.8 months (95% CI: 18.9–38.7). The median OS of the LR + TACE group was higher than that of the TACE group alone, indicating a significant difference between the two groups (χ2 = 16.75, P < 0.001). While it was not achieved in the LR + TACE group, the median OS for patients with lymph node metastases in the TACE group alone was 18.8 months. The two groups differed significantly from one another (χ2 = 4.105, P = 0.043). In patients with distant metastases, the median OS of the LR + TACE treatment group was not achieved, and the median OS of the TACE group alone was 12.0 months. The difference between the two groups was sizable (χ2 = 5.266, P = 0.022). The median OS for patients with PVTT following PSM was 30.1 months in the LR + TACE treatment group and 18.7 months in the TACE alone group, respectively. The two groups differed significantly from one another (χ2 = 5.178, P = 0.023); There was no discernible difference between the two groups in terms of median overall survival (OS), which was 30.1 months for patients with lymph node metastasis and 19.2 months for those without (P > 0.05); Regarding the median OS for patients with distant metastases, which was not achieved and 8.5 months, respectively, there was a significant difference between the two groups (χ2 = 5.759, P = 0.016). We created a new nomogram to predict 1-, 2-, and 3-year survival rates based on multiple independent predictors in COX multivariate analysis. The cohort's C-index is 0.705. The area under the curve (AUC value) for predicting 1-, 2-, and 3-year survival rates were shown by the subject operating characteristic (ROC) curve linked to the nomogram to be 0.730, 0.728, and 0.691, respectively.ConclusionsLR + TACE can increase OS, delay tumor recurrence, and improve prognosis in HCC patients when compared to TACE alone. Additionally, the nomogram we created does a good job of forecasting the 1-year survival rate of hepatocellular carcinoma.

Assessment and management of radiation-induced trismus in patients with nasopharyngeal carcinoma: a best practice implementation project.

Intensity-modulated radiotherapy (IMRT) is the most commonly used radiotherapy technology in oncology, which enables precise conformation of the radiation dose to the target volume and reduces the risk of radiation damage to the adjacent normal structures. Nevertheless, it is still inevitable for IMRT of head and neck cancer to cause radiation-related toxic and side effects, such as dry mouth, mucositis, oral dysarthria, taste disorder, osteonecrosis and trismus. Trismus is one of the most common late side effects caused by radiotherapy of nasopharyngeal carcinoma (NPC), which seriously impact the quality of life for patients with NPC. However, the current clinical assessment and management of trismus after radiotherapy for NPC are still imperfect. This best practice implementation project aimed to implement an evidence-based practice in assessing and managing trismus for NPC patients who underwent radiotherapy, thereby improving the compliance of clinical practice with the best evidence and the quality of life of patients with NPC. This is an evidence-based audit and feedback project implemented using a three-phase approach at a Third-Class hospital in China, following JBI's Practical Application of Clinical Evidence System (PACES) and GRiP evidence application. The first phase included a baseline audit with six evidence-based audit criteria based on the best available evidence. The second phase included analyzing the results of the baseline audit, identifying barriers to compliance with best practice principles, and developing and implementing strategies to address the barriers identified in the baseline audit. The third phase involved a follow-up audit carried out to assess the results of interventions implemented to improve practice. After evidence application, the compliance rate of audit criterion 1 increased from 0% at baseline audit to 70% at follow-up audit. The compliance rate of audit criterion 2 increased from 0 to 100%. The compliance rate of audit criterion 3 increased from 22 to 62%. The compliance rate of audit criterion 4 increased from 88 to 100%. The compliance rate of audit criterion 5 was 100% at baseline audit and follow-up audit. The compliance rate of audit criterion 6 increased from 0 to 55%. Implementation of the best evidence for the assessment and management of trismus of patients with NPC after radiotherapy is conducive to improving the compliance of clinical practice with the best evidence, standardizing clinical nursing practice, improving the quality of clinical nursing, and better preventing severe trismus in patients with NPC after radiotherapy.

The impact of psychological resilience on chronic patients’ depression during the dynamic Zero-COVID policy: the mediating role of stigma and the moderating role of sleep quality

ObjectiveChronic patients are experiencing depression caused by themselves or the surrounding environment, how to cope with the change of mentality and adjust the psychological stress response, especially under the background of the current dynamic Zero-COVID policy in China, is a problem worth further discussion. The researchers constructed a mediating regulation model to test the influence of psychological resilience on depression of chronic patients during dynamic Zero-COVID, as well as the mediating role of stigma and the moderating role of sleep.MethodFrom October 2021 to February 2022, this study used a multi-stage sampling method and random number table method to collect data in the Shang Cheng District of Hangzhou City, Zhejiang Province. Firstly, the Second Affiliated Hospital of the Zhejiang University School of Medicine, a third-class hospital was randomly selected from the Shang Cheng District. Secondly, three departments were strategically selected from this hospital: endocrinology, dermatology, and traditional Chinese medicine. Thirdly, survey points were set up in each department, and chronic patients were strategically selected for questionnaire surveys. Finally, a face-to-face survey was conducted on 398 chronic patients who met the criteria for inclusion. In addition, chronic medical illness burden was assessed using the Cumulative Illness Rating Scale-Geriatrics (CIRS-G), psychological resilience was measured by the Conner-Davidson Resilience Scale (CD-RISC), stigma was measured by the Stigma Scale for Chronic Illness (SSCI), sleep was measured by the Pittsburgh Sleep Quality Index(PSQI) and depression was estimated by the Patient Health Questionaire-9(PHQ-9). SPSS (version 25.0) and PROCESS (version 4.0) were used for correlation analysis, mediation analysis, and mediated moderation analysis.ResultsPsychological resilience was negatively correlated with depression, stigma, and sleep. Depression was positively correlated with stigma and sleep. Stigma and sleep were positively correlated; Stigma played a mediating role in the relationship between psychological resilience and depression; Sleep moderated the first half of the pathway “psychological resilience to stigma to depression”.ConclusionPsychological resilience affected depression directly and indirectly through stigma. At the same time, sleep played a moderating role between psychological resilience and depression. The correlation between psychological resilience and stigma was stronger when levels of sleep levels were higher.

A Nationwide Survey on Detection of Chlamydia trachomatis in Health Facilities in China.

This study evaluated the clinical laboratory capacity for the diagnosis of Chlamydia trachomatis (CT) in China to provide recommendations to improve the diagnostic capacity and quality of this clinically important sexually transmitted disease. An electronic questionnaire-based cross-sectional, survey study was conducted by the National Center for STD Control among different types of healthcare facilities in China from July to December 2021. The surveyed laboratory facilities were located in 332 cities in 31 provinces in China. A total of 4640 records from clinical laboratories were included in the data set for the final analysis. Less than half of the laboratories (41.6% [1931 of 4640]) performed the CT diagnostic test; of these, 721 laboratories (15.5% [721 of 4640]) carried out nucleic acid amplification test (NAAT) methods, and 1318 laboratories (28.4% [1318 of 4640]) performed antigen-based immunochromatographic assays. Most laboratories were equipped with biological safety cabinets (93.7% [4348 of 4640]), 49.2% (2283 of 4640) were equipped with fully automated nucleic acid extractors, and 55.2% (2560 of 4640) were equipped with polymerase chain reaction amplification instruments. The laboratories from Southern China or third-class hospitals (i.e., the highest rated hospitals) had the highest proportion using NAATs to diagnose CT among the surveyed health facilities. Advancing laboratories to use NAAT to detect CT should be phased step-by-step by different areas and levels of hospitals according to the current situation.