Objective To study the five-year survival status and influencing factors of elderly patients with lung cancer complicated with chronic obstructive pulmonary disease (COPD). Methods A cohort study was conducted to follow up 450 patients with lung cancer and chronic obstructive pulmonary disease who were hospitalized in our hospital from January 2018 to December 2023. The endpoint of the follow-up was the end of a five-year period or death. The Life Tables method was used to calculate survival rates and plot survival curves. The Cox proportional hazards model was used to analyze the influencing factors of five-year survival. Results The results indicated that the overall five-year survival rate of patients was 4.89%, and it decreased year by year. Cox regression analysis showed that age, gender, family functioning, and psychological status significantly influenced patient survival rate (all P<0.05). Stratified analysis found that the smoking status, family functioning, and psychological status of male patients all had an impact on survival rate (all P<0.05), while the psychological status of female patients had a more significant impact on survival (P=0.008). Conclusion This study provides a scientific basis for comprehensive intervention of elderly lung cancer patients with COPD. It is recommended that clinical attention should be paid to psychological and family factors to improve patient prognosis.

Objective:To evaluate the relationship between nuclear receptor subfamily 1 group D member 1 (Rev-erbα) and ferroptosis in cardiomyocytes subjected to high-fat/high-glucose (HFHG) and hypoxia-reoxygenation (H/R) injury.Methods:H9c2 cardiomyocytes were cultured under normal conditions. The cells were divided into 4 groups ( n=13 each) using a random number table method: control group (C group), H/R group, HFHG group and HFHG+ H/R1 group. The cells were divided into 3 groups ( n=17 each) using a random number table method: HFHG+ H/R2 group, negative control siRNA + HFHG + H/R group (si-NC+ HFHG+ H/R group), and Rev-erbα gene knockdown + HFHG + H/R group (si-Rev-erbα+ HFHG+ H/R group). The cardiomyocyte model of HFHG combined with H/R injury was established by incubating cells with HFHG medium for 12 h, followed by 6 h of hypoxia and 2 h of reoxygenation. Rev-erbα gene was knocked down using siRNA technology. Cell viability was assessed using CCK-8 and Calcein AM/PI live-dead cell double staining kits. The expression of Rev-erbα, acyl-CoA synthetase long-chain family member 4 (ACSL4), and nuclear receptor coactivator 4 (NCOA4) was detected by Western blot. The levels of lipid peroxide (LPO) were measured by flow cytometry. Results:Compared with C group, the cell viability was significantly decreased, and the expression of Rev-erbα, ACSL4 and NCOA4 was up-regulated in HFHG, H/R and HFHG+ H/R1 groups( P<0.05). Compared with HFHG group or H/R group, the cell viability was significantly decreased, and the expression of Rev-erbα, ACSL4 and NCOA4 was up-regulated in HFHG+ H/R1 group ( P<0.05).There were no significant differences in the cell viability, levels of LPO, or expression of Rev-erbα, ACSL4 and NCOA4 between HFHG+ H/R2 group and si-NC+ HFHG+ H/R group ( P>0.05). Compared with HFHG+ H/R2 group, the cell viability was significantly increased, the levels of LPO were decreased, and the expression of Rev-erbα, ACSL4 and NCOA4 was down-regulated in si-Rev-erbα+ HFHG+ H/R group ( P<0.05). Conclusions:Rev-erbα participates in the process of HFHG and H/R injury to cardiomyocytes by negatively regulating ferroptosis.

Objective:To evaluate the relationship between nuclear receptor subfamily 1 group D member 1 (Rev-erbα) and ferroptosis in cardiomyocytes subjected to high-fat/high-glucose (HFHG) and hypoxia-reoxygenation (H/R) injury.Methods:H9c2 cardiomyocytes were cultured under normal conditions. The cells were divided into 4 groups ( n=13 each) using a random number table method: control group (C group), H/R group, HFHG group and HFHG+ H/R1 group. The cells were divided into 3 groups ( n=17 each) using a random number table method: HFHG+ H/R2 group, negative control siRNA + HFHG + H/R group (si-NC+ HFHG+ H/R group), and Rev-erbα gene knockdown + HFHG + H/R group (si-Rev-erbα+ HFHG+ H/R group). The cardiomyocyte model of HFHG combined with H/R injury was established by incubating cells with HFHG medium for 12 h, followed by 6 h of hypoxia and 2 h of reoxygenation. Rev-erbα gene was knocked down using siRNA technology. Cell viability was assessed using CCK-8 and Calcein AM/PI live-dead cell double staining kits. The expression of Rev-erbα, acyl-CoA synthetase long-chain family member 4 (ACSL4), and nuclear receptor coactivator 4 (NCOA4) was detected by Western blot. The levels of lipid peroxide (LPO) were measured by flow cytometry. Results:Compared with C group, the cell viability was significantly decreased, and the expression of Rev-erbα, ACSL4 and NCOA4 was up-regulated in HFHG, H/R and HFHG+ H/R1 groups( P<0.05). Compared with HFHG group or H/R group, the cell viability was significantly decreased, and the expression of Rev-erbα, ACSL4 and NCOA4 was up-regulated in HFHG+ H/R1 group ( P<0.05).There were no significant differences in the cell viability, levels of LPO, or expression of Rev-erbα, ACSL4 and NCOA4 between HFHG+ H/R2 group and si-NC+ HFHG+ H/R group ( P>0.05). Compared with HFHG+ H/R2 group, the cell viability was significantly increased, the levels of LPO were decreased, and the expression of Rev-erbα, ACSL4 and NCOA4 was down-regulated in si-Rev-erbα+ HFHG+ H/R group ( P<0.05). Conclusions:Rev-erbα participates in the process of HFHG and H/R injury to cardiomyocytes by negatively regulating ferroptosis.

Objective To identify key proteins associated with sudden cardiac death(SCD)caused by lethal arrhythmia and to explore their potential molecular mechanisms through integrated proteomic analysis,data mining,and bioinformatics.Methods A lethal arrhythmia model was established in 8-week-old male Sprague-Dawley rats,which were divided into an arrhythmia group and a control group.Proteomic techniques were applied to identify and quantify proteins in left ventricular myocardial tissue,and differentially expressed proteins related to arrhythmia were screened.Key proteins were further identified through comparison with target proteins in databases combined with joint analyses.Bioinformatics methods were then used to investigate potential molecular mechanisms.Results A total of 356 differentially expressed proteins were identified,including 189 upregulated and 167 downregulated.Association analysis with target gene proteins identified 71 key proteins,and a protein-protein interaction network was constructed.GO enrichment and KEGG pathway analyses indicated that these key proteins were primarily involved in ion channel dysfunction,enhanced oxidative stress,and autonomic nervous system imbalance.Conclusion This study,through the integration of proteomics,data mining,and bioinformatics,revealed critical molecular mechanisms underlying SCD associated with lethal arrhythmia.These findings provide new perspectives and potential biomarkers for forensic identification and research on the mechanisms of death.

BACKGROUND: Approximately 40% of individuals with diabetes worldwide are at risk of developing diabetic kidney disease (DKD), which is not only the leading cause of kidney failure, but also significantly increases the risk of cardiovascular disease, causing significant societal health and financial burdens. This study aimed to describe the burden of DKD and explore its cross-country epidemiological status, predict development trends, and assess its risk factors and sociodemographic transitions. METHODS: Based on the Global Burden of Diseases (GBD) Study 2021, data on DKD due to type 1 diabetes (DKD-T1DM) and type 2 diabetes (DKD-T2DM) were analyzed by sex, age, year, and location. Numbers and age-standardized rates were used to compare the disease burden between DKD-T1DM and DKD-T2DM among locations. Decomposition analysis was used to assess the potential drivers. Locally weighted scatter plot smoothing and Frontier analysis were used to estimate sociodemographic transitions of DKD disability-adjusted life years (DALYs). RESULTS: The DALYs due to DKD increased markedly from 1990 to 2021, with a 74.0% (from 2,227,518 to 3,875,628) and 173.6% (from 4,122,919 to 11,278,935) increase for DKD-T1DM and DKD-T2DM, respectively. In 2030, the estimated DALYs for DKD-T1DM surpassed 4.4 million, with that of DKD-T2DM exceeding 14.6 million. Notably, middle-sociodemographic index (SDI) quintile was responsible for the most significant DALYs. Decomposition analysis revealed that population growth and aging were major drivers for the increased DKD DALYs in most regions. Interestingly, the most pronounced effect of positive DALYs change from 1990 to 2021 was presented in high-SDI quintile, while in low-SDI quintile, DALYs for DKD-T1DM and DKD-T2DM presented a decreasing trend over the past years. Frontiers analysis revealed that there was a negative association between SDI quintiles and age-standardized DALY rates (ASDRs) in DKD-T1DM and DKD-T2DM. Countries with middle-SDI shouldered disproportionately high DKD burden. Kidney dysfunction (nearly 100.0% for DKD-T1DM and DKD-T2DM), high fasting plasma glucose (70.8% for DKD-T1DM and 87.4% for DKD-T2DM), and non-optimal temperatures (low and high, 5.0% for DKD-T1DM and 5.1% for DKD-T2DM) were common risk factors for age-standardized DALYs in T1DM-DKD and T2DM-DKD. There were other specific risk factors for DKD-T2DM such as high body mass index (38.2%), high systolic blood pressure (10.2%), dietary risks (17.8%), low physical activity (6.2%), lead exposure (1.2%), and other environmental risks. CONCLUSIONS DKD markedly increased and varied significantly across regions, contributing to a substantial disease burden, especially in middle-SDI countries. The rise in DKD is primarily driven by population growth, aging, and key risk factors such as high fasting plasma glucose and kidney dysfunction, with projections suggesting continued escalation of the burden by 2030.
Humans ; Global Burden of Disease ; Risk Factors ; Male ; Female ; Disability-Adjusted Life Years ; Diabetic Nephropathies/epidemiology* ; Middle Aged ; Diabetes Mellitus, Type 2/epidemiology* ; Adult ; Diabetes Mellitus, Type 1/complications* ; Aged ; Adolescent ; Young Adult ; Quality-Adjusted Life Years

BACKGROUND: While emotional distress, encompassing anxiety and depression, has been associated with negative clinical outcomes, its impact across various clinical departments and general hospitals has been less explored. Previous studies with limited sample sizes have examined the effectiveness of specific treatments (e.g., antidepressants) rather than a systemic management strategy for outcome improvement in non-psychiatric inpatients. To enhance the understanding of the importance of addressing mental health care needs among non-psychiatric patients in general hospitals, this study retrospectively investigated the impacts of emotional distress and the effects of early detection and management of depression and anxiety on hospital length of stay (LOS) and rate of long LOS (LLOS, i.e., LOS >30 days) in a large sample of non-psychiatric inpatients. METHODS: This retrospective cohort study included 487,871 inpatients from 20 non-psychiatric departments of a general hospital. They were divided, according to whether they underwent a novel strategy to manage emotional distress which deployed the Huaxi Emotional Distress Index (HEI) for brief screening with grading psychological services (BS-GPS), into BS-GPS ( n = 178,883) and non-BS-GPS ( n = 308,988) cohorts. The LOS and rate of LLOS between the BS-GPS and non-BS-GPS cohorts and between subcohorts with and without clinically significant anxiety and/or depression (CSAD, i.e., HEI score ≥11 on admission to the hospital) in the BS-GPS cohort were compared using univariable analyses, multilevel analyses, and/or propensity score-matched analyses, respectively. RESULTS: The detection rate of CSAD in the BS-GPS cohort varied from 2.64% (95% confidence interval [CI]: 2.49%-2.81%) to 20.50% (95% CI: 19.43%-21.62%) across the 20 departments, with a average rate of 5.36%. Significant differences were observed in both the LOS and LLOS rates between the subcohorts with CSAD (12.7 days, 535/9590) and without CSAD (9.5 days, 3800/169,293) and between the BS-GPS (9.6 days, 4335/178,883) and non-BS-GPS (10.8 days, 11,483/308,988) cohorts. These differences remained significant after controlling for confounders using propensity score-matched comparisons. A multilevel analysis indicated that BS-GPS was negatively associated with both LOS and LLOS after controlling for sociodemographics and the departments of patient discharge and remained negatively associated with LLOS after controlling additionally for the year of patient discharge. CONCLUSION Emotional distress significantly prolonged the LOS and increased the LLOS of non-psychiatric inpatients across most departments and general hospitals. These impacts were moderated by the implementation of BS-GPS. Thus, BS-GPS has the potential as an effective, resource-saving strategy for enhancing mental health care and optimizing medical resources in general hospitals.
Humans ; Retrospective Studies ; Male ; Length of Stay/statistics & numerical data* ; Female ; Middle Aged ; Adult ; Psychological Distress ; Inpatients/psychology* ; Aged ; Anxiety/diagnosis* ; Depression/diagnosis*

Objective This study aims to investigate the influence of multimedia technology and micro-lesson combined with case-based teaching on the nursing ability of radiation therapy intern nurses.Methods Sixty-four nursing interns from the radiation therapy department of our hospital between January 2022 and September 2024 were selected.They were randomly divid-ed into two groups,with 32 in each group.The control group received traditional mentoring,while the observation group received multimedia technology and micro-lesson combined with case-based teaching in addition to traditional mentoring.The teaching effects were compared between the two groups.Results The nursing competency level of the interns after performing tasks in the control group was significantly lower than that in the observation group,with statistical significance(P＜0.05).There was no statistically significant difference in the nursing competency level before task implementation between the two groups(P＞0.05).In terms of nursing quality,the control group had a significantly lower level than the observation group,with statistical signifi-cance(P＜0.05).There was no statistically significant difference in nursing quality before task implementation between the two groups(P＞0.05).When comparing the satisfaction level of the two groups of interns with the course teaching effect,the control group had a significantly lower satisfaction level than the observation group,with statistical significance(P＜0.05).Conclusion The use of multimedia technology and micro-lesson combined with case-based teaching can effectively improve the clinical nurs-ing ability of intern nurses.Therefore,this method is worth promoting and applying in clinical settings.

Objective:To investigate and validate the performance of a dosiomics model that utilized 3D dose distribution to forecast radiation-induced temporal lobe injury (RTLI) in nasopharyngeal carcinoma (NPC) patients following intensity-modulated radiotherapy (IMRT).Methods:Clinical data of 3578 patients diagnosed with NPC admitted to Jiangsu Cancer Hospital from January 2011 to December 2021 were retrospectively analyzed. According to the inclusion and exclusion criteria, 97 NPC patients who developed RTLI were assigned into the case group. A 1:1 propensity score matching (PSM) method was used to match 97 NPC patients without RTLI as the control group. Patients were assigned into the training cohort ( n=135) and the validation cohort ( n=59) at a 7:3 ratio by simple random method. Dosiomics features were extracted from the patients' three-dimensional dose distribution maps. Spearman rho and the least absolute shrinkage and selection operator regression were used to select dosiomics features. Clinical features were collected and screened by univariate and multivariate analyses. Eight machine learning classifiers were then trained to build dosiomics models and clinical models, respectively. The area under the ROC curve (AUC), sensitivity, and specificity were calculated to compare the predictive performance of the dosiomics and clinical models. Multivariate analysis was conducted using logistic regression to assess the influencing factors, while comparisons of the ROC curves between two different models were performed using the DeLong test. Results:A total of 1130 dosiomics features were extracted from the three-dimensional dose distribution maps, and 14 features were retained for model building after feature selection. The model based on the support vector machine (SVM) classifier achieved the highest AUC value of 0.977 (95% CI: 0.949-1.000) in the validation cohort, with an AUC of 1.000 (95% CI: 1.000-1.000) in the training cohort. By conducting univariate and multivariate analyses of the patients' clinical features, 2 clinical features were retained to build the clinical model. The model based on the SVM classifier achieved the optimal AUC value of 0.667 (95% CI: 0.523-0.810) in the validation cohort, with an AUC of 0.804 (95% CI: 0.730-0.878) in the training cohort. DeLong test showed that the difference between the dosiomics and clinical models was statistically significant ( P<0.05). Conclusion:The dosiomics model based on 3D dose distribution yields high predictive performance for RTLI in NPC patients after IMRT, which surpasses the clinical feature model, providing a new approach for early clinical prediction of RTLI.