OBJECTIVE To provide references for the accurate identification and management of immune-related cutaneous adverse events （irCAEs） caused by durvalumab， and ensuring safe clinical drug use. METHODS Clinical pharmacists participated in the diagnosis and treatment process of a patient with gallbladder cancer who developed irCAEs caused by durvalumab. The clinical pharmacists systematically reviewed the patient’s past medical history and medication history， and assisted physicians in assessing the association between adverse drug reactions and administered drugs. Meanwhile， the clinical pharmacists conducted a graded assessment of the adverse reaction， proposed recommendations such as discontinuing durvalumab and adjusting the administration regimen of glucocorticoids， assisted physicians in restarting immunotherapy， and carried out medication education and other pharmaceutical care. RESULTS The occurrence of irCAEs in this patient was “highly likely” related to durvalumab and was classified as severe. The physicians adopted the clinical pharmacist’s opinion， and after symptomatic treatment， the patient’s skin symptoms improved， and discharged with medication. After the completion of glucocorticoid therapy for the patient， the physician restarted immunotherapy with tislelizumab， and no related adverse reactions occurred again in the patient. CONCLUSIONS Durvalumab can cause irCAEs such as severe skin maculopapular rash. In clinical practice， it is crucial to promptly identify and discontinue suspicious drugs， immediately implement effective symptomatic treatment measures， and actively resume immunotherapy to ensure the continuity and safety of the patient’s treatment.

Objective This study used The Cancer Genome Atlas (TCGA) database to investigate the methylation levels of PCDHGB7 in lung adenocarcinoma tissues and analyze its association with clinical pathological features of lung adenocarcinoma, and its prognostic predictive value. Methods Methylation data of PCDHGB7 from 473 lung adenocarcinoma tissues and 32 normal tissues in the TCGA database were derived and analyzed to assess between-group variance and determine the correlation of methylation levels with clinical pathological features and overall survival. Results PCDHGB7 exhibited significantly higher methylation levels in lung adenocarcinoma tissues than in normal tissues (P<0.001), demonstrating a strong discriminative ability for lung adenocarcinoma (AUC=0.926, P<0.001). The methylation level was strongly associated with gender (P=0.047) and T stage (P=0.013). The critical prognostic sites of PCDHGB7 were identified through univariate Cox regression analysis. We found significant differences in overall survival between patient groups with low or high methylation levels (P=0.0099). Conclusion PCDHGB7 shows significantly elevated methylation in lung adenocarcinoma, which correlates with tumor malignancy and possesses certain prognostic predictive potential.

ObjectiveTo investigate the prevalence rate of chronic non-communicable diseases （NCDs） and the association with quality of life in middle-aged and elderly patients with HIV/AIDS. MethodsThis cross-sectional study surveyed 432 patients with HIV/AIDS （aged≥45 years） in the Infectious Disease Center in Guangzhou Eighth People’s Hospital of Guangzhou Medical University， and 366 participants were included in the analysis after quality control. A questionnaire and the EuroQol 5-Dimensional 3-level version （EQ-5D-3L） were used to investigate NCDs and quality of life and Tobit regression model was used to estimate the association between chronic diseases and quality of life. ResultsAmong the 366 participants， 29（7.9%） had cardiovascular disease， 45（12.3%） had hypertension， 122（33.3%） had hyperglycemia， 151（41.3%）had hyperlipidemia，7（1.9%） had cancer， 17 （4.6%） had chronic kidney disease， 38 （10.4%） had chronic liver disease， 21（5.7%） had musculoskeletal disorders， and 253（69.1%） suffered from at least one type of chronic diseases. The median （lower and upper quartiles） of EQ-5D utility index was 1.000（0.964~1.000）. Multivariate Tobit regression results of the total population showed that cancer ［b_a=-0.08，95%CI （-0.15，-0.01），P=0.036］， chronic kidney disease ［b_a=-0.07， 95%CI （-0.12，-0.02），P=0.006］， musculoskeletal disease ［b_a=-0.09， 95%CI （-0.13， -0.05），P<0.001］， and ≥3 types of chronic diseases［b_a=-0.05， 95%CI（-0.08，-0.01），P=0.013］ were negatively correlated with EQ-5D utility index. The stratified analysis results of different CD4+T cell levels showed that hypertension ［b_a=-0.07， 95%CI （-0.12， -0.02）， P=0.007］， chronic kidney disease ［b_a=-0.10，95%CI （-0.18，-0.03）， P=0.006］， musculoskeletal disease ［b_a=-0.15， 95%CI （-0.22，-0.07）， P<0.001］ and ≥3 types of chronic diseases ［b_a=-0.09， 95%CI （-0.09， -0.01）， P<0.001］ were negatively correlated with EQ-5D utility index in the group with CD4≤500 （cells/μL）， whereas cancer［b_a=-0.11， 95%CI （-0.20，-0.01）， P=0.031］ was negatively correlated with EQ-5D utility index in the group with CD4＞500（cells/μL）. ConclusionsThe prevalence rate of chronic non-communicable diseases in middle-aged and elderly patients with HIV/AIDS is relatively high. The classification of NCDs such as cancer or chronic kidney disease or other chronic diseases and the numbers of NCDs categories are negatively correlated with quality of life. However，this association varies among patients with HIV/AIDS of different CD4+T cell levels. It is suggested that we should try to prevent and identify NCDs at an early stage， strengthen linkages and integration of health services for AIDS and chronic NCDs， and jointly manage and control AIDS with chronic diseases to improve the quality of life among people living with HIV/AIDS.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

ObjectiveTo explore the effectiveness of feedforward control mode on improving occupational burnout among operating room nurses through theoretical research and clinical practice， with a view to promoting their physical and mental health and enhancing the quality of surgical nursing. MethodsA total of 440 operating room nurses from different regions， scales， and nursing experiences in Shaanxi Province from November 2023 to December 2023 were randomly divided into an experimental group and a control group， with 220 nurses in each group. While the control group received routine intervention measures， the experimental group introduced a feedforward control mode based on the control group， with “emotional exhaustion，” “depersonalization，”and“personal achievement” as observation indicators. ResultsThe incidence of occupational burnout in the experimental group was 11.4%， while that in the control group was 20.0%. The experimental group showed a significantly lower incidence than the control group （P=0.013）. ConclusionThe feedforward control mode can significantly alleviate nurses’ sense of job burnout， promote the improvement of surgical nursing quality， as well as continuously improve the scientific rigor， advancement， and humanistic nature of nursing services， which is conducive to building a harmonious and efficient nursing team. The spirit of teamwork， reflected in mutual support， mutual trust， and joint efforts for surgical success and patient health， has become an important component of nurses’ professional ethics.

BACKGROUND: Metabolic-associated fatty liver disease (MAFLD) is the predominant form of chronic liver disease worldwide. This study was designed to investigate the proportion and characteristics of MAFLD within the general Chinese population and to identify the contributory risk factors for liver fibrosis among MAFLD individuals. METHODS: The participants were recruited from a cohort undergoing routine health evaluations at the Third Hospital of Hebei Medical University between May 2019 and March 2023. The diagnosis of MAFLD was based on the established clinical practice guidelines. The fibrosis-4 index score (FIB-4) was employed to evaluate hepatic fibrosis, with a FIB-4 score of ≥1.3 indicating significant fibrosis. Binary logistic regression analyses were used to determine risk factors associated with significant hepatic fibrosis in MAFLD. RESULTS: A total of 22,970 participants who underwent comprehensive medical examinations were included in the analysis. The overall proportion of MAFLD was 28.77% (6608/22,970), with 16.87% (1115/6608) of these patients showing significant fibrosis as assessed using FIB-4. Independent risk factors for significant liver fibrosis in MAFLD patients were male (odds ratio [OR] = 0.676, 95% confidence interval [CI]: 0.558-0.821), hepatitis B surface antigen (HBsAg) positivity (OR = 2.611, 95% CI: 1.557-4.379), body mass index ≥23.00 kg/m 2 (OR = 0.632, 95% CI: 0.470-0.851), blood pressure ≥130/85 mmHg (OR = 1.885, 95% CI: 1.564-2.272), and plasma glucose ≥5.6 mmol/L (OR = 1.815, 95% CI: 1.507-2.186) (all P <0.001). CONCLUSIONS The proportion of MAFLD in an urban Chinese population is 28.77%. About 16.87% of MAFLD patients presented with significant liver fibrosis. Independent risk factors for significant liver fibrosis in MAFLD patients should be noticed.
Humans ; Male ; Female ; Liver Cirrhosis/pathology* ; Middle Aged ; Risk Factors ; Adult ; Fatty Liver/pathology* ; Aged ; China/epidemiology* ; Logistic Models ; Urban Population ; East Asian People

OBJECTIVES: To evaluate the causal association between circulating levels of zinc, magnesium, and other minerals and autism spectrum disorder (ASD). METHODS: A two-sample Mendelian randomization (MR) analysis was performed using summary statistics from large-scale genome-wide association studies of European populations, including 18 382 ASD cases and 27 969 controls. Genetic data for iron, calcium, and magnesium were obtained from the UK Biobank, and data for zinc and selenium were sourced from an Australian-British cohort. A total of 351 genetic instrumental variables were selected. Causal inference was performed using inverse-variance weighting as the primary analysis method. Sensitivity analyses were performed by Cochran's Q test and MR-PRESSO global test to assess the robustness of the findings. RESULTS: No statistically significant causal effect was observed for circulating zinc, magnesium, calcium, selenium, or iron levels on ASD risk (all P>0.05). The odds ratios and 95% confidence intervals from the inverse-variance weighting analysis were 0.934 (0.869-1.003) for zinc, 1.315 (0.971-1.850) for magnesium, 1.055 (0.960-1.159) for calcium, 1.015 (0.953-1.080) for selenium, and 0.946 (0.687-1.303) for iron. Sensitivity analysis revealed significant heterogeneity in the causal association between circulating calcium and ASD (P=0.006), while the effect estimate remained stable after MR-PRESSO correction (P=0.487). The causal effect estimates for the remaining minerals demonstrated good robustness. CONCLUSIONS This study did not find significant evidence supporting a causal association between circulating zinc, magnesium, calcium, selenium, or iron levels and ASD risk, providing important clues for the etiology of ASD and precision nutritional interventions.
Humans ; Mendelian Randomization Analysis ; Autism Spectrum Disorder/genetics* ; Magnesium/blood* ; Zinc/blood* ; Minerals/blood* ; Genome-Wide Association Study ; Selenium/blood*