Objective: After the end of COVID-19, medical staff were immediately faced with a high workload, leading to widespread occupational burnout. This study aims to explore the level and influencing factors of burnout among medical staff during this period, as well as its relationship with anxiety and depression.Methods: The participants’ levels of burnout were assessed using Maslach Burnout Inventory-Human Services Survey (MBI-HSS), and the reliability and validity of the questionnaire were evaluated through Cronbach’s α and Confirmatory Factor Analysis (CFA). Independent sample t-test, chi-square test, and Pearson analysis were employed to determine the correlation between two sets of variables. Univariate and multivariate logistic regression analyses were conducted to identify significant factors influencing burnout. Finally, nomograms were used to predict the probability of burnout occurrence.Results: This study collected a total of 1,550 questionnaires, and after excluding 45 questionnaires that were duplicates or incomplete, a sample of 1,505 (97.1%) participants were included in the final statistical analysis. Both Cronbach’s α and the fit indices of CFA demonstrated excellent adaptability of the Chinese version of MBI-HSS in this study. The overall prevalence rates for emotional exhaustion (EE), depersonalization (DP), and diminished personal accomplishment (PA) were 52.4, 55.3, and 30.6%, respectively. Obtaining psychological support, health condition, relationship with family members, and insufficient sleep were identified as common contributing factors to burnout among medical staff. Additionally, age and promotion pressure were also associated with burnout among doctors, and exceeding legal working hours was an important factor for nurse burnout. The C-index for the nomograms predicting burnout among doctors and nurses was 0.832 and 0.843, respectively. Furthermore, burnout exhibited a significant linear correlation with anxiety and depression.Conclusion: After the end of COVID-19, medical staff in high workload environments were facing severe burnout, which might lead to anxiety and depression. The occupational burnout of medical staff needed to be taken seriously and actively intervened.

Objective: This study aimed to investigate the prognostic significance of the Prognostic Nutritional Index (PNI) in conjunction with body composition change indices, namely subcutaneous fat area (SFA) and skeletal muscle index (SMI), with regard to clinical outcomes in patients with gastric cancer (GC) undergoing immune checkpoint inhibitors (ICIs) treatment.Methods: This retrospective investigation encompassed patients with comprehensive clinical and pathological data, inclusive of portal phase enhanced CT images. Continuous variables underwent analysis utilizing the Student t‐test or Mann–Whitney U‐test, while categorical variables were assessed employing the Pearson chi‐squared test or Fisher test. Survival outcomes were evaluated using Kaplan–Meier survival curves and the Log‐rank test. Independent prognostic indicators were determined through Cox regression analysis, and a nomogram predicting survival probability for progression‐free survival (PFS) and overall survival (OS) was constructed.Results: Within the PNI‐SFA groups, patients in Group 1 exhibited inferior PFS and OS compared to the other two groups. Similarly, among the PNI‐SMI groups, Group 1 patients demonstrated poorer PFS and OS. PNI‐SMI and Eosi were identified as independent prognostic factors through Cox regression analysis. Furthermore, positive associations with patient prognosis were observed for BMI, SAF, SMI, and PNI.Conclusion: The comprehensive consideration of PNI‐SFA and PNI‐SMI proved to be a superior prognostic predictor for GC patients undergoing ICI treatment.

(1) Background: The aim of this study was to explore the predictive ability of lymphocyte subsets for the prognosis of gastric cancer patients who underwent surgery and the prognostic value of CD19 (+) B cell combined with the Prognostic Nutritional Index (PNI). (2) Methods: This study involved 291 patients with gastric cancer who underwent surgery at our institution between January 2016 and December 2017. All patients had complete clinical data and peripheral lymphocyte subsets. Differences in clinical and pathological characteristics were examined using the Chi-square test or independent sample t-tests. The difference in survival was evaluated using Kaplan–Meier survival curves and the Log-rank test. Cox’s regression analysis was performed to identify independent prognostic indicators, and nomograms were used to predict survival probabilities. (3) Results: Patients were categorized into three groups based on their CD19 (+) B cell and PNI levels, with 56 cases in group one, 190 cases in group two, and 45 cases in group three. Patients in group one had a shorter progression-free survival (PFS) (HR = 0.444, p < 0.001) and overall survival (OS) (HR = 0.435, p < 0.001). CD19 (+) B cell–PNI had the highest area under the curve (AUC) compared with other indicators, and it was also identified as an independent prognostic factor. Moreover, CD3 (+) T cell, CD3 (+) CD8 (+) T cell, and CD3 (+) CD16 (+) CD56 (+) NK T cell were all negatively correlated with the prognosis, while CD19 (+) B cell was positively associated with the prognosis. The C-index and 95% confidence interval (CI) of nomograms for PFS and OS were 0.772 (0.752–0.833) and 0.773 (0.752–0.835), respectively. (4) Conclusions: Lymphocyte subsets including CD3 (+) T cell, CD3 (+) CD8 (+) T cell, CD3 (+) CD16 (+) CD56 (+) NK T cell, and CD19 (+) B cell were related to the clinical outcomes of patients with gastric cancer who underwent surgery. Additionally, PNI combined with CD19 (+) B cell had higher prognostic value and could be used to identify patients with a high risk of metastasis and recurrence after surgery.

Background: This study aimed to investigate the predictive capacity of lymphocyte subpopulations, sarcopenia and myosteatosis for clinical outcomes in patients who underwent gastric cancer surgery. Additionally, the prognostic significance of CD3+/CD4+ cells in conjunction with myosteatosis was explored.Methods: A cohort of 190 patients with gastric cancer who underwent surgery and received computed tomography scans between July 2016 and December 2017 at our institution was examined. Complete clinical information and peripheral lymphocyte subpopulations were available for all patients. A comprehensive array of statistical methodologies was employed to scrutinize variances in both clinical and pathological characteristics among patients, with the aim of identifying autonomous prognostic determinants requisite for the development of a nomogram. Subsequent assessment of the predictive efficacy of the nomogram was conducted via calibration curve analysis.Results: The study comprised a cohort of 190 participants, encompassing 126 males (66.32%) and 64 females (33.68%), with a mean age of 58.47 (±11.37) years. Patients were stratified into three groups based on CD3+/CD4+ cells and myosteatosis, with 24 in Group 1, 87 in Group 2 and 79 in Group 3. Notably, patients in the third group exhibited significantly shorter progression‐free survival (PFS) (hazard ratio [HR] = 0.208, P < 0.001) and overall survival (OS) (HR = 0.193, P < 0.001). The subset of peripheral blood lymphocytes exhibited elevated levels of CD3+/CD4+ cells (HR = 2.485, P < 0.001) and heightened CD4+/CD8+ ratios (HR = 1.705, P = 0.038), whereas diminished CD19+ cell counts (HR = 0.210, P = 0.032) correlated with improved OS in patients. The individuals presenting with sarcopenia (HR = 4.089, P = 0.023) and myosteatosis (HR = 2.857, P < 0.001) displayed reduced OS. The multivariate Cox regression analysis showed that pathological tumour–node–metastasis stage, CD19+ cells, sarcopenia and CD3+/CD4+ cell–myosteatosis were identified as independent prognostic factors for PFS and OS in patients. The constructed nomograms for PFS and OS yielded C‐index values of 0.839 (95% confidence interval [CI]: 0.798–0.880) and 0.836 (95% CI: 0.792–0.879), respectively. The calibration analysis demonstrated that the nomograms accurately predicted the 3‐ and 5‐year survival rates of PFS and OS in patients.Conclusions: Lymphocyte subsets, including CD3+/CD4+ cells, CD4+/CD8+ ratio and CD19+ cells, are indicative of clinical prognosis in gastric cancer surgery patients. Body composition parameters, such as sarcopenia and myosteatosis, are also associated with the patient's prognosis. The combination of CD3+/CD4+ cells with myosteatosis demonstrates enhanced prognostic value, enabling the identification of patients at high risk of post‐operative metastasis and recurrence.

(1) Background: This study aims to explore the predictive capability of the Gastric Cancer Immune Prognostic Score (GCIPS) for an unfavorable prognosis in gastric cancer patients undergoing immune checkpoint inhibitor (ICI) treatment. (2) Methods: This study included 302 gastric cancer patients who underwent treatment with ICIs at our institution from January 2017 to December 2022. The patients were randomly divided into a test set (201 cases) and a validation set (101 cases) using a random number table. Kaplan–Meier survival analysis and the log-rank test were used to investigate survival differences. Cox regression analysis and Lasso regression analysis were employed to establish the GCIPS and identify independent prognostic indicators. ROC curves, time–ROC curves, and nomograms were utilized to further explore the predictive performance of GCIPS. (3) Results: The test set and validation set showed no statistical differences in clinical and pathological features, as well as blood parameters (all p > 0.05). Cox regression analysis revealed that white blood cells (WBC), lymphocytes (LYM), and the international normalized ratio (INR) emerged as independent prognostic blood indicators after eliminating collinearity through Lasso analysis. The GCIPS was established using β coefficients with the following formula: GCIPS = WBC (10⁹/L) × 0.071 − LYM (10⁹/L) × 0.375 + INR × 2.986. ROC curves based on death and time–ROC curves demonstrated that the GCIPS had higher AUCs than other classical markers at most time points. Survival analyses of all subgroups also revealed a significant correlation between the GCIPS and patients’ progression-free survival (PFS) and overall survival (OS) (all p < 0.05). Furthermore, the GCIPS was identified as an independent prognostic factor for both PFS and OS. Analyses in the validation set further confirmed the reliability and stability of the GCIPS in predicting patient prognosis. Finally, nomograms incorporating the GCIPS exhibited high accuracy in both the test and validation sets. Additionally, the nomograms revealed that the GCIPS had a higher prognostic value than any other factor, including the TNM stage. (4) Conclusions: The GCIPS demonstrated its ability to predict adverse outcomes in gastric cancer patients undergoing ICIs treatment and had a high prognostic value. As a readily accessible and simple novel biomarker, it effectively identified high-risk patients.

Objective: The development and advance of gastric cancer are inextricably linked to oxidative and antioxidant imbalance. Although immunotherapy has been shown to be clinically effective, the link between oxidative stress and gastric cancer patients treated with immune checkpoint inhibitor (ICIs) remains unknown. This study aims at looking into the prognostic value of oxidative stress scores in gastric cancer patients treated with ICIs.Methods: By taking the propagation to receiver operating characteristic (ROC) we got the best cut-off values, and divided 265 patients receiving ICIs and chemotherapy into high and low GC-Integrated Oxidative Stress Score (GIOSS) groups. We also used Kaplan-Meier and COX regression models to investigate the relationship between oxidative stress biomarkers and prognosis.Results: Through both univariate and multivariate analyses, it’s shown that GIOSS severs as an independent prognostic factor for progression-free survival (PFS) and Overall survival (OS). Based on GIOSS cutoff values, patients with high GIOSS levels, compared to those with low levels exhibited shorter PFS and OS, both in the high GIOSS group, which performed poorly in the ICIs subgroup and other subgroup analyses.Conclusion: GIOSS is a biomarker that responds to systemic oxidative stress in the body and can predict prognosis in patients with gastric cancer who are taking ICIs. Additionally, it might come to medical professionals’ aid in making more effective or more suitable treatment plans for gastric cancer.