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Abstract Purpose To analyze the key factors influencing the psychological resilience of intensive care unit (ICU) nurses during the COVID-19 pandemic and put forward suggestions promoting resilience based on key improvement factors and clinical experience. Methods Data were collected from 35 ICU nurses in a hospital in Zhejiang Province, China, through a questionnaire survey conducted between January and February 2023. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was then used to construct and visualize the relationship structure between the factors. The DEMATEL-based Analytical Network Process (DANP) was applied to determine the influential weights of all factors. Finally, the key improvement factors were identified using importance-performance analysis (IPA). Results Based on the cause-effect impact network diagram (CEIND), it was concluded that (C 11), (C 22), and (C 32) are the key factors that promote the improvement of psychological resilience among ICU nurses. Additionally, these factors were the key factors that influence psychological resilience. The confidence levels of these results and the gap were 99.6% and 0.4%, respectively, which exceed the threshold value of 95%, indicating good stability. Finally, for the case hospitals, (C 13) was identified as the key improvement factor. Conclusions Hospital administrators should support ICU nurses in enhancing their psychological resilience during major epidemics by: (i) Providing training on comprehensive protective measures and nursing skills; (ii) Effectively managing the human resources of nurses in the hospital to reduce their workload; (iii) Increasing social and organizational support for nurses to alleviate anxiety caused by large-scale public health events and improve their psychological resilience.

Abstract Purpose To identify the key risk factors for venous thromboembolism (VTE) in urological inpatients based on the Caprini scale using an interpretable machine learning method. Methods VTE risk data of urological inpatients were obtained based on the Caprini scale in the case hospital. Based on the data, the Boruta method was used to further select the key variables from the 37 variables in the Caprini scale. Furthermore, decision rules corresponding to each risk level were generated using the rough set (RS) method. Finally, random forest (RF), support vector machine (SVM), and backpropagation artificial neural network (BPANN) were used to verify the data accuracy and were compared with the RS method. Results Following the screening, the key risk factors for VTE in urology were “(C 1) Age,” “(C 2) Minor Surgery planned,” “(C 3) Obesity (BMI > 25),” “(C 8) Varicose veins,” “(C 9) Sepsis ( 45 min),” “(C 19) Laparoscopic surgery (> 45 min),” “(C 20) Patient confined to bed (> 72 h),” “(C18) Malignancy (present or previous),” “(C 23) Central venous access,” “(C 31) History of DVT/PE,” “(C 32) Other congenital or acquired thrombophilia,” and “(C 34) Stroke ( 45 minutes),” and “(C 21) Malignancy (present or previous)” were the main factors influencing mid- and high-risk levels, and some suggestions on VTE prevention were indicated based on these three factors. The average accuracies of the RS, RF, SVM, and BPANN models were 79.5%, 87.9%, 92.6%, and 97.2%, respectively. In addition, BPANN had the highest accuracy, recall, F1-score, and precision. Conclusions The RS model achieved poorer accuracy than the other three common machine learning models. However, the RS model provides strong interpretability and allows for the identification of high-risk factors and decision rules influencing high-risk assessments of VTE in urology. This transparency is very important for clinicians in the risk assessment process.

Age-related macular degeneration (AMD) is a degenerative eye disease leading to central vision loss and is characterized by dysregulated autophagy of the retinal pigment epithelium (RPE) layer. Recent studies have suggested that rho-associated protein kinase (ROCK) inhibitors may enhance autophagy in neurodegenerative diseases and promote the survival of RPE cells. This study investigated the effect of ROCK inhibitors on autophagy gene expression and autophagic vacuole formation in a human RPE (ARPE-19) cell line. The highly selective and potent ROCK inhibitor Y-39983 enhanced the expression of autophagy genes in ARPE-19 cells and increased autophagic vacuole formation. A proteomic analysis using mass spectrometry was performed to further characterize the effects of ROCK inhibition at the protein level. Y-39983 downregulated thrombospondin-1 (THBS1), and suppression of THBS1 in ARPE-19 cells resulted in an increase in autophagic vacuole formation. Our data showed that ROCK inhibitor-induced autophagy was mediated by THBS1 downregulation. We identified ROCK and THBS1 as potential novel therapeutic targets in AMD.

Background: Cardiac surgery is associated with a substantial risk of major adverse events. Although carbon dioxide (CO2)-derived variables such as venous-to-arterial CO2 difference (ΔPCO2), and PCO2 gap to arterial–venous O2 content difference ratio (ΔPCO2/C(a−cv)O2) have been successfully used to predict the prognosis of non-cardiac surgery, their prognostic value after cardiopulmonary bypass (CPB) remains controversial. This hospital-based study explored the relationship between ΔPCO2, ΔPCO2/C(a−cv)O2 and organ dysfunction after CPB.Methods: We prospectively enrolled 114 intensive care unit patients after elective cardiac surgery with CPB. Patients were divided into the organ dysfunction group (OI) and non-organ dysfunction group (n-OI) depending on whether organ dysfunction occurred or not at 48 h after CPB. ΔPCO2 was defined as the difference between central venous and arterial CO2 partial pressure.Results: The OI group has 37 (32.5%) patients, 27 of which (23.7%) had one organ dysfunction and 10 (8.8%) had two or more organ dysfunctions. No statistical significance was found (P = 0.84) for ΔPCO2 in the n-OI group at intensive care unit (ICU) admission (9.0, 7.0–11.0 mmHg), and at 4 (9.0, 7.0–11.0 mmHg), 8 (9.0, 7.0–11.0 mmHg), and 12 h post admission (9.0, 7.0–11.0 mmHg). In the OI group, ΔPCO2 also showed the same trend [ICU admission (9.0, 8.0–12.8 mmHg) and 4 (10.0, 7.0–11.0 mmHg), 8 (10.0, 8.5–12.5 mmHg), and 12 h post admission (9.0, 7.3–11.0 mmHg), P = 0.37]. No statistical difference was found for ΔPCO2/C(a−cv)O2 in the n-OI group (P = 0.46) and OI group (P = 0.39). No difference was detected in ΔPCO2, ΔPCO2/C(a−cv)O2 between groups during the first 12 h after admission (P > 0.05). Subgroup analysis of the patients with two or more failing organs compared to the n-OI group showed that the predictive performance of lactate and Base excess (BE) improved, but not of ΔPCO2 and ΔPCO2/C(a−cv)O2. Regression analysis showed that the BE at 8 h after admission (odds ratio = 1.37, 95%CI: 1.08–1.74, P = 0.009) was a risk factor for organ dysfunction 48 h after CBP.Conclusion : ΔPCO2 and ΔPCO2/C(a−cv)O2 cannot be used as reliable indicators to predict the occurrence of organ dysfunction at 48 h after CBP due to the pathophysiological process that occurs after CBP.

Objective: We investigated whether there were sex differences in adverse reactions to an inactivated SARS-CoV-2 vaccine among medical staff in China.Methods: From 24 February to 7 March 2021 an online cross-sectional survey was conducted with a self-administered COVID-19 vaccine questionnaire among medical staff in Taizhou, China. In total, 1397 interviewees (1,107 women and 290 men) participated in the survey.Results: In our study, 178 (16.1%) women and 23 (7.9%) men reported adverse reactions following their first vaccination, and 169 (15.3%) women and 35 (12.1%) men reported adverse reactions following their second vaccination. After adjusting for confounding factors, adverse reactions to other vaccines, worry about adverse reactions, knowledge of the inactivated vaccine being used in the hospital, taking the vaccine for one's family proactively and receiving an influenza vaccination were significantly related to adverse reactions to both injections in women. In contrast, in men, concerns about adverse reactions independently increased the risk of adverse reactions following either vaccination, and a history of adverse reactions to other vaccines also increased the risk of adverse reactions to both injections.Conclusions: Sex differences in the frequency of reported adverse reactions to an inactivated SARS-CoV-2 vaccine and potential factors were demonstrated in a sample of medical staff.

Abstract Objectives Host immune responses are indispensable to combat the disease. We report the dynamics of peripheral immune cells, cytokines, and human leucocyte antigen‐G (HLA‐G) and its receptor expressions in a patient suffering from critical COVID‐19 pneumonia to convalescence. Methods Clinical data of the patient were collected from medical records. The expressions of HLA‐G and receptors ILT2, ILT4 and KIR2DL4 in peripheral immune cells were measured with flow cytometry. Results From critical COVID‐19 to the convalescent stage, early lymphopenia was improved (median: 0.6 × 109 L−1 vs. 0.9 × 109 L−1, P = 0.009), and an obvious fluctuation in WBC and neutrophil counts was observed. Initially, low levels of CD4+ T cells (from 120 to 528 μL−1) and CD8+ T cells (from 68 to 362 μL−1) gradually increased to normal levels. Meanwhile, high IL‐6 (from 251.8 to 6.32 pg mL−1), IL‐10 (from 39.53 to 5.21 pg mL−1) and IFN‐γ (from 13.55 to 3.16 pg mL−1) levels decreased, and IL‐4 (from 2.36 to 3.19 pg mL−1) and TNF‐α (from 2.27 to 20.2 pg mL−1) levels increased quickly when the viral RNA returned negative. Moreover, the percentage of HLA‐G+ T cells, B cells and monocytes follows high–low–high pattern, while the percentage of receptors ILT2‐, ILT4‐ and KIR2DL4‐expressing cells remained relatively stable. Conclusion Our findings provide valuable information on the dynamics of early peripheral immunological responses in SARS‐CoV‐2 infection. CD4+ and CD8+ T cells, cytokines and HLA‐G+ immune cells are associated with the natural history of the critical COVID‐19 patient; however, future studies are necessary.