Introduction: This study investigated the artificial intelligence (AI) readiness of newly qualified nurses and identified potential influencing factors. The technology acceptance model was extended by including perceived barriers to provide a comprehensive understanding of AI adoption in clinical practice.
Methods: This cross-sectional study was conducted across four tertiary grade A hospitals in Shandong Province in August and September 2022. Using convenience sampling, 329 newly qualified nurses with 1-3 years of clinical experience were surveyed. Data were collected using several instruments: a demographic characteristics questionnaire, the Readiness to Adopt AI in Nursing Practice Scale, the Perceived Usefulness in Nursing Practice Scale, the Perceived Ease of Use in Nursing Practice Scale, and the Perceived Barriers to Accessing AI Technology Scale. Data analysis, including descriptive statistics, correlation analysis, and multiple linear regression, was performed using SPSS 27.0.
Results: Newly qualified nurses' AI readiness was moderate (M = 9.85, SD = 1.97). Multiple linear regression identified three significant factors associated with AI readiness: perceived ease of use (β = 0.211, p = 0.006), prior AI training (β = 0.23, p < 0.001), and awareness of AI in nursing practice (β = 0.201, p = 0.018). Although perceived barriers did not significantly predict readiness in regression analysis, they were widely prevalent in clinical practice, with a lack of AI knowledge and limited computer skills reported as common obstacles.
Discussion: The readiness of newly qualified nurses for AI is influenced by multiple factors. Awareness of AI plays a crucial role, in addition to perceived ease of use and prior AI training. Although perceived barriers did not show a significant relationship with readiness, practical challenges, such as knowledge gaps and limited computer skills, require attention. Enhancing AI training, improving system usability, and ensuring adequate time and resource support are essential to strengthen AI application capabilities among newly qualified nurses.
Background: The co-infection of Clostridium innocuum and Eggerthella lenta in bloodstream is uncommon. The choice of clinical drugs with which to treat such co-infection is limited, which is worthy of study.
Case presentation: A 58-year-old male patient was admitted to the Department of General Surgery of Huashan Hospital on May, for further treatment after chemotherapy for liver metastases from rectal cancer. Laparoscopic anterior rectal resection under general anesthesia, laparoscopic sigmoid-rectal anastomosis, laparoscopic mesenteric lymphadenectomy, laparoscopic temporary ileostomy, and segmentectomy were performed. On the 3rd day after surgery, the patient developed a fever with body temperature up to 38 °C accompanied by cough and yellow sputum. Chest CT showed possible bilateral lung inflammation and metastases. Empirical anti-infection and symptomatic and supportive treatment were given. The patient still had a fever, with a body temperature of up to 40.6 °C, accompanied by fear of cold and chills, abdominal pain and abdominal distension on physical examination, abdominal wound non-healing, visible purulent secretions, and increased C-reactive protein, procalcitonin, and other inflammatory indicators. Aerobic and anaerobic blood culture tests were performed. The anaerobic blood culture bottle was positive after incubation in the automatic incubator for 20 h. After 24 h of anaerobic subculture on blood plate. C. innocuum was identified by matter-assisted laser desorption/ionization time of Flight (MALDI-TOF) mass spectrometry. After anaerobic culture time was extended to 72 h, another small slow-growing colony was observed, and E. lenta was identified. The patient's postoperative history of rectal cancer showed the possibility of intestinal colonizing bacteria invading the bloodstream and causing infection. According to pieces of literature and drug sensitivity tests in our center, vancomycin 1 g + piperacillin / tazobactam 4.5 g were administered every 12 h for anti-infection for 7 days. The patient's fever peak decreased, and blood culture turned negative after reexamination, thus the treatment was considered to be effective. Because the patient also had an abdominal infection and lung infection, antibiotic therapy with cefoperazone sulbactam and levofloxacin was continued for 9 days, and the patient had no further fever and was discharged with improved condition.
Conclusion: Clostridium innocuum and E. lenta can cause bloodstream infection after colorectal surgery, and the above two rare anaerobic bacteria can be rapidly and economically identified by MALDI-TOF mass spectrometry. C. innocuum, and E. lenta isolated from bloodstream infections following colorectal surgery should be considered as pathogens and treated promptly and appropriately.
Objective: Ulcerative colitis (UC), a chronic inflammatory bowel disease marked by recurrent flares and remissions, often necessitates repeated hospitalization owing to disease variability. However, commonly used risk-scoring systems have limited predictive accuracy for hospital readmission. This study aimed to develop and validate a machine learning (ML)-based model to predict the risk of unplanned readmission within 1 year in patients with UC.
Methods: Unplanned readmission within 1 year was defined as an endpoint event, and a predictive model was developed using a retrospective cohort (n = 324) and externally validated using an independent prospective cohort (n = 137). Demographic characteristics, medical history, medication use, clinical symptoms, laboratory findings, and endoscopic data were integrated as input variables. The optimal feature subset was selected using Recursive Feature Elimination (RFE), and eight ML models were constructed. All models were optimized via five-fold cross-validation, and the best-performing model was selected as the final predictive tool and was subjected to external validation. Shapley additive explanation plots were used to interpret the predictive model.
Results: The RFE algorithm identified five critical predictors: C-reactive protein, erythrocyte sedimentation rate, red blood cell count, increased frequency of bowel movements, and platelet count. All ML models achieved an AUC above 0.75 in the training cohort, demonstrating their robust predictive capability. The random forest (RF) model consistently outperformed the others across the training, internal validation, and external validation cohorts, with AUCs of 0.936, 0.815, and 0.813, respectively, reflecting excellent stability and generalization. Building upon the RF model, an online risk prediction platform was developed to estimate the probability of unplanned readmission in patients with UC.
Conclusion: The RF-based model showed strong predictive accuracy for assessing the 1-year risk of unplanned readmission in UC patients. The corresponding web-based risk calculator offers clinicians a valuable tool for personalized risk evaluation and enhanced patient management.
Background: The prognostic value of dynamic body mass index (BMI) changes during hospitalization in surgical intensive care unit (ICU) patients admitted emergently remains unclear. This study aimed to investigate the association between in-hospital BMI change and 28-day mortality in this high-risk population.
Methods: This retrospective cohort study utilized data from the eICU Collaborative Research Database (2014-2015). A total of 20,543 adult surgical ICU patients admitted via the emergency department (ED) were included. BMI change was calculated as discharge BMI minus admission BMI. Multivariable Cox regression, restricted cubic splines, and subgroup analyses were employed to evaluate the association between BMI change and mortality.
Results: The 28-day ICU mortality was 4.70%. BMI change exhibited a U-shaped, non-linear association with death: risk declined modestly as BMI rose toward the nadir of -1.75 kg/m2, then increased sharply thereafter. Each additional kg/m2 above this threshold raised mortality by 9% (HR 1.09, 95% CI 1.05-1.12, p < 0.0001). Patients in the highest BMI-gain quartile faced a 52% higher risk than those in the lowest quartile (HR 1.52, 95% CI 1.27-1.82, p < 0.0001). Dynamic BMI change outperformed static BMI or weight measures (AUC 57.9).
Conclusion: In-hospital BMI change is a significant predictor of 28-day mortality in surgical ICU patients admitted via the ED. A moderate reduction in BMI (-1.75 kg/m2) was associated with the lowest mortality risk. Dynamic BMI monitoring may enhance risk stratification and guide personalized fluid management in this population.
Ulcerative colitis (UC) is a chronic non-specific inflammatory disease, the pathogenesis is not clear, there is no clinical cure. The number of cases of UC has increased worldwide in recent years due to industrialization and social pressures. At present, the therapeutic effectiveness of UC remains controversial. Although researchers have conducted certain studies on the pathogenesis of UC, its pathogenesis and anti-UC pathogenesis have not been fully revealed. Previous studies have found a close relationship between human gut microbes and UC, and may be the most important measure of UC for clinical judgment. Many studies have linked UC to disruption of the gut microbiome, which is one of the most important features of UC. This paper reviews the clinical characteristics, pathogenesis and current treatment strategies of UC, and reviews the interaction between intestinal flora and UC as well as the therapeutic effects of intestinal flora, providing reference for the prevention and treatment of UC.
Background: Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive non-Hodgkin lymphoma (NHL), accounting for 30-40% of NHL cases. It exhibits high heterogeneity in gene expression and genetics, leading to significant variability in clinical treatment outcomes. Currently, various methods are available for predicting the prognosis of DLBCL patients, including the classic International Prognostic Index (IPI), as well as gene sequencing and circulating tumor DNA (ctDNA). However, some of these prognostic stratification methods are invasive and costly, limiting their widespread application. Therefore, there is an urgent need to identify potential prognostic indicators for lymphoma that can be widely used in the prognostic assessment of DLBCL patients, thereby further improving the stratification of DLBCL prognosis.
Objective: This study aims to determine the prognostic value of serum interleukin-2 receptor (IL-2R) and prognostic nutritional index (PNI) in patients diagnosed with diffuse large B-cell lymphoma (DLBCL), as well as their applicability across different DLBCL subtypes.
Methods: A retrospective analysis was conducted on 171 newly diagnosed DLBCL patients who received standard chemotherapy at Tongji Hospital in Shanghai from March 2013 to March 2024. Among them, 136 patients completed serum IL-2R testing. Spearman's correlation analysis was used to describe the associations between different categorical indicators. The optimal cutoff values were determined based on receiver operating characteristic (ROC) curves. Kaplan-Meier analysis and log-rank tests were employed to compare survival rates among different subgroups. Finally, univariate and multivariate Cox proportional hazards regression models were applied to identify factors influencing the prognosis of DLBCL patients.
Results: The baseline levels of IL-2R were correlated with patient age, nutritional status, and inflammatory response. PNI was associated with tumor burden in patients. Among the 136 patients, the cutoff value for IL-2R was 1,202 U/mL, while the cutoff value for PNI in the 171 patients was 44.65. Patients with high IL-2R and low PNI shared common characteristics, including advanced age, higher Ann Arbor stage, more frequent B symptoms, higher IPI scores, a higher proportion of intermediate-to-high-risk patients, poorer performance status, and shorter overall survival (OS) and progression-free survival (PFS). Multivariate analysis indicated that IL-2R > 1,202 U/mL and PNI ≤ 44.65 were independent risk factors for poor PFS and OS in newly diagnosed DLBCL patients.
Background: Intractable depression- and anxiety-like behaviors significantly contribute to methamphetamine (METH) abuse and relapse, which are linked to METH-induced neuroinflammation and impaired neural function. Fermented Gastrodia elata (FGE) is produced through a specific fermentation process. Previous studies have shown that its primary active components, including gamma-aminobutyric acid (GABA) and 4-hydroxybenzyl alcohol (4-HBA), exhibit notable anti-inflammatory and neuroprotective properties. However, the protective effects of FGE against METH-induced neuroinflammation in the brain and the underlying mechanisms remain incompletely understood.
Objective: This study aims to investigate the potential protective effects of FGE against METH-induced neuroinflammation in hippocampus neurons and its impact on anxiety- and depression-like behaviors in mice. Additionally, we seek to elucidate the underlying molecular mechanisms.
Methods: A mouse model of anxiety- and depression-like behaviors was established using METH induction. Pathological changes in hippocampus neurons were examined via H&E staining. The effects of FGE on these neurons were evaluated through pathological analysis. A series of behavioral tests were conducted to assess the impact of FGE on METH-induced depressive- and anxiety-like behaviors. To further investigate the molecular pathways underlying the neuroprotective effects of FGE, network pharmacology, ELISA, and RT-PCR were employed.
Results: The results demonstrated that METH effectively induced anxiety- and depression-like behaviors, which were associated with hippocampus neuroinflammation and neuropathology, along with significant activation of astrocytes and microglia. Intervention with FGE notably improved hippocampus pathology, reduced glial cell activation, and alleviated the associated anxiety- and depression-like behaviors. Furthermore, network pharmacology analysis suggested that the PI3K-AKT signaling pathway may contribute to the protective effects of FGE against METH-induced neuronal injury.
Conclusion: This study demonstrates that FGE, a potential natural agent, alleviates anxiety- and depression-like behaviors induced by METH through the reduction of neuroinflammation in the hippocampus. The protective effects of FGE against METH-induced neuronal damage and behavioral deficits are likely mediated by the PI3K-AKT signaling pathway. These findings suggest FGE as a promising therapeutic strategy for METH-related neurological disorders.
Introduction: Hemophilia A (HA) and hemophilia B (HB) are X-linked-bleeding disorders caused by deficiency of clotting factors VIII and IX, while von Willebrand disease (vWD) type 3 involves the lack of von Willebrand factor and FVIII. Chronic joint damage from recurrent bleeding is a serious complication.
Aim: The aim was to investigate the association of prophylactical treatment, severity of the disease and joint outcome.
Methods: In this retrospective, single-center study we evaluated joint health in 41 patients with HA, HB, and vWD type 3 who visited our outpatient clinic since 2000 using Magnetic resonance imaging (MRI) and applied the International Prophylaxis Study Group (IPSG) score. A total of 246 MRI images (knees, elbows, ankles) were analyzed in relation to disease severity, genetics, inhibitor-formation, and therapy.
Results: Of 41 patients, 28 (68%) had severe HA or HB, 10 (24%) moderate, one (2%) mild, and two (5%) were vWD patients. 19 patients with severe HA/HB received primary prophylaxis. Inhibitors developed in 7 patients (17%), most of them had loss-of-function mutations. We observed hemophilic arthropathy in 7/39 (18%) hemophilia patients (all with severe HA/HB). Only one of the 19 patients receiving early prophylaxis developed arthropathy, in the context of inhibitor development. Minor changes (IPSG score 1-5) were observed in 20% of joints while 74% of joints showed no alterations (IPSG score 0). Only 6% of joints showed hemophilic arthropathy (IPSG score ≥ 8) with ankle joints most frequently affected (10%). Among vWD-patients, one exhibited minor changes; the other had no detectable joint damage despite vWF-inhibitor presence.
Discussion: This study shows that the IPSG score is a suitable tool for assessing joint health in patients with hemophilia and vWD. Reduced joint damage was associated with early diagnosis, consistent prophylaxis, and therapy adherence.
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