What has the appraisal for hospitals brought to job satisfaction of healthcare professionals? A cross-sectional survey in China.

OBJECTIVE: The purpose of this study is to evaluate the effectiveness of hospital appraisals, specifically the Performance Appraisal for Tertiary Public Hospitals (PATPH), and to examine its impact on the job satisfaction of healthcare professionals in tertiary public hospitals in China. DESIGN: A cross-sectional study using a multistage sampling method. Improvements induced by PATPH in the working environment, job satisfaction and other covariates were measured. A series of weighted linear regressions with weights from the inverse probability-of-treatment weighting method were used to examine the effect of PATPH on job satisfaction. SETTING: Nine tertiary public hospitals across three economic and geographic regions in China. PARTICIPANTS: In August 2020, a total of 13 211 hospital employees were surveyed, and 8417 doctors and nurses fully completed questionnaires forming the primary dataset for analysis. Of these respondents, males comprised 18.64% and doctors constituted 28.15%. RESULTS: This study revealed that PATPH had a positive impact on the job satisfaction of healthcare professionals. A 'more effective' PATPH working environment resulted in an improvement of 9.57 points (95% CI 8.99 to 10.16) in job satisfaction scores, controlling for all other variables. The finding persisted consistently through a series of sensitivity analyses. CONCLUSION: The findings offered insights and inspiration for improving the job satisfaction of healthcare professionals, especially in the development of macrolevel policies targeted towards organisational enhancement.

Ecological drivers of nesting behavior in a subtropical city: An observational study on spotted doves.

Due to rapid homogenization in habitat types as a result of urbanization, some urban birds adapt their nesting strategies to changes in local habitat characteristics. Bird nesting decisions might have been mainly linked to resource constraints and ensuring reproductive success. In this study, we examined patterns of nesting behavior by spotted doves (Spilopelia chinensis) in a rapidly urbanizing area of Nanchang, China using ArcGIS 10.8, satellite tracking, camera traps, and field survey. To explore the mechanisms underlying nesting behavior in urban habitats, we assessed the correlations between nest reuse and reproductive success, and between nest reuse and nest predation. From December 2018 to December 2021, a total of 302 breeding nests were surveyed. The results revealed that the nest reuse rate was 38.08% (n = 115). Nests closer to trunk, with lower nest position and higher large-scale urbanization score tended to have higher reuse rate. In addition, nests with the higher the nest height and percent of canopy cover, and the lower small-scale urbanization score were more likely to reproduce successfully, and the reused nests also reproduce more successfully. The reproductive success associated with nest reuse was significantly higher than that associated with new nests (χ 2 = 8.461, p = .004). High degree of urbanization promoted nest reuse of spotted doves (large-scale urbanization score, z = 2.094, p = .036), which apparently enhanced their reproductive success (nest reuse, z = 2.737, p = .006). In conclusion, a nest structure with good permeability is the material basis for the nest reuse in spotted dove, while the relatively low risk of predation in urban habitat and the scarcity of nest site resources due to urbanization increase the tendency of birds to reuse old nests, which is associated with their reproductive success and evolutionary fitness.

Assessing the Impact of an Artificial Intelligence-Based Model for Intracranial Aneurysm Detection in CT Angiography on Patient Diagnosis and Outcomes (IDEAL Study)-a protocol for a multicenter, double-blinded randomized controlled trial.

BACKGROUND: This multicenter, double-blinded, randomized controlled trial (RCT) aims to assess the impact of an artificial intelligence (AI)-based model on the efficacy of intracranial aneurysm detection in CT angiography (CTA) and its influence on patients' short-term and long-term outcomes. METHODS: Study design: Prospective, multicenter, double-blinded RCT. SETTINGS: The model was designed for the automatic detection of intracranial aneurysms from original CTA images. PARTICIPANTS: Adult inpatients and outpatients who are scheduled for head CTA scanning. Randomization groups: (1) Experimental Group: Head CTA interpreted by radiologists with the assistance of the True-AI-integrated intracranial aneurysm diagnosis strategy (True-AI arm). (2) Control Group: Head CTA interpreted by radiologists with the assistance of the Sham-AI-integrated intracranial aneurysm diagnosis strategy (Sham-AI arm). RANDOMIZATION: Block randomization, stratified by center, gender, and age group. PRIMARY OUTCOMES: Coprimary outcomes of superiority in patient-level sensitivity and noninferiority in specificity for the True-AI arm to the Sham-AI arm in intracranial aneurysms. SECONDARY OUTCOMES: Diagnostic performance for other intracranial lesions, detection rates, workload of CTA interpretation, resource utilization, treatment-related clinical events, aneurysm-related events, quality of life, and cost-effectiveness analysis. BLINDING: Study participants and participating radiologists will be blinded to the intervention. SAMPLE SIZE: Based on our pilot study, the patient-level sensitivity is assumed to be 0.65 for the Sham-AI arm and 0.75 for the True-AI arm, with specificities of 0.90 and 0.88, respectively. The prevalence of intracranial aneurysms for patients undergoing head CTA in the hospital is approximately 12%. To establish superiority in sensitivity and noninferiority in specificity with a margin of 5% using a one-sided α = 0.025 to ensure that the power of coprimary endpoint testing reached 0.80 and a 5% attrition rate, the sample size was determined to be 6450 in a 1:1 allocation to True-AI or Sham-AI arm. DISCUSSION: The study will determine the precise impact of the AI system on the detection performance for intracranial aneurysms in a double-blinded design and following the real-world effects on patients' short-term and long-term outcomes. TRIAL REGISTRATION: This trial has been registered with the NIH, U.S. National Library of Medicine at ClinicalTrials.gov, ID: NCT06118840 . Registered 11 November 2023.

Diagnostic and prognostic performance of artificial intelligence-based fully-automated on-site CT-FFR in patients with CAD.

Currently, clinically available coronary CT angiography (CCTA) derived fractional flow reserve (CT-FFR) is time-consuming and complex. We propose a novel artificial intelligence-based fully-automated, on-site CT-FFR technology, which combines the automated coronary plaque segmentation and luminal extraction model with reduced order 3 dimentional (3D) computational fluid dynamics. A total of 463 consecutive patients with 600 vessels from the updated China CT-FFR study in Cohort 1 undergoing both CCTA and invasive fractional flow reserve (FFR) within 90 d were collected for diagnostic performance evaluation. For Cohort 2, a total of 901 chronic coronary syndromes patients with index CT-FFR and clinical outcomes at 3-year follow-up were retrospectively analyzed. In Cohort 3, the association between index CT-FFR from triple-rule-out CTA and major adverse cardiac events in patients with acute chest pain from the emergency department was further evaluated. The diagnostic accuracy of this CT-FFR in Cohort 1 was 0.82 with an area under the curve of 0.82 on a per-patient level. Compared with the manually dependent CT-FFR techniques, the operation time of this technique was substantially shortened by 3 times and the number of clicks from about 60 to 1. This CT-FFR technique has a highly successful (> 99%) calculation rate and also provides superior prediction value for major adverse cardiac events than CCTA alone both in patients with chronic coronary syndromes and acute chest pain. Thus, the novel artificial intelligence-based fully automated, on-site CT-FFR technique can function as an objective and convenient tool for coronary stenosis functional evaluation in the real-world clinical setting.

Prophylactic Intra-abdominal Drainage is Associated With Lower Postoperative Complications in Patients With Crohn's Disease: A Randomized Controlled Trial.

BACKGROUND: Prophylactic intraoperative drains have been shown not superior for patients underwent intestinal surgery. However, for patients with Crohn's disease (CD), this needs further exploration. METHODS: In this pilot study, CD patients were randomly assigned to drain (n = 50) and no-drain (n = 50) groups. The primary endpoint was the rate of postoperative prolonged ileus (PPOI). The secondary endpoints were postoperative abdominal ascites, postoperative systemic inflammatory response syndrome (SIRS) and C-reactive protein (CRP) levels. RESULTS: The incidences of PPOI and postoperative abdominal ascites were significantly lower in the drain group (12% vs 44%; 0% vs 24%, both P < .05). Postoperative SIRS incidence and CRP levels were significantly increased in the no-drain group [36% vs 10%; 54.9 vs 34.3 mg/L, both P < .05]. In multivariate analysis, prophylactic drainage was the independent protective factor for PPOI and postoperative LOS. CONCLUSIONS: Prophylactic drainage may be associated with improved clinical outcomes in CD patients.

Azathioprine Plus Exclusive Enteral Nutrition Versus Azathioprine Monotherapy for the Prevention of Postoperative Recurrence in Patients with Crohn's Disease: An Open-Label, Single-Centre, Randomized Controlled Trial.

BACKGROUND: Azathioprine [AZA] effectively prevents postoperative endoscopic recurrence [ER] in Crohn's disease [CD]. However, the efficacy of AZA emerges after 3 months. Exclusive enteral nutrition [EEN] can maintain remission in CD. The present trial investigates whether AZA plus postoperative 3-month EEN is superior to AZA alone in preventing ER of CD. METHODS: In total, 84 high-risk CD patients undergoing intestinal resection received AZA alone or AZA plus 3 months of EEN [AZA + EEN] postoperatively. The primary endpoint was the rate of ER at 12 months. Secondary endpoints included the rate of ER at 3 months, clinical recurrence [CR], CD activity index [CDAI] scores, faecal calprotectin [FC], and C-reactive protein [CRP]. Quality of life was assessed using Short Form-36 [SF-36] and the Inflammatory Bowel Disease Questionnaire [IBDQ]. RESULTS: Patients in the AZA + EEN group exhibited significantly lower rates of ER compared to the AZA group at both 12 months (33.3% [13/39] vs 63.2% [24/38], P = 0.009) and 3 months (8.6% [3/35] vs 28.1% [9/32], P = 0.037) post-surgery. The rates of CR between the two groups at 3 and 12 months were similar. CDAI scores, FC, albumin level, and CRP were all comparable between the two groups. Quality of life was significantly higher in the AZA group than in the AZA + EEN group at 3 months but became comparable from 5 to 12 months postoperatively. CONCLUSION: In high-risk CD patients, combining AZA with postoperative 3-month EEN reduces 1-year ER but may temporarily impact quality of life. Further large-scale, long-term studies are warranted. TRIAL NUMBER: NCT05214430.

Mental health disparities between physicians and nurses: Analyzing the impact of occupational stress and work environment fitness using random forest algorithm.

BACKGROUND: The impact of occupational stress and work environment fitness on mental health disparities between physicians and nurses are not well understood. This study aims to identify and rank key determinants of mental health in physicians and nurses in China and compare the differences in their impact on mental health between physicians and nurses. METHODS: A large cross-sectional survey with multistage cluster sampling was conducted. The survey included the Self-Rating Anxiety Scale (SAS Scale), the Center for Epidemiologic Studies Depression Scale (CES-D Scale), the Maslach Burnout Inventory-General Survey (MBI-GS) and the Person-Environment (PE) Fit. We applied a principled, machine learning-based variable selection algorithm, using random forests, to identify and rank the determinants of the mental health in physicians and nurses. RESULTS: In our study, we analyzed a sample of 9964 healthcare workers, and 2729 (27 %) were physicians. The prevalence of anxiety and depressive disorders among physicians and nurses was 31.0 % and 53.3 %, 30.8 % and 47.9 %, respectively. Among physicians with anxiety disorder, we observed a higher likelihood of cynicism, emotional exhaustion, reduced personal accomplishment, and poor organization fitness, job fitness, group fitness, and supervisor fitness, in order of importance. When comparing the effects on depressive disorder in physicians, group fitness and supervisor fitness did not have significant impacts. For nurses, emotional exhaustion had a more significant effect on depressive disorder compared to cynicism. Supervisor fitness did not have a significant impact on anxiety disorder in nurses. LIMITATIONS: Cross-sectional design, self-reporting screening scales. CONCLUSIONS: Compared to individual and hospital characteristics, the primary factors influencing mental health disorders are occupational burnout and the compatibility of the work environment. Additionally, the key determinants of depressive and anxiety disorders among doctors and nurses exhibit slight variations. Employing machine learning methods proves beneficial for identifying determinants of mental health disorders among physicians and nurses in China. These findings could help improve policymaking aimed at addressing the mental well-being of healthcare professionals.

Structural dimerization and charge-orbital ordering in a ferromagnetic semiconductor LiV2S4 monolayer.

With the rise of two-dimensional (2D) materials, unique properties that are completely distinct from bulk counterparts continue to emerge at low-dimensional scales, presenting numerous opportunities and challenges. It also provides a new perspective for the study of transition metal systems. Here, based on density functional theory (DFT), the physical properties of 2D monolayer LiV2S4 have been studied. Remarkable changes have been observed, i.e., vanadium dimerization, ferromagnetism, charge distribution and metal-insulator transition (MIT). It is argued that the electronic instability leads to the V dimerization, which further lifts the degeneracy of charge distribution and stabilizes the charge and spin ordering state.

Health care costs of cardiovascular disease in China: a machine learning-based cross-sectional study.

Background: Cardiovascular disease (CVD) causes substantial financial burden to patients with the condition, their households, and the healthcare system in China. Health care costs for treating patients with CVD vary significantly, but little is known about the factors associated with the cost variation. This study aims to identify and rank key determinants of health care costs in patients with CVD in China and to assess their effects on health care costs. Methods: Data were from a survey of patients with CVD from 14 large tertiary grade-A general hospitals in S City, China, between 2018 and 2020. The survey included information on demographic characteristics, health conditions and comorbidities, medical service utilization, and health care costs. We used re-centered influence function regression to examine health care cost concentration, decomposing and estimating the effects of relevant factors on the distribution of costs. We also applied quantile regression forests-a machine learning approach-to identify the key factors for predicting the 10th (low), 50th (median), and 90th (high) quantiles of health care costs associated with CVD treatment. Results: Our sample included 28,213 patients with CVD. The 10th, 50th and 90th quantiles of health care cost for patients with CVD were 6,103 CNY, 18,105 CNY, and 98,637 CNY, respectively. Patients with high health care costs were more likely to be older, male, and have a longer length of hospital stay, more comorbidities, more complex medical procedures, and emergency admissions. Higher health care costs were also associated with specific CVD types such as cardiomyopathy, heart failure, and stroke. Conclusion: Machine learning methods are useful tools to identify determinants of health care costs for patients with CVD in China. Findings may help improve policymaking to alleviate the financial burden of CVD, particularly among patients with high health care costs.

Development and Validation of CCTA-based Radiomics Signature for Predicting Coronary Plaques With Rapid Progression.

BACKGROUND: Rapid plaque progression (RPP) is associated with a higher risk of acute coronary syndromes compared with gradual plaque progression. We aimed to develop and validate a coronary computed tomography angiography (CCTA)-based radiomics signature (RS) of plaques for predicting RPP. METHODS: A total of 214 patients who underwent serial CCTA examinations from 2 tertiary hospitals (development group, 137 patients with 164 lesions; validation group, 77 patients with 101 lesions) were retrospectively enrolled. Conventional CCTA-defined morphological parameters (eg, high-risk plaque characteristics and plaque burden) and radiomics features of plaques were analyzed. RPP was defined as an annual progression of plaque burden ≥1.0% on lesion-level at follow-up CCTA. RS was built to predict RPP using XGBoost method. RESULTS: RS significantly outperformed morphological parameters for predicting RPP in both the development group (area under the receiver operating characteristic curve, 0.82 versus 0.74; P=0.04) and validation group (area under the receiver operating characteristic curve, 0.81 versus 0.69; P=0.04). Multivariable analysis identified RS (odds ratio, 2.35 [95% CI, 1.32-4.46]; P=0.005) as an independent predictor of subsequent RPP in the validation group after adjustment of morphological confounders. Unlike unchanged RS in the non-RPP group, RS increased significantly in the RPP group at follow-up in the whole dataset (P<0.001). CONCLUSIONS: The proposed CCTA-based RS had a better discriminative value to identify plaques at risk of rapid progression compared with conventional morphological plaque parameters. These data suggest the promising utility of radiomics for predicting RPP in a low-risk group on CCTA.