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.

A Coronary CT Angiography Radiomics Model to Identify Vulnerable Plaque and Predict Cardiovascular Events.

Background A noninvasive coronary CT angiography (CCTA)-based radiomics technique may facilitate the identification of vulnerable plaques and patients at risk for future adverse events. Purpose To assess whether a CCTA-based radiomic signature (RS) of vulnerable plaques defined with intravascular US was associated with increased risk for future major adverse cardiac events (MACE). Materials and Methods In a retrospective study, an RS of vulnerable plaques was developed and validated using intravascular US as the reference standard. The RS development data set included patients first undergoing CCTA and then intravascular US within 3 months between June 2013 and December 2020 at one tertiary hospital. The development set was randomly assigned to training and validation sets at a 7:3 ratio. Diagnostic performance was assessed internally and externally from three tertiary hospitals using the area under the curve (AUC). The prognostic value of the RS for predicting MACE was evaluated in a prospective cohort with suspected coronary artery disease between April 2018 and March 2019. Multivariable Cox regression analysis was used to evaluate the RS and conventional anatomic plaque features (eg, segment involvement score) for predicting MACE. Results The RS development data set included 419 lesions from 225 patients (mean age, 64 years ± 10 [SD]; 68 men), while the prognostic cohort included 1020 lesions from 708 patients (mean age, 62 years ± 11; 498 men). Sixteen radiomic features, including two shape features and 14 textural features, were selected to build the RS. The RS yielded a moderate to good AUC in the training, validation, internal, and external test sets (AUC = 0.81, 0.75, 0.80, and 0.77, respectively). A high RS (≥1.07) was independently associated with MACE over a median 3-year follow-up (hazard ratio, 2.01; P = .005). Conclusion A coronary CT angiography-derived radiomic signature of coronary plaque enabled the detection of vulnerable plaques that were associated with increased risk for future adverse cardiac outcomes. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by De Cecco and van Assen in this issue.

Colorimetric and visual determination of iodide ions via morphology transition of gold nanobipyramids.

The gold nanobipyramids (Au NBPs) are widely used in the analytical detection of biochemistry due to their unique localized surface plasmon resonance (LSPR) properties. In our developed approach, I- in kelp was detected by etching Au NBPs in the presence of IO3-. Under acidic conditions, IO3- reacted rapidly with I- to form I2, subsequently I2 reacted with I- to form the intermediate I3-. In the presence of CTAB, Au NBPs were etched by I2 derived from I3-, resulting in a decrease in the aspect ratio of Au NBPs, to form a significant blue shift of LSPR longitudinal peak and color variation of colloid which changed from blue-green to magenta and could be employed to quantitatively detect the concentration of I- with the naked eye. A linear relationship can be found between the LSPR peak changes with the I- concentration in a wide range from 4.0 µM to 15.0 µM, and the sensitive limit of detection (LOD) was 0.2 µM for UV-vis spectroscopy and the obvious color changes with a visual LOD was 4.0 µM for the naked eye. Benefiting from the high specificity, the proposed colorimetric detection of I- in kelp samples was achieved, indicating the available potential of the colorimetric detection for the determination of I- in real samples. What's more, this detection procedure was time-saving and could avoid tedious procedures.

Coordinatized lesion location analysis empowering ROI-based radiomics diagnosis on brain gliomas.

OBJECTIVES: To assess the value of coordinatized lesion location analysis (CLLA), in empowering ROI-based imaging diagnosis of gliomas by improving accuracy and generalization performances. METHODS: In this retrospective study, pre-operative contrasted T1-weighted and T2-weighted MR images were obtained from patients with gliomas from three centers: Jinling Hospital, Tiantan Hospital, and the Cancer Genome Atlas Program. Based on CLLA and ROI-based radiomic analyses, a fusion location-radiomics model was constructed to predict tumor grades, isocitrate dehydrogenase (IDH) status, and overall survival (OS). An inter-site cross-validation strategy was used for assessing the performances of the fusion model on accuracy and generalization with the value of area under the curve (AUC) and delta accuracy (ACC) (ACCtesting-ACCtraining). Comparisons of diagnostic performances were performed between the fusion model and the other two models constructed with location and radiomics analysis using DeLong's test and Wilcoxon signed ranks test. RESULTS: A total of 679 patients (mean age, 50 years ± 14 [standard deviation]; 388 men) were enrolled. Based on tumor location probabilistic maps, fusion location-radiomics models (averaged AUC values of grade/IDH/OS: 0.756/0.748/0.768) showed the highest accuracy in contrast to radiomics models (0.731/0.686/0.716) and location models (0.706/0.712/0.740). Notably, fusion models ([median Delta ACC: - 0.125, interquartile range: 0.130]) demonstrated improved generalization than that of radiomics model ([- 0.200, 0.195], p = 0.018). CONCLUSIONS: CLLA could empower ROI-based radiomics diagnosis of gliomas by improving the accuracy and generalization of the models. CLINICAL RELEVANCE STATEMENT: This study proposed a coordinatized lesion location analysis for glioma diagnosis, which could improve the performances of the conventional ROI-based radiomics model in accuracy and generalization. KEY POINTS: • Using coordinatized lesion location analysis, we mapped anatomic distribution patterns of gliomas with specific pathological and clinical features and constructed glioma prediction models. • We integrated coordinatized lesion location analysis into ROI-based analysis of radiomics to propose new fusion location-radiomics models. • Fusion location-radiomics models, with the advantages of being less influenced by variabilities, improved accuracy, and generalization performances of ROI-based radiomics models on predicting the diagnosis of gliomas.

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.

Automated quantitative lesion water uptake in acute stroke is a predictor of malignant cerebral edema.

OBJECTIVES: Net water uptake (NWU) has been shown to have a linear relationship with brain edema. Based on an automated-Alberta Stroke Program Early Computed Tomography Score (ASPECTS) technique, we automatically derived NWU from baseline multimodal computed tomography (CT), namely ASPECTS-NWU. We aimed to determine if ASPECTS-NWU can predict the development of malignant cerebral edema (MCE). METHODS: One hundred and forty-six patients with large-vessel occlusion were retrospectively enrolled. Quantitative NWU based on automated-ASPECTS was measured both on nonenhanced CT (NECT) and CT angiography (CTA), namely NECT-ASPECT-NWU and CTA-ASPECTS-NWU. The correlation between ASPECTS-NWU and cerebral edema (CED) grades was calculated using Spearman rank correlation. Univariate logistic regression was used to assess the effect of radiological and clinical features on MCE, and a multivariable model with significant factors from the univariate regression analysis was built. Receiver operating characteristic (ROC) was obtained and area under curve (AUC) was compared. RESULTS: CTA-ASPECTS-NWU had a moderate positive correlation with CED grades (r = 0.62; 95% confidence interval [CI], 0.51-0.71; p < 0.001). The CTA-ASPECTS-NWU performed better than the NECT-ASPECTS-NWU with AUC: 0.88 vs. 0.71 (p < 0.001). Multivariable logistic regression model integrating CTA-ASPECTS-NWU, collateral score, and age showed the CTA-ASPECTS-NWU was an independent predictor of MCE with an AUC of 0.94 (95% CI: 0.90-0.98; p < 0.001). CONCLUSIONS: This study demonstrates that ASPECTS-NWU is a quantitative predictor of MCE after large-vessel occlusion of the middle cerebral artery territory. The multivariable logistic regression model may enhance the identification of patients with MCE needing anti-edematous treatment. KEY POINTS: • The automated-ASPECTS technique can automatically detect the affected regions with early ischemic changes and NWU could be manually calculated. • The CTA-ASPECTS-NWU performs better than the NECT-ASPECTS-NWU on predicting the development of MCE. • The multivariable logistic regression model may enhance the identification of patients with MCE needing anti-edematous treatment.

Development and validation of machine learning prediction model based on computed tomography angiography-derived hemodynamics for rupture status of intracranial aneurysms: a Chinese multicenter study.

OBJECTIVES: To build models based on conventional logistic regression (LR) and machine learning (ML) algorithms combining clinical, morphological, and hemodynamic information to predict individual rupture status of unruptured intracranial aneurysms (UIAs), afterwards tested in internal and external validation datasets. METHODS: Patients with intracranial aneurysms diagnosed by computed tomography angiography and confirmed by invasive cerebral angiograph or clipping surgery were included. The prediction models were developed based on clinical, aneurysm morphological, and hemodynamic parameters by conventional LR and ML methods. RESULTS: The training, internal validation, and external validation cohorts were composed of 807 patients, 200 patients, and 108 patients, respectively. The area under curves (AUCs) of conventional LR models 1 (clinical), 2 (clinical and aneurysm morphological), and 3 (clinical, aneurysm morphological and hemodynamic characteristics) were 0.608, 0.765, and 0.886, respectively (all p < 0.05). The AUCs of ML models using random forest (RF), multilayer perceptron (MLP), and support vector machine (SVM) were 0.871, 0.851, and 0.863, respectively. There were no difference among AUCs of conventional LR, RF, and SVM (all p > 0.05/6), while the AUC of MLP was lower than that of conventional LR (p = 0.0055). CONCLUSION: Hemodynamic parameters play an important role in the prediction performance of the models. ML methods cannot outperform conventional LR in prediction models for rupture status of UIAs integrating clinical, aneurysm morphological, and hemodynamic parameters. KEY POINTS: • The addition of hemodynamic parameters can improve prediction performance for rupture status of unruptured intracranial aneurysms. • Machine learning algorithms cannot outperform conventional logistic regression in prediction models for rupture status integrating clinical, aneurysm morphological, and hemodynamic parameters. • Models integrating clinical, aneurysm morphological, and hemodynamic parameters may help choose the optimal management.

A Highly Conductive MOF of Graphene Analogue Ni3 (HITP)2 as a Sulfur Host for High-Performance Lithium-Sulfur Batteries.

Lithium-sulfur (Li-S) batteries have been considered as one of the most promising energy storage systems owing to their high theoretical capacity and energy density. However, their commercial applications are obstructed by sluggish reaction kinetics and rapid capacity degradation mainly caused by polysulfide shuttling. Herein, the first attempt to utilize a highly conductive metal-organic framework (MOF) of Ni3 (HITP)2 graphene analogue as the sulfur host material to trap and transform polysulfides for high-performance Li-S batteries is made. Besides, the traditional conductive additive acetylene black is replaced by carbon nanotubes to construct matrix conduction networks for triggering the rate and cycling performance of the active cathode. As a result, the S@Ni3 (HITP)2 with sulfur content of 65.5 wt% shows excellent sulfur utilization, rate performance, and cyclic durability. It delivers a high initial capacity of 1302.9 mAh g-1 and good capacity retention of 848.9 mAh g-1 after 100 cycles at 0.2 C. Highly reversible discharge capacities of 807.4 and 629.6 mAh g-1 are obtained at 0.5 and 1 C for 150 and 300 cycles, respectively. Such kinds of pristine MOFs with high conductivity and abundant polar sites reveal broad promising prospect for application in the field of high-performance Li-S batteries.

Structural studies of G protein-coupled receptors.

G protein-coupled receptors (GPCRs) comprise the largest membrane protein family. These receptors sense a variety of signaling molecules, activate multiple intracellular signal pathways, and act as the targets of over 40% of marketed drugs. Recent progress on GPCR structural studies provides invaluable insights into the structure-function relationship of the GPCR superfamily, deepening our understanding about the molecular mechanisms of GPCR signal transduction. Here, we review recent breakthroughs on GPCR structure determination and the structural features of GPCRs, and take the structures of chemokine receptor CCR5 and purinergic receptors P2Y1 R and P2Y12 R as examples to discuss the importance of GPCR structures on functional studies and drug discovery. In addition, we discuss the prospect of GPCR structure-based drug discovery. © 2016 IUBMB Life, 68(11):894-903, 2016.

[MedDRA and its applications in statistical analysis of adverse events].

Safety assessment in clinical trials is dependent on an in-depth analysis of the adverse events to a great extent. However, there are difficulties in summary classification, data management and statistical analysis of the adverse events because of the different expressions on the same adverse events caused by regional, linguistic, ethnic, cultural and other differences. In order to ensure the normative expressions, it's necessary to standardize the terms in recording the adverse events. MedDRA (medical dictionary for regulatory activities) has been widely recommended and applied in the world as a powerful support for the adverse events reporting in clinical trials. In this paper, the development history, applicable scope, hierarchy structure, encoding term selection and standardized query strategies of the MedDRA is introduced. Furthermore, the practical process of adverse events encoding with MedDRA is proposed. Finally, the framework of statistical analysis about adverse events is discussed.

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.

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.

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.

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.

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.

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.

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.

Intercalation-induced amorphous hydrated vanadium oxide for boosted aqueous Zn2+ storage.

An amorphous hydrated vanadium oxide induced by Zn2+ intercalation in Mg-ion inserted V2O5·nH2O (MgVOH) is developed as a high-performance cathode for ZIBs. In particular, zinc pyrovanadate as the product of the second phase transition is found to suppress the dissolution issue of the vanadium species for the cathode to facilitate long lifespan.

Meta-analysis of the association between dietary inflammatory index and cognitive health.

Background: Some studies have shown that a pro-inflammatory diet may be associated with cognitive function, but their conclusions have varied considerably. We here present a meta-analysis of the current published literature on DII score and its association with cognitive health. Methods: In this meta-analysis, the PubMed, Embase, Web of Science, and Cochrane databases were searched in September 2022. The reported indexes, specifically OR, RR, and ß, were extracted and analyzed using R version 3.1.0. Results: A total of 636 studies in databases were identified, and 12 were included in the meta-analysis. Higher DII was associated with an increased risk of AD and MCI (OR = 1.34; 95% CI = 1.21-1.49). Meanwhile, it may also cause global function impairment (categorical: OR = 1.63; 95% CI = 1.36-1.96) and verbal fluency impairment (continuous: OR = 0.18; 95% IC = 0.08-0.42). But there was no significant association between DII and executive function (categorical: OR = 1.12; 95% IC = 0.84-1.49; continuous: OR = 0.48; 95% IC = 0.19-1.21) or episodic memory (continuous: OR = 0.56; 95% IC = 0.30-1.03). Conclusion: A pro-inflammatory diet is related to AD, MCI, and the functions of some cognitive domains (specifically global function and verbal fluency). However, the current evidence on the role of diet-induced inflammation in different cognitive domains should be supported by further studies in the future.

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.