Search

This work studies the exhaustive rovibrational state-specific collision-induced dissociation properties of the N2+N system by QCT (quasi-classical trajectory) combined with a neural network method based on the ab initio PES recently published by Varga et al. [Phys. Chem. Chem. Phys. 23, 26273 (2021)]. The QCT combined with a neural network for state-specific dissociation (QCT–NN–SSD) model is developed and used to predict the dissociation cross sections and their energy dependence on the thermal range from a sparsely sampled noisy dataset. It is conservatively estimated that using this method can reduce the cost of the calculation by 96.5%. The rate coefficient of thermal non-equilibrium between different energy modes is obtained by combining the QCT–NN–SSD model with the multi-temperature model. The results show that, for the equilibrium state, dissociation mainly occurs at high vibrational and moderately low rotational levels. When the system is in non-equilibrium, there is no obvious vibrational level preference and highly rotationally excited molecules play a major role in promoting the dissociation by compensating for the lack of vibrational energy. The use of neural network training to generate complete datasets based on limited and discrete data provides an economical and reliable way to obtain a complete kinetic database needed to accurately simulate non-equilibrium flows. [ABSTRACT FROM AUTHOR]

In two recent papers [A. D. Becke, J. Chem. Phys. 156, 214101 (2022) and A. D. Becke, J. Chem. Phys. 157, 234102 (2022)], we compared two Kohn–Sham density functionals based on physical modeling and theory with the best density-functional power-series fits in the literature. The best error statistics reported to date for a hybrid functional on the general main-group thermochemistry, kinetics, and noncovalent interactions (GMTKN55) chemical database of Goerigk et al. [Phys. Chem. Chem. Phys. 19, 32184 (2017)] were obtained. In the present work, additional second-order perturbation-theory terms are considered. The result is a 12-parameter double-hybrid density functional with the lowest GMTKN55 WTMAD2 "weighted total mean absolute deviation" error (1.76 kcal/mol) yet seen for any hybrid or double-hybrid density-functional approximation. We call it "DH23." [ABSTRACT FROM AUTHOR]

The utilisation of DM (Data Mining) and ML (Machine Learning) approaches in the BC (Breast Cancer) diagnosis has recently gained a lot of consideration. However, most of these works still need enhancement since either they were assessed utilising insufficient evaluation-metrics, or they weren't statistically-assessed, or both. Lately, one-of-the-most effective and well-known ML approaches is OSELM (Online Sequential Extreme Learning Machine), it has seen as an efficient and reputable technique for classifying-data, however it has not been implemented in BC diagnosis problem. Consequently, this research proposes the OSELM approach in-order-to enhance the rate of accuracy for the BC diagnosis. The OSELM technique has the ability to (a) capability to be applied on both (multi-class and binary) classification, (b) prevent overfitting, as well as (c) It has a comparable ability to kernel-based SVM (Support Vector Machine) and operates with a neural-network-structure. In this research, two different BC datasets (WDBC (Wisconsin Diagnostic Breast Cancer) and WBCD (Wisconsin Breast Cancer Database)) were utilised to evaluate the OSELM approach performance. The experiments outcomes have revealed the outstanding-performance of the proposed OSELM approach, which attained an average of precision 94.09%, recall 95.57%, accuracy 96.13%, G-Mean 94.82%, F-Measure 94.80%, specificity 96.51%, and MCC 91.76% using WDBC dataset. Besides, attained an average of precision 95.08%, recall 98.89%, accuracy 97.89%, G-Mean 96.96%, F-Measure 96.93%, specificity 97.41%, and MCC 95.39% using WBCD dataset. This indicates that the OSELM approach is a reliable technique for the BC diagnosis and might be suitable for solving other-applications-related issues in the sector of healthcare. Besides, it can serve as a valuable decision-support tool for oncologists, providing additional information and insights to aid in their diagnoses and treatment plans. [ABSTRACT FROM AUTHOR]

All cometary nuclei that formed in the early Solar System incorporated radionuclides and therefore were subject to internal radiogenic heating. Previous work predicts that if comets have a pebble-pile structure internal temperature build-up is enhanced due to very low thermal conductivity, leading to internal differentiation. An internal thermal gradient causes widespread sublimation and migration of either ice condensates, or gases released from amorphous ice hosts during their crystallization. Overall, the models predict that the degree of differentiation and re-distribution of volatile species to a shallower near-surface layer depends primarily on nucleus size. Hence, we hypothesize that cometary activity should reveal a correlation between the abundance of volatile species and the size of the nucleus. To explore this hypothesis, we have conducted a thorough literature search for measurements of the composition and size of cometary nuclei, compiling these into a unified data base. We report a statistically significant correlation between the measured abundance of CO/H2O and the size of cometary nuclei. We further recover the measured slope of abundance as a function of size, using a theoretical model based on our previous thermophysical models, invoking re-entrapment of outward migrating high volatility gases in the near-surface pristine amorphous ice layers. This model replicates the observed trend and supports the theory of internal differentiation of cometary nuclei by early radiogenic heating. We make our data base available for future studies, and we advocate for collection of more measurements to allow more precise and statistically significant analyses to be conducted in the future. [ABSTRACT FROM AUTHOR]

Pulse‐like ground motion can cause extreme damage to long‐period structures. An automatic algorithm is proposed to identify pulse‐like ground motions, in which improved anomaly detection is applied and the structural performance is considered. To characterize the intrinsic pulse‐like features, the distance‐based anomaly detection algorithm is improved, and the relative cumulative energy is added to the Manhattan distance. The first application of the anomaly detection algorithm performs well in pulse‐like motion identification. The pulse‐like ground motions are identified according to the performance of typical long‐period engineering structures in Hazus by the improved capacity spectrum method. The method is applied to 214 strong ground motions in the Next Generation Attenuation West 2 database. Comprehensive comparisons of the proposed approach with the wavelet analysis and the energy method are presented to illustrate the significance of the structural performance on the pulse‐like identification method. [ABSTRACT FROM AUTHOR]

In this study, railway vehicle‐body vibration was applied to rail detection for convenient sensor deployment and cost‐effectiveness. However, the waveform is difficult to analyze due to damping and interference. Data‐driven methods can help concatenate multidimensional signals and complex rail‐surface irregularities but are impressionably uncertain. This study proposes a method in which a deep learning framework is coupled with heterogeneous factors at every link in its ensemble strategy. The instantiation, module foundation, and scenario description establish a concrete system for dealing with the dilemma that an insufficient database hinders feature extraction, causing unproductive capacity. The performance is quantitatively discussed by combining different levels of on‐site rail‐surface conditions, reaching prediction errors of 4.7% and 6.5% and classifier accuracies of 98.4% and 93.7% for irregularities and defect severities, respectively. This work describes a way to extend self‐learner applicability in industry and will facilitate new support for railway track management. [ABSTRACT FROM AUTHOR]

Forecasting an ongoing project's actual duration is an essential aspect of project management which received considerable attention in the research community. In studies using Earned Value Management forecasting, it has been argued that the network topology is a driver to indicate the accuracy of these forecasts. However, a new project indicator has been recently defined, i.e. the project regularity, which reflects the value accrue according to the plan. It has shown to outperform the serial/parallel network topology indicator in specifying the accuracy of project forecasts. This paper introduces a novel way to define the project regularity, which provides project managers with an improved indication of the expected forecasting accuracy for their projects. The study is carried out on an empirical database consisting of 100 projects from different sectors, and the results are compared to the academic literature. The experiments show that the new indicator provides a better categorisation compared to the existing approaches. Further, they have shown that the ability of project categorisers to indicate the expected forecasting accuracy is affected by industry sector and project size. [ABSTRACT FROM AUTHOR]

Study Design. Retrospective cohort study performed in a nationwide insurance claims database. Objective. To evaluate the duration and magnitude of post-operative opioid prescriptions after minimally invasive surgical sacroiliac joint fusion (MIS SIJF) as compared to other common spine surgeries. Summary of Background Data. MIS SIJF has been reported to significantly improve quality of life and reduce pain. However, there is a paucity of reported data on post-operative opioid use in patients undergoing MIS SIJF for sacroiliac joint dysfunction. Methods. A nationwide insurance claims database was queried to identify 4,666 patients who underwent MIS SIJF. Patients were stratified by pre-operative opioid use: Opioid naïve, sporadic use, or chronic use were respectively defined as 0,1, or ≥2 opioid prescriptions filled within 6 months prior to surgery. Duration of opioid use was defined by the time between MIS SIJF and last opioid prescription filled while magnitude of opioid use was determined by milligram morphine equivalents filled by 30 days post-operation. This opioid use data was compared to that of other common spine surgeries. Results. Patients undergoing MIS SIJF continued to fill opioid prescriptions 1-year post-operatively at significantly higher proportions than those undergoing other common spine procedures assessed by prior literature within each of the pre-operative opioid use cohorts (chronic: 73% vs. 49-62%; P<0.0001, sporadic: 39% vs. 23-28%; P<0.0001, opioid naïve: 22% vs. 15-18%; P<0.0001). Chronic users filled the highest opiate dosages during the 30-day postoperative period, filling on average 64.75 MME/d compared to 19.75 MME/d and 24.25 MME/d by the opioid naïve and sporadic users, respectively. Conclusion. After MIS SIJF, opioid naïve patients use fewer opioids and for a shorter period of time compared to patients with sporadic or chronic pre-operative opioid use. MIS SIJF may result in less effective pain reduction when compared to other common spine surgeries evaluated via identical methodology. [ABSTRACT FROM AUTHOR]

Objective. Provide benchmarks for the rates of complications by type and timing. Study Design. Prospective multicenter database. Background. Complication rates following adult spinal deformity (ASD) surgery have been previously reported. However, the interplay between timing and complication type warrants further analysis. Methods. The data for this study were sourced from a prospective, multicenter ASD database. The date and type of complication were collected and classified into three severity groups (minor, major, and major leading to reoperation). Only complications occurring before the two-year visit were retained for analysis. Results. Of the 1260 patients eligible for two-year follow-up, 997 (79.1%) achieved two-year follow-up. The overall complication rate was 67.4% (N=672). 247 patients (24.8%) experienced at least one complication on the day of surgery (including intraoperatively), 359 (36.0%) between postoperative day 1 and six weeks postoperatively, 271 (27.2%) between six weeks and one-year postoperatively, and finally 162 (16.3%) between one year and two years postoperatively. Using Kaplan-Meier survival analysis, the rate of remaining complication-free was estimated at different time points for different severities and types of complications. Stratification by type of complication demonstrated that most of the medical complications occurred within the first 60 days. Surgical complications presented over two distinct timeframes. Operative complications, incision-related complications, and infections occurred early (within 60 d), while implant-related and radiographic complications occurred at a constant rate over the two-year follow-up period. Neurological complications had the highest occurrence within the first 60 days but continued to increase up to the two-year visit. Conclusion. Only one-third of ASD patients remained complication- free by two years, and 2 of 10 patients had a complication requiring a reoperation or revision. An estimation of the timing and type of complications associated with surgical treatment may prove useful for more meaningful patient counseling and aid in assessing the cost-effectiveness of treatment. [ABSTRACT FROM AUTHOR]

Many studies have analyzed the association between family cohesion and depression, but there are different views and the results are inconsistent. It is necessary to use meta-analysis to explore the association between family cohesion and depression and its influencing factors. Chinese database (China National Knowledge Infrastructure) and English databases (ERIC, MEDLINE, Web of Science Core Collection, Elsevier SD, PsycINFO, PsycArticles, and ProQuest dissertations and theses) were searched for articles published by November 2023. Measurements of family cohesion and depression, study design, age, gender, cultural background, and sampling year were analyzed as moderators. Meta-analysis was performed using the random effects model in CMA3.0 software. A total of 71 studies (90,023 participants) were included in this study. The meta-analysis revealed a significant negative correlation between family cohesion and depression (r = −0.31, 95 % CI [−0.35, −0.27]). The association was moderated by measurements of family cohesion and depression, design type, and cultural background, but not by age, gender, or sampling year. The sample size included in this study is relatively small in European and African cultures, making it challenging to analyze cultural differences in the study results at present comprehensively. The findings contribute to the ongoing debate between Social Support Theory and The Circumplex Model, showing that individuals with lower family cohesion tend to experience higher levels of depression. • This meta-analysis found a high correlation between family cohesion and depression. • Measurement tools, cultural background, and design type can moderate this association. • This study clarified the debate on Social Support Theory and the Circumplex Model. [ABSTRACT FROM AUTHOR]

Summary: Background: The value of lower gastrointestinal endoscopy (LGIE; colonoscopy or sigmoidoscopy) relates to its ability to detect clinically relevant findings, predominantly cancers, preneoplastic polyps or inflammatory bowel disease. There are concerns that many LGIEs are performed on low‐risk patients with limited benefit. Aims: To determine the diagnostic outcomes of LGIE for common symptoms. Methods: We performed a cross‐sectional study of diagnostic LGIE between March 2019 and February 2020 using the UK National Endoscopy Database. We used mixed‐effects logistic regression models, incorporating random (endoscopist) and fixed (symptoms, patient age, and sex) effects upon two dependent variables (large polyp [≥10 mm] and cancer diagnosis). Adjusted positive predictive values (aPPVs) were calculated. Results: We analysed 384,510 LGIEs; 33.2% were performed on patients aged under 50 and 53.6% on women. Regarding colonoscopies, the unadjusted PPV for cancer was 1.5% (95% CI: 1.4–1.5); higher for men than women (1.9% vs. 1.1%, p < 0.01). The PPV for large polyps was 3.2% (95% CI: 3.1–3.2). The highest colonoscopy cancer aPPVs were in the over 50s (1.9%) and in those with rectal bleeding (2.5%) or anaemia (2.1%). Cancer aPPVs for other symptoms were <1% despite representing 54.3% of activity. In patients under 50, aPPVs were 0.4% for cancer and 1.6% for large polyps. Results were similar for sigmoidoscopy. Conclusions: Most colonoscopies were performed on patients with low‐risk symptoms, where cancer risk was similar to the general population. Cancer and large polyp yield was highest in elderly patients with rectal bleeding or anaemia, although still fell short of FIT‐based screening yields. [ABSTRACT FROM AUTHOR]

Background: Kawasaki disease (KD) is the most important acquired heart disease in children. This study investigated annual incidence, seasonality, secular trend and the correlation of KD incidence with viral activity in Taiwan. Methods: Through the national health insurance database, we identified KD during 2001–2020. The viral activity was obtained from nationwide surveillance database. We analyzed KD age-specific annual incidence, secular trends, seasonality and the correlation between KD incidence and common enteric or respiratory viral activity. Results: The KD incidence of subjects younger than 18 years significantly increased from 2001 to 2020 (11.78 and 22.40 per 100,000 person-years, respectively), and substantially decreased with age. Infants younger than 1 year presented the highest KD annual incidence at 105.82 to 164.34 per 100,000 person-years from 2001 to 2020. For all KD patients, the most frequently occurring season was summer followed by autumn. The KD incidence of infants younger than 1 year had significantly positive correlation with enteric (r = 0.14) and respiratory (r = 0.18) viral activity. Conclusions: This study demonstrates the increasing trend of KD annual incidence and seasonality (more in summer and autumn) in Taiwan. The activity of common respiratory and enteric viruses was significantly correlated with KD incidence in infants. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to conduct a bibliometric analysis of research articles on the relationship between inflammatory bowel disease (IBD) and colorectal cancer (CRC) using CiteSpace to summarize the current research status, hotspots, and trends in this field and present the results visually. Method: Research articles on the relationship between IBD and CRC published from 2000 to 2023 and in English were selected from the Web of Science Core Collection (Woscc) database. The articles were downloaded as "full record and references". CiteSpace was used to conduct cooperative, cluster, co-citation, and burst analyses. Results: The literature search revealed 4244 articles; of which, 5 duplicates were removed, resulting in the inclusion of 4239 articles in this study. The United States of America had the highest number of publications, with Mayo Clinic and Harvard University being the most active institutions, and Bas Oldenburg being the most active author. Collaboration among core authors was inadequate. JA Eaden was the most cited author, and CRC was the most common keyword. Burst analysis indicated that Sun Yat-sen University might be one of the institutions with a large contribution to this research field in the future. Cluster analysis showed that earlier research focused more on microsatellite instability, whereas "gut microbiota" and "oxidative stress" are considered current research hotspots and trends. Conclusion: At present, the primary focus areas of research are "gut microbiota" and "oxidative stress". With the improvement of healthcare policies and standards, regular endoscopic monitoring of patients with IBD has become an indispensable diagnostic and therapeutic practice. More drugs will be developed to reduce the risk of progression from IBD to CRC. The findings of this study provide valuable insights into the relationship between IBD and CRC for researchers in the same field. [ABSTRACT FROM AUTHOR]

Anthracyclines are associated with enhanced oxidative stress responsible for adverse events in patients with breast cancer. However, no study has investigated the potential anti-inflammatory role of statins in counteracting anthracycline toxicity. In this retrospective study utilizing a federated health network (TriNetX), patients with breast cancer (ICD code C50) treated with anthracyclines were categorized into two groups: statin users (for at least 6 months); and statin non-users. The primary outcome was the 5-year risk of all-cause death. Secondary outcomes were the risk of myocardial infarction, stroke, atrial fibrillation, ventricular arrhythmias, heart failure, and pulmonary embolism. Cox-regression analyses were used to produce hazard ratios (HRs) and 95% confidence intervals (CI) following 1:1 propensity score matching (PSM). We identified 3,701 statin users (68.8 ± 10.4 years) and 37,185 statin non-users (59.6 ± 12.8 years). After PSM, the 5-year risk of all-cause death was significantly lower in statin users (HR 0.82, 95% CI 0.74–0.91) compared to statins non-users. Analyzing the risk for secondary outcomes, only the risk of stroke was significantly increased in statin users (HR 1.27, 95% CI 1.01–1.61), while no associations were found for the other cardiovascular events. The risk of all-cause death in statin users was the lowest during the first year after the anthracycline's initiation. No significant difference was found between lipophilic and hydrophilic statins. In patients with breast cancer treated with anthracyclines, statin use is associated with a reduced risk of all-cause death. Prospective studies are needed to investigate the potential beneficial effect of statin initiation in cancer patients without other indications. [ABSTRACT FROM AUTHOR]

Marine nitrogen (N) fixation is a globally significant biogeochemical process carried out by a specialized group of prokaryotes (diazotrophs), yet our understanding of their ecology is constantly evolving. Although marine dinitrogen (N2)-fixation is often ascribed to cyanobacterial diazotrophs, indirect evidence suggests that non-cyanobacterial diazotrophs (NCDs) might also be important. One widely used approach for understanding diazotroph diversity and biogeography is polymerase chain reaction (PCR)-amplification of a portion of the nifH gene, which encodes a structural component of the N2-fixing enzyme complex, nitrogenase. An array of bioinformatic tools exists to process nifH amplicon data, however, the lack of standardized practices has hindered cross-study comparisons. This has led to a missed opportunity to more thoroughly assess diazotroph biogeography, diversity, and their potential contributions to the marine N cycle. To address these knowledge gaps a bioinformatic workflow was designed that standardizes the processing of nifH amplicon datasets originating from high-throughput sequencing (HTS). Multiple datasets are efficiently and consistently processed with a specialized DADA2 pipeline to identify amplicon sequence variants (ASVs). A series of customizable post-pipeline stages then detect and discard spurious nifH sequences and annotate the subsequent quality-filtered nifH ASVs using multiple reference databases and classification approaches. This newly developed workflow was used to reprocess nearly all publicly available nifH amplicon HTS datasets from marine studies, and to generate a comprehensive nifH ASV database containing 7909 ASVs aggregated from 21 studies that represent the diazotrophic populations in the global ocean. For each sample, the database includes physical and chemical metadata obtained from the Simons Collaborative Marine Atlas Project (CMAP). Here we demonstrate the utility of this database for revealing global biogeographical patterns of prominent diazotroph groups and highlight the influence of sea surface temperature. The workflow and nifH ASV database provide a robust framework for studying marine N2 fixation and diazotrophic diversity captured by nifH amplicon HTS. Future datasets that target understudied ocean regions can be added easily, and users can tune parameters and studies included for their specific focus. The workflow and database are available, respectively, in GitHub (https://github.com/jdmagasin/nifH-ASV-workflow ; Morando et al., 2024) and Figshare (https://doi.org/10.6084/m9.figshare.23795943.v1 ; Morando et al., 2024). [ABSTRACT FROM AUTHOR]

Background: Acute kidney injury (AKI) remains a common complication of coronary revascularization and increases poor outcomes in critically ill surgical patients. Compared to the plasma volume status (PVS), estimated plasma volume status (ePVS) has the advantages of being noninvasive and simple and has been shown to be associated with worse prognosis in patients undergoing coronary revascularization. This study was to evaluate the association of ePVS with the risk of AKI in patients who underwent coronary revascularization. Methods: In this retrospective cohort study, data of patients who underwent coronary revascularization were extracted from the Medical Information Mart for Intensive Care (MIMIC)-IV database (2008–2019). The outcome was the occurrence of AKI after ICU admission. The covariates were screened via the LASSO regression method. Univariate and multivariate Logistic regression models were performed to assess the association of ePVS and PVS and the odds of AKI in patients who underwent coronary revascularization, with results shown as odds ratios (ORs) and 95% confidence intervals (CIs). Subgroup analyses of age, surgery, and anticoagulation agents and sequential organ failure assessment (SOFA) score were performed to further explore the association of ePVS with AKI. Results: A total of 3,961 patients who underwent coronary revascularization were included in this study, of whom 2,863 (72.28%) had AKI. The high ePVS was associated with the higher odds of AKI in patients who received coronary revascularization (OR = 1.06, 95%CI: 1.02–1.10), after adjusting for the covariates such as age, race, SAPS-II score, SOFA score, CCI, weight, heart rate, WBC, RDW-CV, PT, BUN, glucose, calcium, PH, PaO2, mechanical ventilation, vasopressors, and diuretic. Similar results were found in patients who underwent the CABG (OR = 1.07, 95%CI: 1.02–1.11), without anticoagulation agents use (OR = 1.07, 95%CI: 1.03–1.12) and with high SOFA score (OR = 1.10, 95%CI: 1.04–1.17). No relationship was found between PVS and the odds of AKI in patients who underwent the coronary revascularization. Conclusion: The ePVS may be a promising parameter to evaluate the risk of AKI in patients undergoing coronary revascularization, which provides a certain reference for the risk stratification management of ICU patients who underwent coronary revascularization. [ABSTRACT FROM AUTHOR]

Background: Rebamipide has been widely co-prescribed with non-steroidal anti-inflammatory drugs (NSAIDs) in Japan for decades. This study aimed to evaluate the effectiveness of rebamipide in preventing upper gastrointestinal bleeding in new users of NSAIDs without risk factors of NSAID-induced ulcers other than age. Methods: A nested case-control study was conducted using medical claims data of 1.66 million inhabitants of 17 municipalities participating in Japan's Longevity Improvement & Fair Evidence study. The cohort entry (t0) corresponded to a new user of NSAIDs for osteoarthritis or low back pain. Patients with risk factors of NSAID-induced ulcers other than age were excluded. Cases were defined as patients who underwent gastroscopy for upper gastrointestinal bleeding (occurrence date was defined as index date). A maximum of 10 controls were selected from non-cases at the index date of each case by matching sex, age, follow-up time, and type and dosage of NSAIDs. Exposure to rebamipide was defined as prescription status from t0 to index date: Non-user (rebamipide was not co-prescribed during the follow-up period), Continuous-user (rebamipide was co-prescribed from t0 with the same number of tablets as NSAIDs), and Irregular-user (neither Non-user nor Continuous-user). Conditional logistic regression analysis was conducted to estimate each category's odds ratio compared to non-users. Findings: Of 67,561 individuals who met the inclusion criteria, 215 cases and 1,516 controls were selected. Compared with that of Non-users, the odds ratios and 95% confidence interval were 0.65 (0.44–0.96) for Continuous-users and 2.57 (1.73–3.81) for Irregular-users. Conclusions: Continuous co-prescription of rebamipide significantly reduced the risk of upper gastrointestinal bleeding in an Asian cohort of new users of NSAIDs with osteoarthritis or low back pain without risk factors other than age. [ABSTRACT FROM AUTHOR]

During the first year of the COVID-19 pandemic, the Republic of Korea (ROK) experienced three epidemic waves in February, August, and November 2020. These waves, combined with the overarching pandemic, significantly influenced trends in spinal surgery. This study aimed to investigate the trends in degenerative lumbar spinal surgery in ROK during the early COVID-19 pandemic, especially in relation to specific epidemic waves. Using the National Health Information Database in ROK, we identified all patients who underwent surgery for degenerative lumbar spinal diseases between January 1, 2019 and December 31, 2020. A joinpoint regression was used to assess temporal trends in spinal surgeries over the first year of the COVID-19 pandemic. The number of surgeries decreased following the first and second epidemic waves (p<0.01 and p = 0.34, respectively), but these were offset by compensatory increases later on (p<0.01 and p = 0.05, respectively). However, the third epidemic wave did not lead to a decrease in surgical volume, and the total number of surgeries remained comparable to the period before the pandemic. When compared to the pre-COVID-19 period, average LOH was reduced by 1 day during the COVID-19 period (p<0.01), while mean hospital costs increased significantly from 3,511 to 4,061 USD (p<0.01). Additionally, the transfer rate and the 30-day readmission rate significantly decreased (both p<0.01), while the reoperation rate remained stable (p = 0.36). Despite the impact of epidemic waves on monthly surgery numbers, a subsequent compensatory increase was observed, indicating that surgical care has adapted to the challenges of the pandemic. This adaptability, along with the stable total number of operations, highlights the potential for healthcare systems to continue elective spine surgery during public health crises with strategic resource allocation and patient triage. Policies should ensure that surgeries for degenerative spinal diseases, particularly those not requiring urgent care but crucial for patient quality of life, are not unnecessarily halted. [ABSTRACT FROM AUTHOR]

In recent years, spatial transcriptomics (ST) research has become a popular field of study and has shown great potential in medicine. However, there are few bibliometric analyses in this field. Thus, in this study, we aimed to find and analyze the frontiers and trends of this medical research field based on the available literature. A computerized search was applied to the WoSCC (Web of Science Core Collection) Database for literature published from 2006 to 2023. Complete records of all literature and cited references were extracted and screened. The bibliometric analysis and visualization were performed using CiteSpace, VOSviewer, Bibliometrix R Package software, and Scimago Graphica. A total of 1467 papers and reviews were included. The analysis revealed that the ST publication and citation results have shown a rapid upward trend over the last 3 years. Nature Communications and Nature were the most productive and most co-cited journals, respectively. In the comprehensive global collaborative network, the United States is the country with the most organizations and publications, followed closely by China and the United Kingdom. The author Joakim Lundeberg published the most cited paper, while Patrik L. Ståhl ranked first among co-cited authors. The hot topics in ST are tissue recognition, cancer, heterogeneity, immunotherapy, differentiation, and models. ST technologies have greatly contributed to in-depth research in medical fields such as oncology and neuroscience, opening up new possibilities for the diagnosis and treatment of diseases. Moreover, artificial intelligence and big data drive additional development in ST fields. Spatial transcriptomics (ST) technologies and application prospects. (1) Imaging-based approaches, including in situ sequencing (ISS)—where transcripts are amplified and sequenced in tissue—and ISH-based approaches—where imaging probes are sequentially hybridized in tissue. (2) NGS-based techniques, in which positional information is encoded onto transcripts prior to NGS sequencing. [ABSTRACT FROM AUTHOR]

Purpose: Frailty is a vulnerable state to stressors due to the loss of physiological reserve as a result of multisystem dysfunction. The physiological and laboratory-based frailty index (FI-Lab), depending on laboratory values and vital signs, is a powerful tool to capture frailty status. The aim of this study was to assess the relationship between FI-Lab and in-hospital mortality in patients with septic shock. Methods: Baseline data for patients with sepsis in the intensive care unit were retrieved from the Critical Care Medicine Database (MIMIC-IV, v2.2). The primary outcome was mortality during hospitalization. The propensity score matching (PSM) method was used to analyze the basic conditions during hospitalization between groups.The FI-Lab was analysed for its relationship with in-hospital mortality using logistic regression according to continuous and categorical variables, respectively, and described using the restricted cubic spline (RCS). Survival was compared between groups using Kaplan-Meier (KM) curves. Subgroup analyses were used to improve the stability of the results. Results: A total of 9219 patients were included. A cohort score of 1803 matched patients was generated after PSM. The analyses showed that non-surviving patients with septic shock in the ICU had a high FI-Lab index (P<0.001). FI-Lab, whether used as a continuous or categorical variable, increased with increasing FI-Lab and increased in-hospital mortality (P<0.001).Subgroup analyses showed similar results. RCS depicts this non-linear relationship. KM analysis shows the cumulative survival time during hospitalisation was significantly lower as FI-Lab increased (log-rank test, P<0.001). Conclusion: Elevated FI-Lab is associated with increased in-hospital mortality in patients with septic shock. [ABSTRACT FROM AUTHOR]

Background: Small bowel adenocarcinoma (SBA) is a rare gastrointestinal malignancy forwhich survival is hampered by late diagnosis, complex responses to treatment, and poor prognosis. Accurate prognostic tools are crucial for optimizing treatment strategies and improving patient outcomes. This study aimed to develop and validate a nomogram based on the Surveillance, Epidemiology, and End Results (SEER) database to predict cancer-specific survival (CSS) in patients with SBA and compare it to traditional American Joint Committee on Cancer (AJCC) staging. Methods: We analyzed data from 2,064 patients diagnosed with SBA between 2010 and 2020 from the SEER database. Patients were randomly assigned to training and validation cohorts (7:3 ratio). Kaplan‒Meier survival analysis, Cox multivariate regression, and nomograms were constructed for analysis of 3-year and 5-year CSS. The performance of the nomograms was evaluated using Harrell's concordance index (C-index), the area under the receiver operating characteristic (ROC) curve, calibration curves, decision curve analysis (DCA), net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Results: Multivariate Cox regression identified sex, age at diagnosis, marital status, tumor site, pathological grade, T stage, N stage, M stage, surgery, retrieval of regional lymph nodes (RORLN), and chemotherapy as independent covariates associated with CSS. In both the training and validation cohorts, the developed nomograms demonstrated superior performance to that of the AJCC staging system, with C-indices of 0.764 and 0.759, respectively. The area under the curve (AUC) values obtained by ROC analysis for 3-year and 5-year CSS prediction significantly surpassed those of the AJCC model. The nomograms were validated using calibration and decision curves, confirming their clinical utility and superior predictive accuracy. The NRI and IDI indicated the enhanced predictive capability of the nomogram model. Conclusion: The SEER-based nomogram offers a significantly superior ability to predict CSS in SBA patients, supporting its potential application in clinical decision-making and personalized approaches to managing SBA to improve survival outcomes. [ABSTRACT FROM AUTHOR]

Background: Dexmedetomidine (Dex), midazolam, and propofol are three distinct sedatives characterized by varying pharmacological properties. Previous literature has indicated the positive impact of each of these sedatives on ICU patients. However, there is a scarcity of clinical evidence comparing the efficacy of Dex, midazolam, and propofol in reducing mortality among people with epilepsy (PWE). This study aimed to assess the impact of Dex, midazolam, and propofol on the survival of PWE. Methods: The data were retrospectively retrieved from the Medical Information Mart for Intensive Care (MIMIC)-IV database (version 2.0). PWE were categorized into Dex, midazolam, and propofol groups based on the intravenously administered sedatives. PWE without standard drug therapy were included in the control group. Comparative analyses were performed on the data among the groups. Results: The Dex group exhibited a significantly lower proportion of in-hospital deaths and a markedly higher in-hospital survival time compared to the midazolam and propofol groups (p < 0.01) after propensity score matching. Kaplan-Meier curves demonstrated a significant improvement in survival rates for the Dex group compared to the control group (p = 0.025). Analysis of Variance (ANOVA) revealed no significant differences in survival rates among the Dex, midazolam, and propofol groups (F = 1.949, p = 0.143). The nomogram indicated that compared to midazolam and propofol groups, Dex was more effective in improving the survival rate of PWE. Conclusion: Dex might improve the survival rate of PWE in the ICU compared to no standard drug intervention. However, Dex did not exhibit superiority in improving survival rates compared to midazolam and propofol. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to establish the dose-response relationship between volume base dose and tumor local control for vaginal cancer, including primary vaginal cancer and recurrent gynecologic malignancies in the vagina. Materials and methods: We identified studies that reported volume base dose and local control by searching the PubMed, the Web of Science, and the Cochrane Library Database through August 12, 2023. The regression analyses were performed using probit model between volume based dose versus clinical outcomes. Subgroup analyses were performed according to stratification: publication year, country, inclusion time of patients, patients with prior radiotherapy, age, primaries or recurrent, tumor size, concurrent chemoradiotherapy proportion, dose rate, image modality for planning, and interstitial proportion. Results: A total of 879 patients with vaginal cancer were identified from 18 studies. Among them, 293 cases were primary vaginal cancer, 573 cases were recurrent cancer in the vagina, and 13 cases were unknown. The probit model showed a significant relationship between the HR-CTV (or CTV) D90 versus the 2-year and 3-year local control, P values were 0.013 and 0.014, respectively. The D90 corresponding to probabilities of 90% 2-year local control were 79.0 GyEQD2,10 (95% CI: 75.3–96.6 GyEQD2,10). Conclusions: A significant dependence of 2-year or 3-year local control on HR-CTV (or CTV) D90 was found. Our research findings encourage further validation of the dose-response relationship of radical radiotherapy for vaginal cancer through protocol based multicenter clinical trials. [ABSTRACT FROM AUTHOR]

Recent studies have shifted the spotlight from adult disease to gametogenesis and embryo developmental events, and these are greatly affected by various environmental chemicals, such as drugs, metabolites, pollutants, and others. Growing research has highlighted the critical importance of identifying and understanding the roles of chemicals in reproductive biology. However, the functions and mechanisms of chemicals in reproductive processes remain incomplete. We developed a comprehensive database called the Reproductive Chemical Database (RCDB) (https://yu.life.sjtu.edu.cn/ChenLab/RCDB) to facilitate research on chemicals in reproductive biology. This resource is founded on rigorous manual literature extraction and precise protein target prediction methodologies. This database focuses on the delineation of chemicals associated with phenotypes, diseases, or endpoints intricately associated with four important reproductive processes: female and male gamete generation, fertilization, and embryo development in human and mouse. The RCDB encompasses 93 sub-GO processes, and it revealed 1447 intricate chemical–biological process interactions. To date, the RCDB has meticulously cataloged and annotated 830 distinct chemicals, while also predicting 614 target proteins from a selection of 3800 potential candidates. Additionally, the RCDB offers an online predictive tool that empowers researchers to ascertain whether specific chemicals play discernible functional roles in these reproductive processes. The RCDB is an exhaustive, cross-platform, manually curated database, which provides a user-friendly interface to search, browse, and use reproductive processes modulators and their comprehensive related information. The RCDB will help researchers to understand the whole reproductive process and related diseases and it has the potential to promote reproduction research in the pharmacological and pathophysiological areas. [ABSTRACT FROM AUTHOR]

Background: Treatment-related problems (TRPs) interfere with the ability to attain the desired goals of treatment, adding cost to healthcare systems. Patients hospitalized with acute conditions are at particular risk to experience TRPs. Data investigating such burden in patients with acute exacerbation of COPD (AECOPD) is generally scarce with no studies ever conducted in Jordan. This study aimed to investigate and categorize TRPs among patients hospitalized with AECOPD in Jordan, and to estimate their cost savings and cost avoidance. Methods: This was a retrospective population-based cohort study. Patients' cases of AECOPD admitted to the study site from Jan 2017 to Jul 2021 were identified from the electronic clinical database and screened for eligibility. TRPs were identified/categorized using AbuRuz tool and assessed for their severity. Cost saving was estimated by calculating all the extra costs. Cost avoidance was estimated according to Nesbit method. Results: A total of 1243 (mean±SD 3.1±1.5) and 503 (mean±SD 1.3±1.2) TRPs were identified during hospitalization and at discharge respectively, of which 49.4% and 66.7% were classified as "unnecessary drug therapy". In 54.5% of the cases, systemic corticosteroid was administered for a period longer than recommended. Most of the TRPs were of moderate severity. The total direct cost saving, and cost avoidance were estimated to be 15,745.7 USD and 340,455.5 USD respectively. Conclusion: The prevalence and cost of TRPs among AECOPD patients is a concern requiring attention. The study results implicate integrating interventions such as embracing clinical pharmacists' role in the respiratory care units to optimize patients' management. [ABSTRACT FROM AUTHOR]

Customer churn prediction is vital for organizations to mitigate costs and foster growth. Ensemble learning models are commonly used for churn prediction. Diversity and prediction performance are two essential principles for constructing ensemble classifiers. Therefore, developing accurate ensemble learning models consisting of diverse base classifiers is a considerable challenge in this area. In this study, we propose two multi-objective evolutionary ensemble learning models based on clustering (MOEECs), which are include a novel diversity measure. Also, to overcome the data imbalance problem, another objective function is presented in the second model to evaluate ensemble performance. The proposed models in this paper are evaluated with a dataset collected from a mobile operator database. Our first model, MOEEC-1, achieves an accuracy of 97.30% and an AUC of 93.76%, outperforming classical classifiers and other ensemble models. Similarly, MOEEC-2 attains an accuracy of 96.35% and an AUC of 94.89%, showcasing its effectiveness in churn prediction. Furthermore, comparison with previous churn models reveals that MOEEC-1 and MOEEC-2 exhibit superior performance in accuracy, precision, and F-score. Overall, our proposed MOEECs demonstrate significant advancements in churn prediction accuracy and outperform existing models in terms of key performance metrics. These findings underscore the efficacy of our approach in addressing the challenges of customer churn prediction and its potential for practical application in organizational decision-making. [ABSTRACT FROM AUTHOR]

Detection of structural variants (SVs) is currently biased toward those that alter copy number. The relative contribution of inversions toward genetic disease is unclear. In this study, we analyzed genome sequencing data for 33,924 families with rare disease from the 100,000 Genomes Project. From a database hosting >500 million SVs, we focused on 351 genes where haploinsufficiency is a confirmed disease mechanism and identified 47 ultra-rare rearrangements that included an inversion (24 bp to 36.4 Mb, 20/47 de novo). Validation utilized a number of orthogonal approaches, including retrospective exome analysis. RNA-seq data supported the respective diagnoses for six participants. Phenotypic blending was apparent in four probands. Diagnostic odysseys were a common theme (>50 years for one individual), and targeted analysis for the specific gene had already been performed for 30% of these individuals but with no findings. We provide formal confirmation of a European founder origin for an intragenic MSH2 inversion. For two individuals with complex SVs involving the MECP2 mutational hotspot, ambiguous SV structures were resolved using long-read sequencing, influencing clinical interpretation. A de novo inversion of HOXD11-13 was uncovered in a family with Kantaputra-type mesomelic dysplasia. Lastly, a complex translocation disrupting APC and involving nine rearranged segments confirmed a clinical diagnosis for three family members and resolved a conundrum for a sibling with a single polyp. Overall, inversions play a small but notable role in rare disease, likely explaining the etiology in around 1/750 families across heterogeneous clinical cohorts. [Display omitted] By analyzing genome sequencing data for 33,924 families from a heterogeneous rare-disease cohort, Pagnamenta et al. identified 45 families where inversions likely explain the etiology. In six instances, RNA-seq helped support the respective diagnoses, and exemplar cases include complex SVs involving MECP2 where long-read sequencing data influenced the clinical interpretation. [ABSTRACT FROM AUTHOR]

Aim: Acute respiratory distress syndrome or ARDS is an acute, severe form of respiratory failure characterised by poor oxygenation and bilateral pulmonary infiltrates. Advancements in signal processing and machine learning have led to promising solutions for classification, event detection and predictive models in the management of ARDS. Method: In this review, we provide systematic description of different studies in the application of Machine Learning (ML) and artificial intelligence for management, prediction, and classification of ARDS. We searched the following databases: Google Scholar, PubMed, and EBSCO from 2009 to 2023. A total of 243 studies was screened, in which, 52 studies were included for review and analysis. We integrated knowledge of previous work providing the state of art and overview of explainable decision models in machine learning and have identified areas for future research. Results: Gradient boosting is the most common and successful method utilised in 12 (23.1%) of the studies. Due to limitation of data size available, neural network and its variation is used by only 8 (15.4%) studies. Whilst all studies used cross validating technique or separated database for validation, only 1 study validated the model with clinician input. Explainability methods were presented in 15 (28.8%) of studies with the most common method is feature importance which used 14 times. Conclusion: For databases of 5000 or fewer samples, extreme gradient boosting has the highest probability of success. A large, multi-region, multi centre database is required to reduce bias and take advantage of neural network method. A framework for validating with and explaining ML model to clinicians involved in the management of ARDS would be very helpful for development and deployment of the ML model. [ABSTRACT FROM AUTHOR]

Background: Mediation analysis is a powerful tool to identify factors mediating the causal pathway of exposure to health outcomes. Mediation analysis has been extended to study a large number of potential mediators in high-dimensional data settings. The presence of confounding in observational studies is inevitable. Hence, it's an essential part of high-dimensional mediation analysis (HDMA) to adjust for the potential confounders. Although the propensity score (PS) related method such as propensity score regression adjustment (PSR) and inverse probability weighting (IPW) has been proposed to tackle this problem, the characteristics with extreme propensity score distribution of the PS-based method would result in the biased estimation. Methods: In this article, we integrated the overlapping weighting (OW) technique into HDMA workflow and proposed a concise and powerful high-dimensional mediation analysis procedure consisting of OW confounding adjustment, sure independence screening (SIS), de-biased Lasso penalization, and joint-significance testing underlying the mixture null distribution. We compared the proposed method with the existing method consisting of PS-based confounding adjustment, SIS, minimax concave penalty (MCP) variable selection, and classical joint-significance testing. Results: Simulation studies demonstrate the proposed procedure has the best performance in mediator selection and estimation. The proposed procedure yielded the highest true positive rate, acceptable false discovery proportion level, and lower mean square error. In the empirical study based on the GSE117859 dataset in the Gene Expression Omnibus database using the proposed method, we found that smoking history may lead to the estimated natural killer (NK) cell level reduction through the mediation effect of some methylation markers, mainly including methylation sites cg13917614 in CNP gene and cg16893868 in LILRA2 gene. Conclusions: The proposed method has higher power, sufficient false discovery rate control, and precise mediation effect estimation. Meanwhile, it is feasible to be implemented with the presence of confounders. Hence, our method is worth considering in HDMA studies. [ABSTRACT FROM AUTHOR]

The demands of professional tennis, including physical and psychological aspects, contribute to the frequency of retirements at elite levels of the sport. The aim of this study was to analyze epidemiological patterns and risk factors associated with retirements in previous ATP and WTA Tour tournaments. A retrospective cohort study was conducted. This study focused on previous ATP and WTA Tour tournaments. The ATP database encompassed 584,806 matches, while the WTA database included 267,380 matches. To assess retirements, potential risk factors such as playing surface, tournament category, match round, and player age were analyzed. Incidence rates were calculated for the period between 1978–2019 for men and 1994–2018 for women. The overall incidence rate was 1.56 (95%CI: 1.54, 1.59) and 1.36 (95%CI: 1.33, 1.39) retirements per 1000 games played in male and female competitions, respectively. Retirements increased over the years. Higher incidence rates were observed on hard (1.59 [95%CI: 1.56, 1.63] and 1.39 [95%CI: 1.34, 1.44]) and clay (1.60 [95%CI: 1.57, 1.63] and 1.36 [95%CI: 1.32, 1.41]) compared to grass courts (0.79 [95%CI: 0.65, 0.94] and 1.06 [95%CI: 0.88, 1.27]). Risk factors differed by gender, with tournament category significant in males (IRR: 1.23 [95%CI: 1.19, 1.28] in ITF vs ATP) and match round in females (IRR: 0.92 [95%CI: 0.88, 0.98] in preliminary vs final). This study provides valuable insights for coaches, players, support teams, and epidemiologists regarding retirements and associated risk factors in previous ATP and WTA Tour tournaments, contributing to injury prevention strategies. [ABSTRACT FROM AUTHOR]

Atrial Fibrillation (AF), a type of heart arrhythmia, becomes more common with aging and is associated with an increased risk of stroke and mortality. In light of the urgent need for effective automated AF monitoring, existing methods often fall short in balancing accuracy and computational efficiency. To address this issue, we introduce a framework based on Multi-Scale Dilated Convolution (AF-MSDC), aimed at achieving precise predictions with low cost and high efficiency. By integrating Multi-Scale Dilated Convolution (MSDC) modules, our model is capable of extracting features from electrocardiogram (ECG) datasets across various scales, thus achieving an optimal balance between precision and computational savings. We have developed three MSDC modules to construct the AF-MSDC framework and assessed its performance on renowned datasets, including the MIT-BIH Atrial Fibrillation Database and Physionet Challenge 2017. Empirical results unequivocally demonstrate that our technique surpasses existing state-of-the-art (SOTA) methods in the AF detection domain. Specifically, our model, with only a quarter of the parameters of a Residual Network (ResNet), achieved an impressive sensitivity of 99.45%, specificity of 99.64% (on the MIT-BIH AFDB dataset), and an F1all score of 85.63% (on the Physionet Challenge 2017 AFDB dataset). This high efficiency makes our model particularly suitable for integration into wearable ECG devices powered by edge computing frameworks. Moreover, this innovative approach offers new possibilities for the early diagnosis of AF in clinical applications, potentially improving patient quality of life and reducing healthcare costs. [ABSTRACT FROM AUTHOR]

We present Isotòpia, an open-access database compiling over 36,000 stable isotope measurements (δ13C, δ15N, δ18O, δ34S, 87Sr/86Sr, 206Pb/204Pb, 207Pb/204Pb, 208Pb/204Pb, 207Pb/206Pb, and 208Pb/206Pb) on human, animal, and plant bioarchaeological remains dating to Classical Antiquity (approximately 800 BCE ‐ 500 CE). These were recovered from different European regions, particularly from the Mediterranean. Isotòpia provides a comprehensive characterisation of the isotopic data, encompassing various historical, archaeological, biological, and environmental variables. Isotòpia is a resource for meta-analytical research of past human activities and paleoenvironments. The database highlights data gaps in isotopic classical archaeology, such as the limited number of isotopic measurements available for plants and animals, limited number of studies on spatial mobility, and spatial heterogeneity of isotopic research. As such, we emphasise the necessity to address and fill these gaps in order to unlock the reuse potential of this database. [ABSTRACT FROM AUTHOR]

Background Standardized Letters of Evaluation (SLOEs) are an important part of resident selection in many specialties. Often written by a group, such letters may ask writers to rate applicants in different domains. Prior studies have noted inflated ratings; however, the degree to which individual institutions are "doves" (higher rating) or "hawks" (lower rating) is unclear. Objective To characterize institutional SLOE rating distributions to inform readers and developers regarding potential threats to validity from disparate rating practices. Methods Data from emergency medicine (EM) SLOEs between 2016 and 2021 were obtained from a national database. SLOEs from institutions with at least 10 letters per year in all years were included. Ratings on one element of the SLOE—the "global assessment of performance" item (Top 10%, Top Third, Middle Third, and Lower Third)—were analyzed numerically and stratified by predefined criteria for grading patterns (Extreme Dove, Dove, Neutral, Hawk, Extreme Hawk) and adherence to established guidelines (Very High, High, Neutral, Low, Very Low). Results Of 40 286 SLOEs, 20 407 met inclusion criteria. Thirty-five to 50% of institutions displayed Neutral grading patterns across study years, with most other institutional patterns rated as Dove or Extreme Dove. Adherence to guidelines was mixed and fewer than half of institutions had Very High or High adherence each year. Most institutions underutilize the Lower Third rating. Conclusions Despite explicit guidelines for the distribution of global assessment ratings in the EM SLOE, there is high variability in institutional rating practices. [ABSTRACT FROM AUTHOR]

To determine the incidence of thromboembolic events (TEEs) in ovarian cancer patients and to identify risk factors that are significantly associated with the development of venous thromboembolism (VTE), arterial thromboembolism (ATE), or overall TEEs in this population. This is a retrospective cohort study of 4491 patients with epithelial ovarian cancer identified in the British Columbia cancer registry between 1996 and 2017. The presence of TEEs and risk factors were identified in administrative health records from fee-for-service provider visits and hospital data using ICD-9-CM and ICD-10-CM billing codes. Statistical analysis was performed using Chi-squared test and Fischer's exact test. Of 4491 patients with epithelial ovarian cancer included in this study, 1.74% experienced ATE and (9.44%) experienced VTE. There was a significant association found between the occurrence of TEEs and all-cause mortality. Sepsis was significantly associated with both venous and arterial thromboembolism. The top three risk factors for arterial thromboembolism included peripheral vascular disease (PVD), open wound, and aneurysm. Risk factors predictive of thrombosis in ovarian cancer patients are not consistent between ATE and VTE, thus thrombotic events should not be combined for analysis. Differential thrombosis risk assessment is needed to improve prevention strategies and guide thromboprophylaxis for these patients. • In a large cohort of patients with epithelial ovarian cancer, thrombosis rate was 9.44% (VTE) and 1.74% (ATE). • Significant association was found between thrombosis occurrence and all-cause mortality. • Thrombosis risk factors are not consistent between ATE and VTE and sepsis is significantly associated with both. • Differential thrombosis risk assessment is needed to guide thromboprophylaxis for these patients. [ABSTRACT FROM AUTHOR]

The primary objective is to assess factors associated with treatment related high grade (CTCAE grade ≥ 3) adverse event (AE) reporting among participants in gynecologic oncology clinical trials. All AEs recorded in the Princess Margaret Clinical Trial adverse event database between 01/2016 and 12/2018 were evaluated. Gynecologic oncology clinical trials assessing systemic therapy were included. Inferential statistics on risk factors of related grade ≥ 3 adverse event reporting and GEE logistic models with Odds Ratios (OR) were performed. Multivariable analysis adjusting for age, clinical trial phase, sponsor, and therapy type. The gynecology cancer clinical trials accrued 317 unique patients (359 nested on trials) in 42 systemic therapy trials. In the period, 17,175 related AEs were reported in the gynecological cancer trials, 7.4% were grade ≥ 3. On multivariable analysis, no odds differences of grade ≥ 3 related AEs were detected according to study phase. Patients in immunotherapy clinical trials had lower odds of related grade ≥ 3 AEs than patients on targeted or other therapy (adjusted OR [aOR] 0.43; 95% CI 0.24–0.75). There was greater odds of related grade ≥ 3 AEs in clinical trials assessing combination vs single therapeutics (aOR 2.26, 95% CI 1.34–3.80). Patients aged ≥65 (aOR 1.77; 95% CI 1.08–2.89) had greater odds of related grade ≥ 3 AEs than patients aged 50 to 65 years. When compared to other disease sites, the odds of having a grade ≥ 3 related AE reported in gynecology clinical trials was no different. In this cohort, factors influencing the odds of related grade ≥ 3 AE reporting in gynecologic trials included type of therapy and age. The study phase did not correlate with odds of high-grade AE reporting. • The study assesses related high grade adverse event (AE) reporting in gynecology oncology trials at a referral cancer centre. • Study factors associated with higher odds of related grade ≥ 3 AEs were non-immunotherapy trials or drug combinations. • Patient factors associated with higher odds of related grade ≥ 3 AEs reported included age ≥ 65. • No odds differences were detected in related grade ≥ 3 AEs reported according to the clinical trial phase. [ABSTRACT FROM AUTHOR]

The literature has paid very little attention to pericarditis, pericardial effusion and pancreatitis during clozapine treatment in children and adolescents. Cases of clozapine-associated pericarditis and pancreatitis in children were studied using searches in: 1) PubMed (June 16, 2023), and 2) the World Health Organization's pharmacovigilance database (June 1, 2022), VigiBase. VigiBase uses a logarithmic measure of disproportionality called the information component (IC). The PubMed search yielded 3 clozapine-associated pericarditis cases, 1 pancreatitis case and 1 with both. VigiBase provided a significant clozapine-associated pericarditis IC = 3.6 with an IC 025 = 2.9 (only 3 cases were expected while 22 were observed). VigiBase provided a significant clozapine-associated pancreatitis IC = 2.2 with an IC 025 = 1.4 (only 3 cases were expected while 16 were observed). In VigiBase clozapine-associated pericarditis and pericardial effusion in youth looked similar and on a continuum with myocarditis, as myocarditis, pericarditis and pancreatitis appeared to occur mainly during clozapine titration. Combining PubMed and VigiBase we identified: 1) 29 cases of at least possible clozapine-associated pericarditis/pericardial effusion (6 probable and 23 possible) including 7 cases with and 22 without myocarditis, and 2) 17 cases of clozapine-associated pancreatitis (1 definite and 16 possible). Two of the pancreatitis cases occurred during overdoses. No fatal outcomes were found in any clozapine-associated pericarditis and pancreatitis cases. Despite the lack of attention in the literature to clozapine-associated pericarditis and pancreatitis, results demonstrate that they can happen in youth, particularly during titration. Pericarditis and pancreatitis appear to be forms of clozapine-associated inflammation during dose titration. [Display omitted] [ABSTRACT FROM AUTHOR]

Pharmacovigilance findings and box warnings in the clozapine package inserts have marked the history of clozapine. This is the largest review of clozapine adverse drug reactions (ADRs) and their associated fatal outcomes. Reports to the World Health Organization's global pharmacovigilance database, VigiBase™, were analyzed, extending from clozapine's introduction to December 31, 2022. The analysis focused on the top four reporting countries: United States (US), United Kingdom (UK), Canada and Australia (83 % of fatal outcomes worldwide). Attempts were made to control for population and clozapine prescription in each country. Clozapine ADRs worldwide accounted for 191,557 reports, with the highest number (53,505) in "blood and lymphatic system disorder". Of the 22,596 fatal outcomes reported in clozapine patients, 9587 were from the US, 6567 from the UK, 3623 from Canada and 1484 from Australia. The top category worldwide in fatal outcomes was nonspecifically labeled "death" with 46 % (range 22–62 %). "Pneumonia" was second with 30 % (range 17–45 %). Agranulocytosis was numerically only the 35th top clozapine ADR associated with fatal outcomes. On average, 2.3 clozapine ADRs were reported per fatal outcome. Infections were associated with 24.2 % of the UK fatal outcomes (9.4 %–11.9 % in the 3 other countries). The four countries appeared to report clozapine ADRs in different ways, making comparisons difficult. We estimated higher fatal outcomes in the UK and Canada after controlling for cross-sectional estimations of population and published clozapine use. This last hypothesis is limited by the lack of precise estimation of accumulated clozapine use in each country. [Display omitted] [ABSTRACT FROM AUTHOR]

The Bucaramanga seismic nest has the highest concentration in volume of intermediate depth seismic events with light and moderate magnitudes (Mb > 4.8) worldwide. Despite the nest depth (Zhypo ≥ 100 km), these events play a crucial role in the seismic hazard assessment for several cities in northern South America (NoSAm), particularly those situated close to their epicenters. Moreover, these earthquakes are widely felt across the country, even hundreds of kilometers away from the nest. This paper assesses the performance of commonly used subduction intraslab Ground Motion Models (GMMs) in predicting the updated nest database gathered and processed by the Colombian Geological Survey. This analysis confirms the necessity of a partially non-ergodic ground motion model for estimating the spectral accelerations produced by Bucaramanga nest earthquakes in northern South America. The GMM presented herein is the first model developed specifically for seismic nests in the region and is conceived as a regionalization of the recent NGA-Sub Abrahamson and Gülerce (Earthq Spectra 38(4):2638−2681, 2022) GMM. Additionally, we provide estimates of the variance components at both the earthquake and station levels and compare the developed GMM with the spectral accelerations recorded for typical earthquakes, for the highest magnitude earthquake in the database, and for a recent Bucaramanga nest earthquake having a moment magnitude over 5. [ABSTRACT FROM AUTHOR]

Objectives: Reliable detection of disease-specific atrophy in individual T1w-MRI by voxel-based morphometry (VBM) requires scanner-specific normal databases (NDB), which often are not available. The aim of this retrospective study was to design, train, and test a deep convolutional neural network (CNN) for single-subject VBM without the need for a NDB (CNN-VBM). Materials and methods: The training dataset comprised 8945 T1w scans from 65 different scanners. The gold standard VBM maps were obtained by conventional VBM with a scanner-specific NDB for each of the 65 scanners. CNN-VBM was tested in an independent dataset comprising healthy controls (n = 37) and subjects with Alzheimer's disease (AD, n = 51) or frontotemporal lobar degeneration (FTLD, n = 30). A scanner-specific NDB for the generation of the gold standard VBM maps was available also for the test set. The technical performance of CNN-VBM was characterized by the Dice coefficient of CNN-VBM maps relative to VBM maps from scanner-specific VBM. For clinical testing, VBM maps were categorized visually according to the clinical diagnoses in the test set by two independent readers, separately for both VBM methods. Results: The VBM maps from CNN-VBM were similar to the scanner-specific VBM maps (median Dice coefficient 0.85, interquartile range [0.81, 0.90]). Overall accuracy of the visual categorization of the VBM maps for the detection of AD or FTLD was 89.8% for CNN-VBM and 89.0% for scanner-specific VBM. Conclusion: CNN-VBM without NDB provides a similar performance in the detection of AD- and FTLD-specific atrophy as conventional VBM. Clinical relevance statement: A deep convolutional neural network for voxel-based morphometry eliminates the need of scanner-specific normal databases without relevant performance loss and, therefore, could pave the way for the widespread clinical use of voxel-based morphometry to support the diagnosis of neurodegenerative diseases. Key Points: • The need of normal databases is a barrier for widespread use of voxel-based brain morphometry. • A convolutional neural network achieved a similar performance for detection of atrophy than conventional voxel-based morphometry. • Convolutional neural networks can pave the way for widespread clinical use of voxel-based morphometry. [ABSTRACT FROM AUTHOR]