Machine learning approaches to identify spatial factors and their influential distances for heavy metal contamination in downstream sediment.

Contaminated sediments can adversely affect aquatic ecosystems, making the identification and management of pollutant sources extremely important. In this study, we proposed machine learning approaches to reveal sources and their influential distances for heavy metal contamination of downstream sediment. We employed classification models with artificial neural networks (ANN) and random forest (RF), respectively, to predict the heavy metal contamination of stream sediments using upland environmental variables as input features. A comprehensive Korean nationwide monitoring database containing 1546 datasets was used to train and test the models. These datasets encompass the concentrations of eight heavy metals (Ar, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) in sediment samples collected from 160 stream sites across the nation from 2014 to 2018. Model's prediction accuracy was evaluated for input feature sets from different influential upland areas defined by different buffer radii and the watershed boundary for each site. Although both ANN and RF models were unsatisfactory in predicting heavy metal quartile classes, RF-classifiers with adaptive synthetic oversampling (ORFC) showed reasonably well-predicted classes of the sediment samples based on the Canada's Sediment Quality Guidelines (accuracy ranged from 0.67 to 0.94). The best influential distance (i.e., buffer radius) was determined for each heavy metal based on the accuracy of ORFC. The results indicated that Cd, Cu and Pb had shorter influential distances (1.5-2.0 km) than the other heavy metals with little difference in accuracy for different influential distances. Feature importance calculation revealed that upland soil contamination was the primary factor for Hg and Ni, while residential areas and roads were significant features associated with Pb and Zn contamination. This approach offers information on major contamination sources and their influential areas to be prioritized for managing contaminated stream sediments.

Multivariate analysis of multimodal brain structure predicts individual differences in risk and intertemporal preference.

Large changes to brain structure (e.g., from damage or disease) can explain alterations in behavior. It is therefore plausible that smaller structural differences in healthy samples can be used to better understand and predict individual differences in behavior. Despite the brain's multivariate and distributed structure-to-function mapping, most studies have used univariate analyses of individual structural brain measures. Here we used a multivariate approach in a multimodal data set composed of volumetric, surface-based, diffusion-based, and functional resting-state MRI measures to predict reliable individual differences in risk and intertemporal preferences. We show that combining twelve brain structure measures led to better predictions across tasks than using any individual measure, and by examining model coefficients, we visualize the relative contribution of different brain measures from different brain regions. Using a multivariate approach to brain structure-to-function mapping that combines across many brain structure properties, along with reliably measured behavior phenotypes, may increase out-of-sample prediction accuracies and insight into neural underpinnings. Furthermore, this methodological approach may be useful to improve predictions and neural insight across basic, translational, and clinical research fields.

Risk factors and risk stratification approaches for delirium screening: A Geriatric Emergency Department Guidelines 2.0 systematic review.

OBJECTIVE: As part of the Geriatric Emergency Department (ED) Guidelines 2.0 project, we conducted a systematic review to find risk factors or risk stratification approaches that can be used to identify subsets of older adults who may benefit from targeted ED delirium screening. METHODS: An electronic search strategy was developed with a medical librarian, conducted in April 2021 and November 2022. Full-text studies of patients ≥65 years assessed for prevalent delirium in the ED were included. Risk of bias was assessed using the McMaster University Clarity Group tool. Outcomes measures pertained to the risk stratification method used. Due to heterogeneity of patient populations, risk stratification methods, and outcomes, a meta-analysis was not conducted. RESULTS: Our search yielded 1878 unique citations, of which 13 were included. Six studies developed a novel delirium risk score with or without evaluation of specific risk factors, six studies evaluated specific risk factors only, and one study evaluated an existing nondelirium risk score for association with delirium. The most common risk factor was history of dementia, with odds ratios ranging from 3.3 (95% confidence interval [CI] 1.2-8.9) to 18.33 (95% CI 8.08-43.64). Other risk factors that were consistently associated with increased risk of delirium included older age, use of certain medications (such as antipsychotics, antidepressants, and opioids, among others), and functional impairments. Of the studies that developed novel risk scores, the reported area under the curve ranged from 0.77 to 0.90. Only two studies reported potential impact of the risk stratification tool on screening burden. CONCLUSIONS: There is significant heterogeneity, but results suggest that factors such as dementia, age over 75, and functional impairments should be used to identify older adults who are at highest risk for ED delirium. No studies evaluated implementation of a risk stratification method for delirium screening or evaluated patient-oriented outcomes.

A Nationwide Emergency Department Data Analysis to Predict Beers List Medications Use Among Older Adults.

BACKGROUND: The use of potentially inappropriate medications (PIMs) is considered an important quality indicator for older adults seen in the ambulatory care setting. STUDY OBJECTIVES: To evaluate the pattern of potentially inappropriate medication (PIMs) use as specified in the Beers Criteria, for older adults during emergency department (ED) visits in the United States. METHODS: Using data from the National Hospital Ambulatory Care Survey (NHAMCS) we identified older adults (age 65 or older) discharged home from an ED visit in 2019. We defined PIMs as those with an 'avoid' recommendation under the American Geriatrics Society (AGS) 2019 Beers Criteria in older adults. Logistic regression models were used to assess demographic, clinical, and hospital factors associated with the use of any PIMs upon ED discharge. RESULTS: Overall, 5.9% of visits by older adults discharged from the ED included administration or prescriptions for PIMs. Among those who received any PIMs, 25.5% received benzodiazepines, 42.5 % received anticholinergics, 1.4% received nonbenzodiazepine hypnotics, and 0.5% received barbiturates. A multivariable model showed statistically significant associations for age 65 to 74 (OR 1.91, 95% CI 1.39-2.62 vs. age >=75), dementia (OR 0.45, 95% CI 0.21-0.95), lower immediacy (OR 2.45, 95% CI 1.56-3.84 vs. higher immediacy), and Northeastern rural region (OR 0.34, 95% CI 0.21-0.55 vs. Midwestern rural). CONCLUSION: We found that younger age and lower immediacy were associated with increased prescriptions of PIMs for older adults seen, while dementia and Northeastern rural region was associated with reduced use of PIMs seen and discharged from EDs in United States.

Enhancing healthcare access for an older population: The age-friendly emergency department.

Healthcare systems face significant challenges in meeting the unique needs of older adults, particularly in the acute setting. Age-friendly healthcare is a comprehensive approach using the 4Ms framework-what matters, medications, mentation, and mobility-to ensure that healthcare settings are responsive to the needs of older patients. The Age-Friendly Emergency Department (AFED) is a crucial component of a holistic age-friendly health system. Our objective is to provide an overview of the AFED model, its core principles, and the benefits to older adults and healthcare clinicians. The AFED optimizes the delivery of emergency care by integrating age-specific considerations into various aspects of (1) ED physical infrastructure, (2) clinical care policies, and (3) care transitions. Physical infrastructure incorporates environmental modifications to enhance patient safety, including adequate lighting, nonslip flooring, and devices for sensory and ambulatory impairment. Clinical care policies address the physiological, cognitive, and psychosocial needs of older adults while preserving focus on emergency issues. Care transitions include communication and involving community partners and case management services. The AFED prioritizes collaboration between interdisciplinary team members (ED clinicians, geriatric specialists, nurses, physical/occupational therapists, and social workers). By adopting an age-friendly approach, EDs have the potential to improve patient-centered outcomes, reduce adverse events and hospitalizations, and enhance functional recovery. Moreover, healthcare clinicians benefit from the AFED model through increased satisfaction, multidisciplinary support, and enhanced training in geriatric care. Policymakers, healthcare administrators, and clinicians must collaborate to standardize guidelines, address barriers to AFEDs, and promote the adoption of age-friendly practices in the ED.

Delirium detection in the emergency department: A diagnostic accuracy meta-analysis of history, physical examination, laboratory tests, and screening instruments.

INTRODUCTION: Geriatric emergency department (ED) guidelines emphasize timely identification of delirium. This article updates previous diagnostic accuracy systematic reviews of history, physical examination, laboratory testing, and ED screening instruments for the diagnosis of delirium as well as test-treatment thresholds for ED delirium screening. METHODS: We conducted a systematic review to quantify the diagnostic accuracy of approaches to identify delirium. Studies were included if they described adults aged 60 or older evaluated in the ED setting with an index test for delirium compared with an acceptable criterion standard for delirium. Data were extracted and studies were reviewed for risk of bias. When appropriate, we conducted a meta-analysis and estimated delirium screening thresholds. RESULTS: Full-text review was performed on 55 studies and 27 were included in the current analysis. No studies were identified exploring the accuracy of findings on history or laboratory analysis. While two studies reported clinicians accurately rule in delirium, clinician gestalt is inadequate to rule out delirium. We report meta-analysis on three studies that quantified the accuracy of the 4 A's Test (4AT) to rule in (pooled positive likelihood ratio [LR+] 7.5, 95% confidence interval [CI] 2.7-20.7) and rule out (pooled negative likelihood ratio [LR-] 0.18, 95% CI 0.09-0.34) delirium. We also conducted meta-analysis of two studies that quantified the accuracy of the Abbreviated Mental Test-4 (AMT-4) and found that the pooled LR+ (4.3, 95% CI 2.4-7.8) was lower than that observed for the 4AT, but the pooled LR- (0.22, 95% CI 0.05-1) was similar. Based on one study the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) is the superior instrument to rule in delirium. The calculated test threshold is 2% and the treatment threshold is 11%. CONCLUSIONS: The quantitative accuracy of history and physical examination to identify ED delirium is virtually unexplored. The 4AT has the largest quantity of ED-based research. Other screening instruments may more accurately rule in or rule out delirium. If the goal is to rule in delirium then the CAM-ICU or brief CAM or modified CAM for the ED are superior instruments, although the accuracy of these screening tools are based on single-center studies. To rule out delirium, the Delirium Triage Screen is superior based on one single-center study.

Evaluation of medications used for opioid use disorder in emergency departments: A cross-sectional analysis of the 2020 National Hospital Ambulatory Medical Care Survey.

INTRODUCTION: Opioid use disorder (OUD) is a significant health issue impacting millions in the United States (US). Medications used for OUD (MOUD) (e.g., buprenorphine, methadone, naltrexone) and medications for overdose and symptom management (e.g., naloxone, clonidine) have been shown to be safe and effective tools in clinical management. MOUD therapy in Emergency Departments (EDs) improves patient outcomes and enhances engagement with formal addiction treatment; however, provider factors and institutional barriers have created hurdles to ED-based MOUD treatment and heterogeneity in ED based OUD care. We used a nationally representative dataset, the National Hospital Ambulatory Medical Care Survey (NHAMCS) to characterize MOUD prescribing practices across patient demographics, geographic regions, payers, providers, and comorbidities in EDs. METHODS: NHAMCS is a survey conducted by the US Census Bureau assessing utilization of ambulatory healthcare services nationally. Survey staff compile encounter records from a nationally representative sample of EDs. We conducted a cross-sectional study using this data to assess visits in 2020 among patients aged 18-64 presenting with an opioid overdose or OUD. We estimated the proportion of patients who had any MOUD, clonidine, or naloxone treatment and 95% confidence intervals (CI). We modeled the association between patient demographic, location, comorbidities, and provider characteristics with receipt of MOUD treatment as unadjusted odds ratios (OR) and 95% CI. RESULTS: There was a weighted frequency of 469,434 patients who were discharged from EDs after being seen for OUD or overdose. Naloxone, clonidine, and buprenorphine were the most frequent treatments administered and/or prescribed for OUDs or overdose. Overall, 54,123 (11.5%, 95%CI 0-128,977) patients who were discharged from the ED for OUDs or overdose received at least one type of MOUD. Hispanic race, (OR 17.9, 95%CI 1.33-241.90) and Western region (OR43.77, 95%CI 2.97-645.27) were associated with increased odds of receiving MOUDs, while arrival by ambulance was associated with decreased odds of receiving MOUDs (OR0.01, 95%CI 0.001-0.19). Being seen by an APP or physician assistant was associated with MOUD treatment (OR 16.68, 95%CI: 1.41-152.33; OR: 13.84, 95%CI: 3.58-53.51, respectively). CONCLUSION: Our study findings suggest that MOUD and other medications for opioid overdose are infrequently used in the ED setting. This finding was especially notable in race, geographic region, mode of arrival, and those seen by APP, underscoring the need for further study into the root causes of these disparities. Our study provides a foundational understanding of MOUD patterns, guiding future research as the landscape of OUD treatment continues to shift.

Real-world effectiveness of a single conventional disease-modifying anti-rheumatic drug (cDMARD) plus an anti-TNF agent versus multiple cDMARDs in rheumatoid arthritis: a prospective observational study.

Objective: The objective of this prospective, observational multicenter study (NCT03264703) was to compare the effectiveness of single conventional disease-modifying anti-rheumatic drug (cDMARD) plus anti-tumor necrosis factor (TNF) therapy versus multiple cDMARD treatments in patients with moderate-to-severe rheumatoid arthritis (RA) following cDMARD failure in the real-world setting in South Korea. Methods: At the treating physicians' discretion, patients received single cDMARD plus anti-TNF therapy or multiple cDMARDs. Changes from baseline in disease activity score 28-joint count with erythrocyte sedimentation rate (DAS28-ESR), corticosteroid use, and Korean Health Assessment Questionnaire (KHAQ-20) scores were evaluated at 3, 6, and 12 months. Results: Of 207 enrollees, the final analysis included 45 of 73 cDMARD plus anti-TNF and 91 of 134 multiple-cDMARD recipients. There were no significant between-group differences (BGDs) in ANCOVA-adjusted changes from baseline in DAS28-ESR at 3, 6 (primary endpoint), and 12 months (BGDs -0.18, -0.38, and -0.03, respectively). More cDMARD plus anti-TNF than multiple-cDMARD recipients achieved a >50% reduction from baseline in corticosteroid dosage at 12 months (35.7% vs 14.6%; p=0.007). Changes from baseline in KHAQ-20 scores at 3, 6, and 12 months were significantly better with cDMARD plus anti-TNF therapy than with multiple cDMARDs (BGD -0.18, -0.19, and -0.19 points, respectively; all p≤0.024). Conclusion: In the real-world setting, relative to multiple cDMARDs, single cDMARD plus anti-TNF therapy significantly improved quality-of-life scores and reduced corticosteroid use, with no significant BGD in disease activity, in RA patients in whom previous cDMARD therapy had failed.

Usability of the 4Ms Worksheet in the Emergency Department for Older Patients: A Qualitative Study.

Introduction: Older adults often have multiple comorbidities; therefore, they are at high risk for adverse events after discharge. The 4Ms framework-what matters, medications, mentation, mobility-has been used in acute and ambulatory care settings to identify risk factors for adverse events in older adults, although it has not been used in the emergency department (ED). We aimed to determine whether 1) use of the 4Ms worksheet would help emergency clinicians understand older adult patients' goals of care and 2) use of the worksheet was feasible in the ED. Methods: We conducted a qualitative, descriptive study among patients aged ≥60 years and emergency clinicians from January-June 2022. Patients were asked to fill out a 4Ms worksheet; following this, semi-structured interviews were conducted with patients and clinicians separately. We analysed data to create codes, which were divided into categories and sub-categories. Results: A total of 20 older patients and 19 emergency clinicians were interviewed. We identified two categories based on our aims: understanding patient goals of care (sub-categories: clinician/ patient concordance; understanding underlying goals of care; underlying goals of care discrepancy) and use of 4Ms Worksheet (sub-categories: worksheet to discussion discrepancy; challenges using worksheet; challenge completing worksheet before discharge). Rates of concordance between patient and clinician on main concern/goal of care and underlying goals of care were 82.4% and 15.4%, respectively. Conclusion: We found that most patients and emergency clinicians agreed on the main goal of care, although clinicians often failed to elicit patients' underlying goal(s) of care. Additionally, many patients preferred to have the interviewer fill out the worksheet for them. There was often discrepancy between what was written and what was discussed with the interviewer. More research is needed to determine the best way to integrate the 4Ms framework within emergency care.

Very long-lasting spinal anesthesia with dexmedetomidine: A report of two cases.

Spinal anesthesia usually lasts up to two hours, but an infusion of IV dexmedetomidine can prolong it to three to four hours. We report two cases where single spinal anesthesia with IV dexmedetomidine was maintained for more than six hours during tibia fracture surgery. The spinal anesthesia was maintained for 350 and 390 minutes without another medication, and the sensory level confirmed after the surgery was T10 and L1. Dexmedetomidine can very-prolong the duration of spinal anesthesia beyond what has been reported. However, longer infusion times can also result in longer recovery times.

Peptoniphilus gorbachii alleviates collagen-induced arthritis in mice by improving intestinal homeostasis and immune regulation.

Introduction: The intricate connection between gut microbiota and rheumatoid arthritis (RA) pathogenesis has gained prominence, although the specific microbial species contributing to RA development remain largely unknown. Recent studies have sought to comprehensively explore alterations in the human microbiome, focusing on identifying disease-related microbial species through blood analysis. Consequently, this study aimed to identify RA-associated microbial species using a serum microbial array system and to investigate the efficacy and underlying mechanisms of potential microbial species for RA treatment. Methods: Serum immunoglobulin M levels against 384 intestinal microbial species were assessed using a microbial microarray in patients with RA and healthy individuals. We investigated the therapeutic potential of the identified microbial candidate regarding arthritis development, immune responses, gut barrier function, and gut microbiome using a collagen-induced arthritis (CIA) mouse model. Results: Our findings revealed significant alterations in antibody levels against 36 microbial species in patients with RA compared to healthy individuals. Notably, the antibody levels against Peptoniphilus gorbachii (PG) were decreased in patients with RA and exhibited an inverse correlation with RA disease activity. In vitro experiments demonstrated that PG produced acetate and butyrate, while exhibiting anti-inflammatory properties. In CIA mice, PG administration suppressed arthritis symptoms, reduced the accumulation of inflammatory monocytes in the mesenteric lymph nodes, and downregulated gene expression of pro-inflammatory cytokines in the ileum. Additionally, PG supplementation restored intestinal barrier integrity and partially resolved gut microbial dysbiosis in CIA mice. The fecal microbiota in PG-treated mice corresponded to improved intestinal barrier integrity and reduced inflammatory responses. Conclusion: This study highlights the potential of serum-based detection of anti-microbial antibodies to identify microbial targets at the species level for RA treatment. Moreover, our findings suggest that PG, identified through the microbial microarray analysis, holds therapeutic potential for RA by restoring intestinal barrier integrity and suppressing the immunologic response associated with RA.

Can Artificial Intelligence Enhance Syncope Management?: A JACC: Advances Multidisciplinary Collaborative Statement.

Syncope, a form of transient loss of consciousness, remains a complex medical condition for which adverse cardiovascular outcomes, including death, are of major concern but rarely occur. Current risk stratification algorithms have not completely delineated which patients benefit from hospitalization and specific interventions. Patients are often admitted unnecessarily and at high cost. Artificial intelligence (AI) and machine learning may help define the transient loss of consciousness event, diagnose the cause, assess short- and long-term risks, predict recurrence, and determine need for hospitalization and therapeutic intervention; however, several challenges remain, including medicolegal and ethical concerns. This collaborative statement, from a multidisciplinary group of clinicians, investigators, and scientists, focuses on the potential role of AI in syncope management with a goal to inspire creation of AI-derived clinical decision support tools that may improve patient outcomes, streamline diagnostics, and reduce health-care costs.

Promising Therapeutic Effects of Embryonic Stem Cells-Origin Mesenchymal Stem Cells in Experimental Pulmonary Fibrosis Models: Immunomodulatory and Anti-Apoptotic Mechanisms.

Interstitial lung disease (ILD) involves persistent inflammation and fibrosis, leading to respiratory failure and even death. Adult tissue-derived mesenchymal stem cells (MSCs) show potential in ILD therapeutics but obtaining an adequate quantity of cells for drug application is difficult. Daewoong Pharmaceutical's MSCs (DW-MSCs) derived from embryonic stem cells sustain a high proliferative capacity following long-term culture and expansion. The aim of this study was to investigate the therapeutic potential of DW-MSCs in experimental mouse models of ILD. DW-MSCs were expanded up to 12 passages for in vivo application in bleomycin-induced pulmonary fibrosis and collagen-induced connective tissue disease-ILD mouse models. We assessed lung inflammation and fibrosis, lung tissue immune cells, fibrosis-related gene/protein expression, apoptosis and mitochondrial function of alveolar epithelial cells, and mitochondrial transfer ability. Intravenous administration of DW-MSCs consistently improved lung fibrosis and reduced inflammatory and fibrotic markers expression in both models across various disease stages. The therapeutic effect of DW-MSCs was comparable to that following daily oral administration of nintedanib or pirfenidone. Mechanistically, DW-MSCs exhibited immunomodulatory effects by reducing the number of B cells during the early phase and increasing the ratio of Tregs to Th17 cells during the late phase of bleomycin-induced pulmonary fibrosis. Furthermore, DW-MSCs exhibited anti-apoptotic effects, increased cell viability, and improved mitochondrial respiration in alveolar epithelial cells by transferring their mitochondria to alveolar epithelial cells. Our findings indicate the strong potential of DW-MSCs in the treatment of ILD owing to their high efficacy and immunomodulatory and anti-apoptotic effects.