Validation of an Electronic Health Record-Based Machine Learning Model Compared to Clinical Risk Scores for Gastrointestinal Bleeding.

BACKGROUND & AIMS: Guidelines recommend use of risk stratification scores for patients presenting with gastrointestinal bleeding (GIB) to identify very-low-risk patients eligible for discharge from emergency departments. Machine learning models may outperform existing scores and can be integrated within the electronic health record (EHR) to provide real-time risk assessment without manual data entry. We present the first EHR-based machine learning model for GIB. METHODS: The training cohort comprised 2,546 patients and internal validation of 850 patients presenting with overt GIB (hematemesis, melena, hematochezia) to emergency departments of 2 hospitals from 2014-2019. External validation was performed on 926 patients presenting to a different hospital with the same EHR from 2014-2019. The primary outcome was a composite of red-blood-cell transfusion, hemostatic intervention (endoscopic, interventional radiologic, or surgical), and 30-day all-cause mortality. We used structured data fields in the EHR available within 4 hours of presentation and compared performance of machine learning models to current guideline-recommended risk scores, Glasgow-Blatchford Score (GBS) and Oakland Score. Primary analysis was area under the receiver-operating-characteristic curve (AUC). Secondary analysis was specificity at 99% sensitivity to assess proportion of patients correctly identified as very-low-risk. RESULTS: The machine learning model outperformed the GBS (AUC=0.92 vs. 0.89;p<0.001) and Oakland score (AUC=0.92 vs. 0.89;p<0.001). At the very-low-risk threshold of 99% sensitivity, the machine learning model identified more very-low-risk patients: 37.9% vs. 18.5% for GBS and 11.7% for Oakland score (p<0.001 for both comparisons). CONCLUSIONS: An EHR-based machine learning model performs better than currently recommended clinical risk scores and identifies more very-low-risk patients eligible for discharge from the emergency department.

Developing and Testing the Usability of a Novel Child Abuse Clinical Decision Support System: Mixed Methods Study.

BACKGROUND: Despite the impact of physical abuse on children, it is often underdiagnosed, especially among children evaluated in emergency departments (EDs). Electronic clinical decision support (CDS) can improve the recognition of child physical abuse. OBJECTIVE: We aimed to develop and test the usability of a natural language processing-based child abuse CDS system, known as the Child Abuse Clinical Decision Support (CA-CDS), to alert ED clinicians about high-risk injuries suggestive of abuse in infants' charts. METHODS: Informed by available evidence, a multidisciplinary team, including an expert in user design, developed the CA-CDS prototype that provided evidence-based recommendations for the evaluation and management of suspected child abuse when triggered by documentation of a high-risk injury. Content was customized for medical versus nursing providers and initial versus subsequent exposure to the alert. To assess the usability of and refine the CA-CDS, we interviewed 24 clinicians from 4 EDs about their interactions with the prototype. Interview transcripts were coded and analyzed using conventional content analysis. RESULTS: Overall, 5 main categories of themes emerged from the study. CA-CDS benefits included providing an extra layer of protection, providing evidence-based recommendations, and alerting the entire clinical ED team. The user-centered, workflow-compatible design included soft-stop alert configuration, editable and automatic documentation, and attention-grabbing formatting. Recommendations for improvement included consolidating content, clearer design elements, and adding a hyperlink with additional resources. Barriers to future implementation included alert fatigue, hesitancy to change, and concerns regarding documentation. Facilitators of future implementation included stakeholder buy-in, provider education, and sharing the test characteristics. On the basis of user feedback, iterative modifications were made to the prototype. CONCLUSIONS: With its user-centered design and evidence-based content, the CA-CDS can aid providers in the real-time recognition and evaluation of infant physical abuse and has the potential to reduce the number of missed cases.

Correction: Developing and Testing the Usability of a Novel Child Abuse Clinical Decision Support System: Mixed Methods Study.

[This corrects the article DOI: 10.2196/51058.].

Exploratory Descriptive Analysis of Smart Speaker Utilization in the Emergency Department During the COVID-19 Pandemic.

BACKGROUND: In March 2020, the U.S. Department of Health and Human Services Office for Civil Rights stated that they would use discretion when enforcing the Health Insurance Portability and Accountability Act regarding remote communication technologies that promoted telehealth delivery during the COVID-19 pandemic. This was in an effort to protect patients, clinicians, and staff. More recently, smart speakers-voice-activated, hands-free devices-are being proposed as productivity tools within hospitals. OBJECTIVE: We aimed to characterize the novel use of smart speakers in the emergency department (ED). METHODS: A retrospective observational study of Amazon Echo Show® utilization from May 2020 to October 2020 in a large academic Northeast health system ED. Voice commands and queries were classified as either patient care-related or non-patient care-related, and then further subcategorized to explore the content of given commands. RESULTS: Of 1232 commands analyzed, 200 (16.23%) were determined to be patient care-related. Of these commands, 155 (77.5%) were clinical in nature (i.e., "drop in on triage") and 23 (11.5%) were environment-enhancing commands (i.e., "play calming sounds"). Among non-patient care-related commands, 644 (62.4%) were for entertainment. Among all commands, 804 (65.3%) were during night-shift hours, which was statistically significant (p < 0.001). CONCLUSIONS: Smart speakers showed notable engagement, primarily being used for patient communication and entertainment. Future studies should examine content of patient care conversations using these devices, effects on frontline staff wellbeing, productivity, patient satisfaction, and even explore opportunities for "smart" hospital rooms.

Disparities in Accessing and Reading Open Notes in the Emergency Department Upon Implementation of the 21st Century CURES Act.

STUDY OBJECTIVE: There is a continued movement toward health data transparency, accelerated by the 21st Century CURES Act, which mandated the automatic and immediate release of clinical notes, often termed "open notes." Differences in utilization among different patient demographics and disproportionately affected populations within the emergency department (ED) are not yet known. METHODS: This was an observational study of 10 EDs and 3 urgent care centers across a single health system over a 13-week period from February 1, 2021 to May 2, 2021. Primary outcomes included the proportion of patients with patient portal access to open notes at the time of encounter, the proportion of patients with access who opened the clinical note, and time from clinical note signing to patient read. RESULTS: Among 98,725 patient visits, less than half (48.9%) had patient portal access, of which 13.7% read an open note. Access was less likely in patients who were under age 18 (odds ratio 0.10, 95% confidence interval 0.08 to 0.11), older than 65 (0.82, 0.73 to 0.93), Black non-Hispanic (0.66, 0.61 to 0.73), non-English speakers, and on public insurance. Patients were less likely to read open notes if they identified as Black non-Hispanic (0.61, 0.57 to 0.66), spoke Spanish (0.70, 0.60 to 0.81), or were on public insurance. CONCLUSION: We identified substantial differences in digital access to clinical notes as well as patient utilization of open notes in a large, diverse sample. Health transparency initiatives must address not only technology adoption broadly but also the unique barriers faced by populations experiencing disadvantage to facilitate equitable access to and awareness about digital health tools without the unintended consequence of expanding disparities.

Early identification of patients with acute gastrointestinal bleeding using natural language processing and decision rules.

BACKGROUND AND AIM: Guidelines recommend risk stratification scores in patients presenting with gastrointestinal bleeding (GIB), but such scores are uncommonly employed in practice. Automation and deployment of risk stratification scores in real time within electronic health records (EHRs) would overcome a major impediment. This requires an automated mechanism to accurately identify ("phenotype") patients with GIB at the time of presentation. The goal is to identify patients with acute GIB by developing and evaluating EHR-based phenotyping algorithms for emergency department (ED) patients. METHODS: We specified criteria using structured data elements to create rules for identifying patients and also developed multiple natural language processing (NLP)-based approaches for automated phenotyping of patients, tested them with tenfold cross-validation for 10 iterations (n = 7144) and external validation (n = 2988) and compared them with a standard method to identify patient conditions, the Systematized Nomenclature of Medicine. The gold standard for GIB diagnosis was the independent dual manual review of medical records. The primary outcome was the positive predictive value. RESULTS: A decision rule using GIB-specific terms from ED triage and ED review-of-systems assessment performed better than the Systematized Nomenclature of Medicine on internal validation and external validation (positive predictive value = 85% confidence interval:83%-87% vs 69% confidence interval:66%-72%; P < 0.001). The syntax-based NLP algorithm and Bidirectional Encoder Representation from Transformers neural network-based NLP algorithm had similar performance to the structured-data fields decision rule. CONCLUSIONS: An automated decision rule employing GIB-specific triage and review-of-systems terms can be used to trigger EHR-based deployment of risk stratification models to guide clinical decision making in real time for patients with acute GIB presenting to the ED.

Agile Health Care Analytics: Enabling Real-Time Disease Surveillance With a Computational Health Platform.

The ongoing coronavirus disease outbreak demonstrates the need for novel applications of real-time data to produce timely information about incident cases. Using health information technology (HIT) and real-world data, we sought to produce an interface that could, in near real time, identify patients presenting with suspected respiratory tract infection and enable monitoring of test results related to specific pathogens, including severe acute respiratory syndrome coronavirus 2. This tool was built upon our computational health platform, which provides access to near real-time data from disparate HIT sources across our health system. This combination of technology allowed us to rapidly prototype, iterate, and deploy a platform to support a cohesive organizational response to a rapidly evolving outbreak. Platforms that allow for agile analytics are needed to keep pace with evolving needs within the health care system.

Evaluation of the Patient Request Process for Radiology Imaging in U.S. Hospitals.

Background In the United States, patients have the right to access their protected health information. However, to the knowledge of the authors, no study has evaluated the patient request process and the barriers to patient access of their radiology images. Purpose To assess U.S. hospital compliance with federal regulations and patient ease of access to imaging studies. Materials and Methods In this cross-sectional study conducted from June 6 to December 3, 2018, 80 U.S. hospitals were contacted by telephone to determine their patient request process for imaging studies. A scripted interview was used to simulate the patient experience in requesting imaging studies. Hospitals were compared in terms of formats of release (compact disc [CD] via pick up, CD via mail, e-mail, online patient portal, or other online access), departments from which cine files can be requested, fees, and processing times. Results All 80 hospitals stated that they could provide imaging studies on CDs. Only six (8%) hospitals provided imaging studies via e-mail and three (4%) via an online patient portal. Requests for cine files were fulfilled by a department separate from diagnostic radiology in 47 of 80 (59%) hospitals. Patient charges ranged from $0 to $75 for a single CD, no charge to $6 via e-mail, and no charge via an online patient portal. Fifty-nine (74%) hospitals stated that they could release copies within 24 hours, 10 (13%) within 2-5 days, eight (10%) within 5-10 days, and three (4%) within 10-30 days from request date. Imaging studies from outside of the diagnostic radiology department may need to be requested through the departments that performed the study. Conclusion This study demonstrated that although fees and processing times are compliant with federal regulations, patient access to imaging studies is limited primarily to compact disc format. The request process is also complicated for patients because of dispersion of imaging studies across departments. © RSNA, 2019 Online supplemental material is available for this article.

Health Care and Precision Medicine Research: Analysis of a Scalable Data Science Platform.

BACKGROUND: Health care data are increasing in volume and complexity. Storing and analyzing these data to implement precision medicine initiatives and data-driven research has exceeded the capabilities of traditional computer systems. Modern big data platforms must be adapted to the specific demands of health care and designed for scalability and growth. OBJECTIVE: The objectives of our study were to (1) demonstrate the implementation of a data science platform built on open source technology within a large, academic health care system and (2) describe 2 computational health care applications built on such a platform. METHODS: We deployed a data science platform based on several open source technologies to support real-time, big data workloads. We developed data-acquisition workflows for Apache Storm and NiFi in Java and Python to capture patient monitoring and laboratory data for downstream analytics. RESULTS: Emerging data management approaches, along with open source technologies such as Hadoop, can be used to create integrated data lakes to store large, real-time datasets. This infrastructure also provides a robust analytics platform where health care and biomedical research data can be analyzed in near real time for precision medicine and computational health care use cases. CONCLUSIONS: The implementation and use of integrated data science platforms offer organizations the opportunity to combine traditional datasets, including data from the electronic health record, with emerging big data sources, such as continuous patient monitoring and real-time laboratory results. These platforms can enable cost-effective and scalable analytics for the information that will be key to the delivery of precision medicine initiatives. Organizations that can take advantage of the technical advances found in data science platforms will have the opportunity to provide comprehensive access to health care data for computational health care and precision medicine research.

Development and validation of a continuously age-adjusted measure of patient condition for hospitalized children using the electronic medical record.

Awareness of a patient's clinical status during hospitalization is a primary responsibility for hospital providers. One tool to assess status is the Rothman Index (RI), a validated measure of patient condition for adults, based on empirically derived relationships between 1-year post-discharge mortality and each of 26 clinical measurements available in the electronic medical record. However, such an approach cannot be used for pediatrics, where the relationships between risk and clinical variables are distinct functions of patient age, and sufficient 1-year mortality data for each age group simply do not exist. We report the development and validation of a new methodology to use adult mortality data to generate continuously age-adjusted acuity scores for pediatrics. Clinical data were extracted from EMRs at three pediatric hospitals covering 105,470 inpatient visits over a 3-year period. The RI input variable set was used as a starting point for the development of the pediatric Rothman Index (pRI). Age-dependence of continuous variables was determined by plotting mean values versus age. For variables determined to be age-dependent, polynomial functions of mean value and mean standard deviation versus age were constructed. Mean values and standard deviations for adult RI excess risk curves were separately estimated. Based on the "find the center of the channel" hypothesis, univariate pediatric risk was then computed by applying a z-score transform to adult mean and standard deviation values based on polynomial pediatric mean and standard deviation functions. Multivariate pediatric risk is estimated as the sum of univariate risk. Other age adjustments for categorical variables were also employed. Age-specific pediatric excess risk functions were compared to age-specific expert-derived functions and to in-hospital mortality. AUC for 24-h mortality and pRI scores prior to unplanned ICU transfers were computed. Age-adjusted risk functions correlated well with similar functions in Bedside PEWS and PAWS. Pediatric nursing data correlated well with risk as measured by mortality odds ratios. AUC for pRI for 24-h mortality was 0.93 (0.92, 0.94), 0.93 (0.93, 0.93) and 0.95 (0.95, 0.95) at the three pediatric hospitals. Unplanned ICU transfers correlated with lower pRI scores. Moreover, pRI scores declined prior to such events. A new methodology to continuously age-adjust patient acuity provides a tool to facilitate timely identification of physiologic deterioration in hospitalized children.

"What do you know?"--knowledge among village doctors of lead poisoning in children in rural China.

BACKGROUND: This study evaluates the extent of village doctors' knowledge of lead poisoning in children in rural China and assesses the characteristics associated with possessing accurate knowledge. METHODS: A cross-sectional, questionnaire-based survey of 297 village doctors in Fenghuang County, Hunan Province, China was conducted. All village doctors were interviewed face-to-face using a "What do you know" test questionnaire focusing on prevention strategies and lead sources in rural children. RESULTS: A total of 287 (96.6%) village doctors completed the survey in full. Most village doctors had an appropriate degree of general knowledge of lead poisoning; however, they had relatively poor knowledge of lead sources and prevention measures. Village doctors with an undergraduate level education scored an average of 2.7 points higher than those who had a junior college level education (p = 0.033). Village doctors with an annual income ≤ 10,000 RMB yuan scored 1.03 points lower than those whose income was >10,001 RMB yuan. Ethnic Han village doctors scored 1.12 points higher, on average, than ethnic Tujia village doctors (p = 0.027). CONCLUSIONS: This study identified important gaps in knowledge concerning lead poisoning in children among a rural population of village doctors. There is a clear need for multifaceted interventions that target village doctors to improve their knowledge regarding lead poisoning in children. The "What do you know" questionnaire is a new tool to evaluate lead poisoning knowledge and education projects.

Cost-effectiveness of point-of-care testing for dehydration in the pediatric ED.

OBJECTIVES: Acute gastroenteritis (AGE) and subsequent dehydration account for a large proportion of pediatric emergency department (PED) visits. Point-of-care (POC) testing has been used in conjunction with clinical assessment to determine the degree of dehydration. Despite the wide acceptance of POC testing, little formal cost-effective analysis of POC testing in the PED exists. We aim to examine the cost-effectiveness of using POC electrolyte testing vs traditional serum chemistry testing in the PED for children with AGE. METHODS: This was a cost-effective analysis using data from a randomized control trial of children with AGE. A decision analysis model was constructed to calculate cost-savings from the point of view of the payer and the provider. We used parameters obtained from the trial, including cost of testing, admission rates, cost of admission, and length of stay. Sensitivity analyses were performed to evaluate the stability of our model. RESULTS: Using the data set of 225 subjects, POC testing results in a cost savings of $303.30 per patient compared with traditional serum testing from the point of the view of the payer. From the point-of-view of the provider, POC testing results in consistent mean savings of $36.32 ($8.29-$64.35) per patient. Sensitivity analyses demonstrated the stability of the model and consistent savings. CONCLUSIONS: This decision analysis provides evidence that POC testing in children with gastroenteritis-related moderate dehydration results in significant cost savings from the points of view of payers and providers compared to traditional serum chemistry testing.

Natural Language Processing - A Surveillance Stepping Stone to Identify Child Abuse.

OBJECTIVE: We aimed to refine a natural language processing (NLP) algorithm that identified injuries associated with child abuse and identify areas in which integration into a real-time clinical decision support (CDS) tool may improve clinical care. METHODS: We applied an NLP algorithm in "silent mode" to all emergency department (ED) provider notes between July 2021 and December 2022 (n = 353) at 1 pediatric and 8 general EDs. We refined triggers for the NLP, assessed adherence to clinical guidelines, and evaluated disparities in degree of evaluation by examining associations between demographic variables and abuse evaluation or reporting to child protective services. RESULTS: Seventy-three cases falsely triggered the NLP, often due to errors in interpreting linguistic context. We identified common false-positive scenarios and refined the algorithm to improve NLP specificity. Adherence to recommended evaluation standards for injuries defined by nationally accepted clinical guidelines was 63%. There were significant demographic differences in evaluation and reporting based on presenting ED type, insurance status, and race and ethnicity. CONCLUSIONS: Analysis of an NLP algorithm in "silent mode" allowed for refinement of the algorithm and highlighted areas in which real-time CDS may help ED providers identify and pursue appropriate evaluation of injuries associated with child physical abuse.

Is dexamethasone-induced muscle atrophy an alternative model for naturally aged sarcopenia model?

Background: Primary sarcopenia is usually known as age-related skeletal muscle loss; however, other factors like endocrine, lifestyle and inflammation can also cause muscle loss, known as secondary sarcopenia. Although many studies have used different sarcopenia animal models for exploring the underlying mechanism and therapeutic approaches for sarcopenia, limited study has provided evidence of the relevance of these animal models. This study aims to investigate the similarity and difference in muscle qualities between primary and secondary sarcopenia mice models, using naturally aged mice and dexamethasone-induced mice. Methods: 21-month-old mice were used as naturally aged primary sarcopenia mice and 3-month-old mice received daily intraperitoneal injection of dexamethasone (20 mg/ kg body weight) for 10 days were used as secondary sarcopenia model. This study provided measurements for muscle mass and functions, including Dual-energy X-ray absorptiometry (DXA) scanning, handgrip strength test and treadmill running to exhaustion test. Besides, muscle contraction, muscle fibre type measurements and gene expression were also performed to provide additional information on muscle qualities. Results: The results suggest two sarcopenia animal models shared a comparable decrease in forelimb lean mass, muscle fibre size, grip strength and muscle contraction ability. Besides, the upregulation of protein degradation genes was also observed in two sarcopenia animal models. However, only primary sarcopenia mice were identified with an early stage of mtDNA deletion. Conclusion: Collectively, this study evaluated that the dexamethasone-induced mouse model could be served as an alternative model for primary sarcopenia, according to the comparable muscle mass and functional changes. However, whether dexamethasone-induced mice can be used as an animal model when studying the molecular mechanisms of sarcopenia needs to be carefully evaluated. The translational potential of this article: The purpose of sarcopenia research is to investigate appropriate treatments for reversing the loss of skeletal muscle mass and functions. Using animal models for the preclinical study could predict the safety and efficacy of the treatments. This study compared the typical age-related sarcopenia mice model and dexamethasone-induced secondary sarcopenia mice to provide evidence of the pathological and functional changes in the mice models.

Use of an Automated Bilingual Digital Health Tool to Reduce Unhealthy Alcohol Use Among Latino Emergency Department Patients: A Randomized Clinical Trial.

Importance: Alcohol use disorders have a high disease burden among US Latino groups. In this population, health disparities persist, and high-risk drinking has been increasing. Effective bilingual and culturally adapted brief interventions are needed to identify and reduce disease burden. Objective: To compare the effectiveness of an automated bilingual computerized alcohol screening and intervention (AB-CASI) digital health tool with standard care for the reduction of alcohol consumption among US adult Latino emergency department (ED) patients with unhealthy drinking. Design, Setting, and Participants: This bilingual unblinded parallel-group randomized clinical trial evaluated the effectiveness of AB-CASI vs standard care among 840 self-identified adult Latino ED patients with unhealthy drinking (representing the full spectrum of unhealthy drinking). The study was conducted from October 29, 2014, to May 1, 2020, at the ED of a large urban community tertiary care center in the northeastern US that was verified as a level II trauma center by the American College of Surgeons. Data were analyzed from May 14, 2020, to November 24, 2020. Intervention: Patients randomized to the intervention group received AB-CASI, which included alcohol screening and a structured interactive brief negotiated interview in their preferred language (English or Spanish) while in the ED. Patients randomized to the standard care group received standard emergency medical care, including an informational sheet with recommended primary care follow-up. Main Outcomes and Measures: The primary outcome was the self-reported number of binge drinking episodes within the last 28 days, assessed by the timeline followback method at 12 months after randomization. Results: Among 840 self-identified adult Latino ED patients (mean [SD] age, 36.2 [11.2] years; 433 [51.5%] male; and 697 [83.0%] of Puerto Rican descent), 418 were randomized to the AB-CASI group and 422 to the standard care group. A total of 443 patients (52.7%) chose Spanish as their preferred language at enrollment. At 12 months, the number of binge drinking episodes within the last 28 days was significantly lower in those receiving AB-CASI (3.2; 95% CI, 2.7-3.8) vs standard care (4.0; 95% CI, 3.4-4.7; relative difference [RD], 0.79; 95% CI, 0.64-0.99). Alcohol-related adverse health behaviors and consequences were similar between groups. The effect of AB-CASI was modified by age; at 12 months, the relative reduction in the number of binge drinking episodes within the last 28 days in the AB-CASI vs standard care group was 30% in participants older than 25 years (RD, 0.70; 95% CI, 0.54-0.89) compared with an increase of 40% in participants 25 years or younger (RD, 1.40; 95% CI, 0.85-2.31; P = .01 for interaction). Conclusions and Relevance: In this study, US adult Latino ED patients who received AB-CASI had a significant reduction in the number of binge drinking episodes within the last 28 days at 12 months after randomization. These findings suggest that AB-CASI is a viable brief intervention that overcomes known procedural barriers to ED screening, brief intervention, and referral to treatment and directly addresses alcohol-related health disparities. Trial Registration: ClinicalTrials.gov Identifier: NCT02247388.

Real-World Observational Evaluation of Common Interventions to Reduce Emergency Department Prescribing of Opioid Medications.

BACKGROUND: Prior work on opioid prescribing has examined dosing defaults, interruptive alerts, or "harder" stops such as electronic prescribing of controlled substances (EPCS), which has become increasingly required by state policy. Given that real-world opioid stewardship policies are concurrent and overlapping, the authors examined the effect of such policies on emergency department (ED) opioid prescriptions. METHODS: The researchers performed observational analysis of all ED visits discharged between December 17, 2016, and December 31, 2019, across seven EDs of a hospital system. Four interventions were examined in chronological order, with each successive intervention added on top of all previous interventions: 12-pill prescription default, EPCS, electronic health record (EHR) pop-up alert, and 8-pill prescription default. The primary outcome was opioid prescribing, which was described as number of opioid prescriptions per 100 discharged ED visits and modeled as a binary outcome for each visit. Secondary outcomes included prescription morphine milligram equivalents (MME) and non-opioid analgesia prescriptions. RESULTS: A total of 775,692 ED visits were included in the study. Compared to the preintervention period, cumulative reductions in opioid prescribing were seen with incremental interventions, including after adding a 12-pill default (odds ratio [OR] 0.88, 95% confidence interval [CI] 0.82-0.94), after adding EPCS (OR 0.7, 95% CI 0.63-0.77), after adding pop-up alerts (OR 0.67, 95% CI 0.63-0.71), and after adding an 8-pill default (OR 0.61, 95% CI 0.58-0.65). CONCLUSION: EHR-implemented solutions such as EPCS, pop-up alerts, and pill defaults had varying but significant effects on reducing ED opioid prescribing. Policy makers and quality improvement leaders might achieve sustainable improvements in opioid stewardship while balancing clinician alert fatigue through policy efforts promoting implementation of EPCS and default dispense quantities.

Ginkgolide B facilitates muscle regeneration via rejuvenating osteocalcin-mediated bone-to-muscle modulation in aged mice.

BACKGROUND: The progressive deterioration of tissue-tissue crosstalk with aging causes a striking impairment of tissue homeostasis and functionality, particularly in the musculoskeletal system. Rejuvenation of the systemic and local milieu via interventions such as heterochronic parabiosis and exercise has been reported to improve musculoskeletal homeostasis in aged organisms. We have shown that Ginkgolide B (GB), a small molecule from Ginkgo biloba, improves bone homeostasis in aged mice by restoring local and systemic communication, implying a potential for maintaining skeletal muscle homeostasis and enhancing regeneration. In this study, we investigated the therapeutic efficacy of GB on skeletal muscle regeneration in aged mice. METHODS: Muscle injury models were established by barium chloride induction into the hind limb of 20-month-old mice (aged mice) and into C2C12-derived myotubes. Therapeutic efficacy of daily administrated GB (12 mg/kg body weight) and osteocalcin (50 µg/kg body weight) on muscle regeneration was assessed by histochemical staining, gene expression, flow cytometry, ex vivo muscle function test and rotarod test. RNA sequencing was used to explore the mechanism of GB on muscle regeneration, with subsequent in vitro and in vivo experiments validating these findings. RESULTS: GB administration in aged mice improved muscle regeneration (muscle mass, P = 0.0374; myofiber number/field, P = 0.0001; centre nucleus, embryonic myosin heavy chain-positive myofiber area, P = 0.0144), facilitated the recovery of muscle contractile properties (tetanic force, P = 0.0002; twitch force, P = 0.0005) and exercise performance (rotarod performance, P = 0.002), and reduced muscular fibrosis (collagen deposition, P < 0.0001) and inflammation (macrophage infiltration, P = 0.03). GB reversed the aging-related decrease in the expression of osteocalcin (P < 0.0001), an osteoblast-specific hormone, to promote muscle regeneration. Exogenous osteocalcin supplementation was sufficient to improve muscle regeneration (muscle mass, P = 0.0029; myofiber number/field, P < 0.0001), functional recovery (tetanic force, P = 0.0059; twitch force, P = 0.07; rotarod performance, P < 0.0001) and fibrosis (collagen deposition, P = 0.0316) in aged mice, without an increased risk of heterotopic ossification. CONCLUSIONS: GB treatment restored the bone-to-muscle endocrine axis to reverse aging-related declines in muscle regeneration and thus represents an innovative and practicable approach to managing muscle injuries. Our results revealed the critical and novel role of osteocalcin-GPRC6A-mediated bone-to-muscle communication in muscle regeneration, which provides a promising therapeutic avenue in functional muscle regeneration.

Mesenchymal stem cells alleviate dexamethasone-induced muscle atrophy in mice and the involvement of ERK1/2 signalling pathway.

BACKGROUND: High dosage of dexamethasone (Dex) is an effective treatment for multiple diseases; however, it is often associated with severe side effects including muscle atrophy, resulting in higher risk of falls and poorer life quality of patients. Cell therapy with mesenchymal stem cells (MSCs) holds promise for regenerative medicine. In this study, we aimed to investigate the therapeutic efficacy of systemic administration of adipose-derived mesenchymal stem cells (ADSCs) in mitigating the loss of muscle mass and strength in mouse model of DEX-induced muscle atrophy. METHODS: 3-month-old female C57BL/6 mice were treated with Dex (20 mg/kg body weight, i.p.) for 10 days to induce muscle atrophy, then subjected to intravenous injection of a single dose of ADSCs ([Formula: see text] cells/kg body weight) or vehicle control. The mice were killed 7 days after ADSCs treatment. Body compositions were measured by animal DXA, gastrocnemius muscle was isolated for ex vivo muscle functional test, histological assessment and Western blot, while tibialis anterior muscles were isolated for RNA-sequencing and qPCR. For in vitro study, C2C12 myoblast cells were cultured under myogenic differentiation medium for 5 days following 100 [Formula: see text]M Dex treatment with or without ADSC-conditioned medium for another 4 days. Samples were collected for qPCR analysis and Western blot analysis. Myotube morphology was measured by myosin heavy chain immunofluorescence staining. RESULTS: ADSC treatment significantly increased body lean mass (10-20%), muscle wet weight (15-30%) and cross-sectional area (CSA) (~ 33%) in DEX-induced muscle atrophy mice model and down-regulated muscle atrophy-associated genes expression (45-65%). Hindlimb grip strength (~ 37%) and forelimb ex vivo muscle contraction property were significantly improved (~ 57%) in the treatment group. Significant increase in type I fibres (~ 77%) was found after ADSC injection. RNA-sequencing results suggested that ERK1/2 signalling pathway might be playing important role underlying the beneficial effect of ADSC treatment, which was confirmed by ERK1/2 inhibitor both in vitro and in vivo. CONCLUSIONS: ADSCs restore the pathogenesis of Dex-induced muscle atrophy with an increased number of type I fibres, stronger muscle strength, faster recovery rate and more anti-fatigue ability via ERK1/2 signalling pathway. The inhibition of muscle atrophy-associated genes by ADSCs offered this treatment as an intervention option for muscle-associated diseases. Taken together, our findings suggested that adipose-derived mesenchymal stem cell therapy could be a new treatment option for patient with Dex-induced muscle atrophy.

Bioactive glass-elicited stem cell-derived extracellular vesicles regulate M2 macrophage polarization and angiogenesis to improve tendon regeneration and functional recovery.

Effective countermeasures for tendon injury remains unsatisfactory. Mesenchymal stem cell-derived extracellular vesicles (MSC-EVs)-based therapy via regulation of Mφ-mediated angiogenesis has emerged as a promising strategy for tissue regeneration. Still, approaches to tailor the functions of EVs to treat tendon injuries have been limited. We reported a novel strategy by applying MSC-EVs boosted with bioactive glasses (BG). BG-elicited EVs (EVB) showed up-regulation of medicinal miRNAs, including miR-199b-3p and miR-125a-5p, which play a pivotal role in M2 Mφ-mediated angiogenesis. EVB accelerated angiogenesis via the reprogrammed anti-inflammatory M2 Mφs compared with naïve MSC-EVs (EVN). In rodent Achilles tendon rupture model, EVB local administration activated anti-inflammatory responses via M2 polarization and led to a spatial correlation between M2 Mφs and newly formed blood vessels. Our results showed that EVB outperformed EVN in promoting tenogenesis and in reducing detrimental morphological changes without causing heterotopic ossification. Biomechanical test revealed that EVB significantly improved ultimate load, stiffness, and tensile modulus of the repaired tendon, along with a positive correlation between M2/M1 ratio and biomechanical properties. On the basis of the boosted nature to reprogram regenerative microenvironment, EVB holds considerable potential to be developed as a next-generation therapeutic modality for enhancing functional regeneration to achieve satisfying tendon regeneration.

Diagnosis of intussusception by physician novice sonographers in the emergency department.

STUDY OBJECTIVE: We investigate the performance characteristics of bedside emergency department (ED) ultrasonography by nonradiologist physician sonographers in the diagnosis of ileocolic intussusception in children. METHODS: This was a prospective, observational study conducted in a pediatric ED of an urban tertiary care children's hospital. Pediatric emergency physicians with no experience in bowel ultrasonography underwent a focused 1-hour training session conducted by a pediatric radiologist. The session included a didactic component on sonographic appearances of ileocolic intussusception, review of images with positive and negative results for intussusceptions, and a hands-on component with a live child model. On completion of the training, a prospective convenience sample study was performed. Children were enrolled if they were to undergo diagnostic radiology ultrasonography for suspected intussusception. Bedside ultrasonography by trained pediatric emergency physicians was performed and interpreted as either positive or negative for ileocolic intussusception. Ultrasonographic studies were then performed by diagnostic radiologists, and their results were used as the reference standard. Test characteristics (sensitivity, specificity, positive and negative predictive values) and likelihood ratios were calculated. RESULTS: Six pediatric emergency physicians completed the training and performed the bedside studies. Eighty-two patients were enrolled. The median age was 25 months (range 3 to 127 months). Thirteen patients (16%) received a diagnosis of ileocolic intussusception by diagnostic radiology. Bedside ultrasonography had a sensitivity of 85% (95% confidence interval [CI] 54% to 97%), specificity of 97% (95% CI 89% to 99%), positive predictive value of 85% (95% CI 54% to 97%), and negative predictive value of 97% (95% CI 89% to 99%). A positive bedside ultrasonographic result had a likelihood ratio of 29 (95% CI 7.3 to 117), and a negative bedside ultrasonographic result had a likelihood ratio of 0.16 (95% CI 0.04 to 0.57). CONCLUSION: With limited and focused training, pediatric emergency physicians can accurately diagnose ileocolic intussusception in children by using bedside ultrasonography.