Incidence, causative organisms, and risk factors of bloodstream infections in pediatric liver transplant patients: a systematic review.

Bacterial bloodstream infections (BSI) are the leading cause of mortality and morbidity in pediatric solid organ transplant recipients. This systematic review aimed to pool global data from leading transplant institutions and identify the overall incidence, risk factors, and causative organisms of BSI in pediatric liver transplant recipients. A systematic review of the PubMed and OVID databases was conducted from 2000 to 2022. The initial search yielded 252 unique articles, which were independently reviewed by 2 authors. Articles that reported pediatric-specific data on BSI in isolated liver transplant patients were included, including the incidence of BSI, isolated organisms, and involved risk factors involved. This systematic review was registered with PROSPERO (ID: CRD42023403206). Fourteen articles from the United States, France, Iran, Japan, Korea, South Africa, Thailand, and Turkey were included. A total of 4,812 liver transplants were included in the final analysis. The mean patient age was 25 months (age range, 0-18 years), and 50.9% were male. The overall incidence of BSI was 23.5% (range, 14.7%-55%). The most commonly reported organisms were Staphylococcus epidermidis, Enterococcus, Klebsiella spp., and Escherichia coli. Among the risk factors studied, postoperative biliary complications, a medical history of biliary atresia, and younger age were the risk factors most commonly associated with BSI. Bacterial BSI after pediatric liver transplantation occur at a high incidence, with a unique organism profile notable for a higher percentage of gram-negative organisms. Further studies are required to determine the most appropriate prophylactic and empirical antibiotic management strategies for this population.

Multicenter evaluation of the Selux Next-Generation Phenotyping antimicrobial susceptibility testing system.

The Selux Next-Generation Phenotyping (NGP) system (Charlestown, MA) is a new antimicrobial susceptibility testing system that utilizes two sequential assays performed on all wells of doubling dilution series to determine MICs. A multicenter evaluation of the performance of the Selux NGP system compared with reference broth microdilution was conducted following FDA recommendations and using FDA-defined breakpoints. A total of 2,488 clinical and challenge isolates were included; gram-negative isolates were tested against 24 antimicrobials, and gram-positive isolates were tested against 15 antimicrobials. Data is provided for all organism-antimicrobial combinations evaluated, including those that did and did not meet FDA performance requirements. Overall very major error and major error rates were less than 1% (31/3,805 and 107/15,606, respectively), essential agreement and categorical agreement were >95%, reproducibility was ≥95%, and the average time-to-result (from time of assay start to time of MIC result) was 5.65 hours.

Validation of American Society of Echocardiography Guideline-Recommended Parameters of Right Ventricular Dysfunction Using Artificial Intelligence Compared With Cardiac Magnetic Resonance Imaging.

BACKGROUND: Right ventricular (RV) function is important in the evaluation of cardiac function, but its assessment using standard transthoracic echocardiography (TTE) remains challenging. Cardiac magnetic resonance imaging (CMR) is considered the gold standard. The American Society of Echocardiography recommends surrogate measures of RV function and RV ejection fraction (RVEF) by TTE, including fractional area change (FAC), free wall strain (FWS), and tricuspid annular planar systolic excursion (TAPSE), but they require technical expertise in acquisition and quantification. METHODS: The aim of this study was to evaluate the sensitivity, specificity, and positive and negative predictive values of FAC, FWS, and TAPSE derived using a rapid, novel artificial intelligence (AI) software (LVivoRV) from a single-plane transthoracic echocardiographic apical four-chamber, RV-focused view without ultrasound-enhancing agents for detecting abnormal RV function compared with CMR-derived RVEF. RV dysfunction was defined as RVEF < 50% and RVEF < 40% on CMR. RESULTS: TTE and CMR were performed within a median of 10 days (interquartile range, 2-32 days) of each other in 225 consecutive patients without interval procedural or pharmacologic intervention. The sensitivity and negative predictive value to detect CMR-defined RV dysfunction when all three AI-derived parameters (FAC, FWS, and TAPSE) were abnormal were 91% and 96%, while those of expert physician reads were 91% and 97%. Specificity and positive predictive value were lower (50% and 32%) compared with expert physician-read echocardiograms (82% and 56%). CONCLUSIONS: AI-derived measurements of FAC, FWS, and TAPSE had excellent sensitivity and negative predictive value for ruling out significant RV dysfunction (CMR RVEF < 40%), comparable with that of expert physician readers, but lower specificity. Thus AI, using American Society of Echocardiography guidelines, may serve as a useful screening tool for rapid bedside assessment to exclude significant RV dysfunction.

The Trump Administration and the COVID-19 crisis: Exploring the warning-response problems and missed opportunities of a public health emergency.

This article examines the Trump Administration's inability to mount a timely and effective response to the COVID-19 outbreak, despite ample warning. Through an empirical exploration guided by three explanatory perspectives-psychological, bureau-organizational, and agenda-political-developed from the strategic surprise, public administration, and crisis management literature, the authors seek to shed light on the mechanisms that contributed to the underestimation of the coronavirus threat by the Trump Administration and the slow and mismanaged federal response. The analysis highlights the extent to which the factors identified by previous studies of policy surprise and failure in other security domains are relevant for health security. The paper concludes by addressing the crucial role of executive leadership as an underlying factor in all three perspectives and discussing why the US president is ultimately responsible for ensuring a healthy policy process to guard against the pathologies implicated in the federal government's sub-optimal response to the COVID-19 crisis.

Assessment and validation of a novel fast fully automated artificial intelligence left ventricular ejection fraction quantification software.

BACKGROUND: Quantification of left ventricular ejection fraction (LVEF) by transthoracic echocardiography (TTE) is operator-dependent, time-consuming, and error-prone. LVivoEF by DIA is a new artificial intelligence (AI) software, which displays the tracking of endocardial borders and rapidly quantifies LVEF. We sought to assess the accuracy of LVivoEF compared to cardiac magnetic resonance imaging (cMRI) as the reference standard and to compare LVivoEF to the standard-of-care physician-measured LVEF (MD-EF) including studies with ultrasound enhancing agents (UEAs). METHODS: In 273 consecutive patients, we compared MD-EF and AI-derived LVEF to cMRI. AI-derived LVEF was obtained from a non-UEA four-chamber view without manual correction. Thirty-one patients were excluded: 25 had interval interventions or incomplete TTE or cMRI studies and six had uninterpretable non-UEA apical views. RESULTS: In the 242 subjects, the correlation between AI and cMRI was r = .890, similar to MD-EF and cMRI with r = .891 (p = 0.48). Of the 126 studies performed with UEAs, the correlation of AI using the unenhanced four-chamber view was r = .89, similar to MD-EF with r = .90. In the 116 unenhanced studies, AI correlation was r = .87, similar to MD-EF with r = .84. From Bland-Altman analysis, LVivoEF underreported the LVEF with a bias of 3.63 ± 7.40% EF points compared to cMRI while MD-EF to cMRI had a bias of .33 ± 7.52% (p = 0.80). CONCLUSIONS: Compared to cMRI, LVivoEF can accurately quantify LVEF from a standard apical four-chamber view without manual correction. Thus, LVivoEF has the ability to improve and expedite LVEF quantification.

Echocardiography in the time of Covid-19: Ultrasound enhancing agents save time and augment diagnostic information.

BACKGROUND: There are currently no clear guidelines regarding the use of ultrasound enhancing agents (UEAs) with transthoracic echocardiography (TTE) for patients hospitalized with Covid-19. We investigated whether the performance of TTE with UEAs provides more diagnostic information and allows for shorter acquisition time compared to unenhanced TTE imaging in this patient population. METHODS: We analyzed the TTEs of 107 hospitalized Covid-19 patients between April and June 2020 who were administered UEAs (Definity®, Lantheus). The time to acquire images with and without UEAs was calculated. A level III echocardiographer determined if new, clinically significant findings were visualized with the addition of UEAs. RESULTS: There was a mean of 11.84±3.59 UEA cineloops/study vs 20.74±8.10 non-UEA cineloops/study (p < 0.0001). Mean time to acquire UEA cineloop images was 72.28±28.18 s/study compared to 188.07±86.04 s/study for non-UEA cineloop images (p < 0.0001). Forty-eight patients (45%) had at least one new finding on UEA imaging, with a total of 62 new findings seen. New information gained with UEAs was more likely to be found in patients with acute respiratory distress syndrome (21 vs 9, p < 0.001) and in those on mechanical ventilation (21 vs 15, p = 0.046). CONCLUSIONS: TTE with UEAs required less time and fewer cineloop images compared to non-UEA imaging in patients hospitalized with Covid-19. Additionally, Covid-19 patients with severe respiratory disease benefited most with regard to new diagnostic information. Health care personnel should consider early use of UEAs in select hospitalized Covid-19 patients in order to reduce exposure and optimize diagnostic yield.

How neighborhood environment modified the effects of power outages on multiple health outcomes in New York state?

Background: Although power outage (PO) is one of the most important consequences of increasing weather extremes and the health impact of POs has been reported previously, studies on the neighborhood environment underlying the population vulnerability in such situations are limited. This study aimed to identify dominant neighborhood environmental predictors which modified the impact of POs on multiple health outcomes in New York State. Methods: We applied a two-stage approach. In the first stage, we used time series analysis to determine the impact of POs (versus non-PO periods) on multiple health outcomes in each power operating division in New York State, 2001-2013. In the second stage, we classified divisions as risk-elevated and non-elevated, then developed predictive models for the elevation status based on 36 neighborhood environmental factors using random forest and gradient boosted trees. Results: Consistent across different outcomes, we found predictors representing greater urbanization, particularly, the proportion of residents having access to public transportation (importance ranging from 4.9-15.6%), population density (3.3-16.1%), per capita income (2.3-10.7%), and the density of public infrastructure (0.8-8.5%), were associated with a higher possibility of risk elevation following power outages. Additionally, the percent of minority (-6.3-27.9%) and those with limited English (2.2-8.1%), the percent of sandy soil (6.5-11.8%), and average soil temperature (3.0-15.7%) were also dominant predictors for multiple outcomes. Spatial hotspots of vulnerability generally were located surrounding New York City and in the northwest, the pattern of which was consistent with socioeconomic status. Conclusion: Population vulnerability during power outages was dominated by neighborhood environmental factors representing greater urbanization.

Correction and calibration of atmospheric impact observations in GOES GLM data.

The Earth's atmosphere is impacted daily by both meteoroids and artificial objects. Calibrated observations of the emitted light at sufficiently high sampling rates can enable or improve the estimation of impactor attributes such as size, cohesion, trajectory, and composition, but are difficult to obtain owing to the unpredictability, brevity, and high dynamic (brightness) range of impacts. Ground-based camera systems have successfully monitored small regions of the atmosphere at video frame rates and with limited radiometric capabilities, but most impacts occur over the 70% of the Earth's surface covered by water and are therefore missed by these networks. The Geostationary Lightning Mapper (GLM) instruments aboard Geostationary Operational Environmental Satellites 16 and 17 provide near-hemispherical coverage at 500 frames per second. These data have been shown to contain the signatures of many independently confirmed impacts, often from both viewing angles simultaneously, and constitute an observational resource that is currently unparalleled in the public domain. NASA's Asteroid Threat Assessment Project has implemented an automated impact detection pipeline that processes data from GLM daily. Given a detected impact, the GLM data contain a wealth of information for use in quantitative follow-up analyses. However, impact events differ from lightning in ways that violate key assumptions built into GLM's design. The result is that GLM's onboard processing introduces errors into pixel observations of impact events and the calibrated energies near the periphery of the detector may be substantially overestimated. We present methods for mitigating these and other issues to produce a data product more suitable for impact analyses than the existing GLM lightning product.

The immediate effects of winter storms and power outages on multiple health outcomes and the time windows of vulnerability.

BACKGROUND: While most prior research has focused on extreme heat, few assessed the immediate health effects of winter storms and associated power outages (PO), although severe storms have become more frequent. This study evaluates the joint and independent health effects of winter storms and PO, snow versus ice-storm, effects by time window (peak timing, winter/transitional months) and the impacts on critical care indicators including numbers of comorbidity, procedure, length of stay and cost. METHODS: We use distributed lag nonlinear models to assess the impacts of winter storm/PO on hospitalizations due to cardiovascular, lower respiratory diseases (LRD), respiratory infections, food/water-borne diseases (FWBD) and injuries in New York State on 0-6 lag days following storm/PO compared with non-storm/non-PO periods (references), while controlling for time-varying factors and PM2.5. The storm-related hospitalizations are described by time window. We also calculate changes in critical care indicators between the storm/PO and control periods. RESULTS: We found the joint effects of storm/PO are the strongest (risk ratios (RR) range: 1.01-1.90), followed by that of storm alone (1.02-1.39), but not during PO alone. Ice storms have stronger impacts (RRs: 1.04-3.15) than snowstorms (RRs: 1.03-2.21). The storm/PO-health associations, which occur immediately, and some last a whole week, are stronger in FWBD, October/November, and peak between 3:00-8:00 p.m. Comorbidity and medical costs significantly increase after storm/PO. CONCLUSION: Winter storms increase multiple diseases, comorbidity and medical costs, especially when accompanied by PO or ice storms. Early warnings and prevention may be critical in the transitional months and afternoon rush hours.

Longitudinal Risk Communication: A Research Agenda for Communicating in a Pandemic.

In this paper, we present a research agenda for longitudinal risk communication during a global pandemic. Starting from an understanding that traditional approaches to risk communication for epidemics, crises, and disasters have focused on short-duration events, we acknowledge the limitations of existing theories, frameworks, and models for both research and practice in a rapidly changing communication environment. We draw from scholarship in communication, sociology, anthropology, public health, emergency management, law, and technology to identify research questions that are fundamental to the communication challenges that have emerged under the threat of COVID-19. We pose a series of questions focused around 5 topics, then offer a catalog of prior research to serve as points of departure for future research efforts. This compiled agenda offers guidance to scholars engaging in practitioner-informed research and provides risk communicators with a set of substantial research questions to guide future knowledge needs.

Macroprolactinemia Detection by Magnetically Assisted Polyethylene Glycol Precipitation: Potential for Automation.

BACKGROUND: Macroprolactin is an immunoglobulin-prolactin complex that is not bioactive in vivo but the prolactin component remains immunoreactive. The complex is a universal source of interference in prolactin immunoassays and commonly results in misdiagnosis of hyperprolactinemia with consequent clinical mismanagement of patients. Removal of macroprolactin by precipitation with polyethylene glycol (PEG) is an effective technique for identifying such patients but unfortunately not universally employed due to the manual nature of the procedure. METHODS: We developed a modified PEG precipitation technique using magnetic nanoparticles that we termed Magnetically Assisted PEG Precipitation (MAPP). This procedure was verified against an established PEG precipitation procedure. RESULTS: The MAPP procedure we developed was robust, reproducible, and affords the potential for automation of macroprolactin screening in clinical laboratories. Comparisons of prolactin levels obtained following MAPP in sera from patients with either true hyperprolactinemia or macroprolactinemia generated results comparable to that of conventional PEG precipitation. CONCLUSIONS: The MAPP technique yields results comparable to those of traditional PEG precipitation. Elimination of the need for centrifugation affords the possibility of automation and hence more widespread adoption of routine PEG screening by clinical laboratories.

How community vulnerability factors jointly affect multiple health outcomes after catastrophic storms.

BACKGROUND: While previous studies uncovered individual vulnerabilities to health risks during catastrophic storms, few evaluated the population vulnerability which is more important for identifying areas in greatest need of intervention. OBJECTIVES: We assessed the association between community factors and multiple health outcomes, and developed a community vulnerability index. METHODS: We retained emergency department visits for several health conditions from the 2005-2014 New York Statewide Planning and Research Cooperative System. We developed distributed lag nonlinear models at each spatial cluster across eight counties in downstate New York to evaluate the health risk associated with Superstorm Sandy (10/28/2012-11/9/2012) compared to the same period in other years, then defined census tracts in clusters with an elevated risk as "risk-elevated communities", and all others as "unelevated". We used machine-learning techniques to regress the risk elevation status against community factors to determine the contribution of each factor on population vulnerability, and developed a community vulnerability index (CVI). RESULTS: Overall, community factors had positive contributions to increased community vulnerabilities to Sandy-related substance abuse (91.35%), injuries (70.51%), cardiovascular diseases (8.01%), and mental disorders (2.71%) but reversely contributed to respiratory diseases (-34.73%). The contribution of low per capita income (max: 22.08%), the percentage of residents living in group quarters (max: 31.39%), the percentage of areas prone to flooding (max: 38.45%), and the percentage of green coverage (max: 29.73%) tended to be larger than other factors. The CVI based on these factors achieved an accuracy of 0.73-0.90 across outcomes. CONCLUSIONS: Our findings suggested that substance abuse was the most sensitive disease susceptible to less optimal community indicators, whereas respiratory diseases were higher in communities with better social environment. The percentage of residents in group quarters and areas prone to flooding were among dominant predictors for community vulnerabilities. The CVI based on these factors has an appropriate predictive performance.

Microplate-based surface area assay for rapid phenotypic antibiotic susceptibility testing.

Rapid delivery of proper antibiotic therapies to infectious disease patients is essential for improving patient outcomes, decreasing hospital lengths-of-stay, and combating the antibiotic resistance epidemic. Antibiotic stewardship programs are designed to address these issues by coordinating hospital efforts to rapidly deliver the most effective antibiotics for each patient, which requires bacterial identification and antimicrobial susceptibility testing (AST). Despite the clinical need for fast susceptibility testing over a wide range of antibiotics, conventional phenotypic AST requires overnight incubations, and new rapid phenotypic AST platforms restrict the number of antibiotics tested for each patient. Here, we introduce a novel approach to AST based on signal amplification of bacterial surfaces that enables phenotypic AST within 5 hours for non-fastidious bacteria. By binding bacterial surfaces, this novel method allows more accurate measurements of bacterial replication in instances where organisms filament or swell in response to antibiotic exposure. Further, as an endpoint assay performed on standard microplates, this method should enable parallel testing of more antibiotics than is currently possible with available automated systems. This technology has the potential to revolutionize clinical practice by providing rapid and accurate phenotypic AST data for virtually all available antibiotics in a single test.

A Sleep Medicine Curriculum for Pulmonary and Pulmonary/Critical Care Fellowship Programs: A Multisociety Expert Panel Report.

BACKGROUND: Pulmonary medicine specialists find themselves responsible for the diagnosis and management of patients with sleep disorders. Despite the increasing prevalence of many of these conditions, many sleep medicine fellowship training slots go unfilled, leading to a growing gap between the volume of patients seeking care for sleep abnormalities and the number of physicians formally trained to manage them. To address this need, we convened a multisociety panel to develop a list of curricular recommendations related to sleep medicine for pulmonary fellowship training programs. METHODS: Surveys of pulmonary and pulmonary/critical care fellowship program directors and recent graduates of these programs were performed to assess the current state of sleep medicine education in pulmonary training, as well as the current scope of practice of pulmonary specialists. These data were used to inform a modified Delphi process focused on developing curricular recommendations relevant to sleep medicine. RESULTS: Surveys confirmed that pulmonary medicine specialists are often responsible for the diagnosis and treatment of a number of sleep conditions, including several that are not traditionally considered related to respiratory medicine. Through five rounds of voting, the panel crafted a list of 52 curricular competencies relevant to sleep medicine for recommended inclusion in pulmonary training programs. CONCLUSIONS: Practicing pulmonary specialists require a broad knowledge of sleep medicine to provide appropriate care to patients they will be expected to manage. Training program directors may use the list of competencies as a framework to ensure adequate mastery of important content by graduating fellows.

2017 ACR Annual Meeting Open-Microphone Session: Navigating the Landscape of Changing Practice Models: Private Practice, Corporate Radiology, and Enterprise Systems.

Many practice groups are considering adopting new practice models, primarily to secure their practices by adapting to new payment models, government compliance and regulation, and increasing IT and infrastructure costs. As we move toward value-based care and capitation, the value equation (value = quality/cost) will lead us to also compete on cost to improve value. No matter what payment models ultimately dominate, we need to be prepared to lead in a value-based care environment. Measures of value will either be defined by radiologists or imposed by outside entities. It is critical to our continued success that practices and practice leaders continue to fully and strongly support the ACR to avoid the possibility of a decline in membership that may accompany a lack of practice engagement. Consolidation appears inevitable, but with the help of the ACR, radiologists should have a vibrant future if investments are made now in determining appropriate radiology-specific value measures that are meaningful in consolidated health care environments.

Crus Atrophy: Accuracy of Computed Tomography in Diagnosis of Diaphragmatic Paralysis.

PURPOSE: The aim of this study was to measure the association between crus atrophy as depicted by computed tomography (CT) and fluoroscopic diagnosis of hemidiaphragmatic paralysis in patients with suspected diaphragmatic dysfunction. MATERIALS AND METHODS: A retrospective review of patient data was approved by our institutional review board and was HIPPA-compliant. We reviewed 90 patients who had undergone diaphragmatic fluoroscopy; 72 had CT scans available for measurement of crus thickness at the levels of the celiac and superior mesenteric arteries and the L1 vertebral body. Receiver operating characteristic analysis was used to determine the threshold of crus thinning that best distinguished a paralyzed hemidiaphragm from a nonparalyzed one. RESULTS: Hemidiaphragmatic paralysis caused significant crus thinning at the celiac artery level (mean±SD, 1.7±0.6 vs. 3.6±1.3 mm, P=0.017, on the right; 1.1±0.4 vs. 3.0±1.4 mm, P=0.001, on the left) and the L1 vertebral level (mean±SD, 1.5±0.7 vs. 4.4±1.6 mm, P=0.018, on the right; 1.5±0.6 vs. 3.6+1.7 mm, P=0.017, on the left). On axial CT, thinning to ≤2.5 mm at the celiac artery level identified paralysis of the hemidiaphragm with a sensitivity of 100% and a specificity of 86% on the right and with a sensitivity of 100% and a specificity of 64% on the left. On coronal CT, thinning to ≤2.5 mm at the L1 vertebral level identified paralysis of the hemidiaphragm with a sensitivity of 100% and a specificity of 88% on the right and with a sensitivity of 100% and a specificity of 77% on the left. CONCLUSIONS: Atrophy of the crus assessed by CT is a good discriminator of paralyzed versus nonparalyzed hemidiaphragm in patients with suspected diaphragmatic dysfunction.

ACR 2016 Open-Microphone Session: ACR Membership 3.0-Moving From Member Volume to Value.

This report of the 2016 ACR Council Open Microphone session reviews the discussion around interests and concerns of council members and state chapter leaders as to the perceived and real value of their ACR membership, and how the ACR might further enhance membership value and meaningful engagement with members.

ACR CT Accreditation Program and the Lung Cancer Screening Program Designation.

The ACR recognizes that low-dose CT for lung cancer screening has the potential to significantly reduce mortality from lung cancer in the appropriate high-risk population. The ACR supports the recommendations of the US Preventive Services Task Force and the National Comprehensive Cancer Network for screening patients. To be effective, lung cancer screening should be performed at sites providing high-quality low-dose CT examinations overseen and interpreted by qualified physicians using a structured reporting and management system. The ACR has developed a set of tools necessary for radiologists to take the lead on the front lines of lung cancer screening. The ACR Lung Cancer Screening Center designation is built upon the ACR CT accreditation program and requires use of Lung-RADS or a similar structured reporting and management system. This designation provides patients and referring providers with the assurance that they will receive high-quality screening with appropriate follow-up care.