Digital Phenotype Generation and Time to Encounter Closure.

This study evaluates whether implementation of a content expert­developed clinical documentation tool can be beneficial to workflow by reducing time from patient arrival to encounter closure among pediatric patients receiving intestinal rehabilitation.

Plastics select for distinct early colonizing microbial populations with reproducible traits across environmental gradients.

Little is known about early plastic biofilm assemblage dynamics and successional changes over time. By incubating virgin microplastics along oceanic transects and comparing adhered microbial communities with those of naturally occurring plastic litter at the same locations, we constructed gene catalogues to contrast the metabolic differences between early and mature biofilm communities. Early colonization incubations were reproducibly dominated by Alteromonadaceae and harboured significantly higher proportions of genes associated with adhesion, biofilm formation, chemotaxis, hydrocarbon degradation and motility. Comparative genomic analyses among the Alteromonadaceae metagenome assembled genomes (MAGs) highlighted the importance of the mannose-sensitive hemagglutinin (MSHA) operon, recognized as a key factor for intestinal colonization, for early colonization of hydrophobic plastic surfaces. Synteny alignments of MSHA also demonstrated positive selection for mshA alleles across all MAGs, suggesting that mshA provides a competitive advantage for surface colonization and nutrient acquisition. Large-scale genomic characteristics of early colonizers varied little, despite environmental variability. Mature plastic biofilms were composed of predominantly Rhodobacteraceae and displayed significantly higher proportions of carbohydrate hydrolysis enzymes and genes for photosynthesis and secondary metabolism. Our metagenomic analyses provide insight into early biofilm formation on plastics in the ocean and how early colonizers self-assemble, compared to mature, phylogenetically and metabolically diverse biofilms.

The Deterioration Risk Index: Developing and Piloting a Machine Learning Algorithm to Reduce Pediatric Inpatient Deterioration.

OBJECTIVES: Develop and deploy a disease cohort-based machine learning algorithm for timely identification of hospitalized pediatric patients at risk for clinical deterioration that outperforms our existing situational awareness program. DESIGN: Retrospective cohort study. SETTING: Nationwide Children's Hospital, a freestanding, quaternary-care, academic children's hospital in Columbus, OH. PATIENTS: All patients admitted to inpatient units participating in the preexisting situational awareness program from October 20, 2015, to December 31, 2019, excluding patients over 18 years old at admission and those with a neonatal ICU stay during their hospitalization. INTERVENTIONS: We developed separate algorithms for cardiac, malignancy, and general cohorts via lasso-regularized logistic regression. Candidate model predictors included vital signs, supplemental oxygen, nursing assessments, early warning scores, diagnoses, lab results, and situational awareness criteria. Model performance was characterized in clinical terms and compared with our previous situational awareness program based on a novel retrospective validation approach. Simulations with frontline staff, prior to clinical implementation, informed user experience and refined interdisciplinary workflows. Model implementation was piloted on cardiology and hospital medicine units in early 2021. MEASUREMENTS AND MAIN RESULTS: The Deterioration Risk Index (DRI) was 2.4 times as sensitive as our existing situational awareness program (sensitivities of 53% and 22%, respectively; p < 0.001) and required 2.3 times fewer alarms per detected event (121 DRI alarms per detected event vs 276 for existing program). Notable improvements were a four-fold sensitivity gain for the cardiac diagnostic cohort (73% vs 18%; p < 0.001) and a three-fold gain (81% vs 27%; p < 0.001) for the malignancy diagnostic cohort. Postimplementation pilot results over 18 months revealed a 77% reduction in deterioration events (three events observed vs 13.1 expected, p = 0.001). CONCLUSIONS: The etiology of pediatric inpatient deterioration requires acknowledgement of the unique pathophysiology among cardiology and oncology patients. Selection and weighting of diverse candidate risk factors via machine learning can produce a more sensitive early warning system for clinical deterioration. Leveraging preexisting situational awareness platforms and accounting for operational impacts of model implementation are key aspects to successful bedside translation.

The Diagnostic Error Index: A Quality Improvement Initiative to Identify and Measure Diagnostic Errors.

OBJECTIVE: To develop a diagnostic error index (DEI) aimed at providing a practical method to identify and measure serious diagnostic errors. STUDY DESIGN: A quality improvement (QI) study at a quaternary pediatric medical center. Five well-defined domains identified cases of potential diagnostic errors. Identified cases underwent an adjudication process by a multidisciplinary QI team to determine if a diagnostic error occurred. Confirmed diagnostic errors were then aggregated on the DEI. The primary outcome measure was the number of monthly diagnostic errors. RESULTS: From January 2017 through June 2019, 105 cases of diagnostic error were identified. Morbidity and mortality conferences, institutional root cause analyses, and an abdominal pain trigger tool were the most frequent domains for detecting diagnostic errors. Appendicitis, fractures, and nonaccidental trauma were the 3 most common diagnoses that were missed or had delayed identification. CONCLUSIONS: A QI initiative successfully created a pragmatic approach to identify and measure diagnostic errors by utilizing a DEI. The DEI established a framework to help guide future initiatives to reduce diagnostic errors.

Clinical Decision Support for a Multicenter Trial of Pediatric Head Trauma: Development, Implementation, and Lessons Learned.

INTRODUCTION: For children who present to emergency departments (EDs) due to blunt head trauma, ED clinicians must decide who requires computed tomography (CT) scanning to evaluate for traumatic brain injury (TBI). The Pediatric Emergency Care Applied Research Network (PECARN) derived and validated two age-based prediction rules to identify children at very low risk of clinically-important traumatic brain injuries (ciTBIs) who do not typically require CT scans. In this case report, we describe the strategy used to implement the PECARN TBI prediction rules via electronic health record (EHR) clinical decision support (CDS) as the intervention in a multicenter clinical trial. METHODS: Thirteen EDs participated in this trial. The 10 sites receiving the CDS intervention used the Epic(®) EHR. All sites implementing EHR-based CDS built the rules by using the vendor's CDS engine. Based on a sociotechnical analysis, we designed the CDS so that recommendations could be displayed immediately after any provider entered prediction rule data. One central site developed and tested the intervention package to be exported to other sites. The intervention package included a clinical trial alert, an electronic data collection form, the CDS rules and the format for recommendations. RESULTS: The original PECARN head trauma prediction rules were derived from physician documentation while this pragmatic trial led each site to customize their workflows and allow multiple different providers to complete the head trauma assessments. These differences in workflows led to varying completion rates across sites as well as differences in the types of providers completing the electronic data form. Site variation in internal change management processes made it challenging to maintain the same rigor across all sites. This led to downstream effects when data reports were developed. CONCLUSIONS: The process of a centralized build and export of a CDS system in one commercial EHR system successfully supported a multicenter clinical trial.

Use of a remote clinical decision support service for a multicenter trial to implement prediction rules for children with minor blunt head trauma.

OBJECTIVE: To evaluate the architecture, integration requirements, and execution characteristics of a remote clinical decision support (CDS) service used in a multicenter clinical trial. The trial tested the efficacy of implementing brain injury prediction rules for children with minor blunt head trauma. MATERIALS AND METHODS: We integrated the Epic(®) electronic health record (EHR) with the Enterprise Clinical Rules Service (ECRS), a web-based CDS service, at two emergency departments. Patterns of CDS review included either a delayed, near-real-time review, where the physician viewed CDS recommendations generated by the nursing assessment, or a real-time review, where the physician viewed recommendations generated by their own documentation. A backstopping, vendor-based CDS triggered with zero delay when no recommendation was available in the EHR from the web-service. We assessed the execution characteristics of the integrated system and the source of the generated recommendations viewed by physicians. RESULTS: The ECRS mean execution time was 0.74 ±0.72 s. Overall execution time was substantially different at the two sites, with mean total transaction times of 19.67 and 3.99 s. Of 1930 analyzed transactions from the two sites, 60% (310/521) of all physician documentation-initiated recommendations and 99% (1390/1409) of all nurse documentation-initiated recommendations originated from the remote web service. DISCUSSION: The remote CDS system was the source of recommendations in more than half of the real-time cases and virtually all the near-real-time cases. Comparisons are limited by allowable variation in user workflow and resolution of the EHR clock. CONCLUSION: With maturation and adoption of standards for CDS services, remote CDS shows promise to decrease time-to-trial for multicenter evaluations of candidate decision support interventions.

IT in the ED: past, present, and future.

Over the past 40 years, information technology in the emergency department (ED) has evolved from primitive tracking, order entry, and laboratory reporting systems to complex multifunctional applications that permeate all aspects of patient care and ED operations. Spurred by incentive programs and technological improvements, both ED physicians and administrators view these systems as a way to increase staff efficiency, to improve patient care quality and safety, to satisfy compliance and reporting obligations, and to reduce costs. As organizations implement and optimize systems, it is helpful to look back at how these technologies were developed, to review the current impacts and effects of their use, and to glimpse the future of information technology in the ED.

Biogeographic partitioning of Southern Ocean microorganisms revealed by metagenomics.

We performed a metagenomic survey (6.6 Gbp of 454 sequence data) of Southern Ocean (SO) microorganisms during the austral summer of 2007-2008, examining the genomic signatures of communities across a latitudinal transect from Hobart (44°S) to the Mertz Glacier, Antarctica (67°S). Operational taxonomic units (OTUs) of the SAR11 and SAR116 clades and the cyanobacterial genera Prochlorococcus and Synechococcus were strongly overrepresented north of the Polar Front (PF). Conversely, OTUs of the Gammaproteobacterial Sulfur Oxidizer-EOSA-1 (GSO-EOSA-1) complex, the phyla Bacteroidetes and Verrucomicrobia and order Rhodobacterales were characteristic of waters south of the PF. Functions enriched south of the PF included a range of transporters, sulfur reduction and histidine degradation to glutamate, while branched-chain amino acid transport, nucleic acid biosynthesis and methionine salvage were overrepresented north of the PF. The taxonomic and functional characteristics suggested a shift of primary production from cyanobacteria in the north to eukaryotic phytoplankton in the south, and reflected the different trophic statuses of the two regions. The study provides a new level of understanding about SO microbial communities, describing the contrasting taxonomic and functional characteristics of microbial assemblages either side of the PF.

IT in the ED: a new section of Pediatric Emergency Care.

Information technology (IT) has profoundly changed the delivery of health care during the past decade. The pediatric emergency department (ED) represents a specific challenge for applying IT systems to the patient bedside. The rapid pace and unscheduled nature of the ED, the breadth of care delivered, and the range of medical, ethical, cultural, and process issues presented by pediatric patients make this a setting in particular need of thoughtfully designed and usable IT systems. However, reviews of the current state of health IT have documented mixed outcomes, including safety risks introduced by IT systems, significant deficits in usability for clinicians, and unrealized potential. Although some publications have presented methods and outcomes of IT systems in the pediatric ED, the current medical literature is sparse. Professional organizations have not developed successful methods to share best practices across institutions and IT vendors. The authors propose a new section of this journal focused on the application of IT systems to Pediatric Emergency Care. The section will include original research articles and reviews focusing on the application of IT to improve care of acutely ill and injured children. Innovative approaches and articles by physicians in training are particularly encouraged to develop new expertise in informatics within this and related specialties.

Global biogeography of SAR11 marine bacteria.

The ubiquitous SAR11 bacterial clade is the most abundant type of organism in the world's oceans, but the reasons for its success are not fully elucidated. We analysed 128 surface marine metagenomes, including 37 new Antarctic metagenomes. The large size of the data set enabled internal transcribed spacer (ITS) regions to be obtained from the Southern polar region, enabling the first global characterization of the distribution of SAR11, from waters spanning temperatures -2 to 30°C. Our data show a stable co-occurrence of phylotypes within both 'tropical' (>20°C) and 'polar' (<10°C) biomes, highlighting ecological niche differentiation between major SAR11 subgroups. All phylotypes display transitions in abundance that are strongly correlated with temperature and latitude. By assembling SAR11 genomes from Antarctic metagenome data, we identified specific genes, biases in gene functions and signatures of positive selection in the genomes of the polar SAR11-genomic signatures of adaptive radiation. Our data demonstrate the importance of adaptive radiation in the organism's ability to proliferate throughout the world's oceans, and describe genomic traits characteristic of different phylotypes in specific marine biomes.

Virophage control of antarctic algal host-virus dynamics.

Viruses are abundant ubiquitous members of microbial communities and in the marine environment affect population structure and nutrient cycling by infecting and lysing primary producers. Antarctic lakes are microbially dominated ecosystems supporting truncated food webs in which viruses exert a major influence on the microbial loop. Here we report the discovery of a virophage (relative of the recently described Sputnik virophage) that preys on phycodnaviruses that infect prasinophytes (phototrophic algae). By performing metaproteogenomic analysis on samples from Organic Lake, a hypersaline meromictic lake in Antarctica, complete virophage and near-complete phycodnavirus genomes were obtained. By introducing the virophage as an additional predator of a predator-prey dynamic model we determined that the virophage stimulates secondary production through the microbial loop by reducing overall mortality of the host and increasing the frequency of blooms during polar summer light periods. Virophages remained abundant in the lake 2 y later and were represented by populations with a high level of major capsid protein sequence variation (25-100% identity). Virophage signatures were also found in neighboring Ace Lake (in abundance) and in two tropical lakes (hypersaline and fresh), an estuary, and an ocean upwelling site. These findings indicate that virophages regulate host-virus interactions, influence overall carbon flux in Organic Lake, and play previously unrecognized roles in diverse aquatic ecosystems.

An integrative study of a meromictic lake ecosystem in Antarctica.

In nature, the complexity and structure of microbial communities varies widely, ranging from a few species to thousands of species, and from highly structured to highly unstructured communities. Here, we describe the identity and functional capacity of microbial populations within distinct layers of a pristine, marine-derived, meromictic (stratified) lake (Ace Lake) in Antarctica. Nine million open reading frames were analyzed, representing microbial samples taken from six depths of the lake size fractionated on sequential 3.0, 0.8 and 0.1 µm filters, and including metaproteome data from matching 0.1 µm filters. We determine how the interactions of members of this highly structured and moderately complex community define the biogeochemical fluxes throughout the entire lake. Our view is that the health of this delicate ecosystem is dictated by the effects of the polar light cycle on the dominant role of green sulfur bacteria in primary production and nutrient cycling, and the influence of viruses/phage and phage resistance on the cooperation between members of the microbial community right throughout the lake. To test our assertions, and develop a framework applicable to other microbially driven ecosystems, we developed a mathematical model that describes how cooperation within a microbial system is impacted by periodic fluctuations in environmental parameters on key populations of microorganisms. Our study reveals a mutualistic structure within the microbial community throughout the lake that has arisen as the result of mechanistic interactions between the physico-chemical parameters and the selection of individual members of the community. By exhaustively describing and modelling interactions in Ace Lake, we have developed an approach that may be applicable to learning how environmental perturbations affect the microbial dynamics in more complex aquatic systems.

Metaproteogenomic analysis of a dominant green sulfur bacterium from Ace Lake, Antarctica.

Green sulfur bacteria (GSB) (Chlorobiaceae) are primary producers that are important in global carbon and sulfur cycling in natural environments. An almost complete genome sequence for a single, dominant GSB species ('C-Ace') was assembled from shotgun sequence data of an environmental sample taken from the O(2)-H(2)S interface of the water column of Ace Lake, Antarctica. Approximately 34 Mb of DNA sequence data were assembled into nine scaffolds totaling 1.79 Mb, representing approximately 19-fold coverage for the C-Ace composite genome. A high level ( approximately 31%) of metaproteomic coverage was achieved using matched biomass. The metaproteogenomic approach provided unique insight into the protein complement required for dominating the microbial community under cold, nutrient-limited, oxygen-limited and extremely varied annual light conditions. C-Ace shows physiological traits that promote its ability to compete very effectively with other GSB and gain dominance (for example, specific bacteriochlorophylls, mechanisms of cold adaptation) as well as a syntrophic relationship with sulfate-reducing bacteria that provides a mechanism for the exchange of sulfur compounds. As a result we are able to propose an explanation of the active biological processes promoted by cold-adapted GSB and the adaptive strategies they use to thrive under the severe physiochemical conditions prevailing in polar environments.

High-energy response of passive dosemeters in use at LANL.

The high-energy neutron response of three passive dosemeters in use at the Los Alamos National Laboratory (LANL) has been investigated using metrology-grade fields. The dosemeters include the LANL Model 8823 TLD badge and the LANL PN3 track etch device. Both are dosemeters of record at LANL. The third device was the Personal Neutron Dosemeter (PND), a superheated emulsion device, manufactured by Bubble Technology Industries, Inc. (BTI). The response of the three dosemeters at neutron energies exceeding 10 MeV was assessed with monoenergetic neutrons at the Physikalisch-Technische Bundesanstalt facility (14.8 and 19 MeV). For the sake of completeness, data collected at lower energies are also included in this study. High-energy quasi-monoenergetic beams produced by the cyclotron facilities at the Université Catholique de Louvain (UCL) and the The Svedberg Laboratory (TSL) were also utilised as part of this study. These measurements were made to better understand and help interpret dosemeter readings obtained by workers at high-energy accelerators, such as the 800 MeV spallation neutron source facility located at the Los Alamos Neutron Science Center (LANSCE).