Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study.

BACKGROUND: The National Early Warning Score (NEWS2) is currently recommended in the UK for the risk stratification of COVID-19 patients, but little is known about its ability to detect severe cases. We aimed to evaluate NEWS2 for the prediction of severe COVID-19 outcome and identify and validate a set of blood and physiological parameters routinely collected at hospital admission to improve upon the use of NEWS2 alone for medium-term risk stratification. METHODS: Training cohorts comprised 1276 patients admitted to King's College Hospital National Health Service (NHS) Foundation Trust with COVID-19 disease from 1 March to 30 April 2020. External validation cohorts included 6237 patients from five UK NHS Trusts (Guy's and St Thomas' Hospitals, University Hospitals Southampton, University Hospitals Bristol and Weston NHS Foundation Trust, University College London Hospitals, University Hospitals Birmingham), one hospital in Norway (Oslo University Hospital), and two hospitals in Wuhan, China (Wuhan Sixth Hospital and Taikang Tongji Hospital). The outcome was severe COVID-19 disease (transfer to intensive care unit (ICU) or death) at 14 days after hospital admission. Age, physiological measures, blood biomarkers, sex, ethnicity, and comorbidities (hypertension, diabetes, cardiovascular, respiratory and kidney diseases) measured at hospital admission were considered in the models. RESULTS: A baseline model of 'NEWS2 + age' had poor-to-moderate discrimination for severe COVID-19 infection at 14 days (area under receiver operating characteristic curve (AUC) in training cohort = 0.700, 95% confidence interval (CI) 0.680, 0.722; Brier score = 0.192, 95% CI 0.186, 0.197). A supplemented model adding eight routinely collected blood and physiological parameters (supplemental oxygen flow rate, urea, age, oxygen saturation, C-reactive protein, estimated glomerular filtration rate, neutrophil count, neutrophil/lymphocyte ratio) improved discrimination (AUC = 0.735; 95% CI 0.715, 0.757), and these improvements were replicated across seven UK and non-UK sites. However, there was evidence of miscalibration with the model tending to underestimate risks in most sites. CONCLUSIONS: NEWS2 score had poor-to-moderate discrimination for medium-term COVID-19 outcome which raises questions about its use as a screening tool at hospital admission. Risk stratification was improved by including readily available blood and physiological parameters measured at hospital admission, but there was evidence of miscalibration in external sites. This highlights the need for a better understanding of the use of early warning scores for COVID.

Information transfer by leaky, heterogeneous, protein kinase signaling systems.

Cells must sense extracellular signals and transfer the information contained about their environment reliably to make appropriate decisions. To perform these tasks, cells use signal transduction networks that are subject to various sources of noise. Here, we study the effects on information transfer of two particular types of noise: basal (leaky) network activity and cell-to-cell variability in the componentry of the network. Basal activity is the propensity for activation of the network output in the absence of the signal of interest. We show, using theoretical models of protein kinase signaling, that the combined effect of the two types of noise makes information transfer by such networks highly vulnerable to the loss of negative feedback. In an experimental study of ERK signaling by single cells with heterogeneous ERK expression levels, we verify our theoretical prediction: In the presence of basal network activity, negative feedback substantially increases information transfer to the nucleus by both preventing a near-flat average response curve and reducing sensitivity to variation in substrate expression levels. The interplay between basal network activity, heterogeneity in network componentry, and feedback is thus critical for the effectiveness of protein kinase signaling. Basal activity is widespread in signaling systems under physiological conditions, has phenotypic consequences, and is often raised in disease. Our results reveal an important role for negative feedback mechanisms in protecting the information transfer function of saturable, heterogeneous cell signaling systems from basal activity.

Design and Evaluation of an Intensive Care Unit Dashboard Built in Response to the COVID-19 Pandemic: Semistructured Interview Study.

BACKGROUND: Dashboards and interactive displays are becoming increasingly prevalent in most health care settings and have the potential to streamline access to information, consolidate disparate data sources and deliver new insights. Our research focuses on intensive care units (ICUs) which are heavily instrumented, critical care environments that generate vast amounts of data and frequently require individualized support for each patient. Consequently, clinicians experience a high cognitive load, which can translate to suboptimal performance. The global COVID-19 pandemic exacerbated this problem by generating a large number of additional hospitalizations, which necessitated a new tool that would help manage ICUs' census. In a previous study, we interviewed clinicians at the University Hospitals Bristol and Weston National Health Service Foundation Trust to capture the requirements for bespoke dashboards that would alleviate this problem. OBJECTIVE: This study aims to design, implement, and evaluate an ICU dashboard to allow for monitoring of the high volume of patients in need of critical care, particularly tailored to high-demand situations, such as those seen during the COVID-19 pandemic. METHODS: Building upon the previously gathered requirements, we developed a dashboard, integrated it within the ICU of a National Health Service trust, and allowed all staff to access our tool. For evaluation purposes, participants were recruited and interviewed following a 25-day period during which they were able to use the dashboard clinically. The semistructured interviews followed a topic guide aimed at capturing the usability of the dashboard, supplemented with additional questions asked post hoc to probe themes established during the interview. Interview transcripts were analyzed using a thematic analysis framework that combined inductive and deductive approaches and integrated the Technology Acceptance Model. RESULTS: A total of 10 participants with 4 different roles in the ICU (6 consultants, 2 junior doctors, 1 nurse, and 1 advanced clinical practitioner) participated in the interviews. Our analysis generated 4 key topics that prevailed across the data: our dashboard met the usability requirements of the participants and was found useful and intuitive; participants perceived that it impacted their delivery of patient care by improving the access to the information and better equipping them to do their job; the tool was used in a variety of ways and for different reasons and tasks; and there were barriers to integration of our dashboard into practice, including familiarity with existing systems, which stifled the adoption of our tool. CONCLUSIONS: Our findings show that the perceived utility of the dashboard had a positive impact on the clinicians' workflows in the ICU. Improving access to information translated into more efficient patient care and transformed some of the existing processes. The introduction of our tool was met with positive reception, but its integration during the COVID-19 pandemic limited its adoption into practice.

Requirements for a Bespoke Intensive Care Unit Dashboard in Response to the COVID-19 Pandemic: Semistructured Interview Study.

BACKGROUND: Intensive care units (ICUs) around the world are in high demand due to patients with COVID-19 requiring hospitalization. As researchers at the University of Bristol, we were approached to develop a bespoke data visualization dashboard to assist two local ICUs during the pandemic that will centralize disparate data sources in the ICU to help reduce the cognitive load on busy ICU staff in the ever-evolving pandemic. OBJECTIVE: The aim of this study was to conduct interviews with ICU staff in University Hospitals Bristol and Weston National Health Service Foundation Trust to elicit requirements for a bespoke dashboard to monitor the high volume of patients, particularly during the COVID-19 pandemic. METHODS: We conducted six semistructured interviews with clinical staff to obtain an overview of their requirements for the dashboard and to ensure its ultimate suitability for end users. Interview questions aimed to understand the job roles undertaken in the ICU, potential uses of the dashboard, specific issues associated with managing COVID-19 patients, key data of interest, and any concerns about the introduction of a dashboard into the ICU. RESULTS: From our interviews, we found the following design requirements: (1) a flexible dashboard, where the functionality can be updated quickly and effectively to respond to emerging information about the management of this new disease; (2) a mobile dashboard, which allows staff to move around on wards with a dashboard, thus potentially replacing paper forms to enable detailed and consistent data entry; (3) a customizable and intuitive dashboard, where individual users would be able to customize the appearance of the dashboard to suit their role; (4) real-time data and trend analysis via informative data visualizations that help busy ICU staff to understand a patient's clinical trajectory; and (5) the ability to manage tasks and staff, tracking both staff and patient movements, handovers, and task monitoring to ensure the highest quality of care. CONCLUSIONS: The findings of this study confirm that digital solutions for ICU use would potentially reduce the cognitive load of ICU staff and reduce clinical errors at a time of notably high demand of intensive health care.

Curation of an intensive care research dataset from routinely collected patient data in an NHS trust.

In this data note we provide the details of a research database of 4831 adult intensive care patients who were treated in the Bristol Royal Infirmary, UK between 2015 and 2019. The purposes of this publication are to describe the dataset for external researchers who may be interested in making use of it, and to detail the methods used to curate the dataset in order to help other intensive care units make secondary use of their routinely collected data. The curation involves linkage between two critical care datasets within our hospital and the accompanying code is available online. For reasons of data privacy the data cannot be shared without researchers obtaining appropriate ethical consents. In the future we hope to obtain a data sharing agreement in order to publicly share the de-identified data, and to link our data with other intensive care units who use a Philips clinical information system.

The stability of multitrophic communities under habitat loss.

Habitat loss (HL) affects species and their interactions, ultimately altering community dynamics. Yet, a challenge for community ecology is to understand how communities with multiple interaction types-hybrid communities-respond to HL prior to species extinctions. To this end, we develop a model to investigate the response of hybrid terrestrial communities to two types of HL: random and contiguous. Our model reveals changes in stability-temporal variability in population abundances-that are dependent on the spatial configuration of HL. Our findings highlight that habitat area determines the variability of populations via changes in the distribution of species interaction strengths. The divergent responses of communities to random and contiguous HL result from different constraints imposed on individuals' mobility, impacting diversity and network structure in the random case, and destabilising communities by increasing interaction strength in the contiguous case. Analysis of intermediate HL suggests a gradual transition between the two extreme cases.

Highly enantioselective hydrogenation of aromatic-heteroaromatic ketones.

Asymmetric hydrogenation of ketone 1 using trans-RuCl(2)[(R)-xylbinap][(R)-daipen] (3) as a catalyst afforded secondary alcohol 2 quantitatively and in 99.4% ee. Further exploration of the effect of the thiazole ring substitution revealed that the catalyst was highly effective for the enantioselective hydrogenation of 5-benzoyl thiazoles, which afforded corresponding alcohols in 92-99% ee. The same protocol was applicable to a variety of aromatic-heteroaromatic ketones to generate secondary alcohols in excellent enantioselectivities. [reaction: see text]

A practical synthesis of a gamma-secretase inhibitor.

A practical and scaleable synthesis of the gamma-secretase inhibitor 1 is reported. The inhibitor consists of a central trisubstituted cyclohexane core with appended propionic acid, 2,5-difluorophenyl, and 4-chlorophenylsulfonyl moieties. Two alternative synthetic strategies, proceeding by way of a common disubstituted cyclohexanone derivative 5, were studied. In the preferred route, conjugate reduction of acrylonitrile derivative 4 with L-Selectride configures the desired relative stereochemistry of the cyclohexane core with >99.9:0.1 dr. A second strategy, based on catalyst-controlled hydrogenation of racemic cyclohexene derivative 2, is more convergent but less diastereoselective (up to 75:25 dr). The common cyclohexanone intermediate 5 was constructed by a regioselective Diels-Alder condensation of a 1,1-disubstituted vinyl sulfone 6 with 2-trimethylsiloxybutadiene.