Localized bases for kernel spaces on the unit sphere

Approximation/interpolation from spaces of positive definite or conditionally positive definite kernels is an increasingly popular tool for the analysis and synthesis of scattered data, and is central to many meshless methods. For a set of $N$ scattered sites, the standard basis for such a space utilizes $N$ \emph{globally} supported kernels; computing with it is prohibitively expensive for large $N$. Easily computable, well-localized bases, with "small-footprint" basis elements - i.e., elements using only a small number of kernels -- have been unavailable. Working on \sphere, with focus on the restricted surface spline kernels (e.g. the thin-plate splines restricted to the sphere), we construct easily computable, spatially well-localized, small-footprint, robust bases for the associated kernel spaces. Our theory predicts that each element of the local basis is constructed by using a combination of only $\mathcal{O}((\log N)^2)$ kernels, which makes the construction computationally cheap. We prove that the new basis is $L_p$ stable and satisfies polynomial decay estimates that are stationary with respect to the density of the data sites, and we present a quasi-interpolation scheme that provides optimal $L_p$ approximation orders. Although our focus is on $\mathbb{S}^2$, much of the theory applies to other manifolds - $\mathbb{S}^d$, the rotation group, and so on. Finally, we construct algorithms to implement these schemes and use them to conduct numerical experiments, which validate our theory for interpolation problems on $\mathbb{S}^2$ involving over one hundred fifty thousand data sites.Comment: This article supersedes arXiv:1111.1013 "Better bases for kernel spaces," which proved existence of better bases for various kernel spaces. This article treats a smaller class of kernels, but presents an algorithm for constructing better bases and demonstrates its effectiveness with more elaborate examples. A quasi-interpolation scheme is introduced that provides optimal linear convergence rate

Performance of externally validated enhanced computer-aided versions of the National Early Warning Score in predicting mortality following an emergency admission to hospital in England: a cross-sectional study

YesOBJECTIVES: In the English National Health Service, the patient's vital signs are monitored and summarised into a National Early Warning Score (NEWS) to support clinical decision making, but it does not provide an estimate of the patient's risk of death. We examine the extent to which the accuracy of NEWS for predicting mortality could be improved by enhanced computer versions of NEWS (cNEWS). DESIGN: Logistic regression model development and external validation study. SETTING: Two acute hospitals (YH-York Hospital for model development; NH-Northern Lincolnshire and Goole Hospital for external model validation). PARTICIPANTS: Adult (≥16 years) medical admissions discharged over a 24-month period with electronic NEWS (eNEWS) recorded on admission are used to predict mortality at four time points (in-hospital, 24 hours, 48 hours and 72 hours) using the first electronically recorded NEWS (model M0) versus a cNEWS model which included age+sex (model M1) +subcomponents of NEWS (including diastolic blood pressure) (model M2). RESULTS: The risk of dying in-hospital following emergency medical admission was 5.8% (YH: 2080/35 807) and 5.4% (NH: 1900/35 161). The c-statistics for model M2 in YH for predicting mortality (in-hospital=0.82, 24 hours=0.91, 48 hours=0.88 and 72 hours=0.88) was higher than model M0 (in-hospital=0.74, 24 hours=0.89, 48 hours=0.86 and 72 hours=0.85) with higher Positive Predictive Value (PPVs) for in-hospital mortality (M2 19.3% and M0 16.6%). Similar findings were seen in NH. Model M2 performed better than M0 in almost all major disease subgroups. CONCLUSIONS: An externally validated enhanced computer-aided NEWS model (cNEWS) incrementally improves on the performance of a NEWS only model. Since cNEWS places no additional data collection burden on clinicians and is readily automated, it may now be carefully introduced and evaluated to determine if it can improve care in hospitals that have eNEWS systems.This research was supported by the Health Foundation. The Health Foundation is an independent charity working to improve the quality of healthcare in the UK. This research was also supported by the National Institute for Health Research (NIHR) Yorkshire and Humberside Patient Safety Translational Research Centre (YHPSTRC)

The inclusion of delirium in version 2 of the National Early Warning Score will substantially increase the alerts for escalating levels of care: findings from a retrospective database study of emergency medical admissions in two hospitals

YesBackground The National Early Warning Score (NEWS) is being replaced with NEWS2 which adds 3 points for new confusion or delirium. We estimated the impact of adding delirium on the number of medium/high level alerts that are triggers to escalate care. Methods Analysis of emergency medical admissions in two acute hospitals (York Hospital (YH) and Northern Lincolnshire and Goole NHS Foundation Trust hospitals (NH)) in England. Twenty per cent were randomly assigned to have delirium. Results The number of emergency admissions (YH: 35584; NH: 35795), mortality (YH: 5.7%; NH: 5.5%), index NEWS (YH: 2.5; NH: 2.1) and numbers of NEWS recorded (YH: 879193; NH: 884072) were similar in each hospital. The mean number of patients with medium level alerts per day increased from 55.3 (NEWS) to 69.5 (NEWS2), a 25.7% increase in YH and 64.1 (NEWS) to 77.4 (NEWS2), a 20.7% increase in NH. The mean number of patients with high level alerts per day increased from 27.3 (NEWS) to 34.4 (NEWS2), a 26.0% increase in YH and 29.9 (NEWS) to 37.7 (NEWS2), a 26.1% increase in NH. Conclusions The addition of delirium in NEWS2 will have a substantial increase in medium and high level alerts in hospitalised emergency medical patients. Rigorous evaluation of NEWS2 is required before widespread implementation because the extent to which staff can cope with this increase without adverse consequences remains unknown

Companion animals are spillover hosts of the Multidrug-resistant human extraintestinal escherichia coli pandemic Clones ST131 and ST1193

Escherichia coli sequence types 131 (ST131) and 1193 are multidrug-resistant extraintestinal pathogens that have recently spread epidemically among humans and are occasionally isolated from companion animals. This study characterized a nationwide collection of fluoroquinolone-resistant (FQR) E. coli isolates from extraintestinal infections in Australian cats and dogs. For this, 59 cat and dog FQR clinical E. coli isolates (representing 6.9% of an 855-isolate collection) underwent PCR-based phylotyping and whole-genome sequencing (WGS). Isolates from commensal-associated phylogenetic groups A (14/59, 24%) and B1 (18/59, 31%) were dominant, with ST224 (10/59, 17%), and ST744 (8/59, 14%) predominating. Less prevalent were phylogenetic groups D (12/59, 20%), with ST38 (8/59, 14%) predominating, and virulence-associated phylogenetic group B2 (7/59, 12%), with ST131 predominating (6/7, 86%) and no ST1193 isolates identified. In a WGS-based comparison of 20 cat and dog-source ST131 isolates with 188 reference human and animal ST131 isolates, the cat and dog-source isolates were phylogenetically diverse. Although cat and dog-source ST131 isolates exhibited some minor sub-clustering, most were closely related to human-source ST131 strains. Furthermore, the prevalence of ST131 as a cause of FQR infections in Australian companion animals was relatively constant between this study and the 5-year-earlier study of Platell et al. (2010) (9/125 isolates, 7.2%). Thus, although the high degree of clonal commonality among FQR clinical isolates from humans vs. companion animals suggests the possibility of bi-directional between-species transmission, the much higher reported prevalence of ST131 and ST1193 among FQR clinical isolates from humans as compared to companion animals suggests that companion animals are spillover hosts rather than being a primary reservoir for these lineages

Comprehensive analysis of type 1 fimbriae regulation in fimB -null strains from the multidrug resistant Escherichia coli ST131 clone

Summary\ud \ud Uropathogenic Escherichia coli (UPEC) of sequence type 131 (ST131) are a pandemic multidrug resistant clone associated with urinary tract and bloodstream infections. Type 1 fimbriae, a major UPEC virulence factor, are essential for ST131 bladder colonization. The globally dominant sub-lineage of ST131 strains, clade C/H30-R, possess an ISEc55 insertion in the fimB gene that controls phase-variable type 1 fimbriae expression via the invertible fimS promoter. We report that inactivation of fimB in these strains causes altered regulation of type 1 fimbriae expression. Using a novel read-mapping approach based on Illumina sequencing, we demonstrate that ‘off’ to ‘on’ fimS inversion is reduced in these strains and controlled by recombinases encoded by the fimE and fimX genes. Unlike typical UPEC strains, the nucleoid-associated H-NS protein does not strongly repress fimE transcription in clade C ST131 strains. Using a genetic screen to identify novel regulators of fimE and fimX in the clade C ST131 strain EC958, we defined a new role for the guaB gene in the regulation of type 1 fimbriae and in colonisation of the mouse bladder. Our results provide a comprehensive analysis of type 1 fimbriae regulation in ST131, and highlight important differences in its control compared to non-ST131 UPEC

Predictive accuracy of enhanced versions of the on-admission National Early Warning Score in estimating the risk of COVID-19 for unplanned admission to hospital: a retrospective development and validation study

YesThe novel coronavirus SARS-19 produces 'COVID-19' in patients with symptoms. COVID-19 patients admitted to the hospital require early assessment and care including isolation. The National Early Warning Score (NEWS) and its updated version NEWS2 is a simple physiological scoring system used in hospitals, which may be useful in the early identification of COVID-19 patients. We investigate the performance of multiple enhanced NEWS2 models in predicting the risk of COVID-19. Our cohort included unplanned adult medical admissions discharged over 3 months (11 March 2020 to 13 June 2020 ) from two hospitals (YH for model development; SH for external model validation). We used logistic regression to build multiple prediction models for the risk of COVID-19 using the first electronically recorded NEWS2 within ± 24 hours of admission. Model M0' included NEWS2; model M1' included NEWS2 + age + sex, and model M2' extends model M1' with subcomponents of NEWS2 (including diastolic blood pressure + oxygen flow rate + oxygen scale). Model performance was evaluated according to discrimination (c statistic), calibration (graphically), and clinical usefulness at NEWS2 ≥ 5. The prevalence of COVID-19 was higher in SH (11.0 %=277/2520) than YH (8.7 %=343/3924) with a higher first NEWS2 scores ( SH 3.2 vs YH 2.8) but similar in-hospital mortality (SH 8.4 % vs YH 8.2 %). The c-statistics for predicting the risk of COVID-19 for models M0',M1',M2' in the development dataset were: M0': 0.71 (95 %CI 0.68-0.74); M1': 0.67 (95 %CI 0.64-0.70) and M2': 0.78 (95 %CI 0.75-0.80)). For the validation datasets the c-statistics were: M0' 0.65 (95 %CI 0.61-0.68); M1': 0.67 (95 %CI 0.64-0.70) and M2': 0.72 (95 %CI 0.69-0.75) ). The calibration slope was similar across all models but Model M2' had the highest sensitivity (M0' 44 % (95 %CI 38-50 %); M1' 53 % (95 %CI 47-59 %) and M2': 57 % (95 %CI 51-63 %)) and specificity (M0' 75 % (95 %CI 73-77 %); M1' 72 % (95 %CI 70-74 %) and M2': 76 % (95 %CI 74-78 %)) for the validation dataset at NEWS2 ≥ 5. Model M2' appears to be reasonably accurate for predicting the risk of COVID-19. It may be clinically useful as an early warning system at the time of admission especially to triage large numbers of unplanned hospital admissions.The Health Foundation (Award No 7380) and the National Institute for Health Research (NIHR) Yorkshire and Humber Patient Safety Translational Research Centre (NIHR Yorkshire and Humber PSTRC) (Award No PSTRC-2016-006)Research Development Fund Publication Prize Award winner, Aug 2021

The National Early Warning Score and its subcomponents recorded within ±24 hours of emergency medical admission are poor predictors of hospital-acquired acute kidney injury

YesBackground: Hospital-acquired Acute Kidney Injury (H-AKI) is a common cause of avoidable morbidity and mortality. Aim: To determine if the patients’ vital signs data as defined by a National Early Warning Score (NEWS), can predict H-AKI following emergency admission to hospital. Methods: Analyses of emergency admissions to York hospital over 24-months with NEWS data. We report the area under the curve (AUC) for logistic regression models that used the index NEWS (model A0), plus age and sex (A1), plus subcomponents of NEWS (A2) and two-way interactions (A3). Likewise for maximum NEWS (models B0,B1,B2,B3). Results: 4.05% (1361/33608) of emergency admissions had H-AKI. Models using the index NEWS had the lower AUCs (0.59 to 0.68) than models using the maximum NEWS AUCs (0.75 to 0.77). The maximum NEWS model (B3) was more sensitivity than the index NEWS model (A0) (67.60% vs 19.84%) but identified twice as many cases as being at risk of H-AKI (9581 vs 4099) at a NEWS of 5. Conclusions: The index NEWS is a poor predictor of H-AKI. The maximum NEWS is a better predictor but seems unfeasible because it is only knowable in retrospect and is associated with a substantial increase in workload albeit with improved sensitivity.The Health Foundatio

Lineage-Specific Methyltransferases Define the Methylome of the Globally Disseminated Escherichia coli ST131 Clone.

UNLABELLED: Escherichia coli sequence type 131 (ST131) is a clone of uropathogenic E. coli that has emerged rapidly and disseminated globally in both clinical and community settings. Members of the ST131 lineage from across the globe have been comprehensively characterized in terms of antibiotic resistance, virulence potential, and pathogenicity, but to date nothing is known about the methylome of these important human pathogens. Here we used single-molecule real-time (SMRT) PacBio sequencing to determine the methylome of E. coli EC958, the most-well-characterized completely sequenced ST131 strain. Our analysis of 52,081 methylated adenines in the genome of EC958 discovered three (m6)A methylation motifs that have not been described previously. Subsequent SMRT sequencing of isogenic knockout mutants identified the two type I methyltransferases (MTases) and one type IIG MTase responsible for (m6)A methylation of novel recognition sites. Although both type I sites were rare, the type IIG sites accounted for more than 12% of all methylated adenines in EC958. Analysis of the distribution of MTase genes across 95 ST131 genomes revealed their prevalence is highly conserved within the ST131 lineage, with most variation due to the presence or absence of mobile genetic elements on which individual MTase genes are located. IMPORTANCE: DNA modification plays a crucial role in bacterial regulation. Despite several examples demonstrating the role of methyltransferase (MTase) enzymes in bacterial virulence, investigation of this phenomenon on a whole-genome scale has remained elusive until now. Here we used single-molecule real-time (SMRT) sequencing to determine the first complete methylome of a strain from the multidrug-resistant E. coli sequence type 131 (ST131) lineage. By interrogating the methylome computationally and with further SMRT sequencing of isogenic mutants representing previously uncharacterized MTase genes, we defined the target sequences of three novel ST131-specific MTases and determined the genomic distribution of all MTase target sequences. Using a large collection of 95 previously sequenced ST131 genomes, we identified mobile genetic elements as a major factor driving diversity in DNA methylation patterns. Overall, our analysis highlights the potential for DNA methylation to dramatically influence gene regulation at the transcriptional level within a well-defined E. coli clone

Computer-aided National Early Warning Score to predict the risk of sepsis following emergency medical admission to hospital: a model development and external validation study

YesBackground: In English hospitals, the patient’s vital signs are monitored and summarised into a National Early Warning Score (NEWS). NEWS is more accurate than the quick sepsis related organ failure assessment (qSOFA) score at identifying patients with sepsis. We investigate the extent to which the accuracy of the NEWS is enhanced by developing computer-aided NEWS (cNEWS) models. We compared three cNEWS models (M0=NEWS alone; M1=M0 + age + sex; M2=M1 + subcomponents of NEWS + diastolic blood pressure) to predict the risk of sepsis. Methods: All adult emergency medical admissions discharged over 24-months from two acute hospitals (YH–York Hospital for model development; NH–Northern Lincolnshire and Goole Hospital for external model validation). We used a validated Canadian method for defining sepsis from administrative hospital data. Findings: The prevalence of sepsis was lower in YH (4.5%=1596/35807) than NH (8.5%=2983/35161). The c-statistic increased across models (YH: M0: 0.705, M1:0.763, M2:0.777; NH:M0: 0.708, M1:0.777, M2:0.791). At NEWS 5+, sensitivity increased (YH: 47.24% vs 50.56% vs 52.69%; NH: 37.91% vs 43.35% vs 48.07%)., the positive likelihood ratio increased (YH: 2.77 vs 2.99 vs 3.06; NH: 3.18 vs 3.32 vs 3.45) and the positive predictive value increased (YH: 11.44% vs 12.24% vs 12.49%; NH: 22.75% vs 23.55% vs 24.21%). Interpretation: From the three cNEWS models, Model M2 is the most accurate. Since it places no additional data collection burden on clinicians and can be automated, it may now be carefully introduced and evaluated in hospitals with sufficient informatics infrastructure.The Health Foundation, National Institute for Health Research (NIHR) Yorkshire and Humberside Patient Safety Translational Research CentreResearch Development Fund Publication Prize Award winner, April 2019

Subjective and objective outcome in congenital clubfoot; a comparative study of 204 children

<p>Abstract</p> <p>Background</p> <p>Outcome following management of congenital talipes equinovarus (clubfoot) can be assessed in a number of ways. Bjonness stated simply that <it>"the patient is the final judge of whether he has a good foot</it>"; a purely subjective assessment. Others have employed objective measures. Combining subjective evaluation with a more objective assessment of movement and position of the foot, is likely to give a more comprehensive picture of the final result of clubfoot. The purpose of this study was to compare subjective and objective outcome following management of clubfoot, and evaluate sex differences in outcome.</p> <p>Methods</p> <p>We used a patient-administered subjective assessment of outcome following treatment of clubfoot and compared it with objective anthropometry and range of movement of the ankle to assess and compare subjective and objective outcome in clubfoot. Statistical analysis was performed using Pearson correlation coefficients. Significance was tested using Student's t-test test.</p> <p>Results</p> <p>Objective outcome can be assessed using length of the foot, calf circumference and range of movement at the ankle. These are easy to measure, reproducible, and correlate well with subjective outcome. Objective outcome is comparable for boys and girls. However, subjectively, female patients and their parents are less happy with the results of management of clubfoot.</p> <p>Conclusion</p> <p>There is a correlation between the anthropometric measures and the subjective outcome and an objective grading can be designed using foot length, calf muscle bulk and range of movement at the ankle.</p