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Comparison of parametric and non-parametric Bayesian inference for fusing sensory estimates in physiological time-series analysis
No full textThe rapid proliferation of wearable devices for medical applications has necessitated the need for automated algorithms to provide labelling of physiological time-series data to identify abnormal morphology. However, such algorithms are less reliable than gold-standard human expert labels (where the latter are typically difficult and expensive to obtain), due to their large inter- and intra-subject variabilities. Actions taken in response to these algorithms can therefore result in sub-optimal patient care. In a typical scenario where only unevenly sampled continuous or numeric estimates are provided, without access to the “ground truth”, it is challenging to choose which algorithms to trust and which to ignore, or even how to merge the outputs from multiple algorithms to form a more precise final estimate for individual patients. In this work, the novel application of two previously proposed parametric fully-Bayesian graphical models is demonstrated for fusing labels from (i) independent and (ii) potentially correlated algorithms, validated on two publicly available datasets for the task of respiratory rate (RR) estimation. These unsupervised models aggregate RR labels and estimate jointly the assumed bias and precision of each algorithm. Fusing estimates in this way may then be used to infer the underlying ground truth for individual patients. It is shown that modelling the latent correlations between algorithms improves the RR estimates, when compared to commonly employed strategies in the literature. Finally, it is demonstrated that the adoption of a strongly Bayesian approach to inference using Gibbs sampling results in improved estimation over the current state-of-the-art (e.g. hierarchical Gaussian processes) in physiological time-series modelling
S-fold magnetic quivers
No full textMagnetic quivers and Hasse diagrams for Higgs branches of rank r 4d N = 2 SCFTs arising from ℤℓ S-fold constructions are discussed. The magnetic quivers are derived using three different methods: 1) Using clues like dimension, global symmetry, and the folding parameter ℓ to guess the magnetic quiver. 2) From 6d N = (1, 0) SCFTs as UV completions of 5d marginal theories, and specific FI deformations on their magnetic quiver, which is further folded by ℤℓ. 3) From T-duality of Type IIA brane systems of 6d N = (1, 0) SCFTs and explicit mass deformation of the resulting brane web followed by ℤℓ folding. A choice of the ungauging scheme, either on a long node or on a short node, yields two different moduli spaces related by an orbifold action, thus suggesting a larger set of SCFTs in four dimensions than previously expected
Ostend through the eyes of British writers (1830-50): a seaside resort abroad as a home for the British genteel poor
No full textThis article analyzes how the British writers Frances Trollope (1779–1863) and William Makepeace Thackeray (1811–1863) described the Belgian coastal resort Ostend in the 1830s and 1840s. A special focus is placed on both the British travelers passing through Ostend and the British resident communities at Ostend. The article will highlight how the assessments of Frances Trollope and William Makepeace Thackeray of Ostend as a coastal resort frequented by the British can be unpacked fruitfully within two overarching themes: the theme of “genteel poverty” and “respectability” on the one hand, and the theme of “national identity” and “religious identity” on the other. These assessments by Frances Trollope and William Makepeace Thackeray are contextualized against the background of contemporary British guidebooks and travel accounts on Ostend, and against some statistics on the British traveller and resident communities in mid-nineteenth century Belgium. (PF
Risk factors for the development of neonatal sepsis in a neonatal intensive care unit of a tertiary care hospital of Nepal
No full textBackground
Sepsis is an overwhelming and life-threatening response to bacteria in bloodstream and a major cause of neonatal morbidity and mortality. Understanding the etiology and potential risk factors for neonatal sepsis is urgently required, particularly in low-income countries where burden of infection is high and its epidemiology is poorly understood.
Methods
A prospective observational cohort study was conducted between April 2016 and October 2017 in a level three NICU at a tertiary care hospital in Nepal to determine the bacterial etiology and potential risk factors for neonatal sepsis.
Results
Among 142 NICU admitted neonates, 15% (21/142) and 32% (46/142) developed blood culture-positive and -negative neonatal sepsis respectively. Klebsiella pneumoniae (34%, 15/44) and Enterobacter spp. (25%, 11/44) were the most common isolates. The antimicrobial resistance of isolates to ampicillin (100%, 43/43), cefotaxime (74%, 31/42) and ampicillin-sulbactam (55%, 21/38) were the highest. BlaTEM (53%, 18/34) and blaKPC (46%, 13/28) were the commonest ESBL and carbapenemase genes respectively. In univariate logistic regression, the odds of sepsis increased with each additional day of use of invasive procedures such as mechanical ventilation (OR 1.086, 95% CI 1.008–1.170), umbilical artery catheter (OR 1.375, 95% CI 1.049–1.803), intravenous cannula (OR 1.140, 95% CI 1.062–1.225); blood transfusion events (OR 3.084, 95% CI 1.407–6.760); NICU stay (OR 1.109, 95% CI 1.040–1.182) and failure to breast feed (OR 1.130, 95% CI 1.060–1.205). Sepsis odds also increased with leukopenia (OR 1.790, 95% CI 1.04–3.082), increase in C-reactive protein (OR 1.028, 95% CI 1.016–1.040) and decrease in platelets count (OR 0.992, 95% CI 0.989–0.994). In multivariate analysis, increase in IV cannula insertion days (OR 1.147, 95% CI 1.039–1.267) and CRP level (OR 1.028, 95% CI 1.008–1.049) increased the odds of sepsis.
Conclusions
Our study indicated various nosocomial risk factors and underscored the need to improve local infection control measures so as to reduce the existing burden of sepsis. We have highlighted certain sepsis associated laboratory parameters along with identification of antimicrobial resistance genes, which can guide for early and better therapeutic management of sepsis. These findings could be extrapolated to other low-income settings within the region
Monads for measurable queries in probabilistic databases
No full textWe consider a bag (multiset) monad on the category of standard Borel spaces, and show that it gives a free measurable commutative monoid. Firstly, we show that a recent measurability result for probabilistic database queries (Grohe and Lindner, ICDT 2020) follows quickly from the fact that queries can be expressed in monad-based terms. We also extend this measurability result to a
fuller query language. Secondly, we discuss a distributive law between probability and bag monads, and we illustrate that this is useful for generating probabilistic databases
Immunomodulation for optimal cardiac regeneration: insights from comparative analyses
No full textDespite decades of research, regeneration of the infarcted human heart remains an unmet ambition. A significant obstacle facing experimental regenerative therapies is the hostile immune response which arises following a myocardial infarction (MI). Upon cardiac damage, sterile inflammation commences via the release of pro-inflammatory meditators, leading to the migration of neutrophils, eosinophils and monocytes, as well as the activation of local vascular cells and fibroblasts. This response is amplified by components of the adaptive immune system. Moreover, the physical trauma of the infarction and immune-mediated tissue injury provides a supply of autoantigens, perpetuating a cycle of autoreactivity, which further contributes to adverse remodelling. A gradual shift towards an immune-resolving environment follows, culminating in the formation of a collagenous scar, which compromises cardiac function, ultimately driving the development of heart failure. Comparing the human heart with those of animal models that are capable of cardiac regeneration reveals key differences in the innate and adaptive immune responses to MI. By modulating key immune components to better resemble those of regenerative species, a cardiac environment may be established which would, either independently or via the synergistic application of emerging regenerative therapies, improve functional recovery post-MI
Risk of adverse outcomes in patients with underlying respiratory conditions admitted to hospital with COVID-19: a national, multicentre prospective cohort study using the ISARIC WHO Clinical Characterisation Protocol UK
No full textBACKGROUND: Studies of patients admitted to hospital with COVID-19 have found varying mortality outcomes associated with underlying respiratory conditions and inhaled corticosteroid use. Using data from a national, multicentre, prospective cohort, we aimed to characterise people with COVID-19 admitted to hospital with underlying respiratory disease, assess the level of care received, measure in-hospital mortality, and examine the effect of inhaled corticosteroid use.
METHODS: We analysed data from the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK) study. All patients admitted to hospital with COVID-19 across England, Scotland, and Wales between Jan 17 and Aug 3, 2020, were eligible for inclusion in this analysis. Patients with asthma, chronic pulmonary disease, or both, were identified and stratified by age (<16 years, 16-49 years, and ≥50 years). In-hospital mortality was measured by use of multilevel Cox proportional hazards, adjusting for demographics, comorbidities, and medications (inhaled corticosteroids, short-acting β-agonists [SABAs], and long-acting β-agonists [LABAs]). Patients with asthma who were taking an inhaled corticosteroid plus LABA plus another maintenance asthma medication were considered to have severe asthma.
FINDINGS: 75 463 patients from 258 participating health-care facilities were included in this analysis: 860 patients younger than 16 years (74 [8·6%] with asthma), 8950 patients aged 16-49 years (1867 [20·9%] with asthma), and 65 653 patients aged 50 years and older (5918 [9·0%] with asthma, 10 266 [15·6%] with chronic pulmonary disease, and 2071 [3·2%] with both asthma and chronic pulmonary disease). Patients with asthma were significantly more likely than those without asthma to receive critical care (patients aged 16-49 years: adjusted odds ratio [OR] 1·20 [95% CI 1·05-1·37]; p=0·0080; patients aged ≥50 years: adjusted OR 1·17 [1·08-1·27]; p<0·0001), and patients aged 50 years and older with chronic pulmonary disease (with or without asthma) were significantly less likely than those without a respiratory condition to receive critical care (adjusted OR 0·66 [0·60-0·72] for those without asthma and 0·74 [0·62-0·87] for those with asthma; p<0·0001 for both). In patients aged 16-49 years, only those with severe asthma had a significant increase in mortality compared to those with no asthma (adjusted hazard ratio [HR] 1·17 [95% CI 0·73-1·86] for those on no asthma therapy, 0·99 [0·61-1·58] for those on SABAs only, 0·94 [0·62-1·43] for those on inhaled corticosteroids only, 1·02 [0·67-1·54] for those on inhaled corticosteroids plus LABAs, and 1·96 [1·25-3·08] for those with severe asthma). Among patients aged 50 years and older, those with chronic pulmonary disease had a significantly increased mortality risk, regardless of inhaled corticosteroid use, compared to patients without an underlying respiratory condition (adjusted HR 1·16 [95% CI 1·12-1·22] for those not on inhaled corticosteroids, and 1·10 [1·04-1·16] for those on inhaled corticosteroids; p<0·0001). Patients aged 50 years and older with severe asthma also had an increased mortality risk compared to those not on asthma therapy (adjusted HR 1·24 [95% CI 1·04-1·49]). In patients aged 50 years and older, inhaled corticosteroid use within 2 weeks of hospital admission was associated with decreased mortality in those with asthma, compared to those without an underlying respiratory condition (adjusted HR 0·86 [95% CI 0·80-0·92]).
INTERPRETATION: Underlying respiratory conditions are common in patients admitted to hospital with COVID-19. Regardless of the severity of symptoms at admission and comorbidities, patients with asthma were more likely, and those with chronic pulmonary disease less likely, to receive critical care than patients without an underlying respiratory condition. In patients aged 16 years and older, severe asthma was associated with increased mortality compared to non-severe asthma. In patients aged 50 years and older, inhaled corticosteroid use in those with asthma was associated with lower mortality than in patients without an underlying respiratory condition; patients with chronic pulmonary disease had significantly increased mortality compared to those with no underlying respiratory condition, regardless of inhaled corticosteroid use. Our results suggest that the use of inhaled corticosteroids, within 2 weeks of admission, improves survival for patients aged 50 years and older with asthma, but not for those with chronic pulmonary disease.
FUNDING: National Institute for Health Research, Medical Research Council, NIHR Health Protection Research Units in Emerging and Zoonotic Infections at the University of Liverpool and in Respiratory Infections at Imperial College London in partnership with Public Health England
Interactive contouring through contextual deep learning
No full textPurpose: To investigate a deep learning approach that enables 3D segmentation of an arbitrary structure of interest given a user provided 2D contour for context. Such an approach could decrease delineation times and improve contouring consistency, particularly for anatomical structures for which no automatic segmentation tools exist.
Methods: A series of deep learning segmentation models using a Recurrent Residual U-Net with attention gates was trained with a successively expanding training set. Contextual information was provided to the models, using a previously contoured slice as an input, in addition to the slice to be contoured. In total, 6 models were developed, and 19 different anatomical structures were used for training and testing. Each of the models was evaluated for all 19 structures, even if they were excluded from the training set, in order to assess the model’s ability to segment unseen structures of interest. Each model’s performance was evaluated using the Dice Similarity Coefficient (DSC), Hausdorff distance and relative Added Path Length (APL).
Results: The segmentation performance for seen and unseen structures improved when the training set was expanded by addition of structures previously excluded from the training set. A model trained exclusively on heart structures achieved a DSC of 0.33, HD of 44 mm and relative APL of 0.85 when segmenting the spleen, whereas a model trained on a diverse set of structures, but still excluding the spleen, achieved a DSC of 0.80, HD of 13 mm and relative APL of 0.35. Iterative prediction performed better compared to direct prediction when considering unseen structures.
Conclusions: Training a contextual deep learning model on a diverse set of structures increases the segmentation performance for the structures in the training set, but importantly enables the model to generalize and make predictions even for unseen structures that were not represented in the training set. This shows that user-provided context can be incorporated into deep learning contouring to facilitate semi-automatic segmentation of CT images for any given structure. Such an approach can enable faster de-novo contouring in clinical practice
Six-month neurological and psychiatric outcomes in 236,379 survivors of COVID-19
No full textBackground: Neurological and psychiatric sequelae of COVID-19 have been reported, but more data are needed to adequately assess the effects of COVID-19 on brain health. We aimed to provide robust estimates of incidence rates and relative risks of neurological and psychiatric diagnoses in patients in the 6 months following a COVID-19 diagnosis.
Methods: For this retrospective cohort study and time-to-event analysis, we used data obtained from the TriNetX electronic health records network (with over 81 million patients). Our primary cohort comprised patients who had a COVID-19 diagnosis; one matched control cohort included patients diagnosed with influenza, and the other matched control cohort included patients diagnosed with any respiratory tract infection including influenza in the same period. Patients with a diagnosis of COVID-19 or a positive test for SARS-CoV-2 were excluded from the control cohorts. All cohorts included patients older than 10 years who had an index event on or after Jan 20, 2020, and who were still alive on Dec 13, 2020. We estimated the incidence of 14 neurological and psychiatric outcomes in the 6 months after a confirmed diagnosis of COVID-19: intracranial haemorrhage; ischaemic stroke; parkinsonism; Guillain-Barré syndrome; nerve, nerve root, and plexus disorders; myoneural junction and muscle disease; encephalitis; dementia; psychotic, mood, and anxiety disorders (grouped and separately); substance use disorder; and insomnia. Using a Cox model, we compared incidences with those in propensity score-matched cohorts of patients with influenza or other respiratory tract infections. We investigated how these estimates were affected by COVID-19 severity, as proxied by hospitalisation, intensive therapy unit (ITU) admission, and encephalopathy (delirium and related disorders). We assessed the robustness of the differences in outcomes between cohorts by repeating the analysis in different scenarios. To provide benchmarking for the incidence and risk of neurological and psychiatric sequelae, we compared our primary cohort with four cohorts of patients diagnosed in the same period with additional index events: skin infection, urolithiasis, fracture of a large bone, and pulmonary embolism.
Findings: Among 236 379 patients diagnosed with COVID-19, the estimated incidence of a neurological or psychiatric diagnosis in the following 6 months was 33·62% (95% CI 33·17–34·07), with 12·84% (12·36–13·33) receiving their first such diagnosis. For patients who had been admitted to an ITU, the estimated incidence of a diagnosis was 46·42% (44·78–48·09) and for a first diagnosis was 25·79% (23·50–28·25). Regarding individual diagnoses of the study outcomes, the whole COVID-19 cohort had estimated incidences of 0·56% (0·50–0·63) for intracranial haemorrhage, 2·10% (1·97–2·23) for ischaemic stroke, 0·11% (0·08–0·14) for parkinsonism, 0·67% (0·59–0·75) for dementia, 17·39% (17·04–17·74) for anxiety disorder, and 1·40% (1·30–1·51) for psychotic disorder, among others. In the group with ITU admission, estimated incidences were 2·66% (2·24–3·16) for intracranial haemorrhage, 6·92% (6·17–7·76) for ischaemic stroke, 0·26% (0·15–0·45) for parkinsonism, 1·74% (1·31–2·30) for dementia, 19·15% (17·90–20·48) for anxiety disorder, and 2·77% (2·31–3·33) for psychotic disorder. Most diagnostic categories were more common in patients who had COVID-19 than in those who had influenza (hazard ratio [HR] 1·44, 95% CI 1·40–1·47, for any diagnosis; 1·78, 1·68–1·89, for any first diagnosis) and those who had other respiratory tract infections (1·16, 1·14–1·17, for any diagnosis; 1·32, 1·27–1·36, for any first diagnosis). As with incidences, HRs were higher in patients who had more severe COVID-19 (eg, those admitted to ITU compared with those who were not: 1·58, 1·50–1·67, for any diagnosis; 2·87, 2·45–3·35, for any first diagnosis). Results were robust to various sensitivity analyses and benchmarking against the four additional index health events.
Interpretation: Our study provides evidence for substantial neurological and psychiatric morbidity in the 6 months after COVID-19 infection. Risks were greatest in, but not limited to, patients who had severe COVID-19. This information could help in service planning and identification of research priorities. Complementary study designs, including prospective cohorts, are needed to corroborate and explain these findings
The Orbit Problem for parametric linear dynamical systems
No full textWe study a parametric version of the Kannan-Lipton Orbit Problem for linear dynamical systems. We show decidability in the case of one parameter and Skolem-hardness with two or more parameters.
More precisely, consider a d-dimensional square matrix M whose entries are algebraic functions in one or more real variables. Given initial and target vectors u,v ∈ ℚ^d, the parametric point-to-point orbit problem asks whether there exist values of the parameters giving rise to a concrete matrix N ∈ ℝ^{d× d}, and a positive integer n ∈ ℕ, such that N^{n} u = v.
We show decidability for the case in which M depends only upon a single parameter, and we exhibit a reduction from the well-known Skolem Problem for linear recurrence sequences, suggesting intractability in the case of two or more parameters