Real Time QRS Detection Based on M-ary Likelihood Ratio Test on the DFT Coefficients

This paper shows an adaptive statistical test for QRS detection of electrocardiography (ECG) signals. The method is based on a M-ary generalized likelihood ratio test (LRT) defined over a multiple observation window in the Fourier domain. The motivations for proposing another detection algorithm based on maximum a posteriori (MAP) estimation are found in the high complexity of the signal model proposed in previous approaches which i) makes them computationally unfeasible or not intended for real time applications such as intensive care monitoring and (ii) in which the parameter selection conditions the overall performance. In this sense, we propose an alternative model based on the independent Gaussian properties of the Discrete Fourier Transform (DFT) coefficients, which allows to define a simplified MAP probability function. In addition, the proposed approach defines an adaptive MAP statistical test in which a global hypothesis is defined on particular hypotheses of the multiple observation window. In this sense, the observation interval is modeled as a discontinuous transmission discrete-time stochastic process avoiding the inclusion of parameters that constraint the morphology of the QRS complexes.This work has received research funding from the Spanish government (www.micinn.es) under project TEC2012 34306 (DiagnoSIS, Diagnosis by means of Statistical Intelligent Systems, 70K€) and projects P09-TIC-4530 (300K€) and P11-TIC-7103 (156K€) from the Andalusian government (http://www.juntadeandalucia.es/organismo​s/economiainnovacioncienciayempleo.html)

Insulin degludec is not associated with a delayed or diminished response to hypoglycaemia compared with insulin glargine in type 1 diabetes: a double-blind randomised crossover study

Aims/hypothesis: Insulin degludec (Des(B30)LysB29(γ-Glu Nε-hexadecandioyl) human insulin; IDeg) is a new basal insulin with an ultra-long flat action profile. The acute physiological responses to hypoglycaemia with IDeg and insulin glargine (A21Gly,B31Arg,B32Arg human insulin; IGlar) were compared. Methods: Twenty-eight adult type 1 diabetic patients with normal hypoglycaemia awareness (age = 41 ± 12 years, HbA1c = 7.8 ± 0.6% [62.8 ± 7 mmol/mol]) were randomised to once-daily IDeg or IGlar for 5 days in a two-period crossover design. Participants and research staff were blinded to group assignment. Patients were assigned the lowest available randomisation number from a set of blinded randomisation codes provided by the trial sponsor. Hypoglycaemia was induced by administering three times the usual daily insulin dose at midnight on day 5. Plasma glucose (PG) was stabilised by glucose clamp (5.5 mmol/l) for 7–9 h post dosing. Next morning, PG was allowed to decrease stepwise from 5.5 to 3.5 mmol/l (maintained for 30 min) to 2.5 mmol/l (for 15 min). PG was then increased to 3.9 mmol/l (for 120 min), before being returned to baseline. Hypoglycaemic symptom score (HSS), hypoglycaemic awareness, cognitive function, counter-regulatory hormones and vital signs were assessed during each glucose plateau. The primary analysis was to compare IDeg vs IGlar with respect to HSS at nadir PG concentration (2.5 mmol/l). Results: The full analysis set for treatment comparisons comprised data from all 28 exposed patients. Rates of PG decline and PG at nadir were similar for IDeg and IGlar. No treatment differences in HSS (estimated difference: 0.17 [95% CI −1.71, 2.05]; p > 0.05), cognitive function or awareness were observed at any time. Growth hormone and cortisol responses during hypoglycaemia were greater with IDeg than IGlar (AUC treatment ratio [IDeg/IGlar]: 2.44 [1.30, 4.60], p < 0.01; and 1.23 [1.01, 1.50]; p < 0.05), and adrenaline (epinephrine) responses trended higher (1.40 [0.96, 2.04], p = 0.07). The rates of recovery from hypoglycaemia were similar. Conclusions/interpretation: IDeg and IGlar elicit comparable symptomatic and cognitive responses to induced hypoglycaemia. IDeg may elicit a moderately greater endocrine response, but times to PG recovery were similar for the two insulins

Diabetes and the Risk of Multi-System Aging Phenotypes: A Systematic Review and Meta-Analysis

[[abstract]]Background: Observational studies suggested an association between diabetes and the risk of various geriatric conditions (i.e., cognitive impairment, dementia, depression, mobility impairment, disability, falls, and urinary incontinence). However, the magnitude and impact of diabetes on older adults have not been reviewed. Methodology/Principal Findings: MEDLINE and PSYCINFO databases were searched through November 2007 for published studies, supplemented by manual searches of bibliographies of key articles. Population-based, prospective cohort studies that reported risk of geriatric outcomes in relation to diabetes status at baseline were selected. Two authors independently extracted the data, including study population and follow-up duration, ascertainment of diabetes status at baseline, outcomes of interest and their ascertainment, adjusted covariates, measures of association, and brief results. Fifteen studies examined the association of DM with cognitive dysfunction. DM was associated with a faster decline in cognitive function among older adults. The pooled adjusted risk ratio (RR) for all dementia when persons with DM were compared to those without was 1.47 (95% CI, 1.25 to 1.73). Summary RRs for Alzheimer's disease and vascular dementia comparing persons with DM to those without were 1.39 (CI, 1.16 to 1.66) and 2.38 (CI, 1.79 to 3.18), respectively. Four of 5 studies found significant association of DM with faster mobility decline and incident disability. Two studies examined the association of diabetes with falls in older women. Both found statistically significant associations. Insulin users had higher RR for recurrent falls. One study for urinary incontinence in older women found statistically significant associations. Two studies for depression did not suggest that DM was an independent predictor of incident depression. Conclusions/Significance: Current evidence supports that DM is associated with increased risk for selected geriatric conditions. Clinicians should increase their awareness and provide appropriate care. Future research is required to elucidate the underlying pathological pathway. 2009 Lu et al

Determinants of recovery from post-COVID-19 dyspnoea: analysis of UK prospective cohorts of hospitalised COVID-19 patients and community-based controls

Background The risk factors for recovery from COVID-19 dyspnoea are poorly understood. We investigated determinants of recovery from dyspnoea in adults with COVID-19 and compared these to determinants of recovery from non-COVID-19 dyspnoea. Methods We used data from two prospective cohort studies: PHOSP-COVID (patients hospitalised between March 2020 and April 2021 with COVID-19) and COVIDENCE UK (community cohort studied over the same time period). PHOSP-COVID data were collected during hospitalisation and at 5-month and 1-year follow-up visits. COVIDENCE UK data were obtained through baseline and monthly online questionnaires. Dyspnoea was measured in both cohorts with the Medical Research Council Dyspnoea Scale. We used multivariable logistic regression to identify determinants associated with a reduction in dyspnoea between 5-month and 1-year follow-up. Findings We included 990 PHOSP-COVID and 3309 COVIDENCE UK participants. We observed higher odds of improvement between 5-month and 1-year follow-up among PHOSP-COVID participants who were younger (odds ratio 1.02 per year, 95% CI 1.01–1.03), male (1.54, 1.16–2.04), neither obese nor severely obese (1.82, 1.06–3.13 and 4.19, 2.14–8.19, respectively), had no pre-existing anxiety or depression (1.56, 1.09–2.22) or cardiovascular disease (1.33, 1.00–1.79), and shorter hospital admission (1.01 per day, 1.00–1.02). Similar associations were found in those recovering from non-COVID-19 dyspnoea, excluding age (and length of hospital admission). Interpretation Factors associated with dyspnoea recovery at 1-year post-discharge among patients hospitalised with COVID-19 were similar to those among community controls without COVID-19. Funding PHOSP-COVID is supported by a grant from the MRC-UK Research and Innovation and the Department of Health and Social Care through the National Institute for Health Research (NIHR) rapid response panel to tackle COVID-19. The views expressed in the publication are those of the author(s) and not necessarily those of the National Health Service (NHS), the NIHR or the Department of Health and Social Care. COVIDENCE UK is supported by the UK Research and Innovation, the National Institute for Health Research, and Barts Charity. The views expressed are those of the authors and not necessarily those of the funders