Prioritization of COPD protein biomarkers, based on a systematic study of the literature

Chronic Obstructive Pulmonary Disease (COPD) is a chronic lung disease mostly due to smoking and until now diagnosed by spirometry (post bronchodilator FEV1/FVC <70%). However, in spite of the usefulness of FEV1 as diagnostic and prognostic tool, it has proven to be a weak indicator of future exacerbations, unable to predict lung function decline within COPD patients, as well as unable to identify the smokers “susceptible” to developing COPD at an early stage. Thus, there is an urgent need for biomarkers that address these questions and support clinical decision making in the diagnosis and treatment of (early) COPD. In this respect, considerable efforts have been devoted to identifying protein biomarkers that enable a better understanding of this complex disease and leading to better diagnostic and prognostic tools. However, in spite of the wide range of candidates that have been suggested as potentially useful COPD biomarkers, most remained at the level of the initial discovery, and only fibrinogen has been approved by the Food and Drug Administration (FDA) as predictor for all-cause mortality and COPD exacerbations. There is thus a need for future investigations of these biomarkers in large-scale and well characterized studies in order to prove their usefulness as surrogate endpoints. Based on this, the aim of the present review is to advance COPD biomarker development by providing a comprehensive overview of protein biomarker candidates which have been evaluated in clinical studies and prioritize them according to their potential of becoming valid, clinically useful COPD biomarkers.

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Religion and Medicine

10.1093/oso/9780190867355.001.0001 ◽

2020 ◽

Author(s):

Jeff Levin ◽

Stephen G. Post

Keyword(s):

Clinical Decision Making ◽

Well Being ◽

Clinical Decision ◽

Religion And Medicine ◽

Physical And Mental Health ◽

Faith Based ◽

Baylor University ◽

Wide Range ◽

History Of ◽

The Impact

In Religion and Medicine, Dr. Jeff Levin, distinguished Baylor University epidemiologist, outlines the longstanding history of multifaceted interconnections between the institutions of religion and medicine. He traces the history of the encounter between these two institutions from antiquity through to the present day, highlighting a myriad of contemporary alliances between the faith-based and medical sectors. Religion and Medicine tells the story of: religious healers and religiously branded hospitals and healthcare institutions; pastoral professionals involved in medical missions, healthcare chaplaincy, and psychological counseling; congregational health promotion and disease prevention programs and global health initiatives; research studies on the impact of religious and spiritual beliefs and practices on physical and mental health, well-being, and healing; programs and centers for medical research and education within major universities and academic institutions; religiously informed bioethics and clinical decision-making; and faith-based health policy initiatives and advocacy for healthcare reform. Religion and Medicine is the first book to cover the full breadth of this subject. It documents religion-medicine alliances across religious traditions, throughout the world, and over the course of history. It summarizes a wide range of material of relevance to historians, medical professionals, pastors and theologians, bioethicists, scientists, public health educators, and policymakers. The product of decades of rigorous and focused research, Dr. Levin has produced the most comprehensive history of these developments and the finest introduction to this emerging field of scholarship.

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Uncertainty-Aware Deep Learning-Based Cardiac Arrhythmias Classification Model of Electrocardiogram Signals

Computers ◽

10.3390/computers10060082 ◽

2021 ◽

Vol 10 (6) ◽

pp. 82

Author(s):

Ahmad O. Aseeri

Keyword(s):

Deep Learning ◽

Cardiac Arrhythmias ◽

Large Scale ◽

Clinical Decision Making ◽

Probabilistic Approach ◽

Classification Model ◽

Gating Mechanism ◽

Uncertainty Estimates ◽

Wide Range

Deep Learning-based methods have emerged to be one of the most effective and practical solutions in a wide range of medical problems, including the diagnosis of cardiac arrhythmias. A critical step to a precocious diagnosis in many heart dysfunctions diseases starts with the accurate detection and classification of cardiac arrhythmias, which can be achieved via electrocardiograms (ECGs). Motivated by the desire to enhance conventional clinical methods in diagnosing cardiac arrhythmias, we introduce an uncertainty-aware deep learning-based predictive model design for accurate large-scale classification of cardiac arrhythmias successfully trained and evaluated using three benchmark medical datasets. In addition, considering that the quantification of uncertainty estimates is vital for clinical decision-making, our method incorporates a probabilistic approach to capture the model’s uncertainty using a Bayesian-based approximation method without introducing additional parameters or significant changes to the network’s architecture. Although many arrhythmias classification solutions with various ECG feature engineering techniques have been reported in the literature, the introduced AI-based probabilistic-enabled method in this paper outperforms the results of existing methods in outstanding multiclass classification results that manifest F1 scores of 98.62% and 96.73% with (MIT-BIH) dataset of 20 annotations, and 99.23% and 96.94% with (INCART) dataset of eight annotations, and 97.25% and 96.73% with (BIDMC) dataset of six annotations, for the deep ensemble and probabilistic mode, respectively. We demonstrate our method’s high-performing and statistical reliability results in numerical experiments on the language modeling using the gating mechanism of Recurrent Neural Networks.

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Clinician checklist for assessing suitability of machine learning applications in healthcare

BMJ Health & Care Informatics ◽

10.1136/bmjhci-2020-100251 ◽

2021 ◽

Vol 28 (1) ◽

pp. e100251

Author(s):

Ian Scott ◽

Stacey Carter ◽

Enrico Coiera

Keyword(s):

Machine Learning ◽

Large Scale ◽

Clinical Decision Making ◽

Improve Patient Care ◽

Clinical Decision ◽

Routine Care ◽

Machine Learning Algorithms ◽

Clinical Settings ◽

Machine Learning Applications ◽

Key Issues

Machine learning algorithms are being used to screen and diagnose disease, prognosticate and predict therapeutic responses. Hundreds of new algorithms are being developed, but whether they improve clinical decision making and patient outcomes remains uncertain. If clinicians are to use algorithms, they need to be reassured that key issues relating to their validity, utility, feasibility, safety and ethical use have been addressed. We propose a checklist of 10 questions that clinicians can ask of those advocating for the use of a particular algorithm, but which do not expect clinicians, as non-experts, to demonstrate mastery over what can be highly complex statistical and computational concepts. The questions are: (1) What is the purpose and context of the algorithm? (2) How good were the data used to train the algorithm? (3) Were there sufficient data to train the algorithm? (4) How well does the algorithm perform? (5) Is the algorithm transferable to new clinical settings? (6) Are the outputs of the algorithm clinically intelligible? (7) How will this algorithm fit into and complement current workflows? (8) Has use of the algorithm been shown to improve patient care and outcomes? (9) Could the algorithm cause patient harm? and (10) Does use of the algorithm raise ethical, legal or social concerns? We provide examples where an algorithm may raise concerns and apply the checklist to a recent review of diagnostic imaging applications. This checklist aims to assist clinicians in assessing algorithm readiness for routine care and identify situations where further refinement and evaluation is required prior to large-scale use.

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Prognostic Factors for Persistent Symptoms in Adults With Mild Traumatic Brain Injury: an Overview of Systematic Reviews

10.21203/rs.3.rs-948335/v1 ◽

2021 ◽

Author(s):

Julien Déry ◽

Béatrice Ouellet ◽

Élaine de Guise ◽

Ève-Line Bussières ◽

Marie-Eve Lamontagne

Keyword(s):

Traumatic Brain Injury ◽

Prognostic Factors ◽

Brain Injury ◽

Mild Traumatic Brain Injury ◽

Systematic Reviews ◽

Clinical Decision Making ◽

Clinical Decision ◽

Persistent Symptoms ◽

Wide Range ◽

Overview Of Systematic Reviews

Abstract Background: Mild traumatic brain injury (mTBI) is an increasing public health problem, because of its persistent symptoms and several functional consequences. Understanding the prognosis of a condition is an important component of clinical decision-making and can help to guide prevention of persistent symptoms following mTBI. Prognosis of mTBI has stimulated several empirical primary research papers and many systematic reviews leading to the identification of a wide range of factors. We aim to synthesize these factors to get a better understanding of their breadth and scope.Methods: We conducted an overview of systematic reviews. We searched in databases systematic reviews synthesizing evidence about prognosis of persistent symptoms after mTBI in the adult population. Two reviewers independently screened all references and selected eligible reviews based on eligibility criteria. They extracted relevant information using an extraction grid. They also rated independently the risk of bias using the ROBIS tool. We synthesized evidence into a comprehensive conceptual map to facilitate the understanding of prognostic factors that have an impact on persistent post-concussion symptoms.Results: From the 3857 references retrieved in database search, we included 25 systematic reviews integrating the results of 312 primary articles published between 1957 and 2019. We examined 35 prognostic factors from the systematics reviews. No single prognostic factor demonstrated convincing and conclusive results. However, age, sex and multiple concussions showed an affirmatory association with persistent post-concussion outcomes in systematic reviews.Conclusion: We highlighted the need of a comprehensive picture of prognostic factors related to persistent post-concussion symptoms. We believe that these prognostic factors would guide clinical decision and research related to prevention and intervention regarding persistent post-concussion symptoms.Systematic review registration: PROSPERO CRD42020176676

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Awareness, Knowledge, and Utility of RCT Data vs RWE: Results From a Survey of US Cardiologists: Real-world Evidence in Clinical Decision Making

Clinical Medicine Insights Cardiology ◽

10.1177/1179546820953410 ◽

2020 ◽

Vol 14 ◽

pp. 117954682095341 ◽

Cited By ~ 1

Author(s):

Todd C Villines ◽

Mark J Cziraky ◽

Alpesh N Amin

Keyword(s):

Decision Making ◽

Clinical Practice ◽

Real World ◽

Randomized Clinical Trials ◽

Clinical Decision Making ◽

Clinical Decision ◽

The Body ◽

Representative Sampling ◽

Real World Evidence ◽

Wide Range

Real-world evidence (RWE) provides a potential rich source of additional information to the body of data available from randomized clinical trials (RCTs), but there is a need to understand the strengths and limitations of RWE before it can be applied to clinical practice. To gain insight into current thinking in clinical decision making and utility of different data sources, a representative sampling of US cardiologists selected from the current, active Fellows of the American College of Cardiology (ACC) were surveyed to evaluate their perceptions of findings from RCTs and RWE studies and their application in clinical practice. The survey was conducted online via the ACC web portal between 12 July and 11 August 2017. Of the 548 active ACC Fellows invited as panel members, 173 completed the survey (32% response), most of whom were board certified in general cardiology (n = 119, 69%) or interventional cardiology (n = 40, 23%). The survey results indicated a wide range of familiarity with and utilization of RWE amongst cardiologists. Most cardiologists were familiar with RWE and considered RWE in clinical practice at least some of the time. However, a significant minority of survey respondents had rarely or never applied RWE learnings in their clinical practice, and many did not feel confident in the results of RWE other than registry data. These survey findings suggest that additional education on how to assess and interpret RWE could help physicians to integrate data and learnings from RCTs and RWE to best guide clinical decision making.

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Identification and Evaluation of Serum Protein Biomarkers Which Differentiate Psoriatic from Rheumatoid Arthritis

10.1101/2020.06.23.20138552 ◽

2020 ◽

Author(s):

Angela Mc Ardle ◽

Anna Kwasnik ◽

Agnes Szenpetery ◽

Melissa Jones ◽

Belinda Hernandez ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Serum Protein ◽

Clinical Decision Making ◽

Multiple Reaction Monitoring ◽

Area Under The Curve ◽

Clinical Decision ◽

Additional Patient ◽

Second Phase ◽

Protein Biomarkers ◽

Protein Discovery

AbstractObjectivesTo identify serum protein biomarkers which might separate early inflammatory arthritis (EIA) patients with psoriatic arthritis (PsA) from those with rheumatoid arthritis (RA) to provide an accurate diagnosis and support appropriate early intervention.MethodsIn an initial protein discovery phase, the serum proteome of a cohort of patients with PsA and RA was interrogated using unbiased liquid chromatography mass spectrometry (LC-MS/MS) (n=64 patients), a multiplexed antibody assay (Luminex) for 48 proteins (n=64 patients) and an aptamer-based assay (SOMAscan) targeting 1,129 proteins (n=36 patients). Subsequently, analytically validated targeted multiple reaction monitoring (MRM) assays were developed to further evaluate those proteins identified as discriminatory during the discovery. During an initial verification phase, MRM assays were developed to a panel of 150 proteins (by measuring a total of 233 peptides) and used to re-evaluate the discovery cohort (n=60). During a second verification phase, the panel of proteins was expanded to include an additional 23 proteins identified in other proteomic discovery analyses of arthritis patients. The expanded panel was evaluated using a second, independent cohort of PsA and RA patients (n=167).ResultsMultivariate analysis of the protein discovery data revealed that it was possible to discriminate PsA from RA patients with an area under the curve (AUC) of 0.94 for nLC-MS/MS, 0.69 for Luminex based measurements; 0.73 for SOMAscan analysis. During the initial verification phase, random forest models confirmed that proteins measured by MRM could differentiate PsA and RA patients with an AUC of 0.79 and during the second phase of verification the expanded panel could segregate the two disease groups with an AUC of 0.85.ConclusionWe report a serum protein biomarker panel which can separate EIA patients with PsA from those with RA. We suggest that the routine use of such a panel in EIA patients will improve clinical decision making and with continued evaluation and refinement using additional patient cohorts will support the development of a diagnostic test for patients with PsA.

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Single-inhaler triple therapy in symptomatic COPD patients: FULFIL subgroup analyses

ERJ Open Research ◽

10.1183/23120541.00119-2017 ◽

2018 ◽

Vol 4 (2) ◽

pp. 00119-2017 ◽

Cited By ~ 5

Author(s):

David M.G. Halpin ◽

Ruby Birk ◽

Noushin Brealey ◽

Gerard J. Criner ◽

Mark T. Dransfield ◽

...

Keyword(s):

Disease Severity ◽

Clinical Decision Making ◽

Clinical Decision ◽

Forced Expiratory Volume ◽

Phase Iii ◽

Chronic Obstructive ◽

Double Blind Study ◽

Double Blind ◽

Subgroup Analyses ◽

Long Acting

Triple inhaled corticosteroid (ICS)/long-acting muscarinic antagonist (LAMA)/long-acting β2-agonist (LABA) therapy is recommended for symptomatic patients with chronic obstructive pulmonary disease (COPD) and at risk of exacerbations. However, the benefits versus side-effects of triple inhaled therapy for COPD, based on distinct patient clinical profiles, are unclear.FULFIL, a phase III, randomised, double-blind study, compared 24 weeks of once-daily fluticasone furoate/umeclidinium/vilanterol (FF/UMEC/VI) 100/62.5/25 µg using the Ellipta inhaler with twice-daily budesonide/formoterol (BUD/FOR) 400/12 µg using the Turbuhaler. Subgroup analyses of forced expiratory volume in 1 s (FEV1), St George's Respiratory Questionnaire (SGRQ) Total score and exacerbation rates were carried out. Subgroups were defined by COPD medication at screening (ICS+LABA, BUD+FOR, ICS+LABA+LAMA, LAMA alone, tiotropium alone and LAMA+LABA), by disease severity (lung function and exacerbations) and by exacerbation history (exacerbation severity and frequency).In the intent-to-treat population (n=1810) at week 24, FF/UMEC/VI (n=911) versus BUD/FOR (n=899) improved FEV1 and SGRQ Total score and reduced mean annual exacerbation rates in all disease severity and exacerbation history subgroups. FF/UMEC/VI versus BUD/FOR improved FEV1 and SGRQ Total score in all medication subgroups and reduced mean annual exacerbation rates in all medication subgroups, except LAMA+LABA. Adverse events were similar across subgroups.These findings support the benefit of FF/UMEC/VI compared with dual ICS/LABA therapy in patients with symptomatic COPD regardless of disease severity or prior treatment and may help to inform clinical decision making.

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Pathogenesis of Peritoneal Sclerosis

The International Journal of Artificial Organs ◽

10.1177/039139880502800203 ◽

2005 ◽

Vol 28 (2) ◽

pp. 90-96 ◽

Cited By ~ 13

Author(s):

C. Pollock

Keyword(s):

Peritoneal Dialysis ◽

Large Scale ◽

Clinical Decision Making ◽

Inflammatory Cells ◽

Clinical Decision ◽

Cumulative Exposure ◽

Peritoneal Membrane ◽

Peritoneal Fibrosis ◽

Histological Data ◽

The Individual

Peritoneal sclerosis is an almost invariable consequence of peritoneal dialysis. In most circumstances it is “simple” sclerosis, manifesting clinically with an increasing peritoneal transport rate and loss of ultrafiltration capacity. In contrast, encapsulating peritoneal sclerosis is a life threatening and usually irreversible condition, associated with bowel obstruction, malnutrition and death. It is unknown whether common etiological factors underlie the development of these 2 clinically and pathologically distinct forms of peritoneal sclerosis. The majority of studies to date have investigated factors that contribute to “simple” sclerosis, although it remains possible that similar mechanisms are amplified in patients who develop encapsulated peritoneal sclerosis. The cellular elements that promote peritoneal sclerosis include the mesothelial cells, peritoneal fibroblasts and inflammatory cells. Factors that stimulate these cells to promote peritoneal fibrosis and neoangiogenesis, both inherent in the development of peritoneal sclerosis, include cytokines that are induced by exposure of the peritoneal membrane to high concentrations of glucose, advanced glycation of the peritoneal membrane and oxidative stress. The cumulative exposure to bioincompatible dialysate is likely to have an etiological role as the duration of dialysis correlates with the likelihood of developing peritoneal sclerosis. Indeed peritoneal dialysis using more biocompatible fluids has been shown to reduce the development of peritoneal sclerosis. The individual contribution of the factors implicated in the development of peritoneal sclerosis will only be determined by large scale peritoneal biopsy registries, which will be able to prospectively incorporate clinical and histological data and support clinical decision making.

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A164 UPTAKE OF FECAL CALPROTECTIN IN PRACTICE: PATTERNS IN A TERTIARY GI REFERRAL CENTRE

Journal of the Canadian Association of Gastroenterology ◽

10.1093/jcag/gwz047.163 ◽

2020 ◽

Vol 3 (Supplement_1) ◽

pp. 28-30

Author(s):

A Kundra ◽

T Ritchie ◽

M Ropeleski

Keyword(s):

Medical Therapy ◽

Bowel Disease ◽

Large Scale ◽

Clinical Decision Making ◽

Practice Patterns ◽

Clinical Decision ◽

Fecal Calprotectin ◽

Time Interval ◽

Chart Audit ◽

Frequency Pattern

Abstract Background Fecal Calprotectin (FC) is helpful in distinguishing functional from organic bowel disease. Also, it has proven useful in monitoring disease activity in inflammatory bowel disease (IBD). The uptake of its use in clinical practice has increased considerably, though access varies significantly. Studies exploring current practice patterns among GI specialists and how to optimize its use are limited. In 2017, Kingston Health Sciences Centre (KHSC) began funding FC testing at no cost to patients. Aims We aimed to better understand practice patterns of gastroenterologists in IBD patients where there is in house access to FC assays, and to generate hypotheses regarding its optimal use in IBD monitoring. We hypothesize that FC is not being used in a regular manner for monitoring of IBD patients. Methods A retrospective chart audit study was done on all KHSC patients who had FC testing completed from 2017–2018. Qualitative data was gathered from dictated reports using rigorous set definitions regarding indication for the test, change in clinical decision making, and frequency patterns of testing. Specifically, change in use for colonoscopy or in medical therapy was coded only if the dictated note was clear that a decision hinged largely on the FC result. Frequency of testing was based on test order date. Reactive testing was coded as tests ordered to confirm a clinical flare. Variable testing was coded where monitoring tests that varied in intervals greater than 3 months and crossed over the other set frequency codes. Quantitative data regarding FC test values, and dates were also collected. This data was then analyzed using descriptive statistics. Results Of the 834 patients in our study, 7 were under 18 years old and excluded. 562(67.34%) of these patients had a pre-existing diagnosis of IBD; 193 (34%) with Ulcerative Colitis (UC), 369 (66%) with Crohn’s Disease (CD). FC testing changed the clinician’s decision for medical therapy in 12.82% of cases and use for colonoscopy 13.06% of the time for all comers. Of the FC tests, 79.8% were sent in a variable frequency pattern and 2.68% with reactive intent. The remaining 17.5% were monitored with a regular pattern, with 8.57% patients having their FC monitored at regular intervals greater than 6 months, 7.68% every 6 months, and 1.25% less than 6 months. The average FC level of patients with UC was 356.2ug/ml and 330.6 ug/ml for CD. The mean time interval from 1st to 2nd test was 189.6 days. Conclusions FC testing changed clinical decisions regarding medical therapy and use for colonoscopy about 13% of the time. FC testing was done variably 79.8% of the time, where as 17.5% of patients had a regular FC monitoring schedule. An optimal monitoring interval for IBD flares using FC for maximal clinical benefit has yet to be determined. Large scale studies will be required to answer this question. Funding Agencies None

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Multimodality Imaging in the Diagnostic Work-Up of Endocarditis and Cardiac Implantable Electronic Device (CIED) Infection

Journal of Clinical Medicine ◽

10.3390/jcm9072237 ◽

2020 ◽

Vol 9 (7) ◽

pp. 2237

Author(s):

Nicola Galea ◽

Francesco Bandera ◽

Chiara Lauri ◽

Camillo Autore ◽

Andrea Laghi ◽

...

Keyword(s):

Clinical Decision Making ◽

Electronic Device ◽

Multimodality Imaging ◽

Nuclear Imaging ◽

Clinical Decision ◽

Cardiac Device ◽

Systemic Complications ◽

Advantages And Disadvantages ◽

Clinical Scenarios ◽

Wide Range

Infective endocarditis (IE) is a serious cardiac condition, which includes a wide range of clinical presentations, with varying degrees of severity. The diagnosis is multifactorial and a proper characterization of disease requires the identification of the primary site of infection (usually the cardiac valve) and the search of secondary systemic complications. Early depiction of local complications or distant embolization has a great impact on patient management and prognosis, as it may induce to aggressive antibiotic treatment or, in more advanced cases, cardiac surgery. In this setting, the multimodality imaging has assumed a pivotal role in the clinical decision making and it requires the physician to be aware of the advantages and disadvantages of each imaging technique. Echocardiography is the first imaging test, but it has several limitations. Therefore, the integration with other imaging modalities (computed tomography, magnetic resonance imaging, nuclear imaging) becomes often necessary. Different strategies should be applied depending on whether the infection is suspected or already ascertained, whether located in native or prosthetic valves, in the left or right chambers, or if it involves an implanted cardiac device. In addition, detection of extracardiac IE-related lesions is crucial for a correct management and treatment. The aim of this review is to illustrate strengths and weaknesses of the various methods in the most common clinical scenarios.

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