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  1. Article ; Online: The salivary microbiota of patients with acute lower respiratory tract infection–A multicenter cohort study

    Matthew B. Rogers / Ashley Harner / Megan Buhay / Brian Firek / Barbara Methé / Alison Morris / Octavia M. Peck Palmer / Susan B. Promes / Robert L. Sherwin / Lauren Southerland / Alexandre R. Vieira / Sachin Yende / Michael J. Morowitz / David T. Huang

    PLoS ONE, Vol 19, Iss

    2024  Volume 1

    Keywords Medicine ; R ; Science ; Q
    Language English
    Publishing date 2024-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: The salivary microbiota of patients with acute lower respiratory tract infection-A multicenter cohort study.

    Matthew B Rogers / Ashley Harner / Megan Buhay / Brian Firek / Barbara Methé / Alison Morris / Octavia M Peck Palmer / Susan B Promes / Robert L Sherwin / Lauren Southerland / Alexandre R Vieira / Sachin Yende / Michael J Morowitz / David T Huang

    PLoS ONE, Vol 19, Iss 1, p e

    2024  Volume 0290062

    Abstract: The human microbiome contributes to health and disease, but the oral microbiota is understudied relative to the gut microbiota. The salivary microbiota is easily accessible, underexplored, and may provide insight into response to infections. We sought to ...

    Abstract The human microbiome contributes to health and disease, but the oral microbiota is understudied relative to the gut microbiota. The salivary microbiota is easily accessible, underexplored, and may provide insight into response to infections. We sought to determine the composition, association with clinical features, and heterogeneity of the salivary microbiota in patients with acute lower respiratory tract infection (LRTI). We conducted a multicenter prospective cohort study of 147 adults with acute LRTI presenting to the emergency department of seven hospitals in three states (Pennsylvania, Michigan, and Ohio) between May 2017 and November 2018. Salivary samples were collected in the emergency department, at days 2-5 if hospitalized, and at day 30, as well as fecal samples if patients were willing. We compared salivary microbiota profiles from patients to those of healthy adult volunteers by sequencing and analyzing bacterial 16-rRNA. Compared to healthy volunteers, the salivary microbiota of patients with LRTI was highly distinct and strongly enriched with intestinal anaerobes such as Bacteroidaceae, Ruminococcaceae, and Lachnospiraceae (e.g., mean 10% relative abundance of Bacteroides vs < 1% in healthy volunteers). Within the LRTI population, COPD exacerbation was associated with altered salivary microbiota composition compared to other LRTI conditions. The largest determinant of microbiota variation within the LRTI population was geography (city in which the hospital was located).
    Keywords Medicine ; R ; Science ; Q
    Subject code 610
    Language English
    Publishing date 2024-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Development and implementation of the National Heart, Lung, and Blood Institute COVID-19 common data elements

    Alexandra Weissman / Alex Cheng / Alex Mainor / Elizabeth Gimbel / Kayla Nowak / Huaqin (Helen) Pan / Jeran Stratford / Alyssa Merkel / Caroline Taylor / Heather Meier / Jeanette Auman / Tracy L. Nolen / Christopher J. Lindsell / David T. Huang

    Journal of Clinical and Translational Science, Vol

    2022  Volume 6

    Abstract: Abstract Background: Coronavirus Disease 2019 (COVID-19) instigated a flurry of clinical research activity. The unprecedented pace with which trials were launched left an early void in data standardization, limiting the potential for subsequent data ... ...

    Abstract Abstract Background: Coronavirus Disease 2019 (COVID-19) instigated a flurry of clinical research activity. The unprecedented pace with which trials were launched left an early void in data standardization, limiting the potential for subsequent data pooling. To facilitate data standardization across emerging studies, the National Heart, Lung, and Blood Institute (NHLBI) charged two groups with harmonizing data collection, and these groups collaborated to create a concise set of COVID-19 Common Data Elements (CDEs) for clinical research. Methods: Our iterative approach followed three guiding principles: 1) draw from existing multi-center COVID-19 clinical trials as precedents, 2) incorporate existing data elements and data standards whenever possible, and 3) alignment to data standards that facilitate data sharing and regulatory submission. We also supported rapid implementation of the CDEs in NHLBI-funded studies and iteratively refined the CDEs based on feedback from those study teams Results: The NHLBI COVID-19 CDEs are publicly available and being used for current COVID-19 clinical trials. CDEs are organized into domains, and each data element is classified within a three-tiered prioritization system. The CDE manual is hosted publicly at https://nhlbi-connects.org/common_data_elements with an accompanying data dictionary and implementation guidance. Conclusions: The NHLBI COVID-19 CDEs are designed to aid data harmonization across studies to achieve the benefits of pooled analyses. We found that organizing CDE development around our three guiding principles focused our efforts and allowed us to adapt as COVID-19 knowledge advanced. As these CDEs continue to evolve, they could be generalized for use in other acute respiratory illnesses.
    Keywords Common data element ; CDE ; clinical trials ; COVID-19 ; FAIR ; CONNECTS ; Medicine ; R
    Subject code 610
    Language English
    Publishing date 2022-01-01T00:00:00Z
    Publisher Cambridge University Press
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Developing a New Computer-Aided Clinical Decision Support System for Prediction of Successful Postcardioversion Patients with Persistent Atrial Fibrillation

    Mark Sterling / David T. Huang / Behnaz Ghoraani

    Computational and Mathematical Methods in Medicine, Vol

    2015  Volume 2015

    Keywords Computer applications to medicine. Medical informatics ; R858-859.7 ; Medicine (General) ; R5-920 ; Medicine ; R
    Language English
    Publishing date 2015-01-01T00:00:00Z
    Publisher Hindawi Publishing Corporation
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Developing a New Computer-Aided Clinical Decision Support System for Prediction of Successful Postcardioversion Patients with Persistent Atrial Fibrillation

    Mark Sterling / David T. Huang / Behnaz Ghoraani

    Computational and Mathematical Methods in Medicine, Vol

    2015  Volume 2015

    Abstract: We propose a new algorithm to predict the outcome of direct-current electric (DCE) cardioversion for atrial fibrillation (AF) patients. AF is the most common cardiac arrhythmia and DCE cardioversion is a noninvasive treatment to end AF and return the ... ...

    Abstract We propose a new algorithm to predict the outcome of direct-current electric (DCE) cardioversion for atrial fibrillation (AF) patients. AF is the most common cardiac arrhythmia and DCE cardioversion is a noninvasive treatment to end AF and return the patient to sinus rhythm (SR). Unfortunately, there is a high risk of AF recurrence in persistent AF patients; hence clinically it is important to predict the DCE outcome in order to avoid the procedure’s side effects. This study develops a feature extraction and classification framework to predict AF recurrence patients from the underlying structure of atrial activity (AA). A multiresolution signal decomposition technique, based on matching pursuit (MP), was used to project the AA over a dictionary of wavelets. Seven novel features were derived from the decompositions and were employed in a quadratic discrimination analysis classification to predict the success of post-DCE cardioversion in 40 patients with persistent AF. The proposed algorithm achieved 100% sensitivity and 95% specificity, indicating that the proposed computational approach captures detailed structural information about the underlying AA and could provide reliable information for effective management of AF.
    Keywords Computer applications to medicine. Medical informatics ; R858-859.7
    Subject code 006
    Language English
    Publishing date 2015-01-01T00:00:00Z
    Publisher Hindawi Limited
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: The NICU Antibiotics and Outcomes (NANO) trial

    Michael J. Morowitz / Anup C. Katheria / Richard A. Polin / Elizabeth Pace / David T. Huang / Chung-Chou H. Chang / Johathan G. Yabes

    Trials, Vol 23, Iss 1, Pp 1-

    a randomized multicenter clinical trial assessing empiric antibiotics and clinical outcomes in newborn preterm infants

    2022  Volume 16

    Abstract: Abstract Background Early-onset sepsis is an important cause of neonatal morbidity and mortality in the preterm population. Infants perceived to be at increased risk for early-onset sepsis are often treated empirically with broad-spectrum antibiotics ... ...

    Abstract Abstract Background Early-onset sepsis is an important cause of neonatal morbidity and mortality in the preterm population. Infants perceived to be at increased risk for early-onset sepsis are often treated empirically with broad-spectrum antibiotics while awaiting confirmatory blood cultures, despite an overall incidence of early-onset sepsis of 2–3% among extremely-low-birthweight (ELBW) infants. Recent observational studies associate perinatal antibiotic use with an increased incidence of necrotizing enterocolitis, late-onset sepsis, and mortality among ELBW infants. Given currently available data and variability in clinical practice, we designed a prospective multi-institutional randomized controlled trial to determine the safety of early antibiotic use in ELBW infants. Methods The NICU Antibiotics and Outcomes (NANO) trial is a multicenter, double-blinded, randomized controlled trial. A sample of 802 ELBW preterm infants will undergo web-based stratified block randomization to receive empiric antibiotics (EA; ampicillin and gentamicin) or placebo during routine evaluation for early-onset sepsis. Participating sites will use preexisting institutional protocols for antibiotic dosage and duration. Infants born at participating sites with a gestational age of 29 weeks or less are eligible for enrollment. Exclusion criteria include maternal intrauterine infection, hemodynamic or respiratory instability, delivery by caesarean section for maternal indications without labor or prolonged rupture of membranes, and prior administration of antibiotics. The primary outcome is the composite incidence of necrotizing enterocolitis, late-onset sepsis, or death during participants’ index hospitalization. Maternal and infant samples will be collected longitudinally and assessed for differences in microbiome composition and diversity. Discussion The NANO trial is designed to compare the rate of adverse outcomes of EA use at birth versus placebo in ELBW preterm infants. If EA at birth worsens clinical outcomes, then the results ...
    Keywords Microbial colonization ; Extremely-low-birthweight ; Prematurity ; Early-onset neonatal sepsis ; Late-onset neonatal sepsis ; Necrotizing enterocolitis ; Medicine (General) ; R5-920
    Subject code 610
    Language English
    Publishing date 2022-05-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: The UPMC OPTIMISE-C19 (OPtimizing Treatment and Impact of Monoclonal antIbodieS through Evaluation for COVID-19) trial

    David T. Huang / Erin K. McCreary / J. Ryan Bariola / Richard J. Wadas / Kevin E. Kip / Oscar C. Marroquin / Stephen Koscumb / Kevin Collins / Judith A. Shovel / Mark Schmidhofer / Mary Kay Wisniewski / Colleen Sullivan / Donald M. Yealy / Meredith Axe / David A. Nace / Ghady Haidar / Tina Khadem / Kelsey Linstrum / Graham M. Snyder /
    Christopher W. Seymour / Stephanie K. Montgomery / Bryan J. McVerry / Lindsay Berry / Scott Berry / Russell Meyers / Alexandra Weissman / Octavia M. Peck-Palmer / Alan Wells / Robert Bart / Debbie L. Albin / Tami Minnier / Derek C. Angus

    Trials, Vol 22, Iss 1, Pp 1-

    a structured summary of a study protocol for an open-label, pragmatic, comparative effectiveness platform trial with response-adaptive randomization

    2021  Volume 3

    Abstract: Abstract Objectives The primary objective is to evaluate the comparative effectiveness of COVID-19 specific monoclonal antibodies (mABs) with US Food and Drug Administration (FDA) Emergency Use Authorization (EUA), alongside UPMC Health System efforts to ...

    Abstract Abstract Objectives The primary objective is to evaluate the comparative effectiveness of COVID-19 specific monoclonal antibodies (mABs) with US Food and Drug Administration (FDA) Emergency Use Authorization (EUA), alongside UPMC Health System efforts to increase patient access to these mABs. Trial design Open-label, pragmatic, comparative effectiveness platform trial with response-adaptive randomization Participants We will evaluate patients who meet the eligibility criteria stipulated by the COVID-19 mAB EUAs who receive mABs within the UPMC Health System, including infusion centers and emergency departments. EUA eligibility criteria include patients with mild to moderate COVID-19, <10 days of symptoms, and who are at high risk for progressing to severe COVID-19 and/or hospitalization (elderly, obese, and/or with specific comorbidities). The EUA criteria exclude patients who require oxygen for the treatment of COVID-19 and patients already hospitalized for the treatment of COVID-19. We will use data collected for routine clinical care, including data entered into the electronic medical record and from follow-up calls. Intervention and comparator The interventions are the COVID-19 specific mABs authorized by the EUAs. All aspects of mAB treatment, including eligibility criteria, dosing, and post-infusion monitoring, are as per the EUAs. As a comparative effectiveness trial, all patients receive mAB treatment, and the interventions are compared against each other. When U.S. government mAB policies change (e.g., FDA grants or revokes EUAs), UPMC Health System policies and the evaluated mAB interventions will accordingly change. From November 2020 to February 2021, FDA issued EUAs for three mAB treatments (bamlanivimab; bamlanivimab and etesevimab; and casirivimab and imdevimab), and at trial launch on March 10, 2021 we evaluated all three. Due to a sustained increase in SARS-CoV-2 variants in the United States resistant to bamlanivimab administered alone, on March 24, 2021 the U.S. Government halted distribution of bamlanivimab alone, and UPMC accordingly halted bamlanivimab monotherapy on March 31, 2021. On April 16, 2021, FDA revoked the EUA for bamlanivimab monotherapy. At the time of manuscript submission, we are therefore evaluating the two mAB treatments authorized by EUAs (bamlanivimab and etesevimab; and casirivimab and imdevimab). Main outcomes The primary outcome is total hospital free days (HFD) at 28 days after mAB administration, calculated as 28 minus the number of days during the index stay (if applicable – e.g., for patients admitted to hospital after mAB administration in the emergency department) minus the number of days readmitted during the 28 days after treatment. This composite endpoint captures the number of days from the day of mAB administration to the 28 days thereafter, during which the patient is alive and free of hospitalization. Death within 28 days is recorded as -1 HFD, as the worst outcome. Randomisation We will start with equal allocation. Due to uncertainty in sample size, we will use a Bayesian adaptive design and response adaptive randomization to ensure ability to provide statistical inference despite variable sample size. When mABs are ordered by UPMC physicians as a generic referral order, the order is filled by UPMC pharmacy via therapeutic interchange. OPTIMISE-C19 provides the therapeutic interchange via random allocation. Infusion center operations teams and pharmacists use a mAB assignment application embedded in the electronic medical record to determine the random allocation. Blinding (masking) This trial is open-label. However, outcome assessors conducting follow-up calls at day 28 are blinded to mAB assignment, and investigators are blinded to by-mAB aggregate outcome data until a statistical platform trial conclusion is reached. Numbers to be randomised (sample size) Sample size will be determined by case volume throughout the course of the pandemic, supply of FDA authorized mABs, and by that needed to reach a platform trial conclusion of inferiority, superiority, or futility of a given mAB. The trial will continue as long as more than one mAB type is available under EUA, and their comparative effectiveness is uncertain. Trial Status Protocol Version 1.0, February 24, 2021. Recruitment began March 10, 2021 and is ongoing at the time of manuscript submission. The estimated recruitment end date is February 22, 2022, though the final end date is dependent on how the pandemic evolves, mAB availability, and when final platform trial conclusions are reached. As noted above, due to U.S. Government decisions, UPMC Health System halted bamlanivimab monotherapy on March 31, 2021. Trial registration ClinicalTrials.gov Identifier: NCT04790786 . Registered March 10, 2021 Full protocol The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.
    Keywords COVID-19 ; pragmatic trial ; randomised controlled trial ; protocol ; monoclonal antibodies ; bamlanivimab ; Medicine (General) ; R5-920
    Subject code 630
    Language English
    Publishing date 2021-05-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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