Publications by authors named "Bates D"

Neovascular age-related macular degeneration and diabetic macular edema are leading causes of vision-loss evoked by retinal neovascularization and vascular leakage. The glycoprotein microfibrillar-associated protein 4 (MFAP4) is an integrin αβ ligand present in the extracellular matrix. Single-cell transcriptomics reveal MFAP4 expression in cell-types in close proximity to vascular endothelial cells including choroidal vascular mural cells and retinal astrocytes and Müller cells.

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Artificial intelligence (AI) is increasingly permeating the fabric of medicine, but getting full benefits will likely require fundamental changes in practice. Accepting this will be challenging for many clinicians. However, it may be necessary to ensure that AI’s ambitious promises translate into real-life improvement.

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Introduction: Limited research is available regarding recommendations about which drug allergy alerts (DAAs) in clinical decision support (CDS) systems should interrupt provider workflow. The objective was to evaluate the frequency of penicillin and cephalosporin DAA overrides at two institutions. A secondary objective was to redesign DAAs using a new tiered alerting system based on patient factors.

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Background: Interpreter service mode (in person, audio, or video) can impact patient experiences and engagement in the healthcare system, but clinics must balance quality with costs and volume to deliver services. Videoconferencing and telephone services provide lower cost options, effective where on site interpreters are scarce, or patients with limited English proficiency (LEP) and/or interpreters are unable to visit healthcare centers. The COVID 19 pandemic generated these conditions in Northwest Wisconsin (NWWI).

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Background: Patient safety culture is crucial for improving health care quality, however, there is no consensus on its definition.

Purpose: This study aimed to clarify and update the concept of patient safety culture.

Methods: We employed Norris' 6-step concept clarification method.

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Introduction And Objectives: High flow nasal cannula (HFNC) therapy is an increasingly popular mode of non-invasive respiratory support for the treatment of patients with acute hypoxemic respiratory failure (AHRF). Previous experimental studies in healthy subjects have established that HFNC generates flow-dependent positive airway pressures, but no data is available on the levels of mean airway pressure (mP) or positive end-expiratory pressure (PEEP) generated by HFNC therapy in AHRF patients. We aimed to estimate the airway pressures generated by HFNC at different flow rates in patients with AHRF, whose functional lung volume may be significantly reduced compared to healthy subjects due to alveolar consolidation and/or collapse.

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Bacteria can be engineered to manufacture chemicals, but it is unclear how to optimally engineer a single cell to maximise production performance from batch cultures. Moreover, the performance of engineered production pathways is affected by competition for the host's native resources. Here, using a 'host-aware' computational framework which captures competition for both metabolic and gene expression resources, we uncover design principles for engineering the expression of host and production enzymes at the cell level which maximise volumetric productivity and yield from batch cultures.

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Background: Adverse drug events (ADEs) are understudied in the ambulatory care setting. We aim to estimate the prevalence and characteristics of ADEs in outpatient care using electronic health records (EHRs).

Methods: This cross-sectional study included EHR data for patients who had an outpatient encounter at an academic medical center from 1 October 2018 through 31 December 2019.

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Article Synopsis
  • The systematic review investigates users' perceptions of AI-enabled decision aids that help facilitate shared decision-making between patients and clinicians with personalized recommendations.* -
  • The study analyzed 26 articles which found that patients generally found these decision aids easy to use and helpful, enhancing their commitment to treatment.* -
  • However, clinicians raised concerns regarding the accuracy and recency of the information provided, as well as the potential risks of over- or under-treatment, alongside recognizing challenges and biases that need to be managed.*
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Objectives: To estimate the frequency, severity, and preventability of adverse events associated with perioperative care, and to describe the setting and professions concerned.

Design: Multicenter retrospective cohort study.

Setting: 11 US hospitals.

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Background: Distinguishing between mild cognitive impairment (MCI) and early dementia requires both neuropsychological and functional assessment that often relies on caregivers' insights. Contacting a patient's caregiver can be time-consuming in a physician's already-filled workday.

Objective: To assess the utility of a brief, machine learning (ML)-enabled digital cognitive assessment, the Digital Clock and Recall (DCR), for detecting functional dependence.

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Objectives: The purpose of this study was to examine the impact of a contact-free continuous monitoring system on clinical outcomes including unplanned intensive care unit (ICU) transfer (primary), length of stay (LOS), code blue, and mortality. A secondary aim was to evaluate the return on investment associated with implementing the contact-free continuous monitoring program during the COVID public health emergency.

Methods: An interrupted time series evaluation was conducted to examine the association between the use of contact-free continuous monitoring and clinical outcomes.

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Although opioids continue to be used internationally for noncancer pain, evidence to date on the comparative safety of different opioids is sparse and conflicting. The aim of this study was to examine the comparative risk of all-cause mortality in patients newly initiated on opioids for noncancer pain, across 3 jurisdictions in the United Kingdom (UK), United States, and Canada. A multicentre retrospective, population-based cohort study was conducted.

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The tumour microenvironment (TME) significantly influences tumour formation and progression through dynamic interactions. Cholangiocarcinoma (CCA), a highly desmoplastic tumour, lacks early diagnostic biomarkers and has limited effective treatments owing to incomplete understanding of its molecular pathogenesis. Investigating the role of the TME in CCA progression could lead to better therapies.

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Carbamic acid (HNCOOH) is a small organic molecule that is terrestrially unstable in condensed phases under ambient conditions but could survive in the low densities and temperatures of the interstellar medium. In this work, the reaction of formamide (HNCOH) and electronically excited oxygen atoms in the D state, namely, O(D), has been investigated computationally to determine the feasibility of carbamic acid production. Geometries for carbamic acid and other potential reaction products have been calculated, as well as all pertinent transition states.

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Article Synopsis
  • The study investigates the effectiveness of large language models (LLMs) like GPT-4 and Llama 2 in identifying cognitive decline from real electronic health records (EHRs), comparing them with traditional models.
  • Conducted at Mass General Brigham, researchers analyzed clinical notes from patients diagnosed with mild cognitive impairment, using various approaches to optimize LLM performance and create an ensemble model that combined different methods.
  • The findings showed that while GPT-4 was more accurate than Llama 2, it still didn't surpass traditional models; however, an ensemble model significantly outperformed all others in key evaluation metrics.
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Article Synopsis
  • - Antibiotic-resistant infections are a major global health concern, causing over 700,000 deaths annually, leading to the development of ePAMS+, an ePrescribing tool aimed at improving antibiotic usage and combating resistance in healthcare settings.
  • - A non-randomised trial was conducted in two English hospitals during the pandemic to assess the feasibility and usability of ePAMS+, involving interviews and quantitative data collection to evaluate its implementation and effects on antibiotic prescribing practices.
  • - Results from 60 interviews and nearly 2,000 patient admissions indicated some aspects of ePAMS+ were well-received, though improvements are needed for certain features, highlighting both the potential and challenges of adopting this antimicrobial stewardship tool in clinical settings.
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Objectives:  This study aimed to evaluate implementation of a digital remote symptom monitoring intervention that delivered weekly symptom questionnaires and included the option to receive nurse callbacks via a mobile app for asthma patients in primary care.

Methods:  Research questions were structured by the NASSS (Nonadoption, Abandonment, Scale-up Spread, and Sustainability) framework. Quantitative and qualitative methods assessed scalability of the electronic health record (EHR)-integrated app intervention implemented in a 12-month randomized controlled trial.

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Background: Adverse event surveillance approaches underestimate the prevalence of harmful diagnostic errors (DEs) related to hospital care.

Methods: We conducted a single-centre, retrospective cohort study of a stratified sample of patients hospitalised on general medicine using four criteria: transfer to intensive care unit (ICU), death within 90 days, complex clinical events, and none of the aforementioned high-risk criteria. Cases in higher-risk subgroups were over-sampled in predefined percentages.

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Opioid prescription records in existing electronic health record (EHR) databases are a potentially useful, high-fidelity data source for opioid use-related risk phenotyping in genetic analyses. Prescriptions for codeine derived from EHR records were used as targeting traits by screening 16 million patient-level medication records. Genome-wide association analyses were then conducted to identify genomic loci and candidate genes associated with different count patterns of codeine prescriptions.

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This paper describes how a team of researchers, policy stakeholders and community members came together to co-create prevention-oriented and community-informed solutions to address loneliness in women-The Loneliness Project. Our aim is to encourage community partnerships and collective effort to address public health approaches to loneliness by developing a shared understanding of the issue from multiple perspectives and through the co-creation process, highlighting the key factors for co-creating a funding application for a community demonstration project.

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Background: Accurate identification of incident venous thromboembolism (VTE) for quality improvement and health services research is challenging. The purpose of this study was to evaluate the performance of a novel incident VTE phenotyping algorithm defined using standard terminologies, requiring three key indicators documented in the electronic health record (EHR): VTE diagnostic code, VTE-related imaging procedure code, and anticoagulant medication code.

Methods: Retrospective chart reviews were conducted to assess the performance of the algorithm using a random sample of phenotype(+) and phenotype(-) diagnostic encounters from primary care practices and acute care sites affiliated with five hospitals across a large integrated care delivery system in Massachusetts.

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Integrating modern machine learning and clinical decision-making has great promise for mitigating healthcare's increasing cost and complexity. We introduce the Enhanced Transformer for Health Outcome Simulation (ETHOS), a novel application of the transformer deep-learning architecture for analyzing high-dimensional, heterogeneous, and episodic health data. ETHOS is trained using Patient Health Timelines (PHTs)-detailed, tokenized records of health events-to predict future health trajectories, leveraging a zero-shot learning approach.

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Objectives:  This study aimed to pilot an application-based patient diagnostic questionnaire (PDQ) and assess the concordance of the admission diagnosis reported by the patient and entered by the clinician.

Methods:  Eligible patients completed the PDQ assessing patients' understanding of and confidence in the diagnosis 24 hours into hospitalization either independently or with assistance. Demographic data, the hospital principal problem upon admission, and International Classification of Diseases 10th Revision (ICD-10) codes were retrieved from the electronic health record (EHR).

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