Publications by authors named "Mark Segal"

Background: Previous observational studies showed left atrial appendage occlusions with the WATCHMAN device reduced 1-year mortality, which conflicted with evidence generated from randomized controlled trials. We proposed to use the high-dimensional propensity score (hdPS) to assist in nonactive comparator selection (prevalent user of medication) and compared 1-year mortality between patients with atrial fibrillation who received the WATCHMAN device (percutaneous left atrial appendage occlusion device [pLAAO]) and direct oral anticoagulants in 2 matched cohorts based on (1) traditional propensity score (PS) and (2) integrating traditional PS with information learned from hdPS.

Methods: Patients entered the cohort once diagnosed with atrial fibrillation in the 15% of Medicare fee-for-service claims database from 2011 to 2018.

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Abnormal autophagy regulation is implicated in lupus and other autoimmune diseases. We investigated autophagy in the murine pristane-induced lupus model. Pristane causes monocyte/macrophage-mediated endoplasmic reticulum (ER) stress in lung endothelial cells and diffuse alveolar hemorrhage (DAH) indistinguishable from DAH in lupus patients.

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Failure to rapidly diagnose tuberculosis disease (TB) and initiate treatment is a driving factor of TB as a leading cause of death in children. Current TB diagnostic assays have poor performance in children, and identifying novel non-sputum-based TB biomarkers to improve pediatric TB diagnosis is a global priority. We sought to develop a plasma biosignature for TB by probing the plasma proteome of 511 children stratified by TB diagnostic classification and HIV status from sites in four low- and middle-income countries, using high-throughput data-independent acquisition mass-spectrometry (DIA-PASEF-MS).

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Objective: To understand mortality and secondary outcomes in patients with both end-stage kidney disease (ESKD) and chronic limb-threatening ischemia (CLTI) after no procedural treatment, primary amputation, endovascular treatment, and open surgery.

Summary Background Data: ESKD and CLTI commonly cooccur and limited prior work has demonstrated poor outcomes including one-year survival despite treatment.

Methods: We conducted a retrospective national cohort study of United States Renal Data System data from January 1, 2016 to December 31, 2019 to determine mortality, major postoperative complications, and other outcomes.

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Key Points: Machine learning and large-scale proteomics led to a 16-protein secondary cardiovascular risk model in patients with CKD. Hepatic fibrosis and liver X receptor activation represented biologic pathways that link kidney disease and risk of secondary cardiovascular events. An understanding of the circulating proteins associated with secondary cardiovascular events may help to identify novel therapeutic targets.

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Importance: There is no consensus regarding the best method for prediction of hypertensive disorders of pregnancy (HDP), including gestational hypertension and preeclampsia.

Objective: To determine predictive ability in early pregnancy of large-scale proteomics for prediction of HDP.

Design, Setting, And Participants: This was a nested case-control study, conducted in 2022 to 2023, using clinical data and plasma samples collected between 2010 and 2013 during the first trimester, with follow-up until pregnancy outcome.

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Background: Single-lead, smartphone-based mobile electrocardiograms (ECGs) have the potential to provide a noninvasive, rapid, and cost-effective means of screening for atrial fibrillation (AFib) in outpatient settings. AFib has been associated with various comorbid diseases that prompt further investigation and screening methodologies for at-risk populations. A simple 30-second sinus rhythm strip from the KardiaMobile ECG (AliveCor) can provide an effective screen for cardiac rhythm abnormalities.

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Background And Aims: Incident heart failure (HF) among individuals with chronic kidney disease (CKD) incurs hospitalizations that burden patients and health care systems. There are few preventative therapies, and the Pooled Cohort equations to Prevent Heart Failure (PCP-HF) perform poorly in the setting of CKD. New drug targets and better risk stratification are urgently needed.

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Standard race adjustments for estimating glomerular filtration rate (GFR) and reference creatinine can yield a lower acute kidney injury (AKI) and chronic kidney disease (CKD) prevalence among African American patients than non-race adjusted estimates. We developed two race-agnostic computable phenotypes that assess kidney health among 139,152 subjects admitted to the University of Florida Health between 1/2012-8/2019 by removing the race modifier from the estimated GFR and estimated creatinine formula used by the race-adjusted algorithm (race-agnostic algorithm 1) and by utilizing 2021 CKD-EPI refit without race formula (race-agnostic algorithm 2) for calculations of the estimated GFR and estimated creatinine. We compared results using these algorithms to the race-adjusted algorithm in African American patients.

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Background: Patients with kidney failure suffer high mortality, and we currently lack markers for risk stratification for these patients. We carried out a quality control study of a modified aptamer assay (SomaScan v.4.

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Article Synopsis
  • This study investigates the link between 4638 plasma proteins and the risk of kidney failure in 3235 participants over a 10-year period, using data from the Chronic Renal Insufficiency Cohort Study.
  • Researchers identify 100 proteins significantly associated with a 50% decline in kidney function, with a focus on pathways related to bone morphogenetic proteins and ephrin signaling.
  • A developed risk model based on 65 proteins shows strong predictive ability for kidney failure, suggesting that modifiable protein markers could assist in creating treatments to slow chronic kidney disease progression.
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Background: Fiber is a potential therapeutic to suppress microbiota-generated uremic molecules. This study aimed to determine if fiber supplementation decreased serum levels of uremic molecules through the modulation of gut microbiota in adults undergoing hemodialysis.

Methods: A randomized, double-blinded, controlled crossover study was conducted.

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Aims: Chronic kidney disease (CKD) is widely prevalent and independently increases cardiovascular risk. Cardiovascular risk prediction tools derived in the general population perform poorly in CKD. Through large-scale proteomics discovery, this study aimed to create more accurate cardiovascular risk models.

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Background: Methods for inferring the three-dimensional (3D) configuration of chromatin from conformation capture assays that provide strictly pairwise interactions, notably Hi-C, utilize the attendant contact matrix as input. More recent assays, in particular split-pool recognition of interactions by tag extension (SPRITE), capture multi-way interactions instead of solely pairwise contacts. These assays yield contacts that straddle appreciably greater genomic distances than Hi-C, in addition to instances of exceptionally high-order chromatin interaction.

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Background: We carried out a study of the aptamer proteomic assay, SomaScan V4, to evaluate the analytical and biological variability of the assay in plasma samples of patients with moderate to severe chronic kidney disease (CKD).

Methods: Plasma samples were selected from 2 sources: (a) 24 participants from the Chronic Renal Insufficiency Cohort (CRIC) and (b) 49 patients from the Brigham and Women's Hospital-Kidney/Renal Clinic. We calculated intra-assay variability from both sources and examined short-term biological variability in samples from the Brigham clinic.

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Ferroptosis is a druggable, iron-dependent form of cell death that is characterized by lipid peroxidation but has received little attention in lupus nephritis. Kidneys of lupus nephritis patients and mice showed increased lipid peroxidation mainly in the tubular segments and an increase in Acyl-CoA synthetase long-chain family member 4, a pro-ferroptosis enzyme. Nephritic mice had an attenuated expression of SLC7A11, a cystine importer, an impaired glutathione synthesis pathway, and low expression of glutathione peroxidase 4, a ferroptosis inhibitor.

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Article Synopsis
  • Chronic limb-threatening ischemia (CLTI) paired with end-stage kidney disease (ESKD) leads to worse health outcomes and higher hospital costs compared to CLTI alone.
  • A study analyzing hospital data from 2015-2018 revealed that patients with CLTI + ESKD are typically younger and from lower-income backgrounds and are less likely to receive certain surgical treatments.
  • Those with CLTI + ESKD faced significantly higher odds of in-hospital death and complications, resulting in longer hospital stays and increased likelihood of rehabilitation after discharge.
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Objective: The aim of this study was to characterize early urinary gene expression differences between patients with sepsis and patients with sterile inflammation and summarize in terms of a reproducible sepsis probability score. Design: This was a prospective observational cohort study. Setting: The study was conducted in a quaternary care academic hospital.

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The three-dimensional (3D) configuration of chromatin impacts numerous cellular processes. However, directly observing chromatin architecture at high resolution is challenging. Accordingly, 3D structure utilizing chromatin conformation capture assays, notably Hi-C, has received considerable attention, with a multitude of algorithms advanced.

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Article Synopsis
  • This study investigates sepsis in surgical patients using machine learning to analyze blood and urine biomarker profiles, aiming to identify distinct patient subgroups based on their physiological responses and outcomes.* -
  • A total of 243 patients were studied, revealing two main clusters: one with early organ dysfunction linked to higher mortality and chronic illness, and another showing recovery; key differences were noted in clinical scores and disease history.* -
  • The machine learning model achieved a 95% accuracy in predicting patient clusters, highlighting the importance of early identification of severe sepsis phenotypes for better management and outcomes.*
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