First name
Frances
Last name
Balamuth

Title

Two-Tier Lyme Disease Serology in Children with Previous Lyme Disease.

Year of Publication

2021

Date Published

2021 Oct 04

ISSN Number

1557-7759

Abstract

<p>A history of Lyme disease can complicate the interpretation of Lyme disease serology in acutely symptomatic patients. We prospectively enrolled children undergoing evaluation for Lyme disease in the emergency department of one of eight participating Pedi Lyme Net centers. We selected symptomatic children with a Lyme disease history (definite, probable, or none) as well as an available research biosample. We defined a Lyme disease case with either an erythema migrans (EM) lesion or positive two-tier serology with compatible symptoms. Using a generalized estimating equation, we examined the relationship between time from previous Lyme disease diagnosis and current Lyme disease after adjustment for patient demographics and symptoms as well as clustering by center. Of 2501 prospectively enrolled study patients, 126 (5.0%) reported a history of definite or probable Lyme disease. Of these children with previous Lyme disease, 47 met diagnostic criteria for Lyme disease at the time of enrollment (37.3%; 95% confidence interval [CI] 29.1-45.7%); 2 had an EM lesion, and 45 had positive two-tier Lyme disease serology. Over time from the previous Lyme disease diagnosis, the less likely the patient met diagnostic criteria for Lyme disease (adjusted odds ratio 0.62 per time period; 95% CI 0.46-0.84). For children with a history of Lyme disease before enrollment, one-third met the diagnostic criteria for acute Lyme disease with a declining rate over time from previous Lyme disease diagnosis. Novel Lyme disease diagnostics are needed to help distinguish acute from previous Lyme disease.</p>

DOI

10.1089/vbz.2021.0030

Alternate Title

Vector Borne Zoonotic Dis

PMID

34610255

Title

Metric Development for the Multicenter Improving Pediatric Sepsis Outcomes (IPSO) Collaborative.

Year of Publication

2021

Date Published

2021 04 01

ISSN Number

1098-4275

Abstract

<p><strong>BACKGROUND: </strong>A 56 US hospital collaborative, Improving Pediatric Sepsis Outcomes, has developed variables, metrics and a data analysis plan to track quality improvement (QI)-based patient outcomes over time. Improving Pediatric Sepsis Outcomes expands on previous pediatric sepsis QI efforts by improving electronic data capture and uniformity across sites.</p>

<p><strong>METHODS: </strong>An expert panel developed metrics and corresponding variables to assess improvements across the care delivery spectrum, including the emergency department, acute care units, hematology and oncology, and the ICU. Outcome, process, and balancing measures were represented. Variables and statistical process control charts were mapped to each metric, elucidating progress over time and informing plan-do-study-act cycles. Electronic health record (EHR) abstraction feasibility was prioritized. Time 0 was defined as time of earliest sepsis recognition (determined electronically), or as a clinically derived time 0 (manually abstracted), identifying earliest physiologic onset of sepsis.</p>

<p><strong>RESULTS: </strong>Twenty-four evidence-based metrics reflected timely and appropriate interventions for a uniformly defined sepsis cohort. Metrics mapped to statistical process control charts with 44 final variables; 40 could be abstracted automatically from multiple EHRs. Variables, including high-risk conditions and bedside huddle time, were challenging to abstract (reported in &lt;80% of encounters). Size or type of hospital, method of data abstraction, and previous QI collaboration participation did not influence hospitals' abilities to contribute data. To date, 90% of data have been submitted, representing 200 007 sepsis episodes.</p>

<p><strong>CONCLUSIONS: </strong>A comprehensive data dictionary was developed for the largest pediatric sepsis QI collaborative, optimizing automation and ensuring sustainable reporting. These approaches can be used in other large-scale sepsis QI projects in which researchers seek to leverage EHR data abstraction.</p>

DOI

10.1542/peds.2020-017889

Alternate Title

Pediatrics

PMID

33795482

Title

Proteomic Profiling of MIS-C Patients Reveals Heterogeneity Relating to Interferon Gamma Dysregulation and Vascular Endothelial Dysfunction.

Year of Publication

2021

Date Published

2021 Apr 20

Abstract

<p>Multi-system Inflammatory Syndrome in Children (MIS-C) is a major complication of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic in pediatric patients. Weeks after an often mild or asymptomatic initial infection with SARS-CoV-2 children may present with a severe shock-like picture and marked inflammation. Children with MIS-C present with varying degrees of cardiovascular and hyperinflammatory symptoms. We performed a comprehensive analysis of the plasma proteome of more than 1400 proteins in children with SARS-CoV-2. We hypothesized that the proteome would reflect heterogeneity in hyperinflammation and vascular injury, and further identify pathogenic mediators of disease. Protein signatures demonstrated overlap between MIS-C, and the inflammatory syndromes macrophage activation syndrome (MAS) and thrombotic microangiopathy (TMA). We demonstrate that PLA2G2A is a key marker of MIS-C that associates with TMA. We found that IFNγ responses are dysregulated in MIS-C patients, and that IFNγ levels delineate clinical heterogeneity.</p>

DOI

10.1101/2021.04.13.21255439

Alternate Title

medRxiv

PMID

33907759

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