First name
Svetlana
Last name
Ostapenko

Title

Sepsis in Complex Patients in the Emergency Department: Time to Recognition and Therapy in Pediatric Patients With High-Risk Conditions.

Year of Publication

2020

Number of Pages

Date Published

2020 Jan 09

ISSN Number

1535-1815

Abstract

<p><strong>OBJECTIVES: </strong>To compare timeliness of sepsis recognition and initial treatment in patients with and without high-risk comorbid conditions.</p>

<p><strong>METHODS: </strong>This was a retrospective cohort study of patients presenting to a pediatric emergency department (ED) who triggered a vital sign-based electronic sepsis alert resulting in bedside "huddle" assessment per institutional practice. A positive sepsis alert was defined as age-specific tachycardia or hypotension, concern for infection, and at least 1 of the following: abnormal capillary refill, abnormal mental status, or a high-risk condition. High-risk conditions were derived from the American Academy of Pediatrics sepsis alert tool. Patients with a positive alert underwent bedside huddle resulting in a decision regarding initiation of sepsis protocol. Placement on the protocol and time to initiation of protocol and individual therapies were compared for patients with and without high-risk conditions.</p>

<p><strong>RESULTS: </strong>During the 1-year study period, there were 1107 sepsis huddle alerts out of 96,427 ED visits. Of these, 713 (65%) had identified high-risk conditions, and 394 (35%) did not. Among patients with sepsis huddles, there was no difference in sepsis protocol initiation for patients with high-risk conditions compared with those without (24.8% vs 22.0%, P = 0.305). Between patients with high-risk conditions and those without, there were no differences in median time from triage to sepsis protocol activation, triage to initial intravenous antibiotic, triage to initial intravenous fluid therapy, or ED length of stay.</p>

<p><strong>CONCLUSIONS: </strong>Timeliness of care initiation was no different in high-risk patients with sepsis when using an electronic sepsis alert and protocolized sepsis care.</p>

DOI

10.1097/PEC.0000000000002038

Alternate Title

Pediatr Emerg Care

PMID

31929394
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Title

Neonatal sepsis registry: Time to antibiotic dataset.

Year of Publication

2019

Number of Pages

104788

Date Published

2019 Dec

ISSN Number

2352-3409

Abstract

<p>This article describes the process of extracting electronic health record (EHR) data into a format that supports analyses related to the timeliness of antibiotic administration. The de-identified data that accompanies this article were collected from a cohort of infants who were evaluated for possible sepsis in the Neonatal Intensive Care Unit (NICU) at the Children's Hospital of Philadelphia (CHOP). The interpretation of findings from these data are reported in a separate manuscript [1]. For purposes of illustration for interested readers, scripts written in the R programming language related to the creation and use of the dataset have also been provided. Interested researchers are encouraged to contact the research team to discuss opportunities for collaboration.</p>

DOI

10.1016/j.dib.2019.104788

Alternate Title

Data Brief

PMID

31799346
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Title

Surviving Sepsis in a Referral Neonatal Intensive Care Unit: Association between Time to Antibiotic Administration and In-Hospital Outcomes.

Year of Publication

2019

Number of Pages

Date Published

2019 Oct 08

ISSN Number

1097-6833

Abstract

<p><strong>OBJECTIVE: </strong>To determine if time to antibiotic administration is associated with mortality and in-hospital outcomes in a neonatal intensive care unit (NICU) population.</p>

<p><strong>STUDY DESIGN: </strong>We conducted a prospective evaluation of infants with suspected sepsis between September 2014 and February 2018; sepsis was defined as clinical concern prompting blood culture collection and antibiotic administration. Time to antibiotic administration was calculated from time of sepsis identification, defined as the order time of either blood culture or an antibiotic, to time of first antibiotic administration. We used linear models with generalized estimating equations to determine the association between time to antibiotic administration and mortality, ventilator-free and inotrope-free days, and NICU length of stay in patients with culture-proven sepsis.</p>

<p><strong>RESULTS: </strong>Among 1946 sepsis evaluations, we identified 128 episodes of culture-proven sepsis in 113 infants. Among them, prolonged time to antibiotic administration was associated with significantly increased risk of mortality at 14&nbsp;days (OR, 1.47; 95% CI, 1.15-1.87) and 30&nbsp;days (OR, 1.47; 95% CI, 1.11-1.94) as well as fewer inotrope-free days (incidence rate ratio, 0.91; 95% CI, 0.84-0.98). No significant associations with ventilator-free days or NICU length of stay were demonstrated.</p>

<p><strong>CONCLUSIONS: </strong>Among infants with sepsis, delayed time to antibiotic administration was an independent risk factor for death and prolonged cardiovascular dysfunction. Further study is needed to define optimal timing of antimicrobial administration in high-risk NICU populations.</p>

DOI

10.1016/j.jpeds.2019.08.023

Alternate Title

J. Pediatr.

PMID

31604632
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Title

Machine learning models for early sepsis recognition in the neonatal intensive care unit using readily available electronic health record data.

Year of Publication

2019

Number of Pages

e0212665

Date Published

2019

ISSN Number

1932-6203

Abstract

<p><strong>BACKGROUND: </strong>Rapid antibiotic administration is known to improve sepsis outcomes, however early diagnosis remains challenging due to complex presentation. Our objective was to develop a model using readily available electronic health record (EHR) data capable of recognizing infant sepsis at least 4 hours prior to clinical recognition.</p>

<p><strong>METHODS AND FINDINGS: </strong>We performed a retrospective case control study of infants hospitalized ≥48 hours in the Neonatal Intensive Care Unit (NICU) at the Children's Hospital of Philadelphia between September 2014 and November 2017 who received at least one sepsis evaluation before 12 months of age. We considered two evaluation outcomes as cases: culture positive-positive blood culture for a known pathogen (110 evaluations); and clinically positive-negative cultures but antibiotics administered for ≥120 hours (265 evaluations). Case data was taken from the 44-hour window ending 4 hours prior to evaluation. We randomly sampled 1,100 44-hour windows of control data from all times ≥10 days removed from any evaluation. Model inputs consisted of up to 36 features derived from routine EHR data. Using 10-fold nested cross-validation, 8 machine learning models were trained to classify inputs as sepsis positive or negative. When tasked with discriminating culture positive cases from controls, 6 models achieved a mean area under the receiver operating characteristic (AUC) between 0.80-0.82 with no significant differences between them. Including both culture and clinically positive cases, the same 6 models achieved an AUC between 0.85-0.87, again with no significant differences.</p>

<p><strong>CONCLUSIONS: </strong>Machine learning models can identify infants with sepsis in the NICU hours prior to clinical recognition. Learning curves indicate model improvement may be achieved with additional training examples. Additional input features may also improve performance. Further research is warranted to assess potential performance improvements and clinical efficacy in a prospective trial.</p>

DOI

10.1371/journal.pone.0212665

Alternate Title

PLoS ONE

PMID

30794638
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Title

Utilization of Antipyretics for Nonurgent Fever in a Pediatric Emergency Department.

Year of Publication

2017

Number of Pages

722-6

Date Published

2018 Jun

ISSN Number

1938-2707

Abstract

<p>This retrospective cohort study aimed to describe antipyretic use among healthy patients in a pediatric emergency department (ED) with nonurgent fever defined as: triage level 4 or 5, chief complaint fever or temperature 38°C to 39°C, and otherwise normal vital signs, and determine if antipyretic administration is associated with increased ED length of stay (LOS). We compared continuous variables using Kruskal-Wallis and Wilcoxon rank sum testing. We adjusted confounding variables using logistic regression modeling. A total of 22 169 patients were included. Of these, 52% received antipyretic: acetaminophen (38%), ibuprofen (19%), or both antipyretics (5%). ED LOS (median hours) varied by number of antipyretic types given (none, 2.2; ibuprofen, 2.7; acetaminophen, 2.7; and both 3.4, P &lt; .001) and number of doses (0 doses, 2.2, 1 dose, 2.7; 2 doses, 3.4, P &lt; .001). Patients who received antipyretic were more likely to have ED LOS greater than 2 hours (adjusted odds ratio 1.99, 95% CI 1.88-2.11) compared with those with no antipyretic, controlling for age, imaging studies, laboratory studies, antibiotic administration, and disposition.</p>

DOI

10.1177/0009922817734356

Alternate Title

Clin Pediatr (Phila)

PMID

28990430
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Title

Do changes in socio-demographic characteristics impact up-to-date immunization status between 3 and 24 months of age? A prospective study among an inner-city birth cohort in the United States.

Year of Publication

2017

Number of Pages

1-8

Date Published

2017 Feb 27

ISSN Number

2164-554X

Abstract

<p><strong>INTRODUCTION: </strong>Low-income child populations remain under-vaccinated. Our objective was to determine differences in the relative importance of maternal health literacy and socio-demographic characteristics that often change during early childhood on up-to-date (UTD) immunization status among a low-income population.</p>

<p><strong>METHODS: </strong>We performed secondary data analysis of a longitudinal prospective cohort study of 744 Medicaid-eligible mother-infant dyads recruited at the time of the infant's birth from an inner-city hospital in the United States and surveyed every 6 months for 24 months. Our primary outcome was infant UTD status at 24 months abstracted from a citywide registry. We assessed maternal health literacy with the Test of Functional Health Literacy in Adults (short version). We collected socio-demographic information via surveys at birth and every 6 months. We compared predictors of UTD status at 3, 7, and 24 months.</p>

<p><strong>RESULTS: </strong>The cohort consisted of primarily African-American (81.5%) mothers with adequate health literacy (73.9%). Immunizations were UTD among 56.7% of infants at 24 months of age. Maternal health literacy was not a significant predictor of UTD immunization status. Instead, adjusted results showed that significant predictors of not-UTD status at 24 months were lack of a consistent health care location or "medical home" (OR 0.17, 95%CI 0.18-0.37), inadequate prenatal care (OR 0.48, 95%CI 0.25-0.95), and prior not-UTD status (OR 0.31, 95%CI 0.20-0.47). Notably, all upper confidence limits are less than 1.0 for these variables. Health care location type (e.g., hospital-affiliate, community-based, none) was a significant predictor of vaccine status at age 3 months, 7 months, and 24 months.</p>

<p><strong>CONCLUSIONS: </strong>Investing in efforts to support early establishment of a medical home to obtain comprehensive coordinated preventive care, including providing recommended vaccines on schedule, is a prudent strategy to improve vaccination status at the population level.</p>

DOI

10.1080/21645515.2016.1261771

Alternate Title

Hum Vaccin Immunother

PMID

28277088
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