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Implementation of a Pragmatic Biomarker-Driven Algorithm to Guide Antibiotic Use in the Pediatric Intensive Care Unit: the Optimizing Antibiotic Strategies in Sepsis (OASIS) II Study.

ABSTRACT: BACKGROUND:Biomarkers can facilitate safe antibiotic discontinuation in critically ill patients without bacterial infection. METHODS:We tested the ability of a biomarker-based algorithm to reduce excess antibiotic administration in patients with systemic inflammatory response syndrome (SIRS) without bacterial infections (uninfected) in our pediatric intensive care unit (PICU). The algorithm suggested that PICU clinicians stop antibiotics if (1) C-reactive protein <4 mg/dL and procalcitonin <1 ng/mL at SIRS onset and (2) no evidence of bacterial infection by exam/testing by 48 hours. We evaluated excess broad-spectrum antibiotic use, defined as administration on days 3-9 after SIRS onset in uninfected children. Incidence rate ratios (IRRs) compared unadjusted excess length of therapy (LOT) in the 34 months before (Period 1) and 12 months after (Period 2) implementation of this algorithm, stratified by biomarker values. Segmented linear regression evaluated excess LOT among all uninfected episodes over time and between the periods. RESULTS:We identified 457 eligible SIRS episodes without bacterial infection, 333 in Period 1 and 124 in Period 2. When both biomarkers were below the algorithm's cut-points (n = 48 Period 1, n = 31 Period 2), unadjusted excess LOT was lower in Period 2 (IRR, 0.53; 95% confidence interval, 0.30-0.93). Among all 457 uninfected episodes, there were no significant differences in LOT (coefficient 0.9, P = .99) between the periods on segmented regression. CONCLUSIONS:Implementation of a biomarker-based algorithm did not decrease overall antibiotic exposure among all uninfected patients in our PICU, although exposures were reduced in the subset of SIRS episodes where biomarkers were low.

SUBMITTER: Downes KJ

PROVIDER: S-EPMC7317158 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Implementation of a Pragmatic Biomarker-Driven Algorithm to Guide Antibiotic Use in the Pediatric Intensive Care Unit: the Optimizing Antibiotic Strategies in Sepsis (OASIS) II Study.

Downes Kevin J KJ Fitzgerald Julie C JC Schriver Emily E Boge Craig L K CLK Russo Michael E ME Weiss Scott L SL Balamuth Fran F Kubis Sherri E SE Tolomeo Pam P Bilker Warren B WB Han Jennifer H JH Lautenbach Ebbing E Coffin Susan E SE Gerber Jeffrey S JS

Journal of the Pediatric Infectious Diseases Society 20200201 1

<h4>Background</h4>Biomarkers can facilitate safe antibiotic discontinuation in critically ill patients without bacterial infection.<h4>Methods</h4>We tested the ability of a biomarker-based algorithm to reduce excess antibiotic administration in patients with systemic inflammatory response syndrome (SIRS) without bacterial infections (uninfected) in our pediatric intensive care unit (PICU). The algorithm suggested that PICU clinicians stop antibiotics if (1) C-reactive protein <4 mg/dL and proc ...[more]

PMID: 30476186

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Project description:Background: Survivors of pediatric sepsis often develop new morbidities and deterioration in quality of life after sepsis, leading to a need for improved follow-up for children who survive sepsis. Objective: To implement a follow-up system for pediatric sepsis survivors in a pediatric health system. Methods: We performed a retrospective case series of patients treated for sepsis from October 2018 through October 2019 in a pediatric intensive care unit in a quaternary children's hospital, and describe implementation of a follow-up system for sepsis survivors. Program planning started in 2017 with multidisciplinary meetings including physical, occupational, and speech therapists, teachers, neuropsychologists, and coordinators from other survivorship programs (neonatology, stroke, and oncology). In 2018, a workshop was held to consult with local and national experts. The Pediatric Sepsis Survivorship Program launched in October 2018 led by a nurse coordinator who met with families to educate about sepsis and offer post-discharge follow-up. Patients with high pre-existing medical complexity or established subspecialty care were referred for follow-up through existing care coordination or subspecialty services plus guidance to monitor for post-sepsis morbidity. For patients with low-moderate medical complexity, the nurse coordinator administered a telephone-based health-assessment 2-3 months after discharge to screen for new physical or psychosocial morbidity. Patients flagged with concerns were referred to their primary physician and/or to expedited neuropsychological evaluation to utilize existing medical services. Results: Of 80 sepsis patients, 10 died, 20 were referred to care coordination by the program, and 13 had subspecialty follow-up. Five patients were followed in different health systems, four were adults not appropriate for existing follow-up programs, four remained hospitalized, and four were missed due to short stay or unavailable caregivers. The remaining 20 patients were scheduled for follow-up with the Pediatric Sepsis Program. Nine patients completed the telephone assessment. Four patients were receiving new physical or occupational therapy, and one patient was referred for neuropsychology evaluation due to new difficulties with attention, behavior, and completion of school tasks. Conclusions: Implementation of an efficient, low-cost pediatric sepsis survivorship program was successful by utilizing existing systems of care, when available, and filling a follow-up gap in screening for select patients.

Dataset Information

Implementation of a Pragmatic Biomarker-Driven Algorithm to Guide Antibiotic Use in the Pediatric Intensive Care Unit: the Optimizing Antibiotic Strategies in Sepsis (OASIS) II Study.

Publications

Implementation of a Pragmatic Biomarker-Driven Algorithm to Guide Antibiotic Use in the Pediatric Intensive Care Unit: the Optimizing Antibiotic Strategies in Sepsis (OASIS) II Study.

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