Study of Delayed Antibiotic in Pediatric Febrile Immunocompromised Patients and Adverse Events.

OBJECTIVES: Bone marrow transplant (BMT) patients or patients receiving chemotherapy for oncologic diagnoses are at risk for sepsis. The association of time to antibiotics (TTA) with outcomes when adjusting for severity of illness has not been evaluated in the pediatric febrile immunocompromised (FI) population. We evaluated the association of TTA with adverse events in a cohort of FI patients presenting to our pediatric emergency department. METHODS: We performed a retrospective review of consecutive FI patients presenting over a 6.5-year period. Adverse events were defined as intensive care admission within 72 hours of emergency department arrival, laboratory signs of acute kidney injury, inotropic support subsequent to antibiotics, and all-cause mortality within 30 days. Vital signs and interventions were used to define severity of illness. Adjusting for severity of illness at presentation, age, and timing of an institutional intervention designed to reduce TTA in FI patients, we analyzed the association of TTA with individual adverse events as well as with adverse events in aggregate. RESULTS: We analyzed 1489 patient encounters. In oncology patients, TTA was not associated with the aggregate measure of whether any adverse event subsequently occurred nor with other individual adverse events. For the BMT subpopulation, TTA >60 minutes did show increased odds of intensive care admission within 72 hours as well as for aggregate adverse events. CONCLUSIONS: Although TTA >60 minutes did show increased odds of aggregate adverse events in the small subgroup of BMT patients, overall TTA was not associated with adverse events in oncology patients as a whole.

Improving Emergency Department Care for Pediatric Victims of Sexual Abuse.

BACKGROUND AND OBJECTIVE: Evidence-based medical care of sexual abuse victims who present to the pediatric emergency department (PED) is necessary to facilitate forensic evidence collection and prevent pregnancy and sexually transmitted infections. Adherence to testing and treatment guidelines remains low in PEDs, despite recommendations from the American Academy of Pediatrics and Centers for Disease Control and Prevention. We aimed to increase the proportion of patient encounters at a PED for reported sexual abuse that receive algorithm-adherent care from 57% to 90% within 12 months. METHODS: Our team of PED and child abuse pediatricians outlined our theory for improvement, and multiple plan-do-study-act cycles were conducted to test interventions that were aimed at key drivers. Interventions included the construction of a best practice algorithm derived from published guidelines, targeted clinician education, and integration of an electronic order set. Our primary outcome was the proportion of patient encounters in which care adhered to algorithm recommendations. Data were abstracted from the records of all patient encounters evaluated in the PED for reported sexual abuse. RESULTS: We analyzed 657 visits between July 2015 and January 2018. The proportion of patient encounters with algorithm-adherent care improved from 57% to 87% during the study period. This improvement has been sustained for 13 months. Failure to test for hepatitis and syphilis constituted the majority of nonadherent care. CONCLUSIONS: Using improvement methodology, we successfully increased algorithm-adherent evaluation and management of patients presenting for sexual abuse. Targeted education and an electronic order set were associated with improved adherence to a novel care algorithm.

The FAST-AIMS Clinical Mass Spectrometry Analysis System.

Within clinical proteomics, mass spectrometry analysis of biological samples is emerging as an important high-throughput technology, capable of producing powerful diagnostic and prognostic models and identifying important disease biomarkers. As interest in this area grows, and the number of such proteomics datasets continues to increase, the need has developed for efficient, comprehensive, reproducible methods of mass spectrometry data analysis by both experts and nonexperts. We have designed and implemented a stand-alone software system, FAST-AIMS, which seeks to meet this need through automation of data preprocessing, feature selection, classification model generation, and performance estimation. FAST-AIMS is an efficient and user-friendly stand-alone software for predictive analysis of mass spectrometry data. The present resource review paper will describe the features and use of the FAST-AIMS system. The system is freely available for download for noncommercial use.