Apparent Life-Threatening Event: Multicenter Prospective Cohort Study to Develop a Clinical Decision Rule for Admission to the Hospital - 21/03/13

Doi : 10.1016/j.annemergmed.2012.08.035

Amy H. Kaji, MD, PhD ^a,^b,^c,^⁎ , Ilene Claudius, MD ^d,^e, Genevieve Santillanes, MD ^d, Manoj K. Mittal, MD ^f,^g, Katie Hayes, BS ^f, Jumie Lee, CPNP, MSN ^a,^b,^c, Marianne Gausche-Hill, MD ^a,^b,^c
^a Department of Emergency Medicine, Harbor-UCLA Medical Center, Torrance, CA
^b Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA
^c Los Angeles Biomedical Research Institute at Harbor-UCLA, Torrance, CA
^d Department of Emergency Medicine, Keck School of Medicine, Los Angeles County and University of Southern California, Los Angeles, CA
^e Department of Emergency Medicine, Keck School of Medicine, Children's Hospital Los Angeles, Los Angeles, CA
^f Division of Emergency Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA
^g Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA

Address for correspondence: Amy H. Kaji, MD, PhD

Résumé

Study objective

We identify factors in emergency department (ED) patients presenting with apparent life-threatening events that distinguish those safe for discharge from those warranting hospitalization.

Methods

Data were prospectively collected on all subjects presenting to 4 EDs with apparent life-threatening events. Patients were observed for subsequent events or interventions, defined a priori, which would have mandated hospital admission (eg, hypoxia, apnea, bradycardia that is not self-resolving, or serious bacterial infection). For patients discharged from the ED, telephone follow-up was arranged. Classification and regression tree analysis was performed to delineate admission predictors.

Results

A total of 832 subjects were enrolled. The overall median age was 31.5 days (interquartile range 10 to 90 days); 427 (51.3%) were male patients, and 513 (61.7%) arrived by emergency medical services. One hundred ninety-one (23.0%) infants had a significant intervention warranting hospitalization. One hundred thirty-seven patients (16.5%) met predetermined criteria that would obviously mandate hospital admission (eg, persistent hypoxia requiring oxygen) by the end of their ED stay. In addition to these patients for whom it was obvious that admission would be necessary in the ED, classification and regression tree analysis (receiver operating curve=0.90) yielded 2 factors predictive of hospitalization: having a significant medical history and having greater than 1 apparent life-threatening event in 24 hours. The sensitivity was 89.0% (95% confidence interval 83.5% to 92.9%); specificity was 61.9% (95% confidence interval 58.0% to 65.7%).

Conclusion

We found 3 variables (obvious need for admission, significant medical history, >1 apparent life-threatening event in 24 hours) that identified most but not all infants with apparent life-threatening events necessitating admission. These variables require external validation and reliability assessment before clinical implementation.

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Plan

Introduction

Background

Importance

Goals of This Investigation

Materials and Methods

Study Design and Selection of Participants

Setting

Data Collection and Processing

Primary Data Analyses

	Please see page 380 for the Editor's Capsule Summary of this article.
	Funding and support: By Annals policy, all authors are required to disclose any and all commercial, financial, and other relationships in any way related to the subject of this article as per ICMJE conflict of interest guidelines (see www.icmje.org). The authors have stated that no such relationships exist.
	Supervising editor: Steven M. Green, MD
	Author contributions: AHK and MG-H conceived the study. AHK, IC, GS, MKM, and MG-H supervised the conduct of the trial and data collection. AHK, IC, GS, KH, and JL undertook recruitment of participating centers and patients and managed the data, including quality control. AHK provided statistical advice on study design, analyzed the data, and chaired the data oversight committee. AHK drafted the article, and all authors contributed substantially to its revision. AHK takes responsibility for the paper as a whole.
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	Publication date: Available online September 29, 2012.