Direct concurrent comparison of multiple pediatric acute asthma scoring instruments.
OBJECTIVE
Appropriate delivery of Emergency Department (ED) treatment to children with acute asthma requires clinician assessment of acute asthma severity. Various clinical scoring instruments exist to standardize assessment of acute asthma severity in the ED, but their selection remains arbitrary due to few published direct comparisons of their properties. Our objective was to test the feasibility of directly comparing properties of multiple scoring instruments in a pediatric ED.


METHODS
Using a novel approach supported by a composite data collection form, clinicians categorized elements of five scoring instruments before and after initial treatment for 48 patients 2-18 years of age with acute asthma seen at the ED of a tertiary care pediatric hospital ED from August to December 2014. Scoring instruments were compared for inter-rater reliability between clinician types and their ability to predict hospitalization.


RESULTS
Inter-rater reliability between clinician types was not different between instruments at any point and was lower (weighted kappa range 0.21-0.55) than values reported elsewhere. Predictive ability of most instruments for hospitalization was higher after treatment than before treatment (p < 0.05) and may vary between instruments after treatment (p = 0.054).


CONCLUSIONS
We demonstrate the feasibility of comparing multiple clinical scoring instruments simultaneously in ED clinical practice. Scoring instruments had higher predictive ability for hospitalization after treatment than before treatment and may differ in their predictive ability after initial treatment. Definitive conclusions about the best instrument or meaningful comparison between instruments will require a study with a larger sample size.
a Department of Pediatrics , University of Utah School of Medicine , Salt Lake City , UT , USA.
Michael D
MD
Johnson
a Department of Pediatrics , University of Utah School of Medicine , Salt Lake City , UT , USA.|b Department of Biomedical Informatics , University of Utah School of Medicine , Salt Lake City , UT , USA.
Flory L
FL
Nkoy
a Department of Pediatrics , University of Utah School of Medicine , Salt Lake City , UT , USA.
Xiaoming
X
Sheng
c Department of Population Health Sciences , University of Utah School of Medicine , Salt Lake City , UT , USA.
Tom
T
Greene
a Department of Pediatrics , University of Utah School of Medicine , Salt Lake City , UT , USA.
Bryan L
BL
Stone
b Department of Biomedical Informatics , University of Utah School of Medicine , Salt Lake City , UT , USA.
Jennifer
J
Garvin
D000208:Acute Disease; D000293:Adolescent; D001249:Asthma / Q000175:diagnosis* / Q000503:physiopathology*; D015415:Biomarkers; D002648:Child; D002675:Child, Preschool; D004636:Emergency Service, Hospital / Q000592:standards*; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D015588:Observer Variation; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D012720:Severity of Illness Index; D062606:Tertiary Care Centers / Q000592:standards
D015415:Biomarkers
Asthma; child; decision making; emergency service (hospital); hospitalization; validation studies