ArticleThe American journal of emergency medicine2010
Risk stratification for hospitalization in acute asthma: the CHOP classification tree.
Article in The American journal of emergency medicine, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 22 citations in OpenAlex.
- Chronic respiratory diseases risk during the COVID-19 pandemic: an integrated modelling approach based on hospital records across 30 countries.Population health metrics · 2025Article
- Effectiveness of a Vendor Predictive Model for the Risk of Pediatric Asthma Exacerbation: A Difference-in-Differences Analysis.Applied clinical informatics · 2023Article
- Lymph node metastases >5 and metastatic lymph node ratio >0.30 of differentiated thyroid cancer predict response to radioactive iodine.Cancer medicine · 2021Article
- Development of a diagnostic decision tree for obstructive pulmonary diseases based on real-life data.ERJ open research · 2016Article
- Acute Asthma Intensity Research Score: updated performance characteristics for prediction of hospitalization and lung function.Annals of allergy, asthma & immunology : official publication of the American College of Allergy, Asthma, & Immunology · 2015Article
- Article
- Effect of acetylcholinesterase (AChE) point-of-care testing in OP poisoning on knowledge, attitudes and practices of treating physicians in Sri Lanka.BMC health services research · 2014Article
- Novel insights in the fecal egg count reduction test for monitoring drug efficacy against soil-transmitted helminths in large-scale treatment programs.PLoS neglected tropical diseases · 2011Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
objectiveSimple risk stratification rules are limited in acute asthma. We developed and externally validated a classification tree for asthma hospitalization.
methodsData were obtained from 2 large, multicenter studies on acute asthma, the National Emergency Department Safety Study and the Multicenter Airway Research Collaboration cohorts. Both studies involved emergency department (ED) patients aged 18 to 54 years presenting to the ED with acute asthma. Clinical information was obtained from medical record review. The Classification and Regression Tree method was used to generate a simple decision tree. The tree was derived in the National Emergency Department Safety Study cohort and then was validated in the Multicenter Airway Research Collaboration cohort.
resultsThere were 1825 patients in the derivation cohort and 1335 in the validation cohort. Admission rates were 18% and 21% in the derivation and validation cohorts, respectively. The Classification and Regression Tree method identified 4 important variables (CHOP): change [C] in peak expiratory flow severity category, ever hospitalization [H] for asthma, oxygen [O] saturation on room air, and initial peak expiratory flow [P]. In a simple 3-step process, the decision rule risk-stratified patients into 7 groups, with a risk of admission ranging from 9% to 48%. The classification tree performed satisfactorily on discrimination in both the derivation and validation cohorts, with an area under the receiver operating characteristic curve of 0.72 and 0.65, respectively.
conclusionsWe developed and externally validated a novel classification tree for hospitalization among ED patients with acute asthma. Use of this explicit risk stratification rule may aid decision making in the emergency care of acute asthma.
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