Evidence map›Paper›PMID 20837258›Full record

ArticleThe American journal of emergency medicine2010

Risk stratification for hospitalization in acute asthma: the CHOP classification tree.

Chu-Lin Tsai, Sunday Clark, Carlos A Camargo

Abstract readValidation Study
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.4field-weighted citation impact, top 20% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
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  5. 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 · 2015
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Chu-Lin TsaiDepartment of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA. cltsai@post.harvard.edu
Sunday Clark
Carlos A Camargo
Massachusetts General Hospital · USUniversity of Pittsburgh · US

Funding

Prospective Study of Dietary Factors, BMI, and Risk of Asthma in ChildrenR01HL084401 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI CAMARGO, CARLOS ARTURO · 2007 to 2008
$743k
Validation of an Innovative Approach To Error ReductionR01HS013099 · AHRQ · MASSACHUSETTS GENERAL HOSPITAL · PI BLUMENTHAL, DAVID · 2003 to 2004
–
AHRQ HHS R01 HS013099AHRQ HHS R01 HS-13099NHLBI NIH HHS R01 HL084401NHLBI NIH HHS R01 HL-84401
6 · The paper itself

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.

Indexed as

Decision TreesEmergency Service, HospitalPatient AdmissionSeverity of Illness IndexAcute DiseaseAdultAlgorithmsAsthmaChi-Square DistributionCohort StudiesEmergency MedicineFemaleHumansMalePatient SelectionPeak Expiratory Flow Rate

Identifiers

PMID20837258
PMCPMC2939861
OpenAlexW2016146784

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.