Evidence map›Paper›PMID 26958849›Full record

ArticlePloS one2016

Incidence of Hospitalization for Respiratory Syncytial Virus Infection amongst Children in Ontario, Canada: A Population-Based Study Using Validated Health Administrative Data.

Andrea Pisesky, Eric I Benchimol, Coralie A Wong, Charles Hui, Megan Crowe, Marc-Andre Belair, Supichaya Pojsupap, Tim Karnauchow, Katie O'Hearn, Abdool S Yasseen and 1 more

Abstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

52 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

11 authors.

Andrea PiseskyDepartment of Pediatrics, Children's Hospital of Eastern Ontario, University of Ottawa, Ottawa, Ontario, Canada.
Eric I BenchimolDepartment of Pediatrics, Children's Hospital of Eastern Ontario, University of Ottawa, Ottawa, Ontario, Canada.
Coralie A WongInstitute for Clinical Evaluative Sciences (ICES uOttawa), Ottawa, Ontario, Canada.
Charles HuiDepartment of Pediatrics, Children's Hospital of Eastern Ontario, University of Ottawa, Ottawa, Ontario, Canada.
Megan CroweSchool of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Ontario, Canada.
Marc-Andre BelairInstitute for Clinical Evaluative Sciences (ICES uOttawa), Ottawa, Ontario, Canada.
Supichaya PojsupapDepartment of Pediatrics, Children's Hospital of Eastern Ontario, University of Ottawa, Ottawa, Ontario, Canada.
Tim KarnauchowDepartment of Pediatrics, Children's Hospital of Eastern Ontario, University of Ottawa, Ottawa, Ontario, Canada.
Katie O'HearnChildren's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Ontario, Canada.
Abdool S YasseenChildren's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Ontario, Canada.
James D McNallyDepartment of Pediatrics, Children's Hospital of Eastern Ontario, University of Ottawa, Ottawa, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

importanceRSV is a common illness among young children that causes significant morbidity and health care costs.

objectiveRoutinely collected health administrative data can be used to track disease incidence, explore risk factors and conduct health services research. Due to potential for misclassification bias, the accuracy of data-elements should be validated prior to use. The objectives of this study were to validate an algorithm to accurately identify pediatric cases of hospitalized respiratory syncytial virus (RSV) from within Ontario's health administrative data, estimate annual incidence of hospitalization due to RSV and report the prevalence of major risk factors within hospitalized patients. STUDY DESIGN AND

settingA retrospective chart review was performed to establish a reference-standard cohort of children from the Ottawa region admitted to the Children's Hospital of Eastern Ontario (CHEO) for RSV-related disease in 2010 and 2011. Chart review data was linked to Ontario's administrative data and used to evaluate the diagnostic accuracy of algorithms of RSV-related ICD-10 codes within provincial hospitalization and emergency department databases. Age- and sex-standardized incidence was calculated over time, with trends in incidence assessed using Poisson regression.

resultsFrom a total of 1411 admissions, chart review identified 327 children hospitalized for laboratory confirmed RSV-related disease. Following linkage to administrative data and restriction to first admissions, there were 289 RSV patients in the reference-standard cohort. The best algorithm, based on hospitalization data, resulted in sensitivity 97.9% (95%CI: 95.5-99.2%), specificity 99.6% (95%CI: 98.2-99.8%), PPV 96.9% (95%CI: 94.2-98.6%), NPV 99.4% (95%CI: 99.4-99.9%). Incidence of hospitalized RSV in Ontario from 2005-2012 was 10.2 per 1000 children under 1 year and 4.8 per 1000 children aged 1 to 3 years. During the surveillance period, there was no identifiable increasing or decreasing linear trend in the incidence of hospitalized RSV, hospital length of stay and PICU admission rates. Among the Ontario RSV cohort, 16.3% had one or more major risk factors, with a decreasing trend observed over time.

conclusionChildren hospitalized for RSV-related disease can be accurately identified within population-based health administrative data. RSV is a major public health concern and incidence has not changed over time, suggesting a lack of progress in prevention.

Indexed as

ChildChild, PreschoolFemaleHospitalizationHumansIncidenceMaleOntarioRespiratory Syncytial Virus InfectionsRetrospective Studies

Identifiers

PMID26958849
PMCPMC4784925

What OpenQuestion holds

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Registered trials

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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.