Evidence map›Paper›PMID 29208066›Full record

ArticleEpidemiology and infection2018

Estimating the likely true changes in rheumatic fever incidence using two data sources.

J Oliver, N Pierse, D A Williamson, M G Baker

Open access · bronzeAbstract read
In one paragraph

Article in Epidemiology and infection, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.5field-weighted citation impact, top 26% 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

5 citing papers in PubMed, 10 citations in OpenAlex.

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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

4 authors at 2 institutions in 2 countries.

J OliverDepartment of Public Health,University of Otago Wellington,Wellington,New Zealand.
N PierseDepartment of Public Health,University of Otago Wellington,Wellington,New Zealand.
D A WilliamsonPeter Doherty Institute for Infection and Immunity,University of Melbourne,Melbourne,Australia.
M G BakerDepartment of Public Health,University of Otago Wellington,Wellington,New Zealand.
University of Otago · NZPeter Doherty Institute · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute rheumatic fever (ARF) continues to produce a significant burden of disease in New Zealand (NZ) Māori and Pacific peoples. Serious limitations in national surveillance data mean that accurate case totals cannot be generated. Given the changing epidemiology of ARF in NZ and the major national rheumatic fever prevention programme (2012-2017), we updated our previous likely true case number estimates using capture-recapture analyses. Aims were to estimate the likely true incidence of ARF in NZ and comment on the changing ability to detect cases. Data were obtained from national hospitalisation and notification databases. The Chapman Estimate partially adjusted for bias. An estimated 2342 likely true new cases arose from 1997 to 2015, giving a mean annual incidence of 2·9 per 100 000 (95% CI 2·5-3·5). Compared with the pre-intervention (2009-2011) baseline incidence (3·4 per 100 000, 95% CI 2·9-4·0), the likely true 2015 incidence declined 44%. Large gaps in data completeness are slowly closing. During the period 2012-2015, 723 cases were identified; 83·8% of notifications were matched to hospitalisation data, and 87·2% of hospitalisations matched to notifications. Despite this improvement, clinicians need to remain aware of the need to notify atypical patients. A possible unintended consequence of the national ARF prevention programme is increased misdiagnosis.

Indexed as

Databases, FactualAdolescentAdultAgedAged, 80 and overChildChild, PreschoolDisease NotificationEthnicityFemaleHospitalizationHumansIncidenceInfantInformation Storage and RetrievalMaleHealth equityincidencepublic healthrheumatic feversurveillance system

Identifiers

PMID29208066
PMCPMC9134743
OpenAlexW2774855572

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.