Evidence map›Paper›PMID 36404725›Full record

Trial reportJournal of paediatrics and child health2023

Comparison of percentile tables and algorithm-based calculators for classification of blood pressures in children and adolescents with obesity: A secondary analysis of a clinical trial.

William J Pitts, Tami L Cave, Alana Cavadino, Roman J Shypailo, Sarah E Maessen, Paul L Hofman, William Wong, Yvonne C Anderson

Open access · hybridAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of paediatrics and child health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 73% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

8 authors at 3 institutions in 3 countries.

William J PittsLiggins Institute, University of Auckland, Auckland, New Zealand.
Tami L CaveLiggins Institute, University of Auckland, Auckland, New Zealand.ORCID 0000-0001-7532-6441
Alana CavadinoSchool of Population Health, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.ORCID 0000-0002-5709-367X
Roman J ShypailoUSDA/ARS Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA.ORCID 0000-0002-1134-2482
Sarah E MaessenDepartment of Paediatrics: Child and Youth Health, University of Auckland, Auckland, New Zealand.ORCID 0000-0001-9234-4887
Paul L HofmanLiggins Institute, University of Auckland, Auckland, New Zealand.ORCID 0000-0002-8995-8711
William WongDepartment of Paediatric Nephrology, Starship Children's Hospital, Auckland District Health Board, Auckland, New Zealand.ORCID 0000-0002-8031-7408
Yvonne C AndersonDepartment of Paediatrics: Child and Youth Health, University of Auckland, Auckland, New Zealand.ORCID 0000-0003-2054-338X
University of Auckland · NZAuckland District Health Board · NZChildren's Nutrition Research Center at Baylor College of Medicine · US

Funding

A Better Start National Science ChallengeCurekidsHealth Research Council of New ZealandLotteries Health ResearchMaurice and Phyllis Paykel TrustRoyal Australasian College of PhysiciansTaranaki Medical FoundationUniversity of Auckland Summer Research Scholarship
6 · The paper itself

Abstract

aimObesity as a major risk factor for childhood hypertension necessitates careful blood pressure (BP) monitoring of those affected. This study aimed to compare BP classification in a cohort of children affected by obesity using tables versus digital calculations in two sets of guidelines.

methodsThis study was a secondary analysis of data collected from a randomised clinical trial of a multidisciplinary life-style assessment and intervention program. Baseline data from 237 children with a body mass index >99th percentile or >91st percentile with weight-related comorbidities and available BP measurements were analysed. We assessed agreement between tables and algorithms in classification of elevated BP/pre-hypertension and hypertension based on the American Academy of Paediatrics (AAP) clinical practice guidelines (CPG) and the older Fourth Report using Cohen's weighted kappa. The prevalence of hypertensive diagnoses was also compared between the two guidelines.

resultsAgreement between BP tables and algorithmic calculation of percentiles was discordant, though improved in the AAP CPG compared to the Fourth Report (Cohen's kappa = 0.70 vs. 0.57, respectively). None (0%) were missed diagnoses, and 59 (24.9%) were false positives for the Fourth Report, and 0 (0%) were missed diagnoses, and 49 (20.9%) were false positives for the AAP CPG. Under the recent guidelines, there was an increase in prevalence of 6.0% (95% confidence interval (CI) 2.5-9.4%; P = 0.0001) for BP ≥90th percentile, and of 3.0% (95% CI 0.4-5.6%; p = 0.016) for hypertension (BP ≥ 95th percentile) in the cohort (18.0% and 6.8%, respectively, increased from 12.0% and 3.8%).

conclusionsDigital calculators over tables in clinical practice are recommended where possible to improve the accuracy of paediatric BP classification. Substantial rates of elevated BP/Hypertension were found in this cohort of children and adolescents with overweight and obesity.

Indexed as

HypertensionPediatric ObesityAdolescentBlood PressureBlood Pressure DeterminationChildHumansPrevalenceRisk FactorsUnited Statesadolescentblood pressurehypertensionnormative blood pressure tablesobesitypaediatric

Identifiers

PMID36404725
PMCPMC10100042
OpenAlexW4309506059

What OpenQuestion holds

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LicenceCC BY-NC
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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.