Evidence map›Paper›PMID 31447515›Full record

ArticleEthiopian journal of health sciences2019

Prevalence and Predictors of White Coat Hypertension among Newly-Diagnosed Hypertensive Patients in a Tertiary Health Centre in Nigeria.

Bolade Dele-Ojo, Philip Kolo, Ayodele Ogunmodede, Haleema Bello, Ibraheem Katibi, Ayodele Omotoso, Samuel Dada

Open access · diamondAbstract read
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Article in Ethiopian journal of health sciences, 2019. 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 46% 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

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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, 3 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

7 authors at 2 institutions in 1 country.

Bolade Dele-OjoEkiti State University Ado Ekiti Ekiti State, Ado, Ekiti 360001, Nigeria.
Philip KoloUniversity of Ilorin Teaching Hospital, Ilorin, Nigeria.
Ayodele OgunmodedeUniversity of Ilorin Teaching Hospital, Ilorin, Nigeria.
Haleema BelloUniversity of Ilorin Teaching Hospital, Ilorin, Nigeria.
Ibraheem KatibiUniversity of Ilorin Teaching Hospital, Ilorin, Nigeria.
Ayodele OmotosoUniversity of Ilorin Teaching Hospital, Ilorin, Nigeria.
Samuel DadaEkiti State University Ado Ekiti Ekiti State, Ado, Ekiti 360001, Nigeria.
University of Ilorin Teaching Hospital · NGEkiti State University · NG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFailure to diagnose and adequately classify newly-diagnosed hypertensive patients may lead to non-recognition of White Coat Hypertension (WCH) and inappropriate use of antihypertensive medications. This study determined the prevalence and predictors of white coat hypertension among newly-diagnosed hypertensive patients in a tertiary health centre in Nigeria.

methodsOne hundred and twenty newly-diagnosed hypertensive patients and 120 controls were recruited for the study. All the participants had 24-hour Ambulatory Blood Pressure Monitoring (ABPM) using an oscillometric device (CONTEC®). Data were analyzed using SPSS version 20.0.

resultsOut of 120 patients, 52 were males and the mean age was 44.2 ± 9.7 years whereas of the 120 controls, 53 were males and the mean age was 44.0 ± 7.5 years. The mean body mass index of the patients, BMI (27.0 ± 4.5kg/m

conclusionHigh prevalence of WCH existed among participants studied. High level of education and being obese were predictors of white coat hypertension. Hence, ambulatory blood pressure monitoring should be included as part of routine work-up for newly-diagnosed hypertensive patients in order to limit the number of those who may be committed to lifelong antihypertensive medications with its unwanted side effects.

Indexed as

AdultBlood Pressure Monitoring, AmbulatoryBody Mass IndexFemaleHumansMaleNigeriaPrevalenceTertiary Care CentersWhite Coat Hypertensionambulatory blood pressureNigeriapredictorPrevalencewhite coat hypertension

Identifiers

PMID31447515
PMCPMC6689704
OpenAlexW2978284170

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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.