Evidence map›Paper›PMID 14730322›Full record

ArticleJournal of human hypertension2004

Diagnostic value of strategy for the detection of white coat hypertension based on ambulatory and home blood pressure monitoring.

G S Stergiou, C V Alamara, I I Skeva, T D Mountokalakis

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Journal of human hypertension, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

7 citing papers in PubMed, 27 citations in OpenAlex.

  1. Trial
  2. Review
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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 1 institution in 1 country.

G S StergiouHypertension Center, Third University Department of Medicine, Sotiria Hospital, Athens, Greece. gstergi@med.uoa.gr
C V Alamara
I I Skeva
T D Mountokalakis
Sotiria General Hospital · GR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An algorithm has been proposed for the detection of white coat hypertension among subjects with elevated blood pressure (BP) on at least three clinic visits using home BP monitoring (screening test) and, if this is low, ambulatory BP monitoring (diagnostic test). This study aims to test this strategy in practice. The proposed algorithm was applied in 133 untreated subjects with elevated BP assessed in a previous prospective study using repeated clinic, home and ambulatory BP measurements. The proportions of detected and missed cases of white coat hypertension and the diagnostic value of the algorithm were calculated. By applying the algorithm, 99 subjects (74%) were found eligible for home measurements and 35 (26%) for ambulatory monitoring. There were 38 subjects with white coat hypertension (38%), of whom 15 (39%) were not detected by the proposed strategy. The sensitivity, specificity, and the positive and negative predictive value of the algorithm to diagnose white coat hypertension were 61, 81, 66 and 77%, respectively. Of the 34 subjects with normal BP on the third clinic visit, 15 (42%) had elevated home and/or ambulatory BP. These data suggest that, using the proposed strategy, many white coat hypertensives may remain undetected and may receive unnecessary long-term drug treatment. Therefore, more research is needed on the optimal strategy for detecting white coat hypertension in clinical practice.

Indexed as

AlgorithmsBlood PressureBlood Pressure DeterminationBlood Pressure Monitoring, AmbulatoryFemaleHumansHypertensionMaleMiddle AgedPredictive Value of TestsROC CurveSensitivity and Specificity

Identifiers

PMID14730322
OpenAlexW2052986291

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.