Evidence map›Paper›PMID 34699680›Full record

ArticleJournal of clinical hypertension (Greenwich, Conn.)2021

Algorithm for diagnosing hypertension using out-of-office blood pressure measurements.

Je Sang Kim, Moo-Yong Rhee, Chee Hae Kim, Yoo Ri Kim, Ungjeong Do, Ji-Hyun Kim, Young Kwon Kim, Hyun Jung Lee, Jee Yeon Park, June Namgung and 4 more

Abstract read
In one paragraph

Article in Journal of clinical hypertension (Greenwich, Conn.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Algorithm for diagnosing hypertension using out-of-office blood pressure measurements.Journal of clinical hypertension (Greenwich, Conn.) · 2021
    Article
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

14 authors.

Je Sang KimCardiovascular Center, Dongguk University Ilsan Hospital, Goyang, South Korea.
Moo-Yong RheeCardiovascular Center, Dongguk University Ilsan Hospital, Goyang, South Korea.ORCID 0000-0002-1595-3627
Chee Hae KimCardiovascular Center, Dongguk University Ilsan Hospital, Goyang, South Korea.
Yoo Ri KimCardiovascular Center, Dongguk University Ilsan Hospital, Goyang, South Korea.
Ungjeong DoCardiovascular Center, Dongguk University Ilsan Hospital, Goyang, South Korea.
Ji-Hyun KimCardiovascular Center, Dongguk University Ilsan Hospital, Goyang, South Korea.
Young Kwon KimCardiovascular Center, Dongguk University Ilsan Hospital, Goyang, South Korea.
Hyun Jung LeeDivision of Hematology and Medical Oncology, Dongguk University Ilsan Hospital, Goyang, South Korea.
Jee Yeon ParkDepartment of Internal Medicine, Dongguk University Ilsan Hospital, Goyang, South Korea.
June NamgungDivision of Cardiology, Department of Internal Medicine, Ilsan Paik Hospital, Inje University College of Medicine, Goyang, South Korea.
Sung Yun LeeDivision of Cardiology, Department of Internal Medicine, Ilsan Paik Hospital, Inje University College of Medicine, Goyang, South Korea.
Deok-Kyu ChoDivision of Cardiology, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, South Korea.
Tae-Young ChoiDepartment of Internal Medicine, Seoul Red Cross Hospital, Seoul, South Korea.
Seok Yeon KimDepartment of Internal Medicine, Seoul Medical Center, Seoul, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The authors developed and validated a diagnostic algorithm using the optimal upper and lower cut-off values of office and home BP at which ambulatory BP measurements need to be applied. Patients presenting with high BP (≥140/90 mm Hg) at the outpatient clinic were referred to measure office, home, and ambulatory BP. Office and home BP were divided into hypertension, intermediate (requiring diagnosis using ambulatory BP), and normotension zones. The upper and lower BP cut-off levels of intermediate zone were determined corresponding to a level of 95% specificity and 95% sensitivity for detecting daytime ambulatory hypertension by using the receiver operator characteristic curve. A diagnostic algorithm using three methods, OBP-ABP: office BP measurement and subsequent ambulatory BP measurements if office BP is intermediate zone; OBP-HBP-ABP: office BP, subsequent home BP measurement if office BP is within intermediate zone and subsequent ambulatory BP measurement if home BP is within intermediate zone; and HBP-ABP: home BP measurement and subsequent ambulatory BP measurements if home BP is within intermediate zone, were developed and validated. In the development population (n = 256), the developed algorithm yielded better diagnostic accuracies than 75.8% (95%CI 70.1-80.9) for office BP alone and 76.2% (95%CI 70.5-81.3) for home BP alone as follows: 96.5% (95%CI: 93.4-98.4) for OBP-ABP, 93.4% (95%CI: 89.6-96.1) for OBP-HBP-ABP, and 94.9% (95%CI: 91.5-97.3%) for HBP-ABP.  In the validation population (n = 399), the developed algorithm showed similarly improved diagnostic accuracy. The developed algorithm applying ambulatory BP measurement to the intermediate zone of office and home BP improves the diagnostic accuracy for hypertension.

Indexed as

HypertensionAlgorithmsBlood PressureBlood Pressure DeterminationBlood Pressure Monitoring, AmbulatoryHumansalgorithmhypertensionout-of-office blood pressure

Identifiers

PMID34699680
PMCPMC8630611

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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.