ArticleHypertension (Dallas, Tex. : 1979)2016
Predicting Out-of-Office Blood Pressure in the Clinic (PROOF-BP): Derivation and Validation of a Tool to Improve the Accuracy of Blood Pressure Measurement in Clinical Practice.
Article in Hypertension (Dallas, Tex. : 1979), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 27 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.
- Investigation and management of young-onset hypertension: British and Irish hypertension society position statement.Journal of human hypertension · 2024Guideline
- Genetic predisposition to high blood pressure and out-of-office hypertension: Insights from a population sample in liechtenstein.PloS one · 2026Article
- Cutoffs for white-coat and masked blood pressure effects: an ambulatory blood pressure monitoring study.Journal of human hypertension · 2024Article
- Predicting new cases of hypertension in Swedish primary care with a machine learning tool.Preventive medicine reports · 2024Article
- Assessing Machine Learning for Diagnostic Classification of Hypertension Types Identified by Ambulatory Blood Pressure Monitoring.CJC open · 2024Article
- A Continuous Non-Invasive Blood Pressure Prediction Method Based on Deep Sparse Residual U-Net Combined with Improved Squeeze and Excitation Skip Connections.Sensors (Basel, Switzerland) · 2024Article
- Evaluating variable selection methods for multivariable regression models: A simulation study protocol.PloS one · 2024Article
- Diagnostic Accuracy of Office Blood Pressure Measurement and Home Blood Pressure Monitoring for Hypertension Screening Among Adults: Results From the IDH Study.Journal of the American Heart Association · 2023Article
- Cost-Effectiveness of Masked Hypertension Screening and Treatment in US Adults With Suspected Masked Hypertension: A Simulation Study.American journal of hypertension · 2022Article
- Predicting Out-of-Office Blood Pressure in a Diverse US Population.American journal of hypertension · 2022Article
- Article
- Home Blood Pressure Monitoring for Hypertension Diagnosis by Current Recommendations: A Long Way to Go.Hypertension (Dallas, Tex. : 1979) · 2022Article
- Algorithm for diagnosing hypertension using out-of-office blood pressure measurements.Journal of clinical hypertension (Greenwich, Conn.) · 2021Article
- Statistical model building: Background "knowledge" based on inappropriate preselection causes misspecification.BMC medical research methodology · 2021Article
- Rates, risks and routes to reduce vascular dementia (R4vad), a UK-wide multicentre prospective observational cohort study of cognition after stroke: Protocol.European stroke journal · 2021Article
- Impact of Self-Monitoring of Blood Pressure on Processes of Hypertension Care and Long-Term Blood Pressure Control.Journal of the American Heart Association · 2020Article
- Blood pressure cutoffs for white-coat and masked effects in a large population undergoing home blood pressure monitoring.Hypertension research : official journal of the Japanese Society of Hypertension · 2019Article
- Ambulatory monitoring unmasks hypertension among kidney transplant patients: single center experience and review of the literature.BMC nephrology · 2019Review
- Diagnosis and management of resistant hypertension: state of the art.Nature reviews. Nephrology · 2018Review
- Ambulatory blood pressure monitoring in the 21st century.Journal of clinical hypertension (Greenwich, Conn.) · 2018Review
Corrections and comments
- Commented on by
- Erratum issuedCorrection.2016
Authors and funding
15 authors at 7 institutions in 2 countries.
Funding
Abstract
Patients often have lower (white coat effect) or higher (masked effect) ambulatory/home blood pressure readings compared with clinic measurements, resulting in misdiagnosis of hypertension. The present study assessed whether blood pressure and patient characteristics from a single clinic visit can accurately predict the difference between ambulatory/home and clinic blood pressure readings (the home-clinic difference). A linear regression model predicting the home-clinic blood pressure difference was derived in 2 data sets measuring automated clinic and ambulatory/home blood pressure (n=991) using candidate predictors identified from a literature review. The model was validated in 4 further data sets (n=1172) using area under the receiver operator characteristic curve analysis. A masked effect was associated with male sex, a positive clinic blood pressure change (difference between consecutive measurements during a single visit), and a diagnosis of hypertension. Increasing age, clinic blood pressure level, and pulse pressure were associated with a white coat effect. The model showed good calibration across data sets (Pearson correlation, 0.48-0.80) and performed well-predicting ambulatory hypertension (area under the receiver operator characteristic curve, 0.75; 95% confidence interval, 0.72-0.79 [systolic]; 0.87; 0.85-0.89 [diastolic]). Used as a triaging tool for ambulatory monitoring, the model improved classification of a patient's blood pressure status compared with other guideline recommended approaches (93% [92% to 95%] classified correctly; United States, 73% [70% to 75%]; Canada, 74% [71% to 77%]; United Kingdom, 78% [76% to 81%]). This study demonstrates that patient characteristics from a single clinic visit can accurately predict a patient's ambulatory blood pressure. Usage of this prediction tool for triaging of ambulatory monitoring could result in more accurate diagnosis of hypertension and hence more appropriate treatment.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.