Literature DB >> 25858535

Reliability of a Bayesian network to predict an elevated aldosterone-to-renin ratio.

Michel Ducher1, Claire Mounier-Véhier2, Pierre Lantelme3, Bernard Vaisse4, Jean-Philippe Baguet5, Jean-Pierre Fauvel6.   

Abstract

BACKGROUND: Resistant hypertension is common, mainly idiopathic, but sometimes related to primary aldosteronism. Thus, most hypertension specialists recommend screening for primary aldosteronism. AIMS: To optimize the selection of patients whose aldosterone-to-renin ratio (ARR) is elevated from simple clinical and biological characteristics.
METHODS: Data from consecutive patients referred between 1 June 2008 and 30 May 2009 were collected retrospectively from five French 'European excellence hypertension centres' institutional registers. Patients were included if they had at least one of: onset of hypertension before age 40 years, resistant hypertension, history of hypokalaemia, efficient treatment by spironolactone, and potassium supplementation. An ARR>32 ng/L and aldosterone>160 ng/L in patients treated without agents altering the renin-angiotensin system was considered as elevated. Bayesian network and stepwise logistic regression were used to predict an elevated ARR.
RESULTS: Of 334 patients, 89 were excluded (31 for incomplete data, 32 for taking agents that alter the renin-angiotensin system and 26 for other reasons). Among 245 included patients, 110 had an elevated ARR. Sensitivity reached 100% or 63.3% using Bayesian network or logistic regression, respectively, and specificity reached 89.6% or 67.2%, respectively. The area under the receiver-operating-characteristic curve obtained with the Bayesian network was significantly higher than that obtained by stepwise regression (0.93±0.02 vs. 0.70±0.03; P<0.001).
CONCLUSION: In hypertension centres, Bayesian network efficiently detected patients with an elevated ARR. An external validation study is required before use in primary clinical settings.
Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Entities:  

Keywords:  Aldosterone-producing adenoma; Aldosterone-to-renin ratio; Aldostérone; Clinical prediction rule; Hypercholestérolémie primaire; Hypertension résistante; Hypokalaemia; Rapport aldostérone/rénine; Resistant hypertension; Règle de prédiction clinique

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Year:  2015        PMID: 25858535     DOI: 10.1016/j.acvd.2014.09.011

Source DB:  PubMed          Journal:  Arch Cardiovasc Dis        ISSN: 1875-2128            Impact factor:   2.340


  3 in total

1.  A maximum likelihood approach to electronic health record phenotyping using positive and unlabeled patients.

Authors:  Lingjiao Zhang; Xiruo Ding; Yanyuan Ma; Naveen Muthu; Imran Ajmal; Jason H Moore; Daniel S Herman; Jinbo Chen
Journal:  J Am Med Inform Assoc       Date:  2020-01-01       Impact factor: 4.497

2.  Development of a clinical decision tool to reduce diagnostic testing for primary aldosteronism in patients with difficult-to-control hypertension.

Authors:  Monique E A M van Kleef; Frank L J Visseren; Jan Westerink; Michiel L Bots; Peter J Blankestijn; Yolanda van der Graaf; Wilko Spiering
Journal:  BMC Endocr Disord       Date:  2020-04-29       Impact factor: 2.763

3.  Prediction Tool to Estimate Potassium Diet in Chronic Kidney Disease Patients Developed Using a Machine Learning Tool: The UniverSel Study.

Authors:  Maelys Granal; Lydia Slimani; Nans Florens; Florence Sens; Caroline Pelletier; Romain Pszczolinski; Catherine Casiez; Emilie Kalbacher; Anne Jolivot; Laurence Dubourg; Sandrine Lemoine; Celine Pasian; Michel Ducher; Jean Pierre Fauvel
Journal:  Nutrients       Date:  2022-06-10       Impact factor: 6.706

  3 in total

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