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      Validation of three novel clinical prediction tools for primary aldosteronism subtyping

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          Abstract

          The 20-point clinical prediction SPACE score, the aldosterone-to-lowest potassium ratio (APR), aldosterone concentration (AC) and the AC relative reduction rate after saline infusion test (SIT) have recently been proposed for primary aldosteronism (PA) subtyping prior to adrenal vein sampling (AVS). To validate those claims, we performed a retrospective cross-sectional study that included all patients at our center who had positive SIT to confirm PA and were diagnosed with either bilateral disease (BPA) according to AVS or with lateralized disease (LPA) if biochemically cured after adrenalectomy from November 2004 to the end of 2019. Final diagnoses were used to evaluate the diagnostic performance of proposed clinical prediction tools. Our cohort included 144 patients (40 females), aged 32–72 years (mean 54 years); 59 with LPA and 85 with BPA. The originally suggested SPACE score ≤8 and SPACE score >16 rules yielded about 80% positive predictive value (PPV) for BPA and LPA, respectively. Multivariate analyses with the predictors constituting the SPACE score highlighted post-SIT AC as the most important predictor of PA subtype for our cohort. APR-based tool of <5 for BPA and >15 for LPA yielded about 75% PPV for LPA and BPA. The proposed post-SIT AC <8.79 ng/dL criterion yielded 41% sensitivity and 90% specificity, while the relative post-SIT AC reduction rate of >33.8% criterion yielded 80% sensitivity and 51% specificity for BPA prediction. The application of any of the validated clinical prediction tools to our cohort did not predict the PA subtype with the high diagnostic performance originally reported.

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          Most cited references60

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          The Management of Primary Aldosteronism: Case Detection, Diagnosis, and Treatment: An Endocrine Society Clinical Practice Guideline.

          To develop clinical practice guidelines for the management of patients with primary aldosteronism.
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            Bias reduction of maximum likelihood estimates

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              A solution to the problem of separation in logistic regression.

              The phenomenon of separation or monotone likelihood is observed in the fitting process of a logistic model if the likelihood converges while at least one parameter estimate diverges to +/- infinity. Separation primarily occurs in small samples with several unbalanced and highly predictive risk factors. A procedure by Firth originally developed to reduce the bias of maximum likelihood estimates is shown to provide an ideal solution to separation. It produces finite parameter estimates by means of penalized maximum likelihood estimation. Corresponding Wald tests and confidence intervals are available but it is shown that penalized likelihood ratio tests and profile penalized likelihood confidence intervals are often preferable. The clear advantage of the procedure over previous options of analysis is impressively demonstrated by the statistical analysis of two cancer studies. Copyright 2002 John Wiley & Sons, Ltd.
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                Author and article information

                Journal
                Endocr Connect
                Endocr Connect
                EC
                Endocrine Connections
                Bioscientifica Ltd (Bristol )
                2049-3614
                11 April 2022
                01 May 2022
                : 11
                : 5
                : e210532
                Affiliations
                [1 ]Department of Endocrinology , Diabetes and Metabolic Diseases, University Medical Centre Ljubljana, Ljubljana, Slovenia
                [2 ]Faculty of Medicine , University of Ljubljana, Ljubljana, Slovenia
                [3 ]University Rehabilitation Institute , Ljubljana, Slovenia
                [4 ]FAMNIT , University of Primorska, Koper, Slovenia
                [5 ]Clinical Institute of Radiology , University Medical Centre Ljubljana, Ljubljana, Slovenia
                Author notes
                Correspondence should be addressed to T Kocjan: tomaz.kocjan@ 123456kclj.si
                Author information
                http://orcid.org/0000-0001-8606-6825
                Article
                EC-21-0532
                10.1530/EC-21-0532
                9175612
                35521815
                37e6a7c9-2294-4e58-97af-c4e62cb5707c
                © The authors

                This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

                History
                : 22 March 2022
                : 11 April 2022
                Categories
                Research

                adrenal vein sampling,endocrine hypertension,primary hyperaldosteronism,subtype prediction

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