OBJECTIVE: Primary aldosteronism (PA) is the most common endocrine cause of curable hypertension, but no single test unequivocally identifies it. Accordingly, we investigated the usefulness of a logistic multivariate discriminant analysis (MDA) approach for PA screening. DESIGN: Generation of a logistic MDA function based on retrospective analysis of biochemical tests in a large cohort of referred patients with/without confirmed Conn's adenoma (CA), followed by prospective validation of the model. PATIENTS: We investigated 574 selected hypertensives: 206 (32 with and 174 without CA) retrospectively, 48 (with a 13% prevalence of CA) prospectively for the validation of the model, and 320 referred hypertensives (with a 3.4% prevalence of CA) similarly evaluated. Patients were referred to a specialised centre for hypertension (4th Clinica Medica--University of Padua) and to a department of Internal Medicine of a regional hospital (Reggio Emilia). MEASUREMENTS: In all patients we measured several demographic and biochemical variables and performed a captopril test. A stepwise analysis of variance, based on a model fitted with several different variables, identified baseline (sALDO) and captopril-suppressed plasma aldosterone (cALDO), supine plasma renin activity (sPRA) and K+ as the most informative. Therefore, two models of logistic MDA with sPRA, K+, and either sALDO (model A) or cALDO (model B) were developed and used. ROC analysis was also performed to assess the optimal cut-off values. RESULTS: The model B of MDA provided the best performance and identified CA with 100% sensitivity and 81% accuracy. When used prospectively it showed 100% sensitivity, both in the Padua (88% accuracy) and in the Reggio Emilia series (90% accuracy). However, at both institutions most patients with idiopathic hyperaldosteronism (IHA) were also detected. CONCLUSIONS: Thus, although developed from patients with confirmed Conn's adenoma, a strategy based on multivariate discriminant analysis can be used prospectively for accurate screening for primary aldosteronism. Furthermore, it was proven to be accurate and applicable to patients tested with similar modalities at a different institution. Although this approach did not provide a clear-cut discrimination of Conn's adenoma from idiopathic hyperaldosteronism, it may avoid unnecessary and costly further testing in patients with a low probability of primary aldosteronism.
OBJECTIVE: Primary aldosteronism (PA) is the most common endocrine cause of curable hypertension, but no single test unequivocally identifies it. Accordingly, we investigated the usefulness of a logistic multivariate discriminant analysis (MDA) approach for PA screening. DESIGN: Generation of a logistic MDA function based on retrospective analysis of biochemical tests in a large cohort of referred patients with/without confirmed Conn's adenoma (CA), followed by prospective validation of the model. PATIENTS: We investigated 574 selected hypertensives: 206 (32 with and 174 without CA) retrospectively, 48 (with a 13% prevalence of CA) prospectively for the validation of the model, and 320 referred hypertensives (with a 3.4% prevalence of CA) similarly evaluated. Patients were referred to a specialised centre for hypertension (4th Clinica Medica--University of Padua) and to a department of Internal Medicine of a regional hospital (Reggio Emilia). MEASUREMENTS: In all patients we measured several demographic and biochemical variables and performed a captopril test. A stepwise analysis of variance, based on a model fitted with several different variables, identified baseline (sALDO) and captopril-suppressed plasma aldosterone (cALDO), supine plasma renin activity (sPRA) and K+ as the most informative. Therefore, two models of logistic MDA with sPRA, K+, and either sALDO (model A) or cALDO (model B) were developed and used. ROC analysis was also performed to assess the optimal cut-off values. RESULTS: The model B of MDA provided the best performance and identified CA with 100% sensitivity and 81% accuracy. When used prospectively it showed 100% sensitivity, both in the Padua (88% accuracy) and in the Reggio Emilia series (90% accuracy). However, at both institutions most patients with idiopathic hyperaldosteronism (IHA) were also detected. CONCLUSIONS: Thus, although developed from patients with confirmed Conn's adenoma, a strategy based on multivariate discriminant analysis can be used prospectively for accurate screening for primary aldosteronism. Furthermore, it was proven to be accurate and applicable to patients tested with similar modalities at a different institution. Although this approach did not provide a clear-cut discrimination of Conn's adenoma from idiopathic hyperaldosteronism, it may avoid unnecessary and costly further testing in patients with a low probability of primary aldosteronism.
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
Authors: Christina Westerdahl; Anders Bergenfelz; Anders Isaksson; Christina Nerbrand; Stig Valdemarsson Journal: Scand J Prim Health Care Date: 2011-03 Impact factor: 2.581
Authors: Giuseppe Maiolino; Sara Mareso; Valeria Bisogni; Giacomo Rossitto; Matteo Azzolini; Maurizio Cesari; Teresa Maria Seccia; Lorenzo Calò; Gian Paolo Rossi Journal: High Blood Press Cardiovasc Prev Date: 2015-12-16