Cargando…
Validation of Existing Clinical Prediction Tools for Primary Aldosteronism Subtyping
The new clinical prediction score (SCORE) has been recently proposed for primary aldosteronism (PA) subtyping prior to adrenal vein sampling (AVS). This study aimed to compare that SCORE with previously published scores and their validation using a cohort of patients at our center who had had positi...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689974/ https://www.ncbi.nlm.nih.gov/pubmed/36428866 http://dx.doi.org/10.3390/diagnostics12112806 |
_version_ | 1784836669911859200 |
---|---|
author | Kološová, Barbora Waldauf, Petr Wichterle, Dan Kvasnička, Jan Zelinka, Tomáš Petrák, Ondřej Krátká, Zuzana Forejtová, Lubomíra Kaván, Jan Widimský, Jiří Holaj, Robert |
author_facet | Kološová, Barbora Waldauf, Petr Wichterle, Dan Kvasnička, Jan Zelinka, Tomáš Petrák, Ondřej Krátká, Zuzana Forejtová, Lubomíra Kaván, Jan Widimský, Jiří Holaj, Robert |
author_sort | Kološová, Barbora |
collection | PubMed |
description | The new clinical prediction score (SCORE) has been recently proposed for primary aldosteronism (PA) subtyping prior to adrenal vein sampling (AVS). This study aimed to compare that SCORE with previously published scores and their validation using a cohort of patients at our center who had had positive SIT confirming PA and had been diagnosed with either bilateral PA according to AVS or unilateral PA if biochemically cured after an adrenalectomy. Final diagnoses were used to evaluate the diagnostic performance of the proposed clinical prediction tools. Only Kamemura’s model (with a maximum score of 4 points) and Kobayashi’s score (with a maximum score of 12 points) reached 100% reliability for prediction of bilateral PA; however, with sensitivity of only 3%. On the other hand, the values of SCORE = 3 (with sensitivity of 48%), the SPACE score ≥18 (with sensitivity of 35%), the Kobayashi’s score ≤2 (with sensitivity of 28%), and the Kocjan’s score = 3 (with sensitivity of 28%) were able to predict unilateral PA with 100% probability. Furthermore, Umakoshi’s and Young’s models both reached 100% reliability for a unilateral PA with score = 4 and both predictive factors together respectively; however, the sensitivity was lower compared with previous models; 4% and 14%, respectively. None of the clinical prediction tools applied to our cohort predicted unilateral and bilateral subtypes together with the expected high diagnostic performance, and therefore can only be used for precisely defined cases. |
format | Online Article Text |
id | pubmed-9689974 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96899742022-11-25 Validation of Existing Clinical Prediction Tools for Primary Aldosteronism Subtyping Kološová, Barbora Waldauf, Petr Wichterle, Dan Kvasnička, Jan Zelinka, Tomáš Petrák, Ondřej Krátká, Zuzana Forejtová, Lubomíra Kaván, Jan Widimský, Jiří Holaj, Robert Diagnostics (Basel) Article The new clinical prediction score (SCORE) has been recently proposed for primary aldosteronism (PA) subtyping prior to adrenal vein sampling (AVS). This study aimed to compare that SCORE with previously published scores and their validation using a cohort of patients at our center who had had positive SIT confirming PA and had been diagnosed with either bilateral PA according to AVS or unilateral PA if biochemically cured after an adrenalectomy. Final diagnoses were used to evaluate the diagnostic performance of the proposed clinical prediction tools. Only Kamemura’s model (with a maximum score of 4 points) and Kobayashi’s score (with a maximum score of 12 points) reached 100% reliability for prediction of bilateral PA; however, with sensitivity of only 3%. On the other hand, the values of SCORE = 3 (with sensitivity of 48%), the SPACE score ≥18 (with sensitivity of 35%), the Kobayashi’s score ≤2 (with sensitivity of 28%), and the Kocjan’s score = 3 (with sensitivity of 28%) were able to predict unilateral PA with 100% probability. Furthermore, Umakoshi’s and Young’s models both reached 100% reliability for a unilateral PA with score = 4 and both predictive factors together respectively; however, the sensitivity was lower compared with previous models; 4% and 14%, respectively. None of the clinical prediction tools applied to our cohort predicted unilateral and bilateral subtypes together with the expected high diagnostic performance, and therefore can only be used for precisely defined cases. MDPI 2022-11-15 /pmc/articles/PMC9689974/ /pubmed/36428866 http://dx.doi.org/10.3390/diagnostics12112806 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kološová, Barbora Waldauf, Petr Wichterle, Dan Kvasnička, Jan Zelinka, Tomáš Petrák, Ondřej Krátká, Zuzana Forejtová, Lubomíra Kaván, Jan Widimský, Jiří Holaj, Robert Validation of Existing Clinical Prediction Tools for Primary Aldosteronism Subtyping |
title | Validation of Existing Clinical Prediction Tools for Primary Aldosteronism Subtyping |
title_full | Validation of Existing Clinical Prediction Tools for Primary Aldosteronism Subtyping |
title_fullStr | Validation of Existing Clinical Prediction Tools for Primary Aldosteronism Subtyping |
title_full_unstemmed | Validation of Existing Clinical Prediction Tools for Primary Aldosteronism Subtyping |
title_short | Validation of Existing Clinical Prediction Tools for Primary Aldosteronism Subtyping |
title_sort | validation of existing clinical prediction tools for primary aldosteronism subtyping |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689974/ https://www.ncbi.nlm.nih.gov/pubmed/36428866 http://dx.doi.org/10.3390/diagnostics12112806 |
work_keys_str_mv | AT kolosovabarbora validationofexistingclinicalpredictiontoolsforprimaryaldosteronismsubtyping AT waldaufpetr validationofexistingclinicalpredictiontoolsforprimaryaldosteronismsubtyping AT wichterledan validationofexistingclinicalpredictiontoolsforprimaryaldosteronismsubtyping AT kvasnickajan validationofexistingclinicalpredictiontoolsforprimaryaldosteronismsubtyping AT zelinkatomas validationofexistingclinicalpredictiontoolsforprimaryaldosteronismsubtyping AT petrakondrej validationofexistingclinicalpredictiontoolsforprimaryaldosteronismsubtyping AT kratkazuzana validationofexistingclinicalpredictiontoolsforprimaryaldosteronismsubtyping AT forejtovalubomira validationofexistingclinicalpredictiontoolsforprimaryaldosteronismsubtyping AT kavanjan validationofexistingclinicalpredictiontoolsforprimaryaldosteronismsubtyping AT widimskyjiri validationofexistingclinicalpredictiontoolsforprimaryaldosteronismsubtyping AT holajrobert validationofexistingclinicalpredictiontoolsforprimaryaldosteronismsubtyping |