Evidence map›Paper›PMID 39873808›Full record

ArticleLangenbeck's archives of surgery2025

Preoperative predictive indicators for resolution of hypertension in patients with unilateral primary aldosteronism: development of a nomogram model.

Lin Yang, Lei Yan, Laiyuan Qiu, Yi Sun, Gangli Gu

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Article in Langenbeck's archives of surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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5 authors.

Lin Yang *Department of Urology, Qilu Hospital, Shandong University, No 107, Wenhuaxi Road, Jinan, 250012, PR China.
Lei Yan *Department of Urology, Qilu Hospital, Shandong University, No 107, Wenhuaxi Road, Jinan, 250012, PR China.
Laiyuan QiuDepartment of Urology, Qilu Hospital, Shandong University, No 107, Wenhuaxi Road, Jinan, 250012, PR China.
Yi SunDepartment of Urology, Qilu Hospital, Shandong University, No 107, Wenhuaxi Road, Jinan, 250012, PR China.
Gangli GuDepartment of Urology, Qilu Hospital, Shandong University, No 107, Wenhuaxi Road, Jinan, 250012, PR China. ggl0126@126.com.

Funding

Natural Science Foundation of Shandong Province ZR2021MH049
6 · The paper itself

Abstract

backgroundPrimary aldosteronism (PA) is the leading surgically treatable cause of hypertension, with adrenalectomy as the definitive treatment for unilateral PA (UPA). However, some patients have persistent hypertension after surgery. This study aims to identify preoperative factors affecting surgical outcomes and develop a predictive model for postoperative hypertension resolution.

methodsWe reviewed and analyzed the medical records of 206 patients who underwent unilateral adrenalectomy for UPA at Qilu Hospital of Shandong University (2011-2022). As a training cohort, the data of the 166 patients from 2013 to 2022 was analyzed using univariate and multivariate logistic regression to explore the relationship between preoperative clinical and biochemical data and postoperative BP normalization. The remaining 40 patients from 2011 to 2012 were used as a validation cohort. A predictive model of the nomogram was constructed utilizing significant variables through multivariate logistic regression analysis. The model's effectiveness was evaluated using receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration curves and compared with previous prediction models using the Delong test.

resultsIn the training cohort of 166 patients, 78 (46.9%) achieved postoperative normotension without medication, while 88 (53.1%) required ongoing antihypertensive treatment. Multifactorial analysis identified age, number of antihypertensive medications, preoperative maximum systolic blood pressure (SBP), left ventricular ejection fraction (LVEF), serum creatinine (Cr) levels, and a history of hypokalemia as independent predictors of postoperative BP normalization. Calibration curves showed excellent agreement between predicted and actual outcomes, and DCA indicated that clinical interventions based on this model are beneficial at various risk thresholds. Comparison with previous models showed our model outperformed the Aldosteronoma Resolution Score (ARS) in the Asian population and was comparable to the Morisaki score.

conclusionA predictive model developed with variables including age, number of anti-hypertensive medications, preoperative maximum SBP, LVEF, serum Cr levels, and history of hypokalemia effectively predicts therapeutic outcomes following unilateral adrenalectomy for UPA patients.

Indexed as

AdrenalectomyHyperaldosteronismHypertensionNomogramsAdultAgedFemaleHumansMaleMiddle AgedPredictive Value of TestsPreoperative PeriodRetrospective StudiesTreatment OutcomeBiochemical markersComparison with existing modelsHypertensionPredictive modelUnilateral adrenalectomyUnilateral primary aldosteronism

Identifiers

PMID39873808
PMCPMC11775070

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LicenceCC BY-NC-ND
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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 Socratic graph.