10.06.2024 | Original Article
Establishment of a scoring model for predicting clinical outcomes in patients with unilateral primary aldosteronism after superselective adrenal artery embolization
verfasst von:
Tao Luo, Jindong Wan, Sen Liu, Xinquan Wang, Peng Zhou, Qiang Xue, Jixin Hou, Peijian Wang
Erschienen in:
Irish Journal of Medical Science (1971 -)
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Ausgabe 5/2024
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Abstract
Objective
Superselective adrenal arterial embolization (SAAE) is a potential alternative treatment for patients with unilateral primary aldosteronism (PA) who refuse unilateral adrenalectomy. Therefore, we aimed to establish a scoring model to differentiate between hypertensive remission after SAAE.
Methods
This prospective cohort study involved 240 patients who underwent SAAE for unilateral PA. Patients were randomly divided into a model training set and a validation set at a ratio of 7:3. The clinical outcome was a response to hypertension remission, defined as complete, partial, or absent success at 6 months after SAAE. Multivariate logistic regression was performed to identify independent parameters and develop a nomogram to predict clinical outcomes after SAAE. The discrimination, calibration efficacy, and clinical utility of the predictive model were assessed.
Results
Five independent predictors were identified: female sex, duration of hypertension, defined daily dose of antihypertensive medication, diabetes, and target organ damage. The above five independent predictors were put into a predictive model that was presented as a nomogram. Using bootstrapping for internal validation, the C-statistic for the predictive model was 0.866 (95% confidence interval [CI]: 0.834 to 0.898). In the validation cohort, the area under the curve (AUC) of the nomogram for predicting hypertension remission after SAAE was 0.809.
Conclusion
The present model is the first nomogram-based score that specifically predicts hypertension remission after SAAE in patients with unilateral PA using conventional parameters. This is an effective risk stratification tool that can be used by clinicians for timely and tailored preoperative risk discussions.