Renal damage in primary aldosteronism

Monticone, Silvia; Sconfienza, Elisa; D’Ascenzo, Fabrizio; Buffolo, Fabrizio; Satoh, Fumitoshi; Sechi, Leonardo A.; Veglio, Franco; Mulatero, Paolo

doi:10.1097/hjh.0000000000002216

Cited by 80 publications

(37 citation statements)

References 32 publications

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“…Accumulating evidence indicates that chronic aldosterone excess causes an increased risk of target organ damage, cardio, and cerebrovascular events, 7 chronic kidney disease 8 and overall mortality 9 in patients affected by PA compared with patients affected by essential hypertension. Treatment with mineralocorticoid receptor antagonists and surgical adrenalectomy allow a significant reduction of the excess risk.…”

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confidence: 99%

Clinical Score and Machine Learning-Based Model to Predict Diagnosis of Primary Aldosteronism in Arterial Hypertension

Buffolo¹,

Burrello²,

Burrello

et al. 2021

Hypertension

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Primary aldosteronism (PA) is the cause of arterial hypertension in 4% to 6% of patients, and 30% of patients with PA are affected by unilateral and surgically curable forms. Current guidelines recommend screening for PA ≈50% of patients with hypertension on the basis of individual factors, while some experts suggest screening all patients with hypertension. To define the risk of PA and tailor the diagnostic workup to the individual risk of each patient, we developed a conventional scoring system and supervised machine learning algorithms using a retrospective cohort of 4059 patients with hypertension. On the basis of 6 widely available parameters, we developed a numerical score and 308 machine learning-based models, selecting the one with the highest diagnostic performance. After validation, we obtained high predictive performance with our score (optimized sensitivity of 90.7% for PA and 92.3% for unilateral PA [UPA]). The machine learning-based model provided the highest performance, with an area under the curve of 0.834 for PA and 0.905 for diagnosis of UPA, with optimized sensitivity of 96.6% for PA, and 100.0% for UPA, at validation. The application of the predicting tools allowed the identification of a subgroup of patients with very low risk of PA (0.6% for both models) and null probability of having UPA. In conclusion, this score and the machine learning algorithm can accurately predict the individual pretest probability of PA in patients with hypertension and circumvent screening in up to 32.7% of patients using a machine learning-based model, without omitting patients with surgically curable UPA.

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confidence: 99%

Clinical Score and Machine Learning-Based Model to Predict Diagnosis of Primary Aldosteronism in Arterial Hypertension

Buffolo¹,

Burrello²,

Burrello

et al. 2021

Hypertension

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“…Additionally, PA is also associated with other known cardiovascular risk factors such as obstructive sleep apnea [21][22][23], obesity [24][25][26], chronic kidney disease [27,28], the metabolic syndrome, and type 2 diabetes [29][30][31][32], all of which could also contribute to the high cardiovascular risk of these patients.…”

Section: Cardiovascular Risk Associated With Primary Hyperaldosteronism (Pa)mentioning

confidence: 99%

Primary Hyperaldosteronism: When to Suspect It and How to Confirm Its Diagnosis

et al. 2022

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The definition of primary hyperaldosteronism (PA) has shifted, as progress has been made in understanding the disease. PA can be produced by unilateral or bilateral cortical adrenal hyperproduction of aldosterone, due to hyperplasia, aldosterone-secreting cell clusters, aldosterone-producing macro or micro adenoma/s, and combinations of the above, or by an aldosterone-producing carcinoma. PA is a highly prevalent disease, affecting close to 10% of the hypertensive population. However, PA is clearly underdiagnosed. The purpose of this review is to address current knowledge of PA’s clinical manifestations, as well as current methods of diagnosis. PA is associated with a higher cardiovascular morbidity and mortality than essential hypertension with similar blood pressure control. Young hypertensive patients, those with a first-degree relative with PA or ictus, and/or those with apnea/hypopnea syndrome, moderate/severe/resistant hypertension, adrenal incidentaloma, and/or hypokalemia should be screened for PA. PA can induce atrial fibrillation (AF), and those patients should also be screened for PA. We propose the use of the Captopril challenge test (CCT), oral salt loading, or intravenous salt loading for PA diagnosis, given their availability in the majority of hospital centers. CCT could be first-line, since it is safe and easy to perform.

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“…Primary aldosteronism (PA) is a major secondary cause of elevated blood pressure, with an recently estimated prevalence of 16-22% among the hypertensive population [1]. Importantly, it generates more detrimental cardiovascular, renal, and metabolic outcomes than equally severe essential hypertension [2][3][4][5]. Fortunately, targeted treatment is possible.…”

Section: Introductionmentioning

confidence: 99%

Limited diagnostic utility of partially successful adrenal vein sampling for primary aldosteronism subtyping

Kocjan

Vidmar

Vrckovnik

et al. 2021

Endokrynologia Polska

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Introduction: Failure of adrenal vein sampling (AVS) due to difficult cannulation of the right adrenal vein (AV) frequently precludes subtyping of patients with primary aldosteronism (PA) before adrenalectomy. According to a recent study, lateralized PA could be accurately predicted from partial AVS data based on the gradient of the aldosterone-to-cortisol ratios (ACR) between left AV and inferior vena cava (IVC) (LAV/IVC index). We aimed to validate the diagnostic utility of this index for PA subtyping in our cohort.2 Material and methods: A retrospective cross-sectional study included all patients who underwent bilaterally successful AVS at our centre and were diagnosed with either bilateral PA according to AVS or with lateralized PA after successful adrenalectomy from November 2004 to the end of 2019. Final diagnoses were compared to originally suggested LAV/IVC index cut-offs of ≥ 5.5 for ipsilateral disease and of ≤ 0.5 for contralateral disease, respectively. Results:The inclusion criteria were met in 168 patients: 46 women and 122 men, aged 54 years on average (range 32-72 years); 67 with lateralized and 101 with bilateral PA. LAV/IVC index using cut-offs of ≥ 5.5 or ≤ 0.5 anticipated ipsilateral (left lateralized) PA with a sensitivity of 32% and specificity of 97%, while a sensitivity of 47% and specificity of 95%, were found for contralateral (right lateralized) PA in our cohort. The overall inappropriate adrenalectomy rate was 29.7% (p = 0.314 for comparison between sides). When ascertaining ipsilateral disease (LAV/IVC index ≥ 5.5), 4 out of 16 patients (25%) would have been incorrectly sent to left adrenalectomy. Inappropriate right adrenalectomy would have occurred in 7 out of 21 patients (33.3%) when predicting contralateral disease (LAV/IVC index of ≤ 0.5). Thus, 11 patients with bilateral PA (6.5% of the entire cohort) would have been misclassified as lateralized PA and referred to surgery. Failed lateralization would have occurred in 61.2% of patients overall (53.3% for overlooked contralateral disease, 67.6% for missed ipsilateral disease; p = 0.723 for comparison between sides).Conclusions: Based on our cohort, we conclude that application of the suggested LAV/IVC index cut-offs did not predict lateralized PA with the high accuracy previously reported.

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Renal damage in primary aldosteronism

Cited by 80 publications

References 32 publications

Clinical Score and Machine Learning-Based Model to Predict Diagnosis of Primary Aldosteronism in Arterial Hypertension

Clinical Score and Machine Learning-Based Model to Predict Diagnosis of Primary Aldosteronism in Arterial Hypertension

Primary Hyperaldosteronism: When to Suspect It and How to Confirm Its Diagnosis

Limited diagnostic utility of partially successful adrenal vein sampling for primary aldosteronism subtyping

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