Redefining the Diagnostic Approach to Adrenal Insufficiency: Re-Assessment of Baseline and Cortisol Increment Cut-Offs with the 1 µg Synacthen Test

TL;DR

This study proposes a new diagnostic algorithm for adrenal insufficiency using revised cortisol cut-offs and a single 30-minute measurement during a synacthen test to improve accuracy.

Contribution

The study introduces a novel diagnostic algorithm for adrenal insufficiency with revised baseline and cortisol increment cut-offs using a single 30-minute measurement.

Findings

Baseline cortisol ≤ 5.35 μg/dL had 100% specificity but 41.5% sensitivity for adrenal insufficiency.

Single 30 and 60-minute cortisol measurements correctly classified 92.64% and 93.87% of cases, respectively.

A cortisol increment cut-off of 6.35 μg/dL showed 99% specificity for ruling in adrenal insufficiency.

Abstract

Background and Objectives: Adrenal insufficiency (AI) is an endocrine disorder characterized by inadequate cortisol production, leading to non-specific symptoms that delay diagnosis. The Low Dose Synacthen Test (LDST) is commonly used to evaluate adrenal function, but traditional cortisol cut-offs may not accurately reflect adrenal function in all patients. This study aims to identify baseline cortisol cut-offs to accurately rule in and out AI, reassess the value of cortisol increment during LDST, and evaluate the accuracy of 30 and 60 min cortisol measurements in diagnosing AI. Materials and Methods: We conducted a cross-sectional analysis of patients who underwent LDST at Farhat Hached University Hospital. Diagnostic accuracy of baseline cortisol levels and cortisol increment was assessed using ROC curve analysis to determine optimal cut-offs for predicting LDST outcomes. Results: Among 163 patients (mean age 42.9 years, 63% female), baseline cortisol ≤ 5.35 μg/dL had 100% specificity but 41.5% sensitivity for LDST failure. Conversely, baseline cortisol ≥ 12.4 μg/dL had 100% sensitivity with 45.9% specificity. Single measurements at 30 and 60 min correctly classified 92.64% and 93.87% of cases, respectively. ROC analysis of 30 and 60 min cortisol increments showed high diagnostic accuracy (AUC 0.923 and 0.914, respectively). The optimal cortisol increment cut-off was 6.35 μg/dL for ruling in AI (99% specificity). Conclusions: We propose a novel AI diagnostic algorithm based on a single 30 min cortisol measurement, complemented by revised baseline cortisol cut-offs and cortisol increment as additional criteria. This approach may enhance diagnostic accuracy and minimize unnecessary testing, warranting further clinical validation.

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