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Endocrine Abstracts (2015) 38 P39 | DOI: 10.1530/endoabs.38.P39

Royal Gwent Hospital, Newport, UK.

Background: The short Synacthen test (SST) is frequently used to diagnose adrenal insufficiency; however the role of baseline cortisol. With the recent European shortage of synacthen, there was a pressing need to identify the best possible way to use the resource and rationalize the test. Our aim is to identify whether baseline cortisol can be safely used to rule out adrenal insufficiency in clinical practice.

Methods: All SSTs performed at the OPD, Royal Gwent Hospital over a 3 year period were identified. Cortisol was measured at baseline and 30 minutes following administration of 250 μgm of synecthan. The test was defined as a pass or fail based on a 30 min cortisol > or ≤450 nmol/l, respectively. All analyses were performed on the Abbot Architect i2000. Receiver operating Characteristic (ROC) curve was generated to determine the predictive value of the basal cortisol for a failed SST.

Results: 257 SST were performed, among them 203(79%) was declared pass and 54 (21%) were failed. Roc curve showed that despite good predictive value (area under the Curve: 0.92, 95% CI 0.88–0.96) no single value of baseline cortisol was equally sensitive and at the same time specific for failed SST. A basal cortisol <299 had 100% sensitivity but had a specificity of 55%. It also showed that, by performing SST to only those with a basal value of <299 nmol/l, 103 (40%)of the tests could be avoided. This in turn would save a total £4635 for the health service in the cost of tests alone.

Conclusion: Our findings suggest that a baseline cortisol ≧299 nmol/l (for the Abbott Architect assay) could be used to identify whether an SST is clinically necessary. Using a combination of baseline cortisol and the clinical indication, the number of tests performed can be significantly reduced without any cases of adrenal insufficiency being missed.

Volume 38

Society for Endocrinology BES 2015

Edinburgh, UK
02 Nov 2015 - 04 Nov 2015

Society for Endocrinology 

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