Adrenal insufficiency in sickle cell disease: A Case series of a potentially underrecognized complication
Bibliographic record
Abstract
Abstract Introduction: Endocrinopathies, including adrenal insufficiency (AI), are recognized complications that can occur in sickle cell disease (SCD). The exact prevalence of adrenal insufficiency (AI) in SCD is not known. However, there is a growing body of literature suggesting the prevalence of AI is higher in SCD compared to the general population. The proposed pathophysiology of AI in SCD is multifactorial, involving oxidative stress and siderosis from iron overload, vaso-occlusive ischemia, hemorrhagic and thromboembolic complications, and chronic opioid use. Due to the often insidious and non-specific presentation of AI, it is potentially underdiagnosed in SCD, which has implications for delayed treatment and increased risk of adrenal crises. Currently, there is no clear consensus on the strategy for regular screening or the ideal methodology for diagnosing AI. In this case series, we aim to describe the clinical features, diagnosis, management, and outcomes of 5 patients with SCD suspected to have AI. Methods: A retrospective chart review was conducted on patients with sickle cell disease admitted to our tertiary care center between 2018 and 2025 who were suspected to have AI. The identified patients underwent an initial screening test as well as further workup and management for AI during their admission. Results: The 5 identified patients were female, between the ages of 19 and 32. Three patients had HbSS and 2 had HbSD phenotypes. Reasons for admission included sickle cell crisis, syncope, or vomiting and diarrhea. The most common AI-related presenting symptom was uncontrolled nausea and vomiting, followed by presyncope or syncope. Morning cortisol levels were used as the initial screening test for 4 patients, all of whom were found to have hypocortisolism. One additional patient did not undergo morning cortisol screening and only had adrenocorticotropic hormone (ACTH) stimulation testing. All five patients had confirmatory ACTH stimulation tests, which subsequently confirmed AI in 3 patients and ruled out AI in 2 patients. The 3 patients with confirmed AI were started on glucocorticoid therapy with improvement in their AI-related symptoms, and were continued on glucocorticoid therapy following discharge. The time from symptom onset to initiation of glucocorticoid therapy was available for 2 patients, with an average of 6 days. While 2 patients were presumed to have secondary AI, workup in 1 patient was consistent with primary AI. Therefore, fludrocortisone was initiated in this patient in addition to glucocorticoids. Common characteristics shared among the 3 patients included various complications related to SCD. All 3 patients had severe disease requiring regular red cell exchanges, 2 had chronic opioid use, 2 had a history of venous thromboembolism, and 1 had iron overload requiring chelation therapy. Conclusions: Our case series suggests that a high index of suspicion for AI should be maintained in patients with SCD who present with symptoms such as nausea, vomiting, and presyncope. While morning cortisol was a sensitive initial screening test, follow-up ACTH stimulation testing should be considered given the implications of initiating prolonged steroid therapy, especially as AI was ruled out in two patients with an initial positive screen. Severe disease requiring regular red cell exchanges, chronic opioid use, and iron overload, may represent potential risk factors for the development of AI, suggesting that patients with these complications may benefit from targeted or regular screening. These cases underscore the need for further investigation into the prevalence, risk factors, and approach to the evaluation of AI in SCD to better inform screening and diagnostic guidelines.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".