Predictors of 30-Day Readmissions for Adrenal Insufficiency

A Retrospective National Database Study

Asim Kichloo; Zain El-amir; Hafeez Shaka; Farah Wani; Sofia Junaid Syed


Clin Endocrinol. 2021;95(2):269-276. 

In This Article

Abstract and Introduction


Objective: The aim of this study was to describe rates and characteristics of non-elective 30-day readmission among patients hospitalized for adrenal insufficiency and to assess predictors of readmission.

Design: We analysed the 2018 National Readmission Database. Adrenal insufficiency hospitalizations were identified using the International Classification of Diseases, Tenth Revisions, Clinical Modification diagnosis codes for principal diagnostic codes of primary adrenal insufficiency, Addisonian crisis, drug-induced adrenocortical insufficiency, and other and unspecified adrenocortical insufficiency.

Patients During the study period, 7738 index hospitalizations were identified as patients with AI who met the inclusion criteria. Of these, 7691 were discharged alive.

Measurements: We utilized chi-squared tests to compare baseline characteristics between readmissions and index hospitalizations. Multivariate Cox regression was used to identify independent predictors of readmission.

Results: The 30-day all-cause readmission rate for AI was 17.3%. About 1 in 5 readmissions was for AI. Other reasons for readmission included sepsis (10.8%), unspecified pneumonia (3.1%) and acute renal failure unspecified (1.6%). Readmission was associated with significantly higher odds of inpatient mortality. Independent predictors of 30-day all-cause readmissions included index hospitalizations with the Charlson Comorbidity Index (CCI) ≥3 (adjusted hazards ratio (aHR): 2.53, 95% CI: 1.85–3.46, p < .001), protein-energy malnutrition (aHR: 1.28, 95% CI: 1.02–1.60, p = .035) and obesity (aHR: 1.26, 95% CI: 1.02–1.56, p = .035).

Conclusions: The 30-day all-cause readmission rate was 17.3%. AI was the most common reason for readmission among other causes. Readmissions were associated with increased mortality. CCIs of 3 or more, protein-energy malnutrition and obesity were significant predictors of readmission.


Adrenal insufficiency (AI) is defined as the clinical manifestation of absence or deficiency in the production of glucocorticoids.[1] AI can be further classified as either primary or central insufficiency.[2,3] Primary AI is characterized by deficient steroid production in the adrenal cortex, whereas central AI is deficiency secondary to disorders in the hypothalamic-pituitary-adrenal (HPA) axis.[2] Clinically, it is characterized by several cardinal symptoms including anorexia, orthostatic hypotension, salt craving, weakness, fatigue and hyperpigmentation of the skin specifically in primary adrenal insufficiency.[1] If left untreated, most patients with adrenal insufficiency die within 2 years of their diagnosis, underscoring the potential deadliness of AI.[4] Moreover, recent studies have reported increases in standardized mortality in primary AI patients and a reduced life expectancy of up to 11 years, which has been largely attributed to infection and cardiovascular diseases in patients with AI.[4]

Because of its relative rarity, AI hospitalizations have been difficult to study.[4] Previous research has examined patient characteristics, comorbidities and hospitalizations in AI patients. One cohort database study found that patients with AI had higher rates of comorbidities and inpatient admissions than matched 1:1 controls, which were selected from the general population in the same insurance database using the greedy algorithm based on age, region, gender and insurance type.[4] Additionally, research has been published about patient-oriented healthcare outcomes in hospitalized patients and found that AI was associated with longer hospital stay, higher rates of ICU admissions and higher rates of hospital readmission.[5] Despite the known increased rate of readmissions in AI patients, there is a paucity of objective data characterizing readmission hospitalizations, rates of readmission and most importantly the predictors for readmission. This study aimed to contribute to existing literature on AI hospitalizations by evaluating rates of 30-day non-elective readmissions in patients with a diagnosis of AI, differences in readmissions versus index admissions or admissions with a principal diagnosis of AI, and assessing risks of readmission.