{"title":"Clinical characteristics of adrenal crisis in 371 adult patients with glucocorticoid-induced adrenal insufficiency.","authors":"Ying Qiu, Ying Luo, Xinqian Geng, Yujian Li, Yunhua Feng, Ying Yang","doi":"10.3389/fendo.2024.1510433","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Glucocorticoid-induced adrenal insufficiency (GIAI) is a hypothalamic-pituitary-adrenal (HPA) axis dysfunction caused by long-term use of exogenous steroids. Adrenal crisis (AC) is an acute complication of GIAI and one of the reasons for the increased risk of death. This study aims to analyze the clinical characteristics of GIAI patients with AC and explore the related risk factors.</p><p><strong>Methods: </strong>Clinical data of adult GIAI patients treated at our hospital between January 1, 2014, and December 31, 2023 were included. The demographic characteristics, clinical characteristics, laboratory tests and comorbidities of the patients were collected. Univariate and multivariate regression analyses were used to explore the variables related to the occurrence of AC, and prediction models were constructed.</p><p><strong>Results: </strong>51 patients (13.75%) developed AC during hospitalization. Mortality was significantly higher in patients with AC than in those without AC. Multivariate logistic regression analysis showed that infection, psychiatric symptoms, serum sodium, albumin, neutrophil-lymphocyte ratio (NLR) and eosinophil-lymphocyte ratio (ELR) were independent risk factors for AC. Among the prediction models constructed by machine learning algorithms, logistic regression model had the best prediction effect.</p><p><strong>Conclusion: </strong>This study investigated the clinical characteristics of AC in GIAI patients. NLR and ELR may be effective predictors of AC in GIAI patients, and combined with other clinically significant indicators, an effective prediction model was constructed. Logistic regression model had the best performance in predicting AC in GIAI patients.</p>","PeriodicalId":12447,"journal":{"name":"Frontiers in Endocrinology","volume":"15 ","pages":"1510433"},"PeriodicalIF":3.9000,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11685088/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Endocrinology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fendo.2024.1510433","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Glucocorticoid-induced adrenal insufficiency (GIAI) is a hypothalamic-pituitary-adrenal (HPA) axis dysfunction caused by long-term use of exogenous steroids. Adrenal crisis (AC) is an acute complication of GIAI and one of the reasons for the increased risk of death. This study aims to analyze the clinical characteristics of GIAI patients with AC and explore the related risk factors.
Methods: Clinical data of adult GIAI patients treated at our hospital between January 1, 2014, and December 31, 2023 were included. The demographic characteristics, clinical characteristics, laboratory tests and comorbidities of the patients were collected. Univariate and multivariate regression analyses were used to explore the variables related to the occurrence of AC, and prediction models were constructed.
Results: 51 patients (13.75%) developed AC during hospitalization. Mortality was significantly higher in patients with AC than in those without AC. Multivariate logistic regression analysis showed that infection, psychiatric symptoms, serum sodium, albumin, neutrophil-lymphocyte ratio (NLR) and eosinophil-lymphocyte ratio (ELR) were independent risk factors for AC. Among the prediction models constructed by machine learning algorithms, logistic regression model had the best prediction effect.
Conclusion: This study investigated the clinical characteristics of AC in GIAI patients. NLR and ELR may be effective predictors of AC in GIAI patients, and combined with other clinically significant indicators, an effective prediction model was constructed. Logistic regression model had the best performance in predicting AC in GIAI patients.
期刊介绍:
Frontiers in Endocrinology is a field journal of the "Frontiers in" journal series.
In today’s world, endocrinology is becoming increasingly important as it underlies many of the challenges societies face - from obesity and diabetes to reproduction, population control and aging. Endocrinology covers a broad field from basic molecular and cellular communication through to clinical care and some of the most crucial public health issues. The journal, thus, welcomes outstanding contributions in any domain of endocrinology.
Frontiers in Endocrinology publishes articles on the most outstanding discoveries across a wide research spectrum of Endocrinology. The mission of Frontiers in Endocrinology is to bring all relevant Endocrinology areas together on a single platform.