371例成人糖皮质激素致肾上腺功能不全患者肾上腺危象的临床特点。

IF 3.9 2区 医学 Q2 ENDOCRINOLOGY & METABOLISM Frontiers in Endocrinology Pub Date : 2024-12-17 eCollection Date: 2024-01-01 DOI:10.3389/fendo.2024.1510433
Ying Qiu, Ying Luo, Xinqian Geng, Yujian Li, Yunhua Feng, Ying Yang
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引用次数: 0

摘要

背景:糖皮质激素诱导的肾上腺功能不全(GIAI)是长期使用外源性类固醇引起的下丘脑-垂体-肾上腺(HPA)轴功能障碍。肾上腺危机(AC)是GIAI的急性并发症,也是导致死亡风险增加的原因之一。本研究旨在分析GIAI患者合并AC的临床特点,探讨相关危险因素。方法:收集2014年1月1日至2023年12月31日在我院治疗的成人GIAI患者的临床资料。收集患者的人口学特征、临床特征、实验室检查和合并症。采用单因素和多因素回归分析探讨与AC发生相关的变量,并建立预测模型。结果:51例(13.75%)患者在住院期间发生AC。多因素logistic回归分析显示,感染、精神症状、血清钠、白蛋白、中性粒细胞-淋巴细胞比(NLR)和嗜酸性粒细胞-淋巴细胞比(ELR)是AC的独立危险因素。在机器学习算法构建的预测模型中,logistic回归模型的预测效果最好。结论:本研究探讨了GIAI患者AC的临床特点。NLR和ELR可能是GIAI患者AC的有效预测指标,并结合其他具有临床意义的指标,构建了有效的预测模型。Logistic回归模型预测GIAI患者AC的效果最好。
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Clinical characteristics of adrenal crisis in 371 adult patients with glucocorticoid-induced adrenal insufficiency.

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.

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来源期刊
Frontiers in Endocrinology
Frontiers in Endocrinology Medicine-Endocrinology, Diabetes and Metabolism
CiteScore
5.70
自引率
9.60%
发文量
3023
审稿时长
14 weeks
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.
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