Damla N Costa, Yogish C Kudva, Michael D Jensen, Pankaj Shah
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During hospitalization, patients with type 1 diabetes antibodies displayed diminished serum C-peptide concentration (<i>P</i> = 0.014), correlating inversely with subsequent hemoglobin A1c% [<i>r</i> = (-0.22), <i>P</i> = 0.005]. Initial C-peptide concentrations did not differ between patients requiring insulin therapy during follow-up and those who did not (<i>P</i> = 0.16). C-peptide concentrations showed limited predictive capacity for achieving glycemic control. Subgroup analyses in NANP-DM exhibited similar limited capacity for anticipating therapeutic insulin needs and achieving glycemic controls. <b><i>Discussion:</i></b> C-peptide concentration did not exhibit a robust predictive capability for future need of insulin therapy and achieving glycemic control, limiting its utility in clinical practice within inpatient settings.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":""},"PeriodicalIF":5.7000,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Clinical Utility of Serum C-Peptide Concentration for Hospitalized Patients with Hyperglycemia.\",\"authors\":\"Damla N Costa, Yogish C Kudva, Michael D Jensen, Pankaj Shah\",\"doi\":\"10.1089/dia.2024.0246\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><b><i>Background:</i></b> Serum C-peptide concentration is often utilized for diagnostic, prognostic, or therapeutic assessment in diabetes mellitus. 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引用次数: 0
摘要
背景:血清 C 肽浓度通常用于糖尿病的诊断、预后或治疗评估。然而,有关高血糖住院期间测量的 C 肽的诊断和预测价值的临床数据却很有限:我们的研究纳入了 2017 年 1 月至 2022 年 11 月期间因急性高血糖急诊入住梅奥诊所住院设施的成人。在整个队列和非自身免疫性非胰腺炎糖尿病(NANP-DM)亚组中检测了C肽对停用治疗性胰岛素的预测能力:研究共纳入 187 名患者(63 名女性)。住院期间,1 型糖尿病抗体患者的血清 C 肽浓度降低(p=0.014),与随后的 HbA1c% 成反比 [r= (-0.22),p=0.005]。在随访期间需要胰岛素治疗和不需要胰岛素治疗的患者之间,初始 C 肽浓度没有差异(p=0.16)。C肽浓度对实现血糖控制的预测能力有限。对NANP-DM进行的分组分析显示,预测胰岛素治疗需求和实现血糖控制的能力同样有限:C肽浓度对未来胰岛素治疗需求和实现血糖控制的预测能力不强,限制了其在住院临床实践中的应用。
Clinical Utility of Serum C-Peptide Concentration for Hospitalized Patients with Hyperglycemia.
Background: Serum C-peptide concentration is often utilized for diagnostic, prognostic, or therapeutic assessment in diabetes mellitus. However, there are limited clinical data regarding diagnostic and predictive value of C-peptide measured during hospitalizations for hyperglycemia. Materials and Methods: Adults admitted to Mayo Clinic inpatient facilities due to an acute hyperglycemic emergency between January 2017 and November 2022 were included in our study. Predictive capacity of C-peptide for discontinuation of therapeutic insulin was examined in the entire cohort and the subgroup of non-autoimmune non-pancreatitis diabetes (NANP-DM). Results: We included 187 patients (63 women) in our study. During hospitalization, patients with type 1 diabetes antibodies displayed diminished serum C-peptide concentration (P = 0.014), correlating inversely with subsequent hemoglobin A1c% [r = (-0.22), P = 0.005]. Initial C-peptide concentrations did not differ between patients requiring insulin therapy during follow-up and those who did not (P = 0.16). C-peptide concentrations showed limited predictive capacity for achieving glycemic control. Subgroup analyses in NANP-DM exhibited similar limited capacity for anticipating therapeutic insulin needs and achieving glycemic controls. Discussion: C-peptide concentration did not exhibit a robust predictive capability for future need of insulin therapy and achieving glycemic control, limiting its utility in clinical practice within inpatient settings.
期刊介绍:
Diabetes Technology & Therapeutics is the only peer-reviewed journal providing healthcare professionals with information on new devices, drugs, drug delivery systems, and software for managing patients with diabetes. This leading international journal delivers practical information and comprehensive coverage of cutting-edge technologies and therapeutics in the field, and each issue highlights new pharmacological and device developments to optimize patient care.