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基于 FDA 不良事件报告系统数据库的生物信息学指导下,七氟醚相关性肾源性尿崩症的非比例性分析。

Bioinformatics-guided disproportionality analysis of sevoflurane-induced nephrogenic diabetes insipidus using the FDA Adverse Event Reporting System database.

机构信息

Department of Pharmacy Practice, Oxbridge College of Pharmacy, Bengaluru, India.

Department of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, India.

出版信息

Br J Clin Pharmacol. 2024 Aug;90(8):1804-1810. doi: 10.1111/bcp.15869. Epub 2023 Aug 24.

Abstract

AIMS

Sevoflurane is an ether-based inhalational anaesthetic that induces and maintains general anaesthesia. Our study aimed to detect sevoflurane-induced nephrogenic diabetes insipidus using data mining algorithms (DMAs) and molecular docking. The FAERS database was analysed using OpenVigil 2.1 for disproportionality analysis.

METHODS

We analysed FAERS data from 2004 to 2022 to determine the incidence of nephrogenic diabetes insipidus associated with sevoflurane. Reporting odds ratios (RORs) and proportional reporting ratios (PRRs) with 95% confidence intervals were calculated. We also used molecular docking with AutoDock Vina to examine sevoflurane's binding affinity to relevant receptors.

RESULTS

A total of 554 nephrogenic diabetes insipidus cases were reported in FAERS, of which 2.5% (14 cases) were associated with sevoflurane. Positive signals were observed for sevoflurane with ROR of 76.012 (95% CI: 44.67-129.35) and PRR of 75.72 (χ: 934.688). Of the 14 cases, 50% required hospitalization, 14% resulted in death, and the remaining cases were categorized as other outcomes. Molecular docking analysis showed that sevoflurane exhibited high binding affinity towards AQP2 (4NEF) and AVPR2 (6U1N) with docking scores of -4.9 and -5.3, respectively.

CONCLUSIONS

Sevoflurane use is significantly associated with the incidence of nephrogenic diabetes insipidus. Healthcare professionals should be cautious when using this medication and report any adverse events to regulatory agencies. Further research is needed to validate these findings and identify risk factors while performing statistical adjustments to prevent false-positives. Clinical monitoring is crucial to validate potential adverse effects of sevoflurane.

摘要

目的

七氟醚是一种醚类吸入性麻醉剂,可诱导和维持全身麻醉。我们的研究旨在使用数据挖掘算法(DMAs)和分子对接来检测七氟醚引起的肾源性尿崩症。使用 OpenVigil 2.1 对 FAERS 数据库进行了不相称性分析。

方法

我们分析了 2004 年至 2022 年 FAERS 数据,以确定与七氟醚相关的肾源性尿崩症的发生率。计算了报告比值比(ROR)和比例报告比值(PRR)及其 95%置信区间。我们还使用 AutoDock Vina 进行分子对接,以检查七氟醚与相关受体的结合亲和力。

结果

FAERS 共报告了 554 例肾源性尿崩症病例,其中 2.5%(14 例)与七氟醚有关。七氟醚的阳性信号为 ROR 76.012(95%CI:44.67-129.35)和 PRR 75.72(χ:934.688)。在这 14 例病例中,有 50%需要住院治疗,14%导致死亡,其余病例归类为其他结果。分子对接分析表明,七氟醚对 AQP2(4NEF)和 AVPR2(6U1N)具有高结合亲和力,对接评分分别为-4.9 和-5.3。

结论

七氟醚的使用与肾源性尿崩症的发生率显著相关。医护人员在使用这种药物时应谨慎,并向监管机构报告任何不良事件。需要进一步研究来验证这些发现,并在进行统计调整以防止假阳性时确定风险因素。临床监测对于验证七氟醚的潜在不良反应至关重要。

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