巴塞杜氏病的发病率与丹麦全国患者登记摘录中登记诊断的验证和完整性。

IF 3.4 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Clinical Epidemiology Pub Date : 2024-10-09 eCollection Date: 2024-01-01 DOI:10.2147/CLEP.S484335
Frederik Østergaard Klit, Jakob Dal, Stine Linding Andersen, Amar Nikontovic, Peter Vestergaard, Jesper Scott Karmisholt
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引用次数: 0

摘要

目的:巴塞杜氏病(GD)是甲状腺毒症最常见的病因之一。有人建议在丹麦全国患者登记册(DNPR)中使用《国际疾病分类》(ICD-10)第 10 次修订版中的 GD 专用代码 E05.0 来识别 GD 病例。我们旨在报告 GD 的发病率,并以奥尔堡大学医院(AaUH)为单一中心样本,调查 E05.0 登记的有效性和完整性:研究包括2020年至2022年的登记数据。研究人群(n=2,893)包括奥尔堡大学医院集水区(n=244,872)内抗促甲状腺激素受体抗体(TRAb)阳性或在奥尔堡大学医院内分泌科登记有甲状腺疾病相关ICD-10代码E03.0-E07.9、O99.2或O90.5的所有人群(15-99岁)。为了识别偶发病例,所有在2020年首次发病的受试者(n=2339)均被排除在外。事件受试者被分为全科医生组(n=63)或医院护理组(n=491),并通过生化检验和甲状腺成像进行广东验证。通过阳性预测值(PPV)和阴性预测值(NPV)对有效性进行评估,并根据仅在医院护理组和总体组(合并组)中验证的 GD 受试者总数估算 E05.0 登记的完整性:结果:共发现 131 名 GD 患者,发病率为 26.8/100,000/年。E05.0识别GD病例的PPV为90% [95% CI: 81;96],NPV为90% [95% CI: 85;93]。据估计,医院护理的完整率为 73% [95% CI:63;82],总体完整率为 50-60% [95% CI:41;68]:我们报告的 GD 发病率与丹麦之前的研究结果相似。尽管 PPV 很高,但由于完整性较低,E05.0 无法在 DNPR 中充分识别 GD 病例。研究人员应依靠生化检验结果来识别 GD 病例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Incidence of Graves' Disease with Validation and Completeness of the Diagnosis for Registry Extracts in the Danish National Patient Register.

Purpose: Graves' disease (GD) is one of the most common causes of thyrotoxicosis. It has been proposed to identify incident GD by using the GD-specific code, E05.0, of the 10th revision of the International Classification of Disease (ICD-10) in the Danish National Patient Register (DNPR). We aimed to report the incidence of GD and to investigate the validity and completeness of E05.0 registration using Aalborg University Hospital (AaUH) as a single centre-sample.

Patients and methods: The study included registry data from 2020 to 2022. The study population (n=2,893) comprised all people (15-99 years) in the catchment area of AaUH (n=244,872) with either positive anti-thyroid stimulating hormone receptor antibodies (TRAb), or registered with a thyroid disease related ICD-10 code E03.0-E07.9, O99.2 or O90.5 at the Department of Endocrinology, AaUH. To identify incident cases, all subjects occurring for the first time in 2020 were excluded (n=2,339). The incident subjects were categorized into a general practice (n=63) or hospital care group (n=491) and underwent GD verification by biochemical tests and thyroid imaging. Validity was evaluated by positive (PPV) and negative (NPV) predictive values and completeness of E05.0 registration was estimated to the total number of verified GD subjects in hospital care only and in overall (groups combined).

Results: One hundred thirty-one incident GD subjects were identified corresponding to an incidence of 26.8 per 100,000/year. E05.0 had a PPV of 90% [95% CI: 81;96] and a NPV of 90% [95% CI: 85;93] to identify incident cases of GD. Completeness was estimated to be 73% [95% CI: 63;82] in hospital care and 50-60% [95% CI: 41;68] in overall.

Conclusion: We report on a similar incidence of GD as previous studies in Denmark. Despite a high PPV, incident cases of GD could not adequately be identified by E05.0 in DNPR due to low completeness. Researchers should rely on biochemical test results to identify incident GD.

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来源期刊
Clinical Epidemiology
Clinical Epidemiology Medicine-Epidemiology
CiteScore
6.30
自引率
5.10%
发文量
169
审稿时长
16 weeks
期刊介绍: Clinical Epidemiology is an international, peer reviewed, open access journal. Clinical Epidemiology focuses on the application of epidemiological principles and questions relating to patients and clinical care in terms of prevention, diagnosis, prognosis, and treatment. Clinical Epidemiology welcomes papers covering these topics in form of original research and systematic reviews. Clinical Epidemiology has a special interest in international electronic medical patient records and other routine health care data, especially as applied to safety of medical interventions, clinical utility of diagnostic procedures, understanding short- and long-term clinical course of diseases, clinical epidemiological and biostatistical methods, and systematic reviews. When considering submission of a paper utilizing publicly-available data, authors should ensure that such studies add significantly to the body of knowledge and that they use appropriate validated methods for identifying health outcomes. The journal has launched special series describing existing data sources for clinical epidemiology, international health care systems and validation studies of algorithms based on databases and registries.
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