Validation and proposal of case definitions for identifying patients with myasthenia gravis.

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
ACS Applied Bio Materials Pub Date : 2024-11-01 Epub Date: 2024-10-21 DOI:10.1080/03007995.2024.2416984
Bit Na Lee, Kyoungsu Kim, Ha Young Shin, Hyung Jun Park, Seungjin Baek, Namki Hong, Seung Woo Kim
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引用次数: 0

Abstract

Background and purpose: Public medical insurance data are increasingly used to study myasthenia gravis (MG); however, a validated case definition is lacking. We assessed the clinical characteristics of patients identified according to previously used case definitions.

Methods: Patients with diagnosis code G70.0 (myasthenia gravis) who visited Severance Hospital between January 2019 and December 2020 were retrospectively analyzed. Three case definitions used in previous epidemiologic studies were applied to the included patients, and their performance was evaluated based on sensitivity, specificity, and positive predictive value (PPV).

Results: A total of 843 patients with diagnosis code G70.0 were identified, and 796 (96.7%) met the clinical diagnostic criteria for MG. All three previously-used case definitions showed a PPV of >98% in identifying clinically diagnosed MG, with sensitivities ranging from 68.7 to 71.1%. Case definition #1 was unable to identify 230 patients with MG: 42.6% were in remission, 23.5% were lost to follow-up, and 25.2% were receiving prescriptions elsewhere. A similar pattern was observed for definitions #2 and #3: Patients with thymoma-associated MG who were followed-up by thoracic surgeons were frequently missed based on the previously used case definitions. A proposed case definition that additionally includes a history of thymoma enhanced the sensitivity to 77.9%, while maintaining a PPV of 99.4%.

Conclusion: The previously used case definitions showed a high PPV but were unable to identify patients in remission or followed-up elsewhere. These limitations can be overcome by utilizing a new case definition and expanding the study duration.

验证并提出用于识别重症肌无力患者的病例定义。
背景和目的:越来越多的公共医疗保险数据被用于研究重症肌无力(MG);然而,目前尚缺乏有效的病例定义。我们评估了根据以前使用的病例定义确定的患者的临床特征:方法:我们对 2019 年 1 月至 2020 年 12 月期间在 Severance 医院就诊的诊断代码为 G70.0(重症肌无力)的患者进行了回顾性分析。对纳入的患者采用了以往流行病学研究中使用的三种病例定义,并根据敏感性、特异性和阳性预测值(PPV)对其性能进行了评估:结果:共发现 843 例诊断代码为 G70.0 的患者,其中 796 例(96.7%)符合 MG 的临床诊断标准。之前使用的三种病例定义在鉴别临床诊断的 MG 方面的 PPV 均大于 98%,灵敏度在 68.7% 至 71.1% 之间。病例定义 1 无法识别 230 名 MG 患者:42.6% 处于缓解期,23.5% 失去随访,25.2% 在其他地方接受处方治疗。定义2和定义3也有类似情况:根据之前使用的病例定义,胸外科医生随访的胸腺瘤相关MG患者经常被漏诊。提议的病例定义中增加了胸腺瘤病史,使灵敏度提高到77.9%,而PPV保持在99.4%:结论:之前使用的病例定义显示出较高的 PPV,但无法识别病情缓解或在其他地方接受随访的患者。通过使用新的病例定义和延长研究时间,可以克服这些局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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