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复杂网络方法用于研究未破裂的内动脉瘤患者的并发症

Juri Kivelev¹, Ilkka Saarenpää², Antti Karlsson³

¹Department of Neurosurgery, Turku University Hospital, Turku, Finland. j.v.kivelev@gmail.com.

Scientific reports

|April 22, 2024

概括

复杂的网络分析揭示了与未破裂的内动脉瘤相关的关键并发症. 这项研究强调吸烟,高血压和情绪障碍是动脉瘤患者的重要相关疾病.

科学领域:

医疗信息学医学信息学
网络科学网络科学
流行病学流行病学

背景情况:

复杂网络分析是了解疾病关系的新兴工具.
它在未破裂的内动脉瘤 (UIAs) 中的应用仍然在很大程度上未被探索.
了解UIA并发症可以为患者管理和风险分层提供信息.

研究的目的:

评估复杂网络分析在被诊断为未破裂的内动脉瘤的患者中的适用性.
为了确定与UIAs相关的统计验证的并发症.
探索这些协会的特定年龄和性别模式.

主要方法:

对628,831名患者 (2004-2019) 匿名数字健康记录的回顾性分析.
应用年龄队列方法与国际疾病分类 (ICD) 代码.
构建和统计验证不同年龄和性别群体的并发症网络.

主要成果:

识别了267个诊断代码,其中有统计验证的链接到UIA ICD代码.
大多数这些并发症 (76%) 在40-69岁的患者中观察到.
关键的相关疾病包括吸烟,高血压,慢性阻塞性肺病,失脂症和情绪障碍;在女性队伍中发现了不常见的联系.

结论:

复杂网络分析适用于研究UIA患者的并发症.
建立了与UIA相关的疾病的验证网络.
确定了与UIA研究和临床实践相关的特定并发症和人口统计模式.

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