NEuroMuscular Omnicentre (NEMO), Fondazione Serena Onlus, Piazza Ospedale Maggiore 3, 20162, Milano, Italy.
Neurorehabilitation Unit, University of Milan, Via Festa del Perdono 7, 20122, Milano, Italy.
Neurol Sci. 2023 Jun;44(6):2149-2157. doi: 10.1007/s10072-023-06631-0. Epub 2023 Jan 25.
Myotonic dystrophy type 1 is a slowly progressive, multisystem, autosomal dominant disorder, in which the impairments of respiratory systems represent one of the main causes of death.
The aim of our study is to develop prediction models to identify the most appropriate test(s) providing indication for NIV.
DM1 patients attending the NEMO Clinical Center (Milan) between January 2008 and July 2020, who had been subjected to a complete battery of respiratory tests, were retrospectively recruited. Demographic, clinical, and anthropometric characteristics were collected, as well as arterial blood gas (ABG) analysis, spirometry, respiratory muscle strength, cough efficacy, and nocturnal oximetry as respiratory assessments. Patients were stratified in those requiring NIV and those with normal respiratory function.
Out of 151 DM1 patients (median age: 44 years [35.00-53.00]; male/female ratio: 0.80 (67/84)), 76 had an indication for NIV initiation (50.33%). ABG, spirometry, and nocturnal oximetry prediction models resulted in an excellent discriminatory ability in distinguishing patients who needed NIV from those who did not (AUC of 0.818, 0.808, and 0.935, respectively). An easy-to-use calculator was developed to automatically determine a score of NIV necessity based on the prediction equations generated from each aforementioned prediction model.
The proposed prediction models may help to identify which patients are at a higher risk of requiring ventilator support and therefore help in defining individual management plans and criteria for specific interventions early in the disease course.
1 型肌强直性营养不良是一种进展缓慢的多系统常染色体显性疾病,呼吸系统的损害是导致死亡的主要原因之一。
我们的研究旨在开发预测模型,以确定最适合提供 NIV 指征的测试。
回顾性招募了 2008 年 1 月至 2020 年 7 月期间在 NEMO 临床中心(米兰)就诊的 1 型肌强直性营养不良患者,他们接受了全面的呼吸系统检查。收集了人口统计学、临床和人体测量学特征,以及动脉血气(ABG)分析、肺量测定、呼吸肌力量、咳嗽效果和夜间血氧饱和度作为呼吸评估。将患者分为需要 NIV 和呼吸功能正常的两组。
在 151 例 1 型肌强直性营养不良患者中(中位数年龄:44 岁[35.00-53.00];男女比例:0.80(67/84)),76 例患者有启动 NIV 的指征(50.33%)。ABG、肺量测定和夜间血氧饱和度预测模型在区分需要 NIV 和不需要 NIV 的患者方面具有出色的区分能力(AUC 分别为 0.818、0.808 和 0.935)。开发了一个易于使用的计算器,可根据每个上述预测模型生成的预测方程自动确定 NIV 必要性评分。
提出的预测模型可以帮助确定哪些患者需要呼吸机支持的风险更高,从而有助于在疾病早期制定个体管理计划和特定干预措施的标准。