Maggi Lorenzo, Vita Gianluca, Marconi Ettore, Taddeo Daiana, Davì Michele, Lovato Valeria, Cricelli Claudio, Lapi Francesco
Neuroimmunology and Neuromuscular Disease Unit, IRCCS Foundation Carlo Besta Neurological Institute, Milano, Italy.
Unit of Neurology, IRCCS Centro Neurolesi Bonino-Pulejo P.O. Piemonte, Messina, Italy.
Fam Pract. 2023 Mar 28;40(2):308-313. doi: 10.1093/fampra/cmac091.
Spinal muscular atrophy (SMA) is a rare genetic disease with a broad spectrum of severity. Although an early diagnosis of SMA is crucial to allow proper management of patients, the diagnostic delay is still an issue. Therefore, this study aimed to investigate the clinical correlates of SMA among primary care patients.
The Health Search Database (HSD) was adopted. To estimate the prevalence and incidence rate of SMA, a cohort study was conducted on the population (aged ≥6 years) being registered in HSD from 1 January 2000 up to 31 December 2019. To investigate the clinical correlates of SMA, a nested case-control study was performed. SMA cases have been classified according to a clinically based iterative process as "certain", "probable" or "possible". To test the association between clinical correlates and SMA cases a multivariate conditional logistic regression model was estimated.
The SMA prevalence combining "certain", "probable" and "possible" cases was 5.1 per 100,000 in 2019 (i.e. 1.12 per 100,000 when limited to "certain" cases), while the yearly incidence rate ranged from 0.12 to 0.56 cases per 100,000. Comparing "certain" cases with matched controls, the presence of neurology visits (OR = 6.5; 95% CI: 1.6-25.6) and prescription of electromyography (OR = 4.6; 95% CI: 1.1-18.7) were associated with higher odds of SMA diagnosis.
Our findings suggest that primary care databases may be used to enhance the early identification of SMA. Additional efforts are needed to exploit the electronic health records of general practitioners to allow early recognition of SMA.
脊髓性肌萎缩症（SMA）是一种严重程度范围广泛的罕见遗传病。尽管SMA的早期诊断对于患者的妥善管理至关重要，但诊断延迟仍是一个问题。因此，本研究旨在调查基层医疗患者中SMA的临床相关因素。
采用健康搜索数据库（HSD）。为了估计SMA的患病率和发病率，对2000年1月1日至2019年12月31日在HSD登记的≥6岁人群进行了队列研究。为了调查SMA的临床相关因素，进行了一项巢式病例对照研究。SMA病例已根据基于临床的迭代过程分为“确定”、“可能”或“疑似”。为了检验临床相关因素与SMA病例之间的关联，估计了多变量条件逻辑回归模型。
2019年，“确定”、“可能”和“疑似”病例合并的SMA患病率为每10万人5.1例（即仅限于“确定”病例时为每10万人1.12例），而年发病率为每10万人0.12至0.56例。将“确定”病例与匹配的对照进行比较，神经科就诊（比值比=6.5；95%置信区间：1.6-25.6）和肌电图检查处方（比值比=4.6；95%置信区间：1.1-18.7）与SMA诊断的较高几率相关。
我们的研究结果表明，基层医疗数据库可用于加强SMA的早期识别。需要做出更多努力来利用全科医生的电子健康记录，以便早期识别SMA。
