Background: Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disorder with a high multidimensional burden, with an obscure etiopathogenesis.
Methods: We designed a longitudinal, population-based study of people residing in Central Italy (Marche Region) who were beneficiaries of the National Health System. People with an unprecedented ALS hospitalization (335.20 ICD-9 CM) or tagged with an ALS exemption between 2014 and 2021 were considered incident cases. ALS cases residing in the region for <3 years or with an active ALS exemption or hospitalized for ALS before 2014 were excluded. We used secondary sources to identify new ALS diagnoses. The regional referral center for ALS's database was used to test the accuracy of secondary sources in detecting cases. ALS mean incidence was compared to that reported in similar studies conducted in Italy. The incidence rate trend adjusted by sex and age was evaluated using the Poisson regression model.
Results: We detected 425 new ALS cases (median age: 70y) in the 2014-2021 period, with a mean incidence of 3.5:100,000 py (95%CI: 3.2-3.8; M:F = 1.2), similar to that reported in similar studies conducted in Italy. No trend was observed during 2014-2019. After including 2020-2021 in the model, we observed a mean decrease in incidence of 5.8% (95% CI 2.0%; 9.5%, p = 0.003).
Conclusion: We show a decrease in the incidence rate of ALS in Marche, during the 2014-2021 period, as a possible outcome of a delayed neurological assessment and diagnosis during the pandemic. An ad hoc developed identification algorithm, based on healthcare utilization databases, is a valuable tool to assess the health impact of global contingencies.
Keywords: Amyotrophic lateral sclerosis; environment; neuroepidemiology.