Epidemiology of systemic sclerosis: a multi-database population-based study in Tuscany (Italy).
Alessio CoiSimone BarsottiMichele SantoroFabio AlmerigognaElena BargagliMarzia CaproniGiacomo EmmiBruno FredianiSerena GuiducciMarco Matucci CerinicMarta MoscaPaola ParronchiRenato PredilettoEnrico SelviGabriele SimoniniAntonio Gaetano Tavoninull nullFabrizio BianchiAnna PieriniPublished in: Orphanet journal of rare diseases (2021)
The multi-database approach is important in the investigation of rare diseases where it is often difficult to provide accurate epidemiological indicators. A population-based registry can be exploited in synergy with health databases, to provide evidence related to disease outcomes and therapies and to assess the burden of disease, relying on a large cohort of cases. Building an integrated archive of data from multiple databases linking a cohort of patients to their comorbidities, clinical outcomes and survival, is important both in terms of treatment and prevention.
Keyphrases
- systemic sclerosis
- interstitial lung disease
- big data
- end stage renal disease
- newly diagnosed
- healthcare
- public health
- ejection fraction
- high resolution
- prognostic factors
- electronic health record
- rheumatoid arthritis
- risk factors
- emergency department
- mass spectrometry
- type diabetes
- combination therapy
- health information
- weight loss
- metabolic syndrome
- deep learning
- human health
- health promotion