Functional Data Analysis and Clustering of Haematological Parameters in SARS-CoV-2 Patients

This study aims to evaluate haematological parameters of patients who have contracted the COVID-19 infection. In particular, we considered patients who were already hospitalised at the time of nasopharyngeal swab (NF) testing, and patients at the Emergency Department and/or who required hospitalisation following a positive result from the NF swab. The collected data are defined as longitudinal data (i.e. constituted by measurements accumulated sequentially over time), mainly characterised by observation times that are irregular, different for each patient, and distributed non-uniformly across the observation interval. In light of these considerations, we exploit CONNECTOR, a data-driven framework designed for longitudinal data, which returns a grouping of the curves of the haemochromocytometric parameters, based on a functional clustering algorithm. These clusters are analysed in terms of disease outcome and survival, finding a good correlation to mortality rates. Finally, the CONNECTOR clusters are exploited to stratify the patients based on profiles of the haemochromocytometric parameters evolution over time, showing that comorbidities appear to have an impact on mortality independently of the outcome of the monitoring carried out through the laboratory tests considered.