SummaryPeri‐operative SARS‐CoV‐2 infection increases postoperative mortality. The aim of this stu... more SummaryPeri‐operative SARS‐CoV‐2 infection increases postoperative mortality. The aim of this study was to determine the optimal duration of planned delay before surgery in patients who have had SARS‐CoV‐2 infection. This international, multicentre, prospective cohort study included patients undergoing elective or emergency surgery during October 2020. Surgical patients with pre‐operative SARS‐CoV‐2 infection were compared with those without previous SARS‐CoV‐2 infection. The primary outcome measure was 30‐day postoperative mortality. Logistic regression models were used to calculate adjusted 30‐day mortality rates stratified by time from diagnosis of SARS‐CoV‐2 infection to surgery. Among 140,231 patients (116 countries), 3127 patients (2.2%) had a pre‐operative SARS‐CoV‐2 diagnosis. Adjusted 30‐day mortality in patients without SARS‐CoV‐2 infection was 1.5% (95%CI 1.4–1.5). In patients with a pre‐operative SARS‐CoV‐2 diagnosis, mortality was increased in patients having surgery wi...
Multiple sclerosis (MS) is the main cause of chronic disability in young people during their most... more Multiple sclerosis (MS) is the main cause of chronic disability in young people during their most productive years of life and therefore carries a high social and economic burden. The present study aimed to: (1) verify the capacity of an administrative data source to furnish data for constructing a model able to detect the occurrence of clinical relapses in MS patients and (2) validate the constructed theoretical model on a set of real-world data. Two MS experts identified some administrative variables as proxies of clinical relapses. Thereafter, the two MS experts analysed 889 events in 100 MS patients, considering only the administrative data relating to these patients, while a third neurologist independently analysed the real-world data (documented medical history) of the same patients in the same period. Absolute concordance between the theoretical model and the real-world data was found in 86 % of the events. The model we propose is easily and rapidly applicable, requiring the collection of just a few variables that are already present in local health authority administrative databases in Italy. It can be used to estimate, with a good level of reliability, the occurrence of relapses in various settings. Moreover, the model is also exportable to different and larger MS cohorts and could be useful for healthcare planning and for evaluating the efficacy of drugs in the real-world, thus favouring better resource allocation and management.
SummaryPeri‐operative SARS‐CoV‐2 infection increases postoperative mortality. The aim of this stu... more SummaryPeri‐operative SARS‐CoV‐2 infection increases postoperative mortality. The aim of this study was to determine the optimal duration of planned delay before surgery in patients who have had SARS‐CoV‐2 infection. This international, multicentre, prospective cohort study included patients undergoing elective or emergency surgery during October 2020. Surgical patients with pre‐operative SARS‐CoV‐2 infection were compared with those without previous SARS‐CoV‐2 infection. The primary outcome measure was 30‐day postoperative mortality. Logistic regression models were used to calculate adjusted 30‐day mortality rates stratified by time from diagnosis of SARS‐CoV‐2 infection to surgery. Among 140,231 patients (116 countries), 3127 patients (2.2%) had a pre‐operative SARS‐CoV‐2 diagnosis. Adjusted 30‐day mortality in patients without SARS‐CoV‐2 infection was 1.5% (95%CI 1.4–1.5). In patients with a pre‐operative SARS‐CoV‐2 diagnosis, mortality was increased in patients having surgery wi...
Multiple sclerosis (MS) is the main cause of chronic disability in young people during their most... more Multiple sclerosis (MS) is the main cause of chronic disability in young people during their most productive years of life and therefore carries a high social and economic burden. The present study aimed to: (1) verify the capacity of an administrative data source to furnish data for constructing a model able to detect the occurrence of clinical relapses in MS patients and (2) validate the constructed theoretical model on a set of real-world data. Two MS experts identified some administrative variables as proxies of clinical relapses. Thereafter, the two MS experts analysed 889 events in 100 MS patients, considering only the administrative data relating to these patients, while a third neurologist independently analysed the real-world data (documented medical history) of the same patients in the same period. Absolute concordance between the theoretical model and the real-world data was found in 86 % of the events. The model we propose is easily and rapidly applicable, requiring the collection of just a few variables that are already present in local health authority administrative databases in Italy. It can be used to estimate, with a good level of reliability, the occurrence of relapses in various settings. Moreover, the model is also exportable to different and larger MS cohorts and could be useful for healthcare planning and for evaluating the efficacy of drugs in the real-world, thus favouring better resource allocation and management.
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Papers by Antonio Nava