Deaths in SARS-Cov-2 Positive Patients in Italy: The Influence of Underlying Health Conditions on Lethality.
Giovanna DeianaAntonio AzaraMarco DettoriFiorenzo DeloguGavino VargiuIsabella GessaFilippo StroscioMarcello TidoreGiorgio SteriPaolo CastigliaPublished in: International journal of environmental research and public health (2020)
This study aims to underline the clinical characteristics of patients who died after testing positive for SARS-CoV-2 infection in one region of Italian and to evaluate the influence of underlying health conditions on the fatal outcome. A matched case-control study was designed by analyzing the data regarding positive subjects observed up to April 21, 2020. The case fatality rate was 7.9%, with a higher proportion of deaths in men than women. The specific standardized mortality ratio was 0.15-0.13 for males and 0.2 for females, showing that mortality is much lower than expected. Cardiovascular diseases, chronic lung diseases and diabetes mellitus showed a significant association with the outcome. Although the case fatality rate in Sardinia in regard to age and gender patterns seems to be similar to that for Italy as a whole, its quantitative value was far lower than the national one and possible explanations might include the genetic characteristics of the Sardinian population or the immediate closure of its borders as soon as the epidemic started. Our results highlighted that lethality is strongly dependent on the presence of multiple concomitant serious diseases. It is important to have epidemiological strategies for effective guidance on public health actions in order to improve chances of survival.
Keyphrases
- public health
- sars cov
- healthcare
- mental health
- end stage renal disease
- cardiovascular disease
- cardiovascular events
- respiratory syndrome coronavirus
- ejection fraction
- chronic kidney disease
- risk factors
- prognostic factors
- health information
- peritoneal dialysis
- high resolution
- polycystic ovary syndrome
- electronic health record
- global health
- metabolic syndrome
- middle aged
- quality improvement
- pregnant women
- adipose tissue
- climate change
- cardiovascular risk factors
- machine learning
- patient reported