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Testa A, Biondi-Zoccai G, Anticoli S, Pezzella FR, Mangiardi M, DI Giosa A, Marchegiani G, Frati G, Sciarretta S, Perrotta A, Peruzzi M, Cavarretta E, Gaspardone A, Mariano E, Federici M, Montone RA, Dei Giudici A, Versaci B, Versaci F. Cluster analysis of weather and pollution features and its role in predicting acute cardiac or cerebrovascular events. Minerva Med 2022; 113:825-832. [PMID: 35156790 DOI: 10.23736/s0026-4806.22.08036-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
BACKGROUND Despite mounting evidence, the impact of the interplay between weather and pollution features on the risk of acute cardiac and cerebrovascular events has not been entirely appraised. The aim of this study was to perform a comprehensive cluster analysis of weather and pollution features in a large metropolitan area, and their association with acute cardiac and cerebrovascular events. METHODS Anonymized data on acute myocardial infarction (AMI) and acute cerebrovascular events were obtained from 3 tertiary care centers from a single large metropolitan area. Weather and pollution data were obtained averaging measurements from several city measurement stations managed by the competent regional agency for enviromental protection, and from the Metereological Center of Italian Military Aviation. Unsupervised machine learning was performed with hierarchical clustering to identify specific days with distinct weather and pollution features. Clusters were then compared for rates of acute cardiac and cerebrovascular events with Poisson models. RESULTS As expected, significant pairwise correlations were found between weather and pollution features. Building upon these correlations, hierarchical clustering, from a total of 1169 days, generated 4 separate clusters: mostly winter days with low temperatures and high ozone concentrations (cluster 1, N.=60, 5.1%), days with moderately high temperatures and low pollutants concentrations (cluster 2, N.=419, 35.8%), mostly summer and spring days with high temperatures and high ozone concentrations (cluster 3, N.=673, 57.6%), and mostly winter days with low temperatures and low ozone concentrations (cluster 4, N.=17, 1.5%). Overall cluster-wise comparisons showed significant differences in adverse cardiac and cerebrovascular events (P<0.001), as well as in cerebrovascular events (P<0.001) and strokes (P=0.001). Between-cluster comparisons showed that cluster 1 was associated with an increased risk of any event, cerebrovascular events, and strokes in comparison to cluster 2, cluster 3 and cluster 4 (all P<0.05), as well as AMI in comparison to cluster 3 (P=0.047). In addition, cluster 2 was associated with a higher risk of strokes in comparison to cluster 4 (P=0.030). Analysis adjusting for season confirmed the increased risk of any event, cerebrovascular events and strokes for cluster 1 and cluster 2. CONCLUSIONS Unsupervised machine learning can be leveraged to identify specific days with a unique clustering of adverse weather and pollution features which are associated with an increased risk of acute cardiovascular events, especially cerebrovascular events. These findings may improve collective and individual risk prediction and prevention.
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Affiliation(s)
- Alberto Testa
- Department of Medical-Surgical Sciences and Biotechnologies, Sapienza University, Rome, Italy
| | - Giuseppe Biondi-Zoccai
- Mediterranea Cardiocentro, Naples, Italy - .,Scuola Superiore di Study Avanzati, Sapienza University, Rome, Italy
| | | | | | | | | | | | - Giacomo Frati
- Mediterranea Cardiocentro, Naples, Italy.,IRCCS Neuromed, Pozzilli, Isernia, Italy
| | | | | | - Mariangela Peruzzi
- IRCCS Neuromed, Pozzilli, Isernia, Italy.,Department of Clinical, Internal Anestesiology and Cardiovascular Sciences, Sapienza University, Rome, Italy
| | - Elena Cavarretta
- Mediterranea Cardiocentro, Naples, Italy.,Scuola Superiore di Study Avanzati, Sapienza University, Rome, Italy
| | | | - Enrica Mariano
- Department of Systems Medicine, Tor Vergata University, Rome, Italy
| | - Massimo Federici
- Department of Systems Medicine, Tor Vergata University, Rome, Italy
| | - Rocco A Montone
- Department of Cardiovascular Medicine, IRCCS A. Gemelli University Polyclinic Foundation, Rome, Italy
| | - Angela Dei Giudici
- Cardiologic Intensive Care Unit, Hemodynamic and Cardiology, Santa Maria Goretti Hospital, Latina, Italy
| | | | - Francesco Versaci
- Cardiologic Intensive Care Unit, Hemodynamic and Cardiology, Santa Maria Goretti Hospital, Latina, Italy
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Bernardi M, Biondi-Zoccai G, Versaci F. Air pollution and cardiovascular risk: is it time to change guidelines? Open Heart 2022; 9:openhrt-2022-001961. [PMID: 35750421 PMCID: PMC9234796 DOI: 10.1136/openhrt-2022-001961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/11/2022] [Indexed: 11/04/2022] Open
Affiliation(s)
- Marco Bernardi
- Department of Clinical, Internal, Anesthesiology and Cardiovascular Sciences, University of Rome La Sapienza, Rome, Lazio, Italy
| | - Giuseppe Biondi-Zoccai
- Department of Medical-Surgical Sciences and Biotechnologies, University of Rome La Sapienza, Rome, Lazio, Italy .,Mediterranea Cardiocentro, Napoli, Campania, Italy
| | - Francesco Versaci
- UOC UTIC Emodinamica e Cardiologia, Ospedale Santa Maria Goretti, Latina, Lazio, Italy
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