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MULTIVARIATE DATA ANALYSIS PROCEDURE FOR CHARACTERIZING CORRELATION STRUCTURE OF AIR CONTAMINANTS IN OPERATING ROOMS.

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Title: MULTIVARIATE DATA ANALYSIS PROCEDURE FOR CHARACTERIZING CORRELATION STRUCTURE OF AIR CONTAMINANTS IN OPERATING ROOMS.
Authors: Ragosta, Maria1 maria.ragosta@unibas.it, Albertini, Prospero2, Bagattini, Maria2, D'Emilio, Mariagrazia3, Mainardi, Pierangela2, Pennino, Francesca2, Riccio, Patrizia4, Triassi, Maria2
Source: Fresenius Environmental Bulletin. Aug2022, Vol. 31 Issue 8A, p8373-8378. 6p.
Subject Terms: *Air quality, *Indoor air quality, Operating rooms, Surgical site infections, Multivariate analysis, Data analysis
Abstract: In this study, data concerning air quality in Operating Rooms (ORs), collected under different conditions, were analyzed. In 18 ORs of general surgery, concentrations of particles with aerodynamic diameter higher than 5 pm and 10 pm, microbial charge, air change numbers and differential pressure were measured. To quantify the influence of the surgical environment on the Surgical Site Infections (SSIs) so to minimize the risk in hospitalized patients the data were collected under different conditions. The correlation pattern analysis, based on factorial multivariate techniques, put in evidence the indoor environmental conditions in which parameters characterizing air quality show a strong correlation. Moreover, this analysis allowed to define which staff behaviors introduced the greatest variations in the correlation pattern. Moreover, a clustering procedure allows defining different typologies of ORs, based on their characteristics. The multivariate approach allows to identify the role of each air quality parameter in the correlation structure of the data and to evaluate how their role plays when the condition of the surgical environment changes. [ABSTRACT FROM AUTHOR]
Copyright of Fresenius Environmental Bulletin is the property of PRT-Parlar Research & Technology and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: GreenFILE
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PubType: Academic Journal
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  Data: MULTIVARIATE DATA ANALYSIS PROCEDURE FOR CHARACTERIZING CORRELATION STRUCTURE OF AIR CONTAMINANTS IN OPERATING ROOMS.
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  Data: <searchLink fieldCode="JN" term="%22Fresenius+Environmental+Bulletin%22">Fresenius Environmental Bulletin</searchLink>. Aug2022, Vol. 31 Issue 8A, p8373-8378. 6p.
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  Data: *<searchLink fieldCode="DE" term="%22Air+quality%22">Air quality</searchLink><br />*<searchLink fieldCode="DE" term="%22Indoor+air+quality%22">Indoor air quality</searchLink><br /><searchLink fieldCode="DE" term="%22Operating+rooms%22">Operating rooms</searchLink><br /><searchLink fieldCode="DE" term="%22Surgical+site+infections%22">Surgical site infections</searchLink><br /><searchLink fieldCode="DE" term="%22Multivariate+analysis%22">Multivariate analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink>
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  Data: In this study, data concerning air quality in Operating Rooms (ORs), collected under different conditions, were analyzed. In 18 ORs of general surgery, concentrations of particles with aerodynamic diameter higher than 5 pm and 10 pm, microbial charge, air change numbers and differential pressure were measured. To quantify the influence of the surgical environment on the Surgical Site Infections (SSIs) so to minimize the risk in hospitalized patients the data were collected under different conditions. The correlation pattern analysis, based on factorial multivariate techniques, put in evidence the indoor environmental conditions in which parameters characterizing air quality show a strong correlation. Moreover, this analysis allowed to define which staff behaviors introduced the greatest variations in the correlation pattern. Moreover, a clustering procedure allows defining different typologies of ORs, based on their characteristics. The multivariate approach allows to identify the role of each air quality parameter in the correlation structure of the data and to evaluate how their role plays when the condition of the surgical environment changes. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Fresenius Environmental Bulletin is the property of PRT-Parlar Research & Technology and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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      – SubjectFull: Air quality
        Type: general
      – SubjectFull: Indoor air quality
        Type: general
      – SubjectFull: Operating rooms
        Type: general
      – SubjectFull: Surgical site infections
        Type: general
      – SubjectFull: Multivariate analysis
        Type: general
      – SubjectFull: Data analysis
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      – TitleFull: MULTIVARIATE DATA ANALYSIS PROCEDURE FOR CHARACTERIZING CORRELATION STRUCTURE OF AIR CONTAMINANTS IN OPERATING ROOMS.
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            NameFull: Ragosta, Maria
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              M: 08
              Text: Aug2022
              Type: published
              Y: 2022
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