Construction of variables from arterial pressure.

<div><p>Objective</p><p>Mean arterial pressure is widely used as the variable to monitor during anesthesia. But there are many other variables proposed to define intraoperative arterial hypotension. The goal of the present study was to search arterial pressure variables linked with prolonged postoperative length of stay (pLOS).</p><p>Design</p><p>Retrospective cohort study of adult patients having received general anesthesia for a scheduled non-cardiac surgical procedure between 15<sup>th</sup> July 2017 and 31st December 2019.</p><p>Methods</p><p>pLOS was defined as a stay longer than the median (main outcome), adjusted for surgery type and duration. 330 arterial pressure variables were analyzed and organized through a clustering approach. An unsupervised hierarchical aggregation method for optimal cluster determination, employing Kendall’s tau coefficients and a penalized Bayes information criterion was used. Variables were ranked using the absolute standardized mean distance (aSMD) to measure their effect on pLOS. Finally, after multivariate independence analysis, the number of variables was reduced to three.</p><p>Results</p><p>Our study examined 9,516 patients. When LOS is defined as strictly greater than the median, 34% of patients experienced pLOS. Key arterial pressure variables linked with this definition of pLOS included the difference between the highest and lowest pulse pressure values computed throughout the surgery (aSMD[95%CI] = 0.39[0.31–0.40], p<0.001), the accumulated time pulse pressure above 61mmHg (aSMD = 0.21[0.17–0.25], p<0.001), and the lowest MAP during surgery (aSMD = 0.20[0.16–0.24], p<0.001).</p><p>Conclusions</p><p>By applying a clustering approach, three arterial pressure variables were associated with pLOS. This scalable method can be applied to various dichotomized outcomes.</p></div>

Publication Details

Journal
Figshare
Published
2024-09-13
DOI
https://doi.org/10.1371/journal.pone.0308910.s001
Primary Topic
Hemodynamic Monitoring and Therapy
Type
article
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article

Construction of variables from arterial pressure.

Figshare
Hemodynamic Monitoring and Therapy
article

Construction of variables from arterial pressure.

article en

Abstract

<div><p>Objective</p><p>Mean arterial pressure is widely used as the variable to monitor during anesthesia. But there are many other variables proposed to define intraoperative arterial hypotension. The goal of the present study was to search arterial pressure variables linked with prolonged postoperative length of stay (pLOS).</p><p>Design</p><p>Retrospective cohort study of adult patients having received general anesthesia for a scheduled non-cardiac surgical procedure between 15<sup>th</sup> July 2017 and 31st December 2019.</p><p>Methods</p><p>pLOS was defined as a stay longer than the median (main outcome), adjusted for surgery type and duration. 330 arterial pressure variables were analyzed and organized through a clustering approach. An unsupervised hierarchical aggregation method for optimal cluster determination, employing Kendall’s tau coefficients and a penalized Bayes information criterion was used. Variables were ranked using the absolute standardized mean distance (aSMD) to measure their effect on pLOS. Finally, after multivariate independence analysis, the number of variables was reduced to three.</p><p>Results</p><p>Our study examined 9,516 patients. When LOS is defined as strictly greater than the median, 34% of patients experienced pLOS. Key arterial pressure variables linked with this definition of pLOS included the difference between the highest and lowest pulse pressure values computed throughout the surgery (aSMD[95%CI] = 0.39[0.31–0.40], p<0.001), the accumulated time pulse pressure above 61mmHg (aSMD = 0.21[0.17–0.25], p<0.001), and the lowest MAP during surgery (aSMD = 0.20[0.16–0.24], p<0.001).</p><p>Conclusions</p><p>By applying a clustering approach, three arterial pressure variables were associated with pLOS. This scalable method can be applied to various dichotomized outcomes.</p></div>

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Hemodynamic Monitoring and Therapy
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Construction of variables from arterial pressure. · Figshare (2024) | TGRS Research Map | TGRS