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2144. Vital Signs Are Vital in Identifying High-Risk Postoperative Patients

BACKGROUND: Changes in vital signs are frequently the first sign to point to pathology in the postoperative setting. There is no prediction model that exists that evaluates risk of postoperative complication in real-time. We are interested in understanding if we are able to risk stratify patients af...

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Autores principales: Bhaimia, Eric, Ravichandran, Urmila, Baied, Elias, Lahrman, Frances, Saeed, Huma, Kaplar, Katherine, Parikh, Ronak, Paruch, Jennifer, Padman, Rema, Grant, Jennifer, Shah, Nirav
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6252617/
http://dx.doi.org/10.1093/ofid/ofy210.1800
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author Bhaimia, Eric
Ravichandran, Urmila
Baied, Elias
Lahrman, Frances
Saeed, Huma
Kaplar, Katherine
Parikh, Ronak
Paruch, Jennifer
Padman, Rema
Grant, Jennifer
Shah, Nirav
author_facet Bhaimia, Eric
Ravichandran, Urmila
Baied, Elias
Lahrman, Frances
Saeed, Huma
Kaplar, Katherine
Parikh, Ronak
Paruch, Jennifer
Padman, Rema
Grant, Jennifer
Shah, Nirav
author_sort Bhaimia, Eric
collection PubMed
description BACKGROUND: Changes in vital signs are frequently the first sign to point to pathology in the postoperative setting. There is no prediction model that exists that evaluates risk of postoperative complication in real-time. We are interested in understanding if we are able to risk stratify patients after surgery using novel predictors, trajectories of the various vital signs and evaluating their ability to risk stratify patients. METHODS: We reviewed patients who underwent pancreatectomy at an academic health system from January 2015 to February 2018. Postoperative complications were abstracted using definitions set by the National Surgical Quality Improvement Program (NSQIP) and vital signs, including pain score, were extracted from the Data Warehouse. Group-based trajectory modeling, a technique used to identify distinct clusters of patients with similar trajectories, was used to group patients with similar temperature, heart rate, blood pressure and pain scores. Postoperative complications were tabulated for each risk group and chi-square test was used to compare categorical variables. RESULTS: A total of 195 patients with pancreatectomy were evaluated and the rate of NSQIP complications was 35.4%. Pancreatectomy patients clustered into two distinct clusters for temperature, heart rate, systolic blood pressure and pain score. All four of these vital signs were able to stratify infectious and inflammatory complications between low- and high-risk groups but only systolic blood pressure was significant in stratifying readmission risk and heart rate and pain score for stratifying sepsis risk (Table 1). CONCLUSION: Trends of vital signs may be important predictors of complications. Some vital signs may be better at predicting distinct complications. More work is required to understand if different covariates within trajectory analysis can be combined to further enhance risk stratification for any and specific postoperative complications. DISCLOSURES: All authors: No reported disclosures.
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spelling pubmed-62526172018-11-28 2144. Vital Signs Are Vital in Identifying High-Risk Postoperative Patients Bhaimia, Eric Ravichandran, Urmila Baied, Elias Lahrman, Frances Saeed, Huma Kaplar, Katherine Parikh, Ronak Paruch, Jennifer Padman, Rema Grant, Jennifer Shah, Nirav Open Forum Infect Dis Abstracts BACKGROUND: Changes in vital signs are frequently the first sign to point to pathology in the postoperative setting. There is no prediction model that exists that evaluates risk of postoperative complication in real-time. We are interested in understanding if we are able to risk stratify patients after surgery using novel predictors, trajectories of the various vital signs and evaluating their ability to risk stratify patients. METHODS: We reviewed patients who underwent pancreatectomy at an academic health system from January 2015 to February 2018. Postoperative complications were abstracted using definitions set by the National Surgical Quality Improvement Program (NSQIP) and vital signs, including pain score, were extracted from the Data Warehouse. Group-based trajectory modeling, a technique used to identify distinct clusters of patients with similar trajectories, was used to group patients with similar temperature, heart rate, blood pressure and pain scores. Postoperative complications were tabulated for each risk group and chi-square test was used to compare categorical variables. RESULTS: A total of 195 patients with pancreatectomy were evaluated and the rate of NSQIP complications was 35.4%. Pancreatectomy patients clustered into two distinct clusters for temperature, heart rate, systolic blood pressure and pain score. All four of these vital signs were able to stratify infectious and inflammatory complications between low- and high-risk groups but only systolic blood pressure was significant in stratifying readmission risk and heart rate and pain score for stratifying sepsis risk (Table 1). CONCLUSION: Trends of vital signs may be important predictors of complications. Some vital signs may be better at predicting distinct complications. More work is required to understand if different covariates within trajectory analysis can be combined to further enhance risk stratification for any and specific postoperative complications. DISCLOSURES: All authors: No reported disclosures. Oxford University Press 2018-11-26 /pmc/articles/PMC6252617/ http://dx.doi.org/10.1093/ofid/ofy210.1800 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of Infectious Diseases Society of America. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Abstracts
Bhaimia, Eric
Ravichandran, Urmila
Baied, Elias
Lahrman, Frances
Saeed, Huma
Kaplar, Katherine
Parikh, Ronak
Paruch, Jennifer
Padman, Rema
Grant, Jennifer
Shah, Nirav
2144. Vital Signs Are Vital in Identifying High-Risk Postoperative Patients
title 2144. Vital Signs Are Vital in Identifying High-Risk Postoperative Patients
title_full 2144. Vital Signs Are Vital in Identifying High-Risk Postoperative Patients
title_fullStr 2144. Vital Signs Are Vital in Identifying High-Risk Postoperative Patients
title_full_unstemmed 2144. Vital Signs Are Vital in Identifying High-Risk Postoperative Patients
title_short 2144. Vital Signs Are Vital in Identifying High-Risk Postoperative Patients
title_sort 2144. vital signs are vital in identifying high-risk postoperative patients
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6252617/
http://dx.doi.org/10.1093/ofid/ofy210.1800
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