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External Validation Of The Surgical Mortality Probability Model (S-MPM) In Patients Undergoing Non-Cardiac Surgery
BACKGROUND: Preoperative risk assessment is a key issue in the process of patient preparation for surgery and the control of quality improvement in health care and certification programs. Hence, there is a need for a prognostic tool, whose usefulness can be assessed only after validation in the cent...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6781942/ https://www.ncbi.nlm.nih.gov/pubmed/31632044 http://dx.doi.org/10.2147/TCRM.S212308 |
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author | Kazimierczak, Sebastian Rybicka, Anita Strauss, Jochen Schram, Malgorzata Kazimierczak, Arkadiusz Grochans, Elżbieta |
author_facet | Kazimierczak, Sebastian Rybicka, Anita Strauss, Jochen Schram, Malgorzata Kazimierczak, Arkadiusz Grochans, Elżbieta |
author_sort | Kazimierczak, Sebastian |
collection | PubMed |
description | BACKGROUND: Preoperative risk assessment is a key issue in the process of patient preparation for surgery and the control of quality improvement in health care and certification programs. Hence, there is a need for a prognostic tool, whose usefulness can be assessed only after validation in the center other than the home one. The aim of the study was to validate the Surgical Mortality Probability Model (S-MPM) for detecting deaths and complications in patients undergoing non-cardiac surgery and to assess its suitability for various surgical disciplines. METHODS: This retrospective study involved 38,555 adult patients undergoing non-cardiac surgery in a single center in 2012–2015. The observation period concerned in-hospital mortality. RESULTS: In-hospital mortality for the total population was 0.89%. Mortality in the S-MPM I class amounted to 0.26%, S-MPM II 2.51%, and in the S-MPM III class 22.14%. This result was in line with those obtained by the authors. The discriminatory power for in-hospital mortality was good (area under curve (AUC) = 0.852, 95% CI: 0.834–0.869, p = 0.0000). The scale was the most accurate in general surgery (AUC = 0.89, 95% CI: 0.858–0.922) and trauma (AUC = 0.89; 95% CI: 0.87–0.915). In the logistic regression analysis, the scale showed a perfect fit/goodness of fit in the cross-validation method (v-fold cross-validation): Hosmer–Lemeshow (HL) = 7.945; p = 0.159. This result was confirmed by the traditional derivation and validation data set method (1:3; 9712 vs 22.748 cases): HL test = 3.073 (p = 0.546) in the teaching derivation data set and 10.77 (p = 0.029) in the test sample (validation data set). CONCLUSION: The S-MPM scale by Glance et al has proven to be a useful tool to assess the risk of in-hospital death and can be taken into account when considering treatment indications, patient information, planning post-operative care, and quality control. |
format | Online Article Text |
id | pubmed-6781942 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-67819422019-10-18 External Validation Of The Surgical Mortality Probability Model (S-MPM) In Patients Undergoing Non-Cardiac Surgery Kazimierczak, Sebastian Rybicka, Anita Strauss, Jochen Schram, Malgorzata Kazimierczak, Arkadiusz Grochans, Elżbieta Ther Clin Risk Manag Original Research BACKGROUND: Preoperative risk assessment is a key issue in the process of patient preparation for surgery and the control of quality improvement in health care and certification programs. Hence, there is a need for a prognostic tool, whose usefulness can be assessed only after validation in the center other than the home one. The aim of the study was to validate the Surgical Mortality Probability Model (S-MPM) for detecting deaths and complications in patients undergoing non-cardiac surgery and to assess its suitability for various surgical disciplines. METHODS: This retrospective study involved 38,555 adult patients undergoing non-cardiac surgery in a single center in 2012–2015. The observation period concerned in-hospital mortality. RESULTS: In-hospital mortality for the total population was 0.89%. Mortality in the S-MPM I class amounted to 0.26%, S-MPM II 2.51%, and in the S-MPM III class 22.14%. This result was in line with those obtained by the authors. The discriminatory power for in-hospital mortality was good (area under curve (AUC) = 0.852, 95% CI: 0.834–0.869, p = 0.0000). The scale was the most accurate in general surgery (AUC = 0.89, 95% CI: 0.858–0.922) and trauma (AUC = 0.89; 95% CI: 0.87–0.915). In the logistic regression analysis, the scale showed a perfect fit/goodness of fit in the cross-validation method (v-fold cross-validation): Hosmer–Lemeshow (HL) = 7.945; p = 0.159. This result was confirmed by the traditional derivation and validation data set method (1:3; 9712 vs 22.748 cases): HL test = 3.073 (p = 0.546) in the teaching derivation data set and 10.77 (p = 0.029) in the test sample (validation data set). CONCLUSION: The S-MPM scale by Glance et al has proven to be a useful tool to assess the risk of in-hospital death and can be taken into account when considering treatment indications, patient information, planning post-operative care, and quality control. Dove 2019-10-04 /pmc/articles/PMC6781942/ /pubmed/31632044 http://dx.doi.org/10.2147/TCRM.S212308 Text en © 2019 Kazimierczak et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Kazimierczak, Sebastian Rybicka, Anita Strauss, Jochen Schram, Malgorzata Kazimierczak, Arkadiusz Grochans, Elżbieta External Validation Of The Surgical Mortality Probability Model (S-MPM) In Patients Undergoing Non-Cardiac Surgery |
title | External Validation Of The Surgical Mortality Probability Model (S-MPM) In Patients Undergoing Non-Cardiac Surgery |
title_full | External Validation Of The Surgical Mortality Probability Model (S-MPM) In Patients Undergoing Non-Cardiac Surgery |
title_fullStr | External Validation Of The Surgical Mortality Probability Model (S-MPM) In Patients Undergoing Non-Cardiac Surgery |
title_full_unstemmed | External Validation Of The Surgical Mortality Probability Model (S-MPM) In Patients Undergoing Non-Cardiac Surgery |
title_short | External Validation Of The Surgical Mortality Probability Model (S-MPM) In Patients Undergoing Non-Cardiac Surgery |
title_sort | external validation of the surgical mortality probability model (s-mpm) in patients undergoing non-cardiac surgery |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6781942/ https://www.ncbi.nlm.nih.gov/pubmed/31632044 http://dx.doi.org/10.2147/TCRM.S212308 |
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