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Development and validation of a Score for Preoperative Prediction of Obstructive Sleep Apnea (SPOSA) and its perioperative outcomes
BACKGROUND: Postoperative respiratory complications (PRCs) are associated with significant morbidity, mortality, and hospital costs. Obstructive sleep apnea (OSA), often undiagnosed in the surgical population, may be a contributing factor. Thus, we aimed to develop and validate a score for preoperat...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5450400/ https://www.ncbi.nlm.nih.gov/pubmed/28558716 http://dx.doi.org/10.1186/s12871-017-0361-z |
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author | Shin, Christina H. Grabitz, Stephanie D. Timm, Fanny P. Mueller, Noomi Chhangani, Khushi Ladha, Karim Devine, Scott Kurth, Tobias Eikermann, Matthias |
author_facet | Shin, Christina H. Grabitz, Stephanie D. Timm, Fanny P. Mueller, Noomi Chhangani, Khushi Ladha, Karim Devine, Scott Kurth, Tobias Eikermann, Matthias |
author_sort | Shin, Christina H. |
collection | PubMed |
description | BACKGROUND: Postoperative respiratory complications (PRCs) are associated with significant morbidity, mortality, and hospital costs. Obstructive sleep apnea (OSA), often undiagnosed in the surgical population, may be a contributing factor. Thus, we aimed to develop and validate a score for preoperative prediction of OSA (SPOSA) based on data available in electronic medical records preoperatively. METHODS: OSA was defined as the occurrence of an OSA diagnostic code preceded by a polysomnography procedure. A priori defined variables were analyzed by multivariable logistic regression analysis to develop our score. Score validity was assessed by investigating the score’s ability to predict non-invasive ventilation. We then assessed the effect of high OSA risk, as defined by SPOSA, on PRCs within seven postoperative days and in-hospital mortality. RESULTS: A total of 108,781 surgical patients at Partners HealthCare hospitals (2007–2014) were studied. Predictors of OSA included BMI >25 kg*m(−2) and comorbidities, including pulmonary hypertension, hypertension, and diabetes. The score yielded an area under the curve of 0.82. Non-invasive ventilation was significantly associated with high OSA risk (OR 1.44, 95% CI 1.22–1.69). Using a dichotomized endpoint, 26,968 (24.8%) patients were identified as high risk for OSA and 7.9% of these patients experienced PRCs. OSA risk was significantly associated with PRCs (OR 1.30, 95% CI 1.19–1.43). CONCLUSION: SPOSA identifies patients at high risk for OSA using electronic medical record-derived data. High risk of OSA is associated with the occurrence of PRCs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12871-017-0361-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5450400 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-54504002017-06-01 Development and validation of a Score for Preoperative Prediction of Obstructive Sleep Apnea (SPOSA) and its perioperative outcomes Shin, Christina H. Grabitz, Stephanie D. Timm, Fanny P. Mueller, Noomi Chhangani, Khushi Ladha, Karim Devine, Scott Kurth, Tobias Eikermann, Matthias BMC Anesthesiol Research Article BACKGROUND: Postoperative respiratory complications (PRCs) are associated with significant morbidity, mortality, and hospital costs. Obstructive sleep apnea (OSA), often undiagnosed in the surgical population, may be a contributing factor. Thus, we aimed to develop and validate a score for preoperative prediction of OSA (SPOSA) based on data available in electronic medical records preoperatively. METHODS: OSA was defined as the occurrence of an OSA diagnostic code preceded by a polysomnography procedure. A priori defined variables were analyzed by multivariable logistic regression analysis to develop our score. Score validity was assessed by investigating the score’s ability to predict non-invasive ventilation. We then assessed the effect of high OSA risk, as defined by SPOSA, on PRCs within seven postoperative days and in-hospital mortality. RESULTS: A total of 108,781 surgical patients at Partners HealthCare hospitals (2007–2014) were studied. Predictors of OSA included BMI >25 kg*m(−2) and comorbidities, including pulmonary hypertension, hypertension, and diabetes. The score yielded an area under the curve of 0.82. Non-invasive ventilation was significantly associated with high OSA risk (OR 1.44, 95% CI 1.22–1.69). Using a dichotomized endpoint, 26,968 (24.8%) patients were identified as high risk for OSA and 7.9% of these patients experienced PRCs. OSA risk was significantly associated with PRCs (OR 1.30, 95% CI 1.19–1.43). CONCLUSION: SPOSA identifies patients at high risk for OSA using electronic medical record-derived data. High risk of OSA is associated with the occurrence of PRCs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12871-017-0361-z) contains supplementary material, which is available to authorized users. BioMed Central 2017-05-30 /pmc/articles/PMC5450400/ /pubmed/28558716 http://dx.doi.org/10.1186/s12871-017-0361-z Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Shin, Christina H. Grabitz, Stephanie D. Timm, Fanny P. Mueller, Noomi Chhangani, Khushi Ladha, Karim Devine, Scott Kurth, Tobias Eikermann, Matthias Development and validation of a Score for Preoperative Prediction of Obstructive Sleep Apnea (SPOSA) and its perioperative outcomes |
title | Development and validation of a Score for Preoperative Prediction of Obstructive Sleep Apnea (SPOSA) and its perioperative outcomes |
title_full | Development and validation of a Score for Preoperative Prediction of Obstructive Sleep Apnea (SPOSA) and its perioperative outcomes |
title_fullStr | Development and validation of a Score for Preoperative Prediction of Obstructive Sleep Apnea (SPOSA) and its perioperative outcomes |
title_full_unstemmed | Development and validation of a Score for Preoperative Prediction of Obstructive Sleep Apnea (SPOSA) and its perioperative outcomes |
title_short | Development and validation of a Score for Preoperative Prediction of Obstructive Sleep Apnea (SPOSA) and its perioperative outcomes |
title_sort | development and validation of a score for preoperative prediction of obstructive sleep apnea (sposa) and its perioperative outcomes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5450400/ https://www.ncbi.nlm.nih.gov/pubmed/28558716 http://dx.doi.org/10.1186/s12871-017-0361-z |
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