Protocol for the derivation and external validation of a 30-day mortality risk prediction model for older patients having emergency general surgery (PAUSE score—Probability of mortality Associated with Urgent/emergent general Surgery in oldEr patients score)
Introduction People 65 years and older represent the fastest growing segment of the surgical population. Older age is associated with doubling of risk when undergoing emergency general surgery (EGS) procedures and often coexists with medical complexity and considerations of end-of-life care, creatin...
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BMJ Publishing Group
2020-01-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/10/1/e034060.full |
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| author | Carl van Walraven Daniel I McIsaac Manoj Lalu Simon Feng Husein Moloo Reilly Musselman |
| author_facet | Carl van Walraven Daniel I McIsaac Manoj Lalu Simon Feng Husein Moloo Reilly Musselman |
| author_sort | Carl van Walraven |
| collection | DOAJ |
| description | Introduction People 65 years and older represent the fastest growing segment of the surgical population. Older age is associated with doubling of risk when undergoing emergency general surgery (EGS) procedures and often coexists with medical complexity and considerations of end-of-life care, creating prognostic and decisional uncertainty. Combined with the time-sensitive nature of EGS, it is challenging to gauge perioperative risk and ensure that clinical decisions are aligned with the patient values. Current preoperative risk prediction models for older EGS patients have major limitations regarding derivation and validation, and do not address the specific risk profile of older patients. Accurate and externally validated models specific to older patients are needed to inform care and decision making.Methods and analysis We will derive, internally and externally validate a multivariable model to predict 30-day mortality in EGS patients >65 years old. Our derivation sample will be individuals enrolled in the National Surgical Quality Improvement Program (NSQIP) database between 2012 and 2016 having 1 of 7 core EGS procedures. Postulated predictor variables have been identified based on previous research, clinical and epidemiological knowledge. Our model will be derived using logistic regression penalised with elastic net regularisation and ensembled using bootstrap aggregation. The resulting model will be internally validated using k-fold cross-validation and bootstrap validation techniques and externally validated using population-based health administrative data. Discrimination and calibration will be reported at each step.Ethics and dissemination Ethics for NSQIP data use was obtained from the Ottawa Hospital Research Ethics Board; external validation will use routinely collected anonymised data legally exempt from research ethics review. The final risk score will be published in a peer-reviewed journal. We plan to further disseminate the model as an online calculator or application for clinical use. Future research will be required to test the clinical application of the final model. |
| format | Article |
| id | doaj-art-e99d398a11ce4da1bce3fcf990736b3e |
| institution | Kabale University |
| issn | 2044-6055 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open |
| spelling | doaj-art-e99d398a11ce4da1bce3fcf990736b3e2024-12-07T02:10:09ZengBMJ Publishing GroupBMJ Open2044-60552020-01-0110110.1136/bmjopen-2019-034060Protocol for the derivation and external validation of a 30-day mortality risk prediction model for older patients having emergency general surgery (PAUSE score—Probability of mortality Associated with Urgent/emergent general Surgery in oldEr patients score)Carl van Walraven0Daniel I McIsaac1Manoj Lalu2Simon Feng3Husein Moloo4Reilly Musselman58 Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, Ontario, Canada1 Anaesthesiology and Pain Medicine, Ottawa Hospital Research Institute Clinical Epidemiology Programme, Ottawa, Ontario, Canada2 Department of Anesthesiology and Pain Medicine, The Ottawa Hospital, Ottawa, Ontario, Canada1 Anesthesiology and Pain Medicine, The Ottawa Hospital, Ottawa, Ontario, CanadaGeneral Surgery, University of Ottawa, Ottawa, Ontario, Canada3 Surgery, The Ottawa Hospital, Ottawa, Ontario, CanadaIntroduction People 65 years and older represent the fastest growing segment of the surgical population. Older age is associated with doubling of risk when undergoing emergency general surgery (EGS) procedures and often coexists with medical complexity and considerations of end-of-life care, creating prognostic and decisional uncertainty. Combined with the time-sensitive nature of EGS, it is challenging to gauge perioperative risk and ensure that clinical decisions are aligned with the patient values. Current preoperative risk prediction models for older EGS patients have major limitations regarding derivation and validation, and do not address the specific risk profile of older patients. Accurate and externally validated models specific to older patients are needed to inform care and decision making.Methods and analysis We will derive, internally and externally validate a multivariable model to predict 30-day mortality in EGS patients >65 years old. Our derivation sample will be individuals enrolled in the National Surgical Quality Improvement Program (NSQIP) database between 2012 and 2016 having 1 of 7 core EGS procedures. Postulated predictor variables have been identified based on previous research, clinical and epidemiological knowledge. Our model will be derived using logistic regression penalised with elastic net regularisation and ensembled using bootstrap aggregation. The resulting model will be internally validated using k-fold cross-validation and bootstrap validation techniques and externally validated using population-based health administrative data. Discrimination and calibration will be reported at each step.Ethics and dissemination Ethics for NSQIP data use was obtained from the Ottawa Hospital Research Ethics Board; external validation will use routinely collected anonymised data legally exempt from research ethics review. The final risk score will be published in a peer-reviewed journal. We plan to further disseminate the model as an online calculator or application for clinical use. Future research will be required to test the clinical application of the final model.https://bmjopen.bmj.com/content/10/1/e034060.full |
| spellingShingle | Carl van Walraven Daniel I McIsaac Manoj Lalu Simon Feng Husein Moloo Reilly Musselman Protocol for the derivation and external validation of a 30-day mortality risk prediction model for older patients having emergency general surgery (PAUSE score—Probability of mortality Associated with Urgent/emergent general Surgery in oldEr patients score) BMJ Open |
| title | Protocol for the derivation and external validation of a 30-day mortality risk prediction model for older patients having emergency general surgery (PAUSE score—Probability of mortality Associated with Urgent/emergent general Surgery in oldEr patients score) |
| title_full | Protocol for the derivation and external validation of a 30-day mortality risk prediction model for older patients having emergency general surgery (PAUSE score—Probability of mortality Associated with Urgent/emergent general Surgery in oldEr patients score) |
| title_fullStr | Protocol for the derivation and external validation of a 30-day mortality risk prediction model for older patients having emergency general surgery (PAUSE score—Probability of mortality Associated with Urgent/emergent general Surgery in oldEr patients score) |
| title_full_unstemmed | Protocol for the derivation and external validation of a 30-day mortality risk prediction model for older patients having emergency general surgery (PAUSE score—Probability of mortality Associated with Urgent/emergent general Surgery in oldEr patients score) |
| title_short | Protocol for the derivation and external validation of a 30-day mortality risk prediction model for older patients having emergency general surgery (PAUSE score—Probability of mortality Associated with Urgent/emergent general Surgery in oldEr patients score) |
| title_sort | protocol for the derivation and external validation of a 30 day mortality risk prediction model for older patients having emergency general surgery pause score probability of mortality associated with urgent emergent general surgery in older patients score |
| url | https://bmjopen.bmj.com/content/10/1/e034060.full |
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