Development of a national Department of Veterans Affairs mortality risk prediction model among patients with cirrhosis
Objective Cirrhotic patients are at high hospitalisation risk with subsequent high mortality. Current risk prediction models have varied performances with methodological room for improvement. We used current analytical techniques using automatically extractable variables from the electronic health r...
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2019-08-01
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| Series: | BMJ Open Gastroenterology |
| Online Access: | https://bmjopengastro.bmj.com/content/6/1/e000342.full |
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| author | Jejo David Koola Samuel Ho Guanhua Chen Amy M Perkins Aize Cao Sharon E Davis Michael E Matheny |
| author_facet | Jejo David Koola Samuel Ho Guanhua Chen Amy M Perkins Aize Cao Sharon E Davis Michael E Matheny |
| author_sort | Jejo David Koola |
| collection | DOAJ |
| description | Objective Cirrhotic patients are at high hospitalisation risk with subsequent high mortality. Current risk prediction models have varied performances with methodological room for improvement. We used current analytical techniques using automatically extractable variables from the electronic health record (EHR) to develop and validate a posthospitalisation mortality risk score for cirrhotic patients and compared performance with the model for end-stage liver disease (MELD), model for end-stage liver disease with sodium (MELD-Na), and the CLIF Consortium Acute Decompensation (CLIF-C AD) models.Design We analysed a retrospective cohort of 73 976 patients comprising 247 650 hospitalisations between 2006 and 2013 at any of 123 Department of Veterans Affairs hospitals. Using 45 predictor variables, we built a time-dependent Cox proportional hazards model with all-cause mortality as the outcome. We compared performance to the three extant models and reported discrimination and calibration using bootstrapping. Furthermore, we analysed differential utility using the net reclassification index (NRI).Results The C-statistic for the final model was 0.863, representing a significant improvement over the MELD, MELD-Na, and the CLIF-C AD, which had C-statistics of 0.655, 0.675, and 0.679, respectively. Multiple risk factors were significant in our model, including variables reflecting disease severity and haemodynamic compromise. The NRI showed a 24% improvement in predicting survival of low-risk patients and a 30% improvement in predicting death of high-risk patients.Conclusion We developed a more accurate mortality risk prediction score using variables automatically extractable from an EHR that may be used to risk stratify patients with cirrhosis for targeted postdischarge management. |
| format | Article |
| id | doaj-art-9f39e6e65b08446087a36e6ecc0ac4b9 |
| institution | OA Journals |
| issn | 2054-4774 |
| language | English |
| publishDate | 2019-08-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open Gastroenterology |
| spelling | doaj-art-9f39e6e65b08446087a36e6ecc0ac4b92025-08-20T02:37:57ZengBMJ Publishing GroupBMJ Open Gastroenterology2054-47742019-08-016110.1136/bmjgast-2019-000342Development of a national Department of Veterans Affairs mortality risk prediction model among patients with cirrhosisJejo David Koola0Samuel Ho1Guanhua Chen2Amy M Perkins3Aize Cao4Sharon E Davis5Michael E Matheny6Department of Medicine, University of California San Diego, La Jolla, California, USADepartment of Medicine, University of California San Diego, La Jolla, California, USADepartment of Biostatistics and Medical Informatics, University of Wisconsin Madison, Madison, Wisconsin, USADepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USAVeteran`s Health Administration, VA Tennessee Valley Healthcare System, Nashville, Tennessee, USAVeteran`s Health Administration, VA Tennessee Valley Healthcare System, Nashville, Tennessee, USATennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USAObjective Cirrhotic patients are at high hospitalisation risk with subsequent high mortality. Current risk prediction models have varied performances with methodological room for improvement. We used current analytical techniques using automatically extractable variables from the electronic health record (EHR) to develop and validate a posthospitalisation mortality risk score for cirrhotic patients and compared performance with the model for end-stage liver disease (MELD), model for end-stage liver disease with sodium (MELD-Na), and the CLIF Consortium Acute Decompensation (CLIF-C AD) models.Design We analysed a retrospective cohort of 73 976 patients comprising 247 650 hospitalisations between 2006 and 2013 at any of 123 Department of Veterans Affairs hospitals. Using 45 predictor variables, we built a time-dependent Cox proportional hazards model with all-cause mortality as the outcome. We compared performance to the three extant models and reported discrimination and calibration using bootstrapping. Furthermore, we analysed differential utility using the net reclassification index (NRI).Results The C-statistic for the final model was 0.863, representing a significant improvement over the MELD, MELD-Na, and the CLIF-C AD, which had C-statistics of 0.655, 0.675, and 0.679, respectively. Multiple risk factors were significant in our model, including variables reflecting disease severity and haemodynamic compromise. The NRI showed a 24% improvement in predicting survival of low-risk patients and a 30% improvement in predicting death of high-risk patients.Conclusion We developed a more accurate mortality risk prediction score using variables automatically extractable from an EHR that may be used to risk stratify patients with cirrhosis for targeted postdischarge management.https://bmjopengastro.bmj.com/content/6/1/e000342.full |
| spellingShingle | Jejo David Koola Samuel Ho Guanhua Chen Amy M Perkins Aize Cao Sharon E Davis Michael E Matheny Development of a national Department of Veterans Affairs mortality risk prediction model among patients with cirrhosis BMJ Open Gastroenterology |
| title | Development of a national Department of Veterans Affairs mortality risk prediction model among patients with cirrhosis |
| title_full | Development of a national Department of Veterans Affairs mortality risk prediction model among patients with cirrhosis |
| title_fullStr | Development of a national Department of Veterans Affairs mortality risk prediction model among patients with cirrhosis |
| title_full_unstemmed | Development of a national Department of Veterans Affairs mortality risk prediction model among patients with cirrhosis |
| title_short | Development of a national Department of Veterans Affairs mortality risk prediction model among patients with cirrhosis |
| title_sort | development of a national department of veterans affairs mortality risk prediction model among patients with cirrhosis |
| url | https://bmjopengastro.bmj.com/content/6/1/e000342.full |
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