Cargando…
1567. Predicting Mortality Among Immunocompromised Patients Who Present with Infection
BACKGROUND: Recent sepsis definitions for the general population include Sequential Organ Failure Assessment (SOFA) ≥ 2 for patients admitted to intensive care unit (ICU), and quick SOFA (qSOFA) ≥ 2 for non-ICU patients. The objective of this study was to validate the predictive value of SOFA and qS...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6252879/ http://dx.doi.org/10.1093/ofid/ofy210.1395 |
_version_ | 1783373366730686464 |
---|---|
author | Henig, Oryan Rao, Krishna Albin, Owen Putler, Rosemary Kaul, Daniel Kaye, Keith S |
author_facet | Henig, Oryan Rao, Krishna Albin, Owen Putler, Rosemary Kaul, Daniel Kaye, Keith S |
author_sort | Henig, Oryan |
collection | PubMed |
description | BACKGROUND: Recent sepsis definitions for the general population include Sequential Organ Failure Assessment (SOFA) ≥ 2 for patients admitted to intensive care unit (ICU), and quick SOFA (qSOFA) ≥ 2 for non-ICU patients. The objective of this study was to validate the predictive value of SOFA and qSOFA in immunocompromised patients. METHODS: Adult patients admitted between 2014 and 2017 with ICD-9 and ICD-10 codes for hematologic malignancies or transplant diagnoses who had suspected infection were included. Index date of suspected infection was defined as the time when blood culture was obtained, followed by intravenous antibiotic therapy, or vice versa (based on the definition used in SEPSIS-3 study, Seymour et al.). SOFA, qSOFA and SIRS components within 1 day of the index date were extracted from the medical record. A baseline risk model of mortality was created including age, race, gender, and Charlson comorbidity index. Each score was added to the baseline mortality risk model as a dichotomous variable (SOFA ≥ 2, qSOFA ≥ 2, and SIRS ≥ 2). For each risk model, a receiver operating characteristic (ROC) curve was developed and the area under ROC (AUROC) was calculated. Sensitivities of SOFA ≥ 2, qSOFA ≥ 2, and SIRS ≥ 2 for predicting in-hospital mortality were calculated. RESULTS: A total of 2,917 patients with a mean age of 57.0 ± 15.7 were included; 57% were male and 84% white. The most common immunocompromising conditions were solid-organ transplantation (45%), lymphoma (24%), acute leukemia (17%) and hematopoietic stem cell transplantation (6%). Two hundred and seventeen patients died during index admission (7.4%). The sensitivities of SOFA ≥ 2, qSOFA ≥ 2 and SIRS ≥ 2 for predicting in-hospital mortality were 94.9, 64.1 and 91.7%, respectively (P < 0.001 for each score ≥2 compared with <2). In the mortality risk model, the AUROCs for qSOFA, SOFA and SIRS were 0.75, 0.70 and 0.71, respectively (Figure). The AUROC for qSOFA ≥2 was significantly higher than for SIRS ≥2 and SOFA ≥2 (P = 0.004, P < 0.001, respectively). CONCLUSION: qSOFA ≥2 was the strongest predictor of mortality in immunocompromised patients and may aid in risk stratification and clinical decision-making. Additional analyses are needed to evaluate alternative and potentially improved scoring systems for sepsis in immunocompromised populations. [Image: see text] DISCLOSURES: All authors: No reported disclosures. |
format | Online Article Text |
id | pubmed-6252879 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-62528792018-11-28 1567. Predicting Mortality Among Immunocompromised Patients Who Present with Infection Henig, Oryan Rao, Krishna Albin, Owen Putler, Rosemary Kaul, Daniel Kaye, Keith S Open Forum Infect Dis Abstracts BACKGROUND: Recent sepsis definitions for the general population include Sequential Organ Failure Assessment (SOFA) ≥ 2 for patients admitted to intensive care unit (ICU), and quick SOFA (qSOFA) ≥ 2 for non-ICU patients. The objective of this study was to validate the predictive value of SOFA and qSOFA in immunocompromised patients. METHODS: Adult patients admitted between 2014 and 2017 with ICD-9 and ICD-10 codes for hematologic malignancies or transplant diagnoses who had suspected infection were included. Index date of suspected infection was defined as the time when blood culture was obtained, followed by intravenous antibiotic therapy, or vice versa (based on the definition used in SEPSIS-3 study, Seymour et al.). SOFA, qSOFA and SIRS components within 1 day of the index date were extracted from the medical record. A baseline risk model of mortality was created including age, race, gender, and Charlson comorbidity index. Each score was added to the baseline mortality risk model as a dichotomous variable (SOFA ≥ 2, qSOFA ≥ 2, and SIRS ≥ 2). For each risk model, a receiver operating characteristic (ROC) curve was developed and the area under ROC (AUROC) was calculated. Sensitivities of SOFA ≥ 2, qSOFA ≥ 2, and SIRS ≥ 2 for predicting in-hospital mortality were calculated. RESULTS: A total of 2,917 patients with a mean age of 57.0 ± 15.7 were included; 57% were male and 84% white. The most common immunocompromising conditions were solid-organ transplantation (45%), lymphoma (24%), acute leukemia (17%) and hematopoietic stem cell transplantation (6%). Two hundred and seventeen patients died during index admission (7.4%). The sensitivities of SOFA ≥ 2, qSOFA ≥ 2 and SIRS ≥ 2 for predicting in-hospital mortality were 94.9, 64.1 and 91.7%, respectively (P < 0.001 for each score ≥2 compared with <2). In the mortality risk model, the AUROCs for qSOFA, SOFA and SIRS were 0.75, 0.70 and 0.71, respectively (Figure). The AUROC for qSOFA ≥2 was significantly higher than for SIRS ≥2 and SOFA ≥2 (P = 0.004, P < 0.001, respectively). CONCLUSION: qSOFA ≥2 was the strongest predictor of mortality in immunocompromised patients and may aid in risk stratification and clinical decision-making. Additional analyses are needed to evaluate alternative and potentially improved scoring systems for sepsis in immunocompromised populations. [Image: see text] DISCLOSURES: All authors: No reported disclosures. Oxford University Press 2018-11-26 /pmc/articles/PMC6252879/ http://dx.doi.org/10.1093/ofid/ofy210.1395 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 Henig, Oryan Rao, Krishna Albin, Owen Putler, Rosemary Kaul, Daniel Kaye, Keith S 1567. Predicting Mortality Among Immunocompromised Patients Who Present with Infection |
title | 1567. Predicting Mortality Among Immunocompromised Patients Who Present with Infection |
title_full | 1567. Predicting Mortality Among Immunocompromised Patients Who Present with Infection |
title_fullStr | 1567. Predicting Mortality Among Immunocompromised Patients Who Present with Infection |
title_full_unstemmed | 1567. Predicting Mortality Among Immunocompromised Patients Who Present with Infection |
title_short | 1567. Predicting Mortality Among Immunocompromised Patients Who Present with Infection |
title_sort | 1567. predicting mortality among immunocompromised patients who present with infection |
topic | Abstracts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6252879/ http://dx.doi.org/10.1093/ofid/ofy210.1395 |
work_keys_str_mv | AT henigoryan 1567predictingmortalityamongimmunocompromisedpatientswhopresentwithinfection AT raokrishna 1567predictingmortalityamongimmunocompromisedpatientswhopresentwithinfection AT albinowen 1567predictingmortalityamongimmunocompromisedpatientswhopresentwithinfection AT putlerrosemary 1567predictingmortalityamongimmunocompromisedpatientswhopresentwithinfection AT kauldaniel 1567predictingmortalityamongimmunocompromisedpatientswhopresentwithinfection AT kayekeiths 1567predictingmortalityamongimmunocompromisedpatientswhopresentwithinfection |