@article{ab2ab52aac7745a3bbe6437b4bc52ae8,
title = "Serial daily organ failure assessment beyond ICU day 5 does not independently add precision to ICU risk-of-death prediction",
abstract = "Objectives: To identify circumstances in which repeated measures of organ failure would improve mortality prediction in ICU patients. Design: Retrospective cohort study, with external validation in a deidentified ICU database. Setting: Eleven ICUs in three university hospitals within an academic healthcare system in 2014. Patients: Adults (18 yr old or older) who satisfied the following criteria: 1) two of four systemic inflammatory response syndrome criteria plus an ordered blood culture, all within 24 hours of hospital admission; and 2) ICU admission for at least 2 calendar days, within 72 hours of emergency department presentation. Intervention: None Measurements and Main Results: Data were collected until death, ICU discharge, or the seventh ICU day, whichever came first. The highest Sequential Organ Failure Assessment score from the ICU admission day (ICU day 1) was included in a multivariable model controlling for other covariates. The worst Sequential Organ Failure Assessment scores from the first 7 days after ICU admission were incrementally added and retained if they obtained statistical significance (p < 0.05). The cohort was divided into seven subcohorts to facilitate statistical comparison using the integrated discriminatory index. Of the 1,290 derivation cohort patients, 83 patients (6.4%) died in the ICU, compared with 949 of the 8,441 patients (11.2%) in the validation cohort. Incremental addition of Sequential Organ Failure Assessment data up to ICU day 5 improved the integrated discriminatory index in the validation cohort. Adding ICU day 6 or 7 Sequential Organ Failure Assessment data did not further improve model performance. Conclusions: Serial organ failure data improve prediction of ICU mortality, but a point exists after which further data no longer improve ICU mortality prediction of early sepsis.",
keywords = "Intensive care unit, Mortality, Organ failure, Prognostication, Sepsis",
author = "Holder, {Andre L.} and Elizabeth Overton and Peter Lyu and Kempker, {Jordan A.} and Shamim Nemati and Fereshteh Razmi and Martin, {Greg S.} and Buchman, {Timothy G.} and Murphy, {David J.}",
note = "Funding Information: Dr. Holder received support from CR Bard. Dr. Kempker{\textquoteright}s institution received funding from National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health (NIH) under Award Number UL1TR000454 and KL2 TR000455, and he received funding from the NIH. Dr. Nemati is supported by the National Institute of Environmental Health Sciences of the NIH (K01 ES025445). Dr. Martin{\textquoteright}s institution received funding from the NIH (NCATS UL1 TR000454), the Food and Drug Admin- istration, and Baxter Healthcare; he received funding from Bard Medical, Edwards, Grifols, and the Society of Critical Care Medicine (SCCM) (Proj- ect Help); he received support for article research from the NIH; and he is supported by the National Institute for General Medical Sciences (R01 GM113228) and the National Center for Advancing Translational Sciences of the NIH (UL1 TR000454). Dr. Buchman{\textquoteright}s institution received funding Worsening organ dysfunction is associated with higher from Henry M Jackson Foundation supporting the Surgical Critical Care Ini- mortality in septic patients who are critically ill (1). Funding Information: Care Medicine), and the Coulter Foundation (grant support). He receivedtiative (http://www.sc2i.org), SCCM (services as Editor-in-Chief of Critical The Sequential Organ Failure Assessment (SOFA) funding from Philips Corporation paid to a physician organization in the score is a validated tool used to temporally track changes in phys-Republic of Korea as an unrestricted educational grant (this defrayed travel iologic derangements, providing real-time organ dysfunction disclosed that they do not have any potential conflicts of interest.costs for him to present findings of eICU work). The remaining authors have data (1–3). Predictive modeling using repeated measurements For information regarding this article, E-mail: andre.holder@emory.edu over time may improve prognostication, but this comes at a cost. Publisher Copyright: {\textcopyright} 2017 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc.",
year = "2017",
doi = "10.1097/CCM.0000000000002708",
language = "English",
volume = "45",
pages = "2014--2022",
journal = "Critical Care Medicine",
issn = "0090-3493",
number = "12",
}