Describing organ dysfunction in the intensive care unit: a cohort study of 20,000 patients

BackgroundMultiple organ dysfunction is a common cause of morbidity and mortality in intensive care units (ICUs). Original development of the Sequential Organ Failure Assessment (SOFA) score was not to predict outcome, but to describe temporal changes in organ dysfunction in critically ill patients. Organ dysfunction scoring may be a reasonable surrogate outcome in clinical trials but further exploration of the impact of case mix on the temporal sequence of organ dysfunction is required. Our aim was to compare temporal changes in SOFA scores between hospital survivors and non-survivors.MethodsWe performed a population-based observational retrospective cohort study of critically ill patients admitted from January 1, 2004, to December 31, 2013, to 4 multisystem adult intensive care units (ICUs) in Calgary, Canada. The primary outcome was temporal changes in daily SOFA scores during the first 14 days of ICU admission. SOFA scores were modeled between hospital survivors and non-survivors using generalized estimating equations (GEE) and were also stratified by admission SOFA (≤ 11 versus > 11).ResultsThe cohort consisted of 20,007 patients with at least one SOFA score and was mostly male (58.2%) with a median age of 59 (interquartile range [IQR] 44–72). Median ICU length of stay was 3.5 (IQR 1.7–7.5) days. ICU and hospital mortality were 18.5% and 25.5%, respectively. Temporal change in SOFA scores varied by survival and admission SOFA score in a complicated relationship. Area under the receiver operating characteristic (ROC) curve using admission SOFA as a predictor of hospital mortality was 0.77. The hospital mortality rate was 5.6% for patients with an admission SOFA of 0–2 and 94.4% with an admission SOFA of 20–24. There was an approximately linear increase in hospital mortality for SOFA scores of 3–19 (range 8.7–84.7%).ConclusionsExamining the clinical course of organ dysfunction in a large non-selective cohort of patients provides insight into the utility of SOFA. We have demonstrated that hospital outcome is associated with both admission SOFA and the temporal rate of change in SOFA after admission. It is necessary to further explore the impact of additional clinical factors on the clinical course of SOFA with large datasets.

[1]  A. Baue.  Multiple, progressive, or sequential systems failure. A syndrome of the 1970s. , 1975, Archives of surgery.

[2]  J. Marshall,et al.  Multiple-organ-failure syndrome. , 1986, Archives of surgery.

[3]  E. DeLong,et al.  Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. , 1988, Biometrics.

[4]  R. Prentice.  Surrogate endpoints in clinical trials: definition and operational criteria. , 1989, Statistics in medicine.

[5]  J. Ward,et al.  Statistical analysis of the stages of HIV infection using a Markov model. , 1989, Statistics in medicine.

[6]  M. Fink,et al.  Multiple Organ Failure Syndrome—Part I: Epidemiology, Prognosis, and Pathophysiology , 1991 .

[7]  E. Deitch,et al.  Multiple organ failure. Pathophysiology and potential future therapy. , 1992, Annals of surgery.

[8]  C. Sprung,et al.  Multiple organ dysfunction score: a reliable descriptor of a complex clinical outcome. , 1995, Critical care medicine.

[9]  J. Vincent,et al.  Yearbook of Intensive Care and Emergency Medicine , 1995, Yearbook of Intensive Care and Emergency Medicine.

[10]  Corinne Alberti,et al.  The Logistic Organ Dysfunction system. A new way to assess organ dysfunction in the intensive care unit. ICU Scoring Group. , 1996, JAMA.

[11]  S Lemeshow,et al.  The Logistic Organ Dysfunction system. A new way to assess organ dysfunction in the intensive care unit. ICU Scoring Group. , 1996, JAMA.

[12]  A. Baue.  Multiple organ failure, multiple organ dysfunction syndrome, and systemic inflammatory response syndrome. Why no magic bullets? , 1997, Archives of surgery.

[13]  J. Marshall.  Organ dysfunction as an outcome measure in clinical trials. , 1999, The European journal of surgery. Supplement. : = Acta chirurgica. Supplement.

[14]  C. Sprung,et al.  The use of maximum SOFA score to quantify organ dysfunction/failure in intensive care. Results of a prospective, multicentre study , 1999, Intensive Care Medicine.

[15]  P Wright,et al.  Changing pattern of organ dysfunction in early human sepsis is related to mortality , 2000, Critical care medicine.

[16]  M. Singer,et al.  Multi-Organ Dysfunction in the Critically Ill: Epidemiology, Pathophysiology and Management , 2000, Journal of the Royal College of Physicians of London.

[17]  A. Seely,et al.  Multiple organ dysfunction syndrome: Exploring the paradigm of complex nonlinear systems , 2000, Critical care medicine.

[18]  J. Vincent,et al.  Serial evaluation of the SOFA score to predict outcome in critically ill patients. , 2001, JAMA.

[19]  Measuring Organ Dysfunction , 2002 .

[20]  G. Rubenfeld.  Surrogate Measures of Patient-centered Outcomes in Critical Care , 2003 .

[21]  D. Menon,et al.  Non-neurological organ dysfunction in neurocritical care. , 2003, Journal of critical care.

[22]  J. Vincent.  Endpoints in sepsis trials: More than just 28-day mortality? , 2004, Critical care medicine.

[23]  C. Doig,et al.  Study of clinical course of organ dysfunction in intensive care , 2004, Critical care medicine.

[24]  Thomas Lengauer,et al.  ROCR: visualizing classifier performance in R , 2005, Bioinform..

[25]  J. Vincent,et al.  The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure , 1996, Intensive Care Medicine.

[26]  Kevin B Laupland,et al.  Neuroanesthesia and Intensive Care Limited ability of SOFA and MOD scores to discriminate outcome: a prospective evaluation in 1,436 patients , 2005, Canadian journal of anaesthesia = Journal canadien d'anesthesie.

[27]  C. Doig,et al.  Non-neurologic organ dysfunction in severe traumatic brain injury* , 2005, Critical care medicine.

[28]  J. Solsona,et al.  Multicenter study of the multiple organ dysfunction syndrome in intensive care units: the usefulness of Sequential Organ Failure Assessment scores in decision making , 2005, Intensive Care Medicine.

[29]  Søren Højsgaard,et al.  The R Package geepack for Generalized Estimating Equations , 2005 .

[30]  K. Laupland,et al.  Limites de la capacité discriminatoire des scores de SOFA et de DMV : une évaluation prospective chez 1 436 patients , 2005 .

[31]  T. Cook,et al.  Development of a triage protocol for critical care during an influenza pandemic , 2006, Canadian Medical Association Journal.

[32]  A. Baue.  MOF, MODS, and SIRS: what is in a name or an acronym? , 2006, Shock.

[33]  C. Doig,et al.  SOFA is superior to MOD score for the determination of non-neurologic organ dysfunction in patients with severe traumatic brain injury: a cohort study , 2006, Critical care.

[34]  N. Matsuda,et al.  Systemic inflammatory response syndrome (SIRS): molecular pathophysiology and gene therapy. , 2006, Journal of Pharmacological Sciences.

[35]  A. Abu-Hanna,et al.  Evaluation of SOFA-based models for predicting mortality in the ICU: A systematic review , 2008, Critical care.

[36]  J. Hulme,et al.  An assessment of the validity of SOFA score based triage in H1N1 critically ill patients during an influenza pandemic , 2009, Anaesthesia.

[37]  Xavier Robin,et al.  pROC: an open-source package for R and S+ to analyze and compare ROC curves , 2011, BMC Bioinformatics.

[38]  J. Marshall,et al.  Critical illness is an iatrogenic disorder , 2010, Critical care medicine.

[39]  C. Sprung,et al.  Recommendations for intensive care unit and hospital preparations for an influenza epidemic or mass disaster: summary report of the European Society of Intensive Care Medicine’s Task Force for intensive care unit triage during an influenza epidemic or mass disaster , 2010, Intensive Care Medicine.

[40]  T. Matsuo,et al.  Serial evaluation of SOFA score in a Brazilian teaching hospital. , 2010, Intensive & critical care nursing.

[41]  C. Doig,et al.  Sequential Organ Failure Assessment in H1N1 pandemic planning* , 2011, Critical care medicine.

[42]  A. Badreldin,et al.  Daily-Mean-SOFA, a New Derivative to Increase Accuracy of Mortality Prediction in Cardiac Surgical Intensive Care Units , 2012, Thoracic and Cardiovascular Surgeon.

[43]  C. Doig,et al.  Incidence of neurologic death among patients with brain injury: a cohort study in a Canadian health region , 2013, Canadian Medical Association Journal.

[44]  Samuel M. Brown,et al.  Glasgow Coma Scale score dominates the association between admission Sequential Organ Failure Assessment score and 30-day mortality in a mixed intensive care unit population. , 2014, Journal of critical care.

[45]  Ileana Baldi,et al.  Dynamic Bayesian Networks to predict sequences of organ failures in patients admitted to ICU , 2014, J. Biomed. Informatics.

[46]  Jesse B. Hall,et al.  Power and Limitations of Daily Prognostications of Death in the Medical ICU for Outcomes in the Following 6 Months* , 2014, Critical care medicine.

[47]  Survival in fully manifest multiple organ dysfunction syndrome. , 2014, Surgical infections.

[48]  Mu-Chun Su,et al.  Prediction of survival of ICU patients using computational intelligence , 2014, Comput. Biol. Medicine.

[49]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[50]  Survival in fully manifest multiple organ dysfunction syndrome. , 2014 .

[51]  W. Chung,et al.  Consideration of additional factors in Sequential Organ Failure Assessment score. , 2014, Journal of critical care.

[52]  Predicting death and disability, is it really possible? A medical ICU prognostication model study. , 2014, Critical care medicine.

[53]  J. Keilwagen,et al.  Area under Precision-Recall Curves for Weighted and Unweighted Data , 2014, PloS one.

[54]  Filip De Turck,et al.  Predictive modelling of survival and length of stay in critically ill patients using sequential organ failure scores , 2015, Artif. Intell. Medicine.

[55]  R. Kanter,et al.  Would triage predictors perform better than first-come, first-served in pandemic ventilator allocation? , 2015, Chest.

[56]  Jens Keilwagen,et al.  PRROC: computing and visualizing precision-recall and receiver operating characteristic curves in R , 2015, Bioinform..

[57]  A. Pavlovic,et al.  Scoring Systems in Assessing Survival of Critically Ill ICU Patients , 2015, Medical science monitor : international medical journal of experimental and clinical research.

[58]  B. Scheller,et al.  Individual Organ Failure and Concomitant Risk of Mortality Differs According to the Type of Admission to ICU – A Retrospective Study of SOFA Score of 23,795 Patients , 2015, PloS one.

[59]  J. Vincent,et al.  SOFA and mortality endpoints in randomized controlled trials: a systematic review and meta-regression analysis , 2017, Critical Care.

[60]  David J Murphy,et al.  Serial Daily Organ Failure Assessment Beyond ICU Day 5 Does Not Independently Add Precision to ICU Risk-of-Death Prediction , 2017, Critical care medicine.

[61]  J. D. Young,et al.  Defining multiple organ failure after major trauma: A comparison of the Denver, Sequential Organ Failure Assessment, and Marshall scoring systems , 2017, The journal of trauma and acute care surgery.

[62]  S. Bagshaw,et al.  Secondary EMR data for quality improvement and research: A comparison of manual and electronic data collection from an integrated critical care electronic medical record system , 2018, Journal of critical care.

[63]  Omar Badawi,et al.  Evaluation of ICU Risk Models Adapted for Use as Continuous Markers of Severity of Illness Throughout the ICU Stay* , 2018, Critical care medicine.