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

ABSTRACT: BACKGROUND:Multiple 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. METHODS:We 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). RESULTS:The 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%). CONCLUSIONS:Examining 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.

SUBMITTER: Soo A

PROVIDER: S-EPMC6533687 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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

Soo Andrea A Zuege Danny J DJ Fick Gordon H GH Niven Daniel J DJ Berthiaume Luc R LR Stelfox Henry T HT Doig Christopher J CJ

Critical care (London, England) 20190523 1

<h4>Background</h4>Multiple 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 ...[more]

PMID: 31122276

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Project description:BackgroundMultiple organ dysfunction syndrome (MODS) occurs in the setting of a variety of pathologies including infection and trauma. Some patients decompensate and require Veno-Arterial extra corporeal membrane oxygenation (ECMO) as a palliating manoeuvre for recovery of cardiopulmonary function. The molecular mechanisms driving progression from MODS to cardiopulmonary collapse remain incompletely understood, and no biomarkers have been defined to identify those MODS patients at highest risk for progression to requiring ECMO support.MethodsWhole blood RNA-seq profiling was performed for 23 MODS patients at three time points during their ICU stay (at diagnosis of MODS, 72 hours after, and 8 days later), as well as four healthy controls undergoing routine sedation. Of the 23 MODS patients, six required ECMO support (ECMO patients). The predictive power of conventional demographic and clinical features was quantified for differentiating the MODS and ECMO patients. We then compared the performance of markers derived from transcriptomic profiling including [1] transcriptomically imputed leukocyte subtype distribution, [2] relevant published gene signatures and [3] a novel differential gene expression signature computed from our data set. The predictive power of our novel gene expression signature was then validated using independently published datasets.FindingNone of the five demographic characteristics and 14 clinical features, including The Paediatric Logistic Organ Dysfunction (PELOD) score, could predict deterioration of MODS to ECMO at baseline. From previously published sepsis signatures, only the signatures positively associated with patient's mortality could differentiate ECMO patients from MODS patients, when applied to our transcriptomic dataset (P-value ranges from 0.01 to 0.04, Student's test). Deconvolution of bulk RNA-Seq samples suggested that lower neutrophil counts were associated with increased risk of progression from MODS to ECMO (P-value = 0.03, logistic regression, OR=2.82 [95% CI 0.63 - 12.45]). A total of 30 genes were differentially expressed between ECMO and MODS patients at baseline (log2 fold change ≥ 1 or ≤ -1 with false discovery rate ≤ 0.01). These genes are involved in protein maintenance and epigenetic-related processes. Further univariate analysis of these 30 genes suggested a signature of seven DE genes associated with ECMO (OR > 3.0, P-value ≤ 0.05, logistic regression). Notably, this contains a set of histone marker genes, including H1F0, HIST2H3C, HIST1H2AI, HIST1H4, HIST1H2BL and HIST1H1B, that were highly expressed in ECMO. A risk score derived from expression of these genes differentiated ECMO and MODS patients in our dataset (AUC = 0.91, 95% CI 0.79-1.00, P-value = 7e-04, logistic regression) as well as validation dataset (AUC= 0.73, 95% CI 0.53-0.93, P-value = 2e-02, logistic regression).InterpretationThis study demonstrates that transcriptomic features can serve as indicators of severity that could be superior to traditional methods of ascertaining acuity in MODS patients. Analysis of expression of signatures identified in this study could help clinicians in the diagnosis and prognostication of MODS patients after arrival to the Hospital.

Project description:BackgroundA structure and staffing model similar to that in general intensive care unit (ICUs) is applied to cardiac intensive care unit (CICUs) for patients with acute heart failure. However, there is limited evidence on the structure and staffing model of CICUs. The present study aimed to assess whether critical care for patients with acute heart failure in the ICUs is associated with improved outcomes than care in the high-dependency care units (HDUs), the hospital units in which patient care levels and costs are between the levels found in the ICU and general ward.MethodsThis nationwide, propensity score-matched, retrospective cohort study was performed using a national administrative inpatient database in Japan. We identified all patients who were hospitalized for acute heart failure and admitted to the ICU or HDU on the day of hospital admission from April 2014 to March 2019. Propensity score-matching analysis was performed to compare the in-hospital mortality between acute heart failure patients treated in the ICU and HDU on the day of hospital admission.ResultsOf 202,866 eligible patients, 78,646 (39%) and 124,220 (61%) were admitted to the ICU and HDU, respectively, on the day of admission. After propensity score matching, there was no statistically significant difference in in-hospital mortality between patients who were admitted to the ICU and HDU on the day of admission (10.7% vs. 11.4%; difference, - 0.6%; 95% confidence interval, - 1.5% to 0.2%). In the subgroup analyses, there was a statistically significant difference in in-hospital mortality between the ICU and HDU groups among patients receiving noninvasive ventilation (9.4% vs. 10.5%; difference, - 1.0%; 95% confidence interval, - 1.9% to - 0.1%) and patients receiving intubation (32.5% vs. 40.6%; difference, - 8.0%; 95% confidence interval, - 14.5% to - 1.5%). There were no statistically significant differences in other subgroup analyses.ConclusionsCritical care in ICUs was not associated with lower in-hospital mortality than critical care in HDUs among patients with acute heart failure. However, critical care in ICUs was associated with lower in-hospital mortality than critical care in HDUs among patients receiving noninvasive ventilation and intubation.

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

Publications

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

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