Objectives: To evaluate the performance of the logistic organ dysfunction (LOD) system for the assessment of morbidity and mortality in multiple organ dysfunction/failure (MOD/F) in an independent database and to evaluate the use of sequential LOD measurements for the prediction of outcome. Design and setting: Prospective, multicentric cohort study in 13 adult medical, surgical, and mixed intensive care units (ICUs) in Austria. Patients: A total of 2893 consecutive admissions to the ICUs. Measurements and main results: Patient vital status at ICU and hospital discharge was recorded. Univariate analysis showed that the LOD was able to distinguish between survivors and nonsurvivors (2 vs. 6 median score). Within organ systems, higher levels of the severity of organ dysfunction were consistently associated with higher mortality. For the prediction of hospital mortality, the original prognostic LOD model did not perform well in our patients, as indicated by the goodness-of-fit Ĉ statistic. Using multiple logistic regression we developed a prognostic model with a satisfactory fit in our patients. The integration of further measurements during the ICU stay increased discrimination but not calibration. Conclusions: The LOD system is well correlated well with the numbers and levels of organ dysfunctions and discriminates well between survivors and nonsurvivors. It can thus be used to quantify the baseline severity of organ dysfunction. Moreover, after customization of the predictive equation the LOD predicted hospital mortality in our patients with high precision. It thus provides a combined measure of morbidity and mortality for critically ill patients with MOD/F.
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Final revision received: 7 November 2000
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Metnitz, P., Le Gall, J., Steltzer, H. et al. Evaluation of the logistic organ dysfunction system for the assessment of organ dysfunction and mortality in critically ill patients. Intensive Care Med 27, 992–998 (2001). https://doi.org/10.1007/s001340100888
- Severity of illness Outcome Organ dysfunction Organ failure Prognostic systems