ISSN:
1432-1238
Keywords:
Organ dysfunctions
;
Infection
;
Severity of disease
;
Prognosis
Source:
Springer Online Journal Archives 1860-2000
Topics:
Medicine
Notes:
Abstract Objective To evaluate the sensitivity, specificity and overall accuracy of a model based on the presence or absence of organ dysfunctions and/or infection (ODIN) to predict the outcome for intensive care unit patients. Design Prospective study. Setting General intensive care unit in a university teaching hospital. Patients 1070 consecutive, unselected patients. Interventions There were no interventions. Measurements and main results We recorded within the first 24h of admission the presence or absence of dysfunction in 6 organ systems: respiratory, cardiovascular, renal, hematologic, hepatic and neurologic, and/or infection (ODIN) in all patients admitted to our ICU, thus establishing a profile of organ dysfunctions in each patient. Using univariate analysis, a strong correlation was found between the number of ODIN and the death rate (2.6, 9.7, 16.7, 32.3, 64.9, 75.9, 94.4 and 100% for 0, 1, 2, 3, 4, 5, 6 and 7 ODIN, respectively; (p〈0.001). In addition, the highest mortality rates were associated with hepatic (60.8%), hematologic (58.1%) and renal (54.8%) dysfunctions, and the lowest with respiratory dysfunction (36.5%) and infection (38.3%). For taking into account both the number and the type of organ dysfunction, a logistic regression model was then used to calculate individual probabilities of death that depended upon the statistical weight assigned to each ODIN (in the following order of descending severity: cardiovascular, renal, respiratory, neurologic, hematologic, hepatic dysfunctions and infection). The ability of this severity-of-disease classification system to stratify a wide variety of patients prognostically (sensitivity 51.4%, specificity 93.4%, overall accuracy 82.1%) was not different from that of currently used scoring systems. Conclusions These findings suggest that determination of the number and the type of organ dysfunctions and infection offers a clear and reliable method for characterizing ICU patients. Before a widespread use, this model requires to be validated in other institutions.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF01720528
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