Severity of illness scores rest on the assumption that patients have normal physiologic values at baseline and that patients with similar severity of illness scores have the same degree of deviation from their usual state. Prior studies have reported differences in baseline physiology, including laboratory markers, between obese and normal weight individuals, but these differences have not been analyzed in the ICU. We compared deviation from baseline of pertinent ICU laboratory test results between obese and normal weight patients, adjusted for the severity of illness.
Retrospective cohort study in a large ICU database.
Tertiary teaching hospital.
Obese and normal weight patients who had laboratory results documented between 3 days and 1 year prior to hospital admission.
Seven hundred sixty-nine normal weight patients were compared with 1,258 obese patients. After adjusting for the severity of illness score, age, comorbidity index, baseline laboratory result, and ICU type, the following deviations were found to be statistically significant: WBC 0.80 (95% CI, 0.27–1.33) × 109/L; p = 0.003; log (blood urea nitrogen) 0.01 (95% CI, 0.00–0.02); p = 0.014; log (creatinine) 0.03 (95% CI, 0.02–0.05), p < 0.001; with all deviations higher in obese patients. A logistic regression analysis suggested that after adjusting for age and severity of illness at least one of these deviations had a statistically significant effect on hospital mortality (p = 0.009).
Among patients with the same severity of illness score, we detected clinically small but significant deviations in WBC, creatinine, and blood urea nitrogen from baseline in obese compared with normal weight patients. These small deviations are likely to be increasingly important as bigger data are analyzed in increasingly precise ways. Recognition of the extent to which all critically ill patients may deviate from their own baseline may improve the objectivity, precision, and generalizability of ICU mortality prediction and severity adjustment models.
1Critical Care Department, Hospital Israelita Albert Einstein, São Paulo, Brazil.
2Laboratory for Computational Physiology, Harvard-MIT Health Sciences & Technology, MIT, Cambridge, MA.
3Harvard T.H. Chan School of Public Health, Boston, MA.
4Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, United Kingdom.
5Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA.
6Grupo de Bioingenieria y Telemedicina, Universidad Politecnica de Madrid, Madrid, Spain.
7Unidad de Innovación, Instituto de Investigación Sanitaria San Carlos, Hospital Clínico San Carlos, Madrid, Spain.
8Department of Chemical Engineering, Institute of Medical Engineering & Science, MIT, Cambridge, MA.
9Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA.
10Departments of Anesthesiology and Neurosurgery, University of Virginia School of Medicine, Charlottesville, VA.
*See also p. 484.
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Supported, in part, by Cancer Research Institute Irvington Fellowship (awarded to M.P.F.).
Dr. Komorowski received support for article research from Research Counciles UK. Drs. Raffa, Johnson, and Celi received support for article research from the National Institutes of Health. The remaining authors have disclosed that they do not have any potential conflicts of interest.
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