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Methods Inf Med. 2013;52(6):494-502. doi: 10.3414/ME12-01-0093. Epub 2013 Aug 28.

Disease-based modeling to predict fluid response in intensive care units.

Author information

1
André S. Fialho, PhD, Massachusetts Institute of Technology, Engineering Systems Division, 77 Massachusetts Avenue, 02139 Cambridge, MA, USA, E-mail: afialho@mit.edu.

Abstract

OBJECTIVE:

To compare general and disease-based modeling for fluid resuscitation and vasopressor use in intensive care units.

METHODS:

Retrospective cohort study involving 2944 adult medical and surgical intensive care unit (ICU) patients receiving fluid resuscitation. Within this cohort there were two disease-based groups, 802 patients with a diagnosis of pneumonia, and 143 patients with a diagnosis of pancreatitis. Fluid resuscitation either progressing to subsequent vasopressor administration or not was used as the primary outcome variable to compare general and disease-based modeling.

RESULTS:

Patients with pancreatitis, pneumonia and the general group all shared three common predictive features as core variables, arterial base excess, lactic acid and platelets. Patients with pneumonia also had non-invasive systolic blood pressure and white blood cells added to the core model, and pancreatitis patients additionally had temperature. Disease-based models had significantly higher values of AUC (p < 0.05) than the general group (0.82 ± 0.02 for pneumonia and 0.83 ± 0.03 for pancreatitis vs. 0.79 ± 0.02 for general patients).

CONCLUSIONS:

Disease-based predictive modeling reveals a different set of predictive variables compared to general modeling and improved performance. Our findings add support to the growing body of evidence advantaging disease specific predictive modeling.

KEYWORDS:

Disease-based modeling; decision modeling; fluid resuscitation; intensive care units

PMID:
23986268
PMCID:
PMC5693240
DOI:
10.3414/ME12-01-0093
[Indexed for MEDLINE]
Free PMC Article

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