Abstract: Poster Presentations |


Brian Nathanson, PhD; Wayne Copes, PhD; Maureen Stark, MS; Andrew Kramer, PhD; Daniel Teres, MD; Thomas L. Higgins, MD*
Author and Funding Information

Baystate Medical Center/Tufts University School of Medicine, Springfield, MA


Chest. 2005;128(4_MeetingAbstracts):349S. doi:10.1378/chest.128.4_MeetingAbstracts.349S
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PURPOSE:  The Mortality Probability Model on ICU admission (MPM0) is used by Project IMPACT as a benchmarking tool. A recent update (MPM0-III) has been validated and shown to perform well on a large dataset. New MPM models based on specific patient subsets have been constructed to improve assessment with specialized ICU populations.

METHODS:  Project IMPACT data from 2001-2004 for 124,855 patients eligible for MPM scoring treated in 135 ICUs were randomly split into design (60%) and validation (40%) samples. Logistic regression models were developed to predict hospital mortality from MPM0-III variables for patients in each of the following subgroups: Complex Cardiovascular, Trauma, Elective Surgery, Medical, Neurosurgery and Other Emergency Surgery. Discrimination was assessed by area under the Receiver Operator Characteristic (ROC) curve and calibration by Hosmer Lemeshow Goodness of Fit (HL-GOF) C-statistics. We compared ICU-specific Standardized Mortality Ratios (SMRs) and associated confidence intervals (CIs) from MPM0-III to those based on the Subgroup models, using the validation sample.

RESULTS:  The six Subgroup models had good calibration and discrimination on the validation sample (Table 1-performance on validation dataset). MPM0-III and Subgroup model SMRs and CIs were in substantial agreement (overall agreement 94.8%, Kappa Statistic 0.88; p-value<0.001). Important SMR differences were observed for some units with an atypical case mix or when a unit’s CI bordered on significance.

CONCLUSION:  The MPM0-III Subgroup models calibrate well on specialized populations and complement the general MPM0-III model for benchmarking.

CLINICAL IMPLICATIONS:  MPM0-III Subgroup models are useful when ICU case mix is atypical or SMR performance is near the significance boundary. Subgroup models will also be valuable in studies of specific patient subsets. Subgroup ModelComplex CardiovascularTraumaElective SurgeryMedicalNeuro-surgicalOther Emergency SurgerySample Size3434424898122663322983605    H-L statistic10.389.1716.4412.206.0111.63    p Value0.410.520.090.070.810.31    ROC AUC0.870.900.790.790.850.79

DISCLOSURE:  Thomas Higgins, Consultant fee, speaker bureau, advisory committee, etc. Dr. Higgins serves on the Cerner Critical Care Transformation Council; Grant monies (from industry related sources); Dr. Nathanson received grant funding from Cerner.

Wednesday, November 2, 2005

12:30 PM - 2:00 PM




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