Abstract: Poster Presentations |


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

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


Chest. 2005;128(4_MeetingAbstracts):348S. doi:10.1378/chest.128.4_MeetingAbstracts.348S
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PURPOSE:  The Mortality Probability Model on ICU admission (MPM0-II), developed on an international sample of 12,610 patients treated in 1989-90, is used by Project IMPACT as a benchmarking tool, but no longer calibrates. We updated the model based on 2001-2004 patient data.

METHODS:  Project IMPACT data on 124,855 patients age>18 and eligible for MPM scoring were randomly split into development (60%) and validation (40%) samples and analyzed using logistic regression. Independent variables considered were MPM -II variables, patient location and lead time prior to ICU admission and code status at the time of ICU admission. Discrimination was assessed by area under the ROC curve (AUC) and calibration by graphic display and Hosmer-Lemeshow Goodness of Fit (HL-GOF) C-statistics.

RESULTS:  Observed hospital mortality was 13.8%. The MPM0-III model includes MPM0-II variables and several interaction terms. Lead time and pre-ICU location did not influence outcome. Addition of a “zero-factor” term for patients with no risk factors other than age improved calibration. Coefficients are in the table, and improved calibration can be seen in the figure. Validation set HL-GOF=10.94, p=0.36 and ROC AUC=0.823.

CONCLUSION:  MPM0-III is well calibrated to current clinical data and requires collecting only one additional term (code status).

CLINICAL IMPLICATIONS:  Use of MPM0-III will allow more accurate comparisons of actual versus expected outcomes based on patient condition at the time of ICU admission. VariableCoefficientConstant-5.397338Coma-stupor2.032949HR >150 bpm0.4286778SBP < 90 mmHg1.578148Chronic Renal0.4041341Chronic GI2.078154Metastatic Neoplasm3.187064Acute Renal0.7026929Dysrhythmia0.8247331Cerebrovascular Incident0.4103774GI Bleed-0.1593359Intracranial Mass1.838082Age (in years)0.0387999CPR w/i 24hr1.499682Mech. Ventilation0.891268Medical/Unscheduled Surgical Admission0.916912Zero Factors-0.4025265Full Code-0.8016462SBP x MV Admit-0.1620224Age x Coma-0.0074014Age x SBP<90-0.0092765Age x ChronicGI-0.0225957Age x Mets-0.0328078Age x CardDys-0.0100795Age x ICM-0.0168818Age x CPR-0.0112155

DISCLOSURE:  Thomas Higgins, Consultant fee, speaker bureau, advisory committee, etc. Dr. Higgins serves on the Cerner Critical Care Transformation Council (advisory committee).

Wednesday, November 2, 2005

12:30 PM - 2:00 PM




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