Literature DB >> 16236950

Outcome prediction in chest injury by a mathematical search and display program.

William C Shoemaker1, David S Bayard, Charles C J Wo, Linda S Chan, Li-Chien Chien, Kevin Lu, Roger W Jelliffe.   

Abstract

OBJECTIVE: This study applies a stochastic or probability search and display model to prospectively predict outcome and to evaluate therapeutic effects in a consecutively monitored series of 396 patients with severe thoracic and thoracoabdominal injuries. STUDY
DESIGN: Prospective observational study of outcome prediction using noninvasive hemodynamic monitoring by previously designed protocols and tested against actual outcome at hospital discharge in a level 1 trauma service of a university-run, inner-city public hospital.
METHODS: Cardiac index (CI), heart rate (HR), mean arterial pressure (MAP), arterial oxygen saturation measured by pulse oximetry (Sp(O2)), transcutaneous oxygen tension (PtC(O2)), and transcutaneous carbon dioxide tension (Ptc(CO2)) were monitored beginning shortly after admission to the emergency department. The stochastic search and display model with a decision support program based on noninvasive hemodynamic monitoring was applied to 396 severely ill patients with major thoracic and thoracoabdominal trauma. The survival probability (SP) was calculated during initial resuscitation continuously until patients were stabilized, and compared with the actual outcome when the patient was discharged from the hospital usually a week or more later.
RESULTS: The CI, Sp(O2), Ptc(O2), and MAP were appreciably higher in survivors than in nonsurvivors. HR and Ptc(CO2) were higher in the nonsurvivors. The calculated SP in the first 24-h observation period of survivors of chest wounds averaged 83 +/- 18% (+/- SD) and 62 +/- 19% for nonsurvivors. Misclassifications were 9.6%. The relative effects of alternative therapies were evaluated before and after therapy, using hemodynamic monitoring and SP as criteria.
CONCLUSIONS: Noninvasive hemodynamic monitoring with an information system provided a feasible approach to early outcome predictions and therapeutic decision support.

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Year:  2005        PMID: 16236950     DOI: 10.1378/chest.128.4.2739

Source DB:  PubMed          Journal:  Chest        ISSN: 0012-3692            Impact factor:   9.410


  2 in total

Review 1.  Using what you get: dynamic physiologic signatures of critical illness.

Authors:  Andre L Holder; Gilles Clermont
Journal:  Crit Care Clin       Date:  2015-01       Impact factor: 3.598

2.  A comparison of methods for assessing penetrating trauma on retrospective multi-center data.

Authors:  Bilal A Ahmed; Michael E Matheny; Phillip L Rice; John R Clarke; Omolola I Ogunyemi
Journal:  J Biomed Inform       Date:  2008-10-01       Impact factor: 6.317

  2 in total

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