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Related Experiment Videos

Predicting deaths among intensive care unit patients.

R W Chang1, S Jacobs, B Lee

  • 1Department of Surgery, Riyadh Armed Forces Hospital, Saudi Arabia.

Critical Care Medicine
|January 1, 1988
PubMed
Summary

Daily APACHE II scoring trends improve ICU patient mortality prediction. This method enhances prediction accuracy by analyzing score changes over time, offering a superior alternative to single-day assessments for critical care outcomes.

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Area of Science:

  • Critical Care Medicine
  • Health Outcomes Research
  • Biostatistics

Background:

  • Intensive Care Unit (ICU) patient outcomes require accurate prediction for effective management.
  • The APACHE II (Acute Physiology and Chronic Health Evaluation II) score is a common severity-of-illness measure.
  • Dynamic monitoring of ICU patients' physiological status is crucial for predicting hospital outcomes.

Purpose of the Study:

  • To prospectively assess the utility of daily APACHE II scores in predicting hospital outcomes for ICU admissions.
  • To develop and validate criteria for predicting mortality using trend analysis of daily APACHE II scores.
  • To compare the predictive power of dynamic APACHE II scoring with single-day assessments.

Main Methods:

  • Prospective study of 212 adult ICU admissions.

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  • Daily APACHE II assessments were performed.
  • Trend analysis of daily APACHE II scores, considering absolute values and daily changes, was used to derive prediction criteria.

    • Main Results:

    • Initial criteria identified 16 of 34 deaths among 100 patients.
    • A second set of criteria, with adjusted limits, improved predictive power.
    • Daily APACHE II scoring with the second criteria set was four times more predictive than single APACHE II scores.

    Conclusions:

    • Dynamic trend analysis of daily APACHE II scores offers superior prediction of ICU patient mortality compared to single scores.
    • The developed criteria provide a more sensitive and specific method for predicting hospital outcomes in critical care settings.
    • This approach can aid in risk stratification and resource allocation for ICU patients.