Time-dependent uncertainty of critical care transitions in very old patients - lessons for time-limited trials Academic Article uri icon

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abstract

  • Purpose

    Prognostication for patients with critical conditions remains challenging, especially for very old individuals. Time-limited trials (TLT) are used to decrease prognostic uncertainty in the individual patient by monitoring the response to treatment over a pre-determined period of time. However, there are substantial difficulties with determining the length of that period. This study presents a probabilistic method to estimate a suitable duration of a TLT based on temporal profiles of uncertainty about critical care and outcome.

    Materials and methods

    The study included very old patients (age ≥ 80 years, n = 1209) from the VIP2 study cohort who were admitted to the ICU for between 2 and 14 days, with respiratory or circulatory support from day 1 and with either no limitations of life-sustaining treatment or a decision to withdraw that treatment, as well as with complete data. Multi-state modelling of critical care trajectories to obtain time-dependent probabilities for transitions between distinct levels of organ support and to outcome states. The extent of uncertainty is quantified by Shannon's entropy of probability distributions at discrete points in time.

    Results

    We detected periods of enhanced prognostic uncertainty of up to 7 days after admission. The duration of these periods depends on patient characteristics at baseline (frailty, severity of critical illness) and the extent of organ support.

    Conclusion

    Time-dependent patterns of uncertainty concerning the response to critical care can inform decisions about the duration of TLTs which may last up to a week in very old patients.

authors

  • Beil, Michael
  • Flaatten, Hans
  • Guidet, Bertrand
  • Joskowicz, Leo
  • Jung, Christian
  • de Lange, Dylan
  • Leaver, Susannah
  • Fjølner, Jesper
  • Szczeklik, Wojciech
  • Sviri, Sigal
  • van Heerden, Peter Vernon

publication date

  • October 2022