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Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...
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Related Experiment Video

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Clinical Anthropometrics and Body Composition from 3-Dimensional Optical Imaging
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Assessing fitness, predicting outcome, and the missing axis.

J B Carlisle1

  • 1Department of Anaesthetics, Torbay Hospital, South Devon Healthcare NHS Foundation Trust, Lawes Bridge, Torquay, Devon TQ2 7AA, UK. john.carlisle@nhs.net

British Journal of Anaesthesia
|June 2, 2012
PubMed
Summary

Estimating postoperative mortality risk is crucial for surgical patients. This article also highlights the challenge of assessing surgery

Area of Science:

  • Medical Statistics
  • Surgical Outcomes
  • Patient Quality of Life

Background:

  • Postoperative mortality affects a significant patient minority after surgery.
  • Assessing the impact of surgery on survivors' quality of life remains a challenge.
  • Current survival metrics often omit quality of life considerations.

Purpose of the Study:

  • To provide methods for estimating the risk of postoperative death.
  • To address the critical gap in evaluating surgery's effect on quality of life.
  • To highlight the 'missing axis' in postoperative survival analysis.

Main Methods:

  • Discussion of risk estimation calculations for postoperative mortality.
  • Exploration of methodologies to characterize quality of life changes post-surgery.

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  • Reference to online resources for risk assessment tools.
  • Main Results:

    • Provides a framework for calculating postoperative mortality risk.
    • Identifies the deficiency in current analyses regarding quality of life.
    • Emphasizes the need to incorporate quality of life into survival assessments.

    Conclusions:

    • Accurate estimation of postoperative death risk is essential.
    • There is a significant need to develop methods for assessing quality of life after surgery.
    • A comprehensive understanding of surgical outcomes requires considering both survival and quality of life.