Literature DB >> 31076463

Imminent death: clinician certainty and accuracy of prognostic predictions.

Nicola White1, Fiona Reid2, Victoria Vickerstaff3, Priscilla Harries4,5, Christopher Tomlinson6, Patrick Stone7.   

Abstract

OBJECTIVES: To determine the accuracy of predictions of dying at different cut-off thresholds and to acknowledge the extent of clinical uncertainty.
DESIGN: Secondary analysis of data from a prospective cohort study.
SETTING: An online prognostic test, accessible by eligible participants across the UK. PARTICIPANTS: Eligible participants were members of the Association of Palliative Medicine. 99/166 completed the test (60%), resulting in 1980 estimates (99 participants × 20 summaries). MAIN OUTCOME MEASURES: The probability of death occurring within 72 hours (0% certain survival-100% certain death) for 20 patient summaries. The estimates were analysed using five different thresholds: 50/50%, 40/60%, 30/70%, 20/80% and 10/90%, with percentage values between these extremes being regarded as 'indeterminate'. The positive predictive value (PPV), negative predictive value (NPV) and the number of indeterminate cases were calculated for each cut-off.
RESULTS: Using a <50% versus >50% threshold produced a PPV of 62%, an NPV of 74% and 5% indeterminate cases. When the threshold was changed to ≤10% vs ≥90%, the PPV and NPV increased to 75% and 88%, respectively, at the expense of an increase of indeterminate cases up to 62%.
CONCLUSION: When doctors assign a very high (≥90%) or very low (≤10%) probability of imminent death, their prognostic accuracy is improved; however, this increases the number of 'indeterminate' cases. This suggests that clinical predictions may continue to have a role for routine prognostication but that other approaches (such as the use of prognostic scores) may be required for those cases where doctors' estimates are indeterminate. © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Entities:  

Keywords:  clinical decisions; palliative care; prognosis

Year:  2019        PMID: 31076463     DOI: 10.1136/bmjspcare-2018-001761

Source DB:  PubMed          Journal:  BMJ Support Palliat Care        ISSN: 2045-435X            Impact factor:   3.568


  1 in total

1.  Temporal convolutional networks allow early prediction of events in critical care.

Authors:  Finneas J R Catling; Anthony H Wolff
Journal:  J Am Med Inform Assoc       Date:  2020-03-01       Impact factor: 4.497

  1 in total

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