Division of Psychiatry, Marie Curie Palliative Care Research Departent, University College London, London, UK
Department of Primary Care & Public Health Sciences, King's College London, London, UK.
BMJ Support Palliat Care. 2022 Dec;12(e6):e785-e791. doi: 10.1136/bmjspcare-2018-001761. Epub 2019 May 10.
To determine the accuracy of predictions of dying at different cut-off thresholds and to acknowledge the extent of clinical uncertainty.
Secondary analysis of data from a prospective cohort study.
An online prognostic test, accessible by eligible participants across the UK.
Eligible participants were members of the Association of Palliative Medicine. 99/166 completed the test (60%), resulting in 1980 estimates (99 participants × 20 summaries).
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.
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%.
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.
确定不同截断阈值下死亡预测的准确性,并承认临床不确定性的程度。
对一项前瞻性队列研究数据的二次分析。
在线预后测试,符合条件的参与者可在英国各地使用。
符合条件的参与者是姑息医学协会的成员。99/166 人完成了测试(60%),产生了 1980 个估计值(99 名参与者×20 个总结)。
20 个患者总结中 72 小时内死亡的概率(0%确定存活-100%确定死亡)。使用五个不同的阈值分析估计值:50/50%、40/60%、30/70%、20/80%和 10/90%,这些极端值之间的百分比值被视为“不确定”。计算每个截止值的阳性预测值(PPV)、阴性预测值(NPV)和不确定病例数。
使用<50%与>50%的阈值产生的 PPV 为 62%,NPV 为 74%,不确定病例为 5%。当阈值更改为≤10%与≥90%时,PPV 和 NPV 分别提高到 75%和 88%,但不确定病例数增加到 62%。
当医生给出非常高(≥90%)或非常低(≤10%)的即将死亡概率时,他们的预后准确性会提高;然而,这会增加“不确定”病例的数量。这表明临床预测可能继续在常规预后中发挥作用,但对于那些医生估计不确定的病例,可能需要其他方法(如预后评分的使用)。