Moman Rajat N, Loprinzi Brauer Caitlin E, Kelsey Katherine M, Havyer Rachel D, Lohse Christine M, Bellolio M Fernanda
Department of Emergency Medicine, Rochester, MN.
Mayo Clinic, and the Mayo Clinic School of Medicine, Rochester, MN.
Acad Emerg Med. 2017 Jul;24(7):822-831. doi: 10.1111/acem.13197. Epub 2017 May 29.
The Choosing Wisely campaign has called for better engagement of palliative and hospice care services for patients in the emergency department (ED). PREDICT is a clinical prediction tool that was derived in an Australian ED cohort. It assesses a patient's risk of mortality at 1 year to select those who would benefit from advanced care planning. Such goals-of-care discussion can improve patients' ability to communicate what they want out of their healthcare and, in cases of end of life, potentially reduce the number of futile interventions. Using a cutoff of 13 points, PREDICT had a reported 95.3% specificity and 53.9% sensitivity for 1-year mortality. We externally validated PREDICT and derived a simpler modified PREDICT tool to systematically identify high-risk patients eligible for goals-of-care discussions and palliative care consultation in the ED.
This was an observational cohort study of a random sample of 927 patients aged 55+ seen in the ED in 2014. We identified advance healthcare directives (AHDs) on file. We summarized diagnostic accuracy of the clinical tool to predict 1-year mortality using sensitivity, specificity, and area under the curve (AUC). We refined PREDICT using multivariable modeling. We followed reporting guidelines including STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) for cohort studies and Standards for Reporting of Diagnostic Accuracy (STARD).
A total of 927 patients were included: 55.0% were male, 63 (7.0%) were nursing home residents, 389 (42.0%) patients had an AHD in their medical record at the time of ED visit, and 245 (26.4%) were deceased at 1 year. Of the 780 patients with PREDICT scores < 13, a total of 164 (21.0%; 95% confidence interval [CI] = 18.3-24.1) were deceased at 1 year, and of the 147 patients with PREDICT scores ≥ 13, a total of 81 (55.1%; 95% CI = 46.7-63.2) were deceased at 1 year. The AUC of the PREDICT score was 0.717 (95% CI = 0.680-0.754), sensitivity was 33.1% (95% CI = 27.3-39.4), and specificity was 90.3% (95% CI = 87.8-92.4) to predict 1-year mortality. The modified PREDICT tool resulted in an AUC of 0.709 (95% CI = 0.671-0.747). We decided to select this model as the preferred model, as the variable of intensive care unit (ICU) admission with multiorgan failure can be difficult to assess in the ED and may delay advanced care planning. Reweighting the score did not improve fit or the AUC, so points assigned to each variable were not adjusted.
PREDICT is an easy tool to administer to be able to identify patients who are at high risk of 1-year mortality and who could benefit from AHDs, goals-of-care discussion, and when appropriate in the context of an end-of-life setting, palliative medicine consultation. External validation of PREDICT was successful in our population. We simplified PREDICT and derived a new tool, the modified PREDICT minus ICU tool, without significantly altering the sensitivity, specificity, and AUC for death at 1 year. The next steps include external validation of the newly derived rule and prospective implementation.
“明智选择”运动呼吁急诊科更好地为患者提供姑息治疗和临终关怀服务。PREDICT是一种临床预测工具,源自澳大利亚急诊科队列研究。它评估患者1年内的死亡风险,以筛选出能从预立医疗计划中受益的患者。这种医疗目标讨论可以提高患者表达自身医疗需求的能力,在临终情况下,还可能减少无效干预的数量。据报告,PREDICT以13分为临界值时,对1年死亡率的特异性为95.3%,敏感性为53.9%。我们对PREDICT进行了外部验证,并推导出一个更简单的改良PREDICT工具,以系统地识别急诊科中符合医疗目标讨论和姑息治疗咨询条件的高危患者。
这是一项对2014年在急诊科就诊的927名55岁及以上患者的随机样本进行的观察性队列研究。我们确定了存档的预立医疗指示(AHD)。我们使用敏感性、特异性和曲线下面积(AUC)总结了该临床工具预测1年死亡率的诊断准确性。我们使用多变量模型对PREDICT进行了优化。我们遵循了报告指南,包括队列研究的加强流行病学观察性研究报告(STROBE)和诊断准确性报告标准(STARD)。
共纳入927名患者:55.0%为男性,63名(7.0%)是养老院居民,389名(42.0%)患者在急诊科就诊时病历中有AHD,245名(26.4%)在1年后死亡。在PREDICT评分<13的780名患者中,共有164名(21.0%;95%置信区间[CI]=18.3 - 24.1)在1年后死亡;在PREDICT评分≥13的147名患者中,共有81名(55.1%;95%CI = 46.7 - 63.2)在1年后死亡。PREDICT评分的AUC为0.717(95%CI = 0.680 - 0.754),预测1年死亡率的敏感性为33.1%(95%CI = 27.3 - 39.4),特异性为9