Department of Palliative Care and Rehabilitation Medicine, The University of Texas M.D. Anderson Cancer Center, 1515 Holcombe Blvd., Houston, TX 77030, USA.
J Palliat Med. 2012 Aug;15(8):902-9. doi: 10.1089/jpm.2011.0437. Epub 2012 Jun 4.
Acute palliative care units (APCUs) provide intensive symptom support and transition of care for advanced cancer patients. Better understanding of the predictors of in-hospital mortality is needed to facilitate program planning and patient care. In this prospective study, we identified predictors of APCU mortality, and developed a four-item In-hospital Mortality Prediction in Advanced Cancer Patients (IMPACT) predictive model.
Between April and July 2010, we documented baseline demographics, the Edmonton Symptom Assessment Scale (ESAS), 80 clinical signs including known prognostic factors, and 26 acute complications on admission in consecutive APCU patients. Multivariate logistic regression analysis was used to identify factors for inclusion in a nomogram, which was cross-validated with bootstrap analysis.
Among 151 consecutive patients, the median age was 58, 13 (9%) had hematologic malignancies, and 52 (34%) died in the hospital. In multivariate analysis, factors associated with in-hospital mortality were advanced education (odds ration [OR]=11.8, p=0.002), hematologic malignancies (OR=8.6, p=0.02), delirium (OR=4.3, p=0.02), and high ESAS global distress score (OR=20.8, p=0.01). In a nomogram based on these four factors, total scores of 6, 10, 14, 17, and 21 corresponded to a risk of death of 10%, 25%, 50%, 75%, and 90%, respectively. The model has 92% sensitivity and 88% specificity for predicting patients at low/high risk of dying in the hospital, and a receiver-operator characteristic curve concordance index of 83%.
Higher education was associated with increased utilization of the interdisciplinary palliative care unit until at the end of life. Patients with higher symptom burden, delirium, and hematologic malignancies were also more likely to require APCU care until death.
急性姑息治疗病房（APCUs）为晚期癌症患者提供强化症状支持和护理过渡。为了便于规划项目和患者护理，需要更好地了解院内死亡率的预测因素。在这项前瞻性研究中，我们确定了 APCU 死亡率的预测因素，并开发了一个四项目的先进癌症患者院内死亡预测（IMPACT）预测模型。
在 2010 年 4 月至 7 月期间，我们记录了连续入住 APCU 的患者的基线人口统计学数据、埃德蒙顿症状评估量表（ESAS）、80 种临床体征（包括已知的预后因素）和 26 种急性并发症。采用多变量逻辑回归分析确定纳入列线图的因素，并用 bootstrap 分析进行交叉验证。
在 151 例连续患者中，中位年龄为 58 岁，13 例（9%）患有血液恶性肿瘤，52 例（34%）在院内死亡。多变量分析显示，与院内死亡相关的因素包括高等教育（比值比[OR]=11.8，p=0.002）、血液恶性肿瘤（OR=8.6，p=0.02）、谵妄（OR=4.3，p=0.02）和 ESAS 全球困扰评分高（OR=20.8，p=0.01）。在基于这四个因素的列线图中，总分 6、10、14、17 和 21 分别对应于 10%、25%、50%、75%和 90%的死亡风险。该模型对低/高院内死亡风险患者的预测具有 92%的敏感性和 88%的特异性，受试者工作特征曲线一致性指数为 83%。
高等教育与姑息治疗团队的使用增加有关，直到生命的最后阶段。症状负担较高、谵妄和血液恶性肿瘤的患者也更有可能需要 APCU 护理直至死亡。
