科研之友
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摘要
Background: Early, data-driven discussion surrounding palliative care can improve care delivery and patient experience. Objective: To develop a 30-day mortality prediction tool for older patients in intensive care unit (ICU) with pneumonia that will initiate palliative care earlier in hospital course. Design: Retrospective Electronic Health Record (EHR) review. Setting: Four urban and suburban hospitals in a Western New York hospital system. Participants: A total of 1237 consecutive patients (>75 years) admitted to the ICU with pneumonia from July 2011 to December 2014. Measurements: Data abstracted included demographics, insurance type, comorbidities, and clinical factors. Thirty-day mortality was also determined. Logistic regression identified predictors of 30-day mortality. Area under the receiver operating curve (ROC) was calculated to quantify the degree to which the model accurately classified participants. Using the coordinates of the ROC, a predicted probability was identified to indicate high risk. Results: A total of 1237 patients were included with 30-day mortality data available for 100% of patients. The mortality rate equaled 14.3%. Age >85 years, having active cancer, Congestive Heart Failure (CHF), Chronic Obstructive Pulmonary Disease (COPD), sepsis, and being on a vasopressor all predicted mortality. Using the derived index, with a predicted probability of mortality >0.146 as a cutoff, sensitivity equaled 70.6% and specificity equaled 65.6%. The area under the ROC was 0.735. Conclusion: Our risk tool can help care teams make more informed decisions among care options by identifying a patient group for whom a careful review of goals of care is indicated both during and after hospitalization. External validation and further refinement of the index with a larger sample will improve prognostic value.
- 出版日期2018-9
