Importance Major postoperative complications and delirium contribute independently to adverse outcomes and high resource utilization in patients undergoing major surgery; however, their inter-relationship is not well-examined. Objective To evaluate the association of major postoperative complications and delirium, alone and in combination, with adverse outcomes after surgery. Design Prospective cohort study. Setting Two large academic medical centers. Participants Patients without recognized dementia or history of delirium, age 70 and older who underwent elective major orthopedic, vascular, and abdominal surgeries with a minimum 3-day hospitalization. Main Outcome and Measures Major postoperative complications, defined as life altering or threatening events (Accordion Severity ≥ grade 2), were identified by expert panel adjudication. Delirium was measured daily with the Confusion Assessment Method and a validated chart review method. Four subgroups were analyzed: (1) no complications, no delirium; (2) complications alone; (3) delirium alone; and (4) both complications and delirium. Adverse outcomes included length of stay (LOS) > 5 days, institutional discharge, and rehospitalization within 30 days of discharge. Results Of 566 participants, mean age (±SD) was 76.7± 5.2 years, 42% male and 92% white. Forty-seven (8%) developed major complications, and 135 (24%) developed delirium. When compared to no complications, no delirium as the reference group, major complications alone contributed only to prolonged LOS (RR 2.8, 95% CI 1.9–4.0); by contrast, delirium alone significantly increased all adverse outcomes, including prolonged LOS (RR 1.9, 95% CI 1.4–2.7), institutional discharge (RR 1.5, 95% CI 1.3–1.7), and 30-day readmission (RR 2.3, 95% CI 1.4–3.7). The subgroup with both complications and delirium had the highest rates of all adverse outcomes, including prolonged LOS (RR 3.4, 95% CI 2.3–4.8), institutional discharge (RR 1.8, 95% CI 1.4–2.5) and 30-day readmission (RR 3.0, 95% CI 1.3–6.8). Delirium exerted the highest attributable risk at a population level (5.8%, 95% CI 4.7–6.8) compared with all other adverse events (prolonged LOS, institutional discharge, or readmission). Conclusions and Relevance Major postoperative complications and delirium are separately associated with adverse events and demonstrate a strong combined effect. Delirium occurs more frequently, and has greater impact at the population level than other major complications.

A facilitated discussion about end-of-life care between patients and their health care agents helps define and document the patient's wishes for both patient and agent.

Background and Objectives: While there are qualitative studies examining the delirium-related experiences of patients, family caregivers, and nurses separately, little is known about common aspects of delirium burden among all three groups. We describe common delirium burdens from the perspectives of patients, family caregivers, and nurses. Research Design and Methods: We conducted semistructured qualitative interviews about delirium burden with 18 patients who had recently experienced a delirium episode, with 16 family caregivers, and with 15 nurses who routinely cared for patients with delirium. We recruited participants from a large, urban teaching hospital in Boston, Massachusetts. Interviews were recorded and transcribed. We used interpretive description as the approach to data analysis. Results: We identified three common burden themes of the delirium experience: Symptom Burden (Disorientation,

Importance: Measurement of delirium severity has been recognized as highly important for tracking prognosis, monitoring response to treatment, and estimating burden of care both during and after hospitalization. Rather than simply rating delirium as present or absent, the ability to quantify its severity will enable development and monitoring of more effective treatment approaches for delirium. Objective: This study had 3 major goals: to present a comprehensive review of delirium severity instruments; to conduct a methodologic quality rating of the original validation study of the most commonly used instruments; and to select a group of top-rated instruments. Evidence Review: Using key words, subject headings, and full text approaches, we conducted a systematic review of the following databases,

ORIGINAL RESEARCHwith a model developed using traditional stepwise logistic regression (AUC = 0.69, 95% CI 0.57-0.82). Calibration for all models and feature sets was poor. CONCLUSIONS: We developed machine learning prediction models for post-operative delirium that performed better than chance and are comparable with traditional stepwise logistic regression. Delirium proved to be a phenotype that was difficult to predict with appreciable accuracy.