The Impact of Time of Admission on the Delivery of Care and Outcomes in High Risk Patients with Acute Leukemia

Abstract BACKGROUND At a large academic teaching hospital, there are a variety of physicians and midlevel providers at the point of initial contact, and the extent of supervision of specifically trained oncology personnel may vary based on time of admission. Patients with acute leukemia may present with high risk disease processes that must be recognized and require prompt intervention to reduce both morbidity and short-term mortality. This is a retrospective review of the delivery of care at admission and key clinical outcomes for high risk patients presenting with acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL) based on time of admission. The hypothesis of this study was that high risk patients with AML or ALL admitted overnight may have significant delays in management of the complications of acute leukemia with subsequent increases in morbidity and short-term mortality. METHODS An institutional electronic database was queried to identify patients with ICD9 codes specific for AML/ALL. Inclusion criteria consisted of adults >18 years admitted to a single institution from 2010-2013. Key clinical data were then abstracted from the electronic medical records including lab values, time of admission (Daytime: 7am-8pm vs Nightime: 8pm-7am), and specific clinically important outcomes (time to specific therapy, time to chemotherapy, length of stay, ICU length of stay, organ failure, and mortality). Patients were categorized as high risk if they met established criteria requiring specific intervention [hyperleukocytosis defined as WBC >50 10^9/L, hyperuricemia defined as uric acid >8 mg/dL, and clinical suspicion for acute promyleocytic leukemia (APL)]. Variables with binary outcomes were tested for association with overnight admission using Fisher's exact test. All other variables were tested using the Wilcoxon two-group test. RESULTS Between 2010 and 2013, 161 patients with AML/ALL were included in our analysis. Of those, 66 were classified as high risk (Table 1). In the high risk patients there were no significant differences in time to intervention based on time of admission including patients presenting with hyperleukocytosis and time to hydroxyurea administration (p=.32), patients presenting with hyperuricemia and time to allopurinol administration (p=.71) or rasburicase administration (p=.22), and in time to tretinoin (ATRA) administration in patients presenting with APL (p=.23). Time to definitive chemotherapy was significantly less for high risk patients admitted overnight (overnight median=48 hours, day median=56 hours, p=.042). However, rates of mechanical ventilation (p=.09), vasopressor usage (p=.37), and renal failure (p=.43) appeared similar between the groups. Additionally, length of stay (p=.83) and ICU length of stay (p=.44) was not significantly different for the two groups. 30-day mortality did not statistically differ between the two groups (overnight=19.4%, daytime=20%, p=.57). CONCLUSIONS This is the first comprehensive analysis of the impact of the time of admission of acute leukemia patients at an academic tertiary cancer hospital, to our knowledge. Interestingly, nighttime admissions did not appear to significantly impact time to key clinical interventions or clinical outcomes in high risk patients admitted with acute leukemia. Although time to definitive chemotherapy was found to be significantly less in patients admitted overnight, confounding variables such as severity of illness at the time of admission may have impacted this analysis, and 30-day mortality rates were similar. Overall, this data supports the triage of patients with newly diagnosed or suspected acute leukemia to tertiary care centers as soon as possible. Table 1 . Baseline Characteristics of High Risk Patients Age at Diagnosis Number % 31 47.0 50-64 24 36.3 65+ 11 16.7 Sex Male 38 57.6 Diagnosis Number % AML (Excluding APL) 37 56.1 APL 18 27.2 ALL 11 16.7 High Risk Features Hyperleukocytosis 42 63.6 Hyperuricemia 20 30.3 APL 18 27.2 >1 High Risk Feature 66 100.0 Initial Point of Contact Number % Referring Hospital 45 68.2 Admission Time Number % Day Shift (7a-8p) 30 45.5 Night Shift (8p-7a) 36 54.5 Admission Location Number % Oncology Inpatient Service 53 80.3 Internal Medicine Inpatient Service 2 3.0 Medical ICU 11 16.7 Disclosures Foster: Celgene: Research Funding.