Exploring the weekend effect and other predictors of mortality in tumor lysis syndrome among hospitalized adults.

e23137 Background: Tumor lysis syndrome (TLS) is an oncologic emergency characterized by rapid cell lysis and metabolic disturbances leading to potentially fatal complications. While TLS is well understood, some limited evidence suggests patients admitted on weekends experience worse outcomes, potentially reflecting disparities in access to timely oncologic care and resources. We hypothesized that TLS not only has a robust weekend effect, but that this effect may be mediated by procedural delays over the weekend. Methods: We performed a retrospective analysis using the 2017–2019 National Inpatient Sample (NIS) dataset to identify hospitalized TLS patients based on ICD-10 codes (E88.3). Key variables included mortality, weekend admission, demographics, hospital teaching status, Charlson comorbidity index, and procedural data. Logistic regression assessed mortality predictors, with model performance evaluated via ROC analysis. Results: A total of 8,650 TLS hospitalizations were included. The median age was 64 years (IQR: 51–73), with 37% being female. The population was 66% White, 14% Black, 11% Hispanic, 4% Asian/Pacific Islander, 0.4% Native American, and 5% classified as Other. The median comorbidity score was 4 (IQR: 2–6).The final logistic regression model demonstrated a moderate discriminatory ability with an AUC of 0.71. Mortality and Weekend Effect: Overall mortality rate was 22.2%, with higher rates in weekend admissions (27.2%) compared to weekday admissions (21.1%). (p = 0.003, OR: 1.25, 95% CI: 1.08–1.44). Analysis of Procedures: Procedures performed on the day of admission significantly predicted mortality (OR: 1.11, 95% CI: 1.06–1.17, p < 0.001). No significant interaction between admission day procedures and weekend admission was present. (OR: 1.06, 95% CI: 0.97–1.16, p = 0.24). Predictors of Mortality: Age (OR: 1.02, 95% CI: 1.02–1.02, p < 0.001), gender, and Charlson Comorbidity Index (OR: 1.15, 95% CI: 1.13–1.18, p < 0.001) were significant predictors of mortality. Female patients were found to have increased risk (OR: 1.14, 95% CI: 1.02–1.28, p = 0.016). Conclusions: Our analysis identifies further predictors of mortality in TLS and confirms the presence of the weekend effect; however, procedural factors were not found to be linked to the phenomenon. Variability in staffing levels or institutional factors may account for this disparity. Future quality improvement initiatives aimed at improving weekend care processes may help further understand and mitigate these disparities and enhance outcomes in TLS patients.