90-Day Mortality After Emergency Department Discharge in Advanced Cancer

Overview

This retrospective observational study investigates factors associated with 90-day mortality among patients with advanced cancer who present to the emergency department (ED). The study will include stage IV solid tumor patients who visited the ED of Etlik City Hospital between December 2022 and March 2025. Demographic, clinical, and laboratory parameters such as performance status, nutritional and inflammatory markers, and biochemical values will be analyzed. The primary objective is to identify prognostic indicators that predict short-term mortality following ED visits. By establishing risk profiles, the study aims to optimize patient triage, guide timely referral to supportive and palliative care services, and improve overall care strategies for advanced cancer patients in acute settings.

Patients with advanced-stage cancer frequently present to emergency departments (EDs) due to complications related to disease progression, treatment side effects, or acute clinical deterioration. Such unplanned visits represent a critical point in the trajectory of cancer care, as they are often associated with poor short-term outcomes, repeated hospitalizations, and increased healthcare burden. Identifying reliable predictors of mortality following ED discharge is therefore essential for improving triage processes, tailoring management strategies, and ensuring timely referral to supportive or palliative care. This retrospective cohort study will evaluate prognostic factors associated with 90-day mortality among patients with stage IV solid tumors presenting to the ED of Etlik City Hospital between December 2022 and March 2025. The study population will consist of patients who were discharged on the same day, admitted to the hospital, or who died during their ED visit. Clinical data will be retrieved from the hospital information system, and mortality outcomes will be verified using both institutional records and the national death registry. Collected parameters will include demographic variables (age, sex, body mass index, smoking history), disease characteristics (primary tumor type, metastatic sites, prior systemic treatment), performance status (ECOG score), and laboratory values routinely obtained during ED visits (hemoglobin, leukocyte and platelet counts, neutrophil-to-lymphocyte ratio, C-reactive protein, albumin, lactate dehydrogenase, renal and liver function tests, and electrolytes). The primary endpoint will be 90-day all-cause mortality after ED presentation. Secondary outcomes will include in-hospital mortality during ED stay, 30-day ED re-admission rates, and 90-day re-hospitalizations. Statistical analyses will be conducted to assess associations between clinical and laboratory variables and short-term mortality. Group comparisons will be performed using chi-square tests, Fisher's exact test, independent t-test, or Mann-Whitney U test, as appropriate. Multivariable logistic regression models will identify independent predictors of 90-day mortality, while Kaplan-Meier and Cox regression analyses will explore survival differences across patient subgroups stratified by ECOG status, albumin, BMI, and inflammatory markers. Post-hoc power analysis will be conducted to ensure robustness of the findings. Existing literature highlights the prognostic significance of poor performance status, malnutrition, and systemic inflammation in cancer patients presenting to EDs. Low serum albumin (\<3.5 g/dL), high neutrophil-to-lymphocyte ratio, low hemoglobin, and elevated LDH have consistently been associated with higher mortality risk. Similarly, unplanned ED visits often correlate with advanced disease burden, impaired quality of life, and reduced survival. However, most available studies are limited by small sample sizes, heterogeneous populations, or lack of integration between clinical and laboratory data. By analyzing a large cohort of 1,250-1,650 patients from a single tertiary cancer center, this study aims to overcome these limitations and provide a more comprehensive understanding of risk profiles in this vulnerable population. The findings are expected to contribute valuable insights into the early identification of high-risk patients at the time of ED admission. Ultimately, these results could support the development of evidence-based prognostic models that inform clinical decision-making, improve allocation of healthcare resources, and enhance the integration of supportive and palliative care interventions for patients with advanced malignancies.