INTRODUCTION-Leukaemia is the most common cancer in children. Three-fourth of these cases are acute lympoblastic leukaemia (ALL). The 5- year survival rate of ALL is around 90% and for acute myelogenous leukaemia (AML) is around 65-70%. Two-thirds of these children get admitted to the ICU for various reasons, the commonest being sepsis. Other common reasons for ICU admission are tumor lysis syndrome, respiratory failure, circulatory collapse, bleeding. Improving survival in pediatric haematological malignancies over the years can be attributed to newer and more aggressive administration of chemotherapeutic drugs, improvement in supportive care, identifying and treating children with fever and neutropenia, prevention of opportunistic infections and administration of blood products when necessary. ALL are risk stratified based on their age, presentation features, tumour genetics and treatment response. High risk includes B Cell Precursor-ALL patients with any high-risk feature, including high-risk genetics, central nervous system leukaemia, T-lineage ALL, poor response to prednisolone at treatment on day 8 and high MRD (≥ 0·01%) at the end of induction phase. AML are risk stratified based on age, cytogenetics, molecular features and treatment response.

HYPOTHESIS- The high morbidity and mortality in critically ill paediatric oncology patients stem from both aggressive cancer pathophysiology (organ infiltration and immunodeficiency) and intensive anti-neoplastic therapies, which can cause systemic toxicity. Haematological malignancies cause significant myelosuppression and the intensive phage of chemotherapy adds to the toxicity and this cohort has the highest risk of life threatening infections. Induction phase of leukaemia and lymphoma are part of high risk diagnosis in severity of illness scores and account for high resource utilization. In this study we want to evaluate the outcomes of children admitted to the ICU during various phases of treatments. This will help us guide decisions regarding triaging decisions and resource allocation.

METHODOLOGY-We aim to retrospectively analyse the data collected from Electronic Medical Records of patients less than 18 years, with provisional or confirmed diagnosis of acute leukaemia (AML, ALL) admitted to the ICU from January 2022 to December 2022, to understand the impact of the stage of treatment on the ICU outcomes.

STATISTICAL ANALYSIS- The statistical analysis plan encompasses descriptive statistics, survival analysis using Kaplan-Meier curves and log-rank tests, multivariate analyses employing Cox proportional hazards regression to adjust for confounders, stratified and subgroup analyses, as well as sensitivity analyses to ensure the robustness of the findings. Categorical variables (e.g., gender, oncological stage) will be represented in the form of frequencies and percentages and continuous variables (e.g., age, duration of ICU stay) will be represented as mean and standard deviations. Kaplan-Meier survival analysis will be done to determine the mortality rate at various oncological stages of treatment in the acute leukaemia paediatric populations in an ICU. Log-rank test will be done to compare survival curves between different oncological stages.Multivariate Analysis will be done using Cox proportional hazards regression model to assess the impact of the oncological stage and other relevant variables such as severity and duration of neutropenia, severity of illness scores (PRISM 3/PIM3), SOFA, need for ventilation, need for vasopressors, need for RRT, etc., on mortality.