Prognostic Modelling for Prediction of Mortality and Functional Disability in Critically-ill Elderly Patients

Study Design This is a prospective observational study to develop \& validate a prognostic predictive model to predict ICU mortality (primary outcome) using Multi-Biomarkers concept. The study design for Predictive Modelling Study (Prognostic) will be "Type 2a: Nonrandom split-sample development and validation" study design according to "Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis".

3.2 Study Sites

• General ICU, Hospital Universiti Sains Malaysia
• Intensive Care Unit, Sultan Ahmad Shah Medical Center (SASMEC)
• Intensive Care Unit, Hospital Queen Elizabeth
• Intensive Care Unit, Hospital Queen Elizabeth II

3.3 Study Duration Part of the study already ongoing in General ICU, Hospital Universiti Sains Malaysia and Intensive Care Unit SASMEC. Study duration will start in both Hospital Queen Elizabeth and Hospital Queen Elizabeth II when approval from MREC is obtained. Study duration expected for 2 years, estimated to complete in the end of 2023. Tentatively, it will start on 1st of June 2022 till 31st December 2022.

3.4 Target Population: Inclusion \& Exclusion Criteria 3.4.1 Inclusion Criteria

• All patients admitted to ICU age > 65 years old 3.4.2 Exclusion Criteria
• Readmission into participating ICU within the same hospital admission 3.5 Sample Size The number of ICU admission over the suggested 3-year period in the four participating ICUs is expected to be around 2256. Using estimated proportion of elderly of 0.52, at desired precision of estimate of 0.05, confidence level of 0.95 and population size of 2256, the sample size required is at least 329 elderly patients.

3.6 Sampling Method Sampling method that will be employed is consecutive sampling, starting from the set period of study duration (earliest patient record in the database) until completion of 329 patients enrolled

3.7 Outcome Measures

• Primary Outcome
• Risk factors contributing towards Mortality in the ICU: Death occurred during ICU stay
• Measurement method: Prospective clinical data collection \& biomarkers measurement
• Time point measurement: On ICU admission and throughout ICU Stay
• Secondary Outcome
• Risk factors contributing towards Mortality in the Hospital: Death occurred during hospital stay after discharged from the ICU Measurement method: Prospective clinical data collection \& biomarkers measurement. Determination of Hospital death is by daily follow-up of patient survival status in the ward after ICU discharge Time point measurement: On ICU admission and throughout ICU Stay for the risk factors and prospectively seeing the outcome of death in hospital after ICU discharge
• Risk factors contributing towards 6-month Mortality post-ICU admission: Survival status at 6-months Measurement method: Prospective clinical data collection \& biomarkers measurement. Determination of death by interview via communication with family member at 6-month after first day of ICU admission Time point measurement: On ICU admission and throughout ICU Stay for the risk factors and prospectively seeing the outcome of death after hospital discharge at 6-month counting from the first day of ICU admission
• Risk factors contributing towards Severe Functional Disability at 6-month post-ICU admission: at 6-month after first day ICU admission Measurement method: Prospective clinical data collection \& biomarkers measurement and Questionnaire using Barthel-Index Score via telephone/other types of communication Time point measurement: On ICU admission and throughout ICU Stay for the risk factors and prospectively seeing the outcome of Severe Functional Disability after hospital discharge 6-month counting from the first day of ICU admission

3.8 Data Collection 3.8.1 Data Collection Form Data will be collected and collected into a de-identified physical CRF 3.8.2 Data to be collected All the necessary demographic data as well as previous variables found to be significant in previous studies looking into prognostic factors of the elderly. Multi-biomarker investigations will be performed on the patients upon admission. In addition, as much data as possible that was collected from the database will be entered into the prognostic modeling to improve the robustness of the prognostic model.