What is a PIM 3 calculator?
A PIM 3 calculator estimates mortality risk for children admitted to a pediatric intensive care unit (PICU) using the PIM3 (Pediatric Index of Mortality 3) model. It combines early admission data—such as blood pressure, ventilation status, blood gas values, and diagnostic risk categories—into a single predicted probability.
This estimate is typically used for benchmarking and quality reporting across groups, not for making life-and-death decisions for one patient in isolation.
How to use this calculator
Step-by-step inputs
- Pupils fixed: Select “Yes” if pupils are fixed to bright light.
- Elective admission: Mark if the ICU admission is elective.
- Mechanical ventilation: Indicate ventilation in the first ICU hour.
- Systolic BP: Enter initial systolic blood pressure (mmHg).
- Base excess: Enter measured base excess (mmol/L), including negative values.
- FiO₂ and PaO₂: Enter oxygen fraction and arterial oxygen values from early assessment.
- Recovery category: Choose the applicable procedural recovery classification.
- Diagnosis risk: Select low/high/very high risk category if applicable.
Understanding the output
The result is shown as a predicted mortality percentage. A higher value means higher predicted risk according to the model. The tool also displays the underlying logit score used in the logistic equation.
Why clinicians use PIM 3
- To compare expected versus observed outcomes at unit level.
- To support case-mix adjustment in audit and research.
- To track quality improvement over time.
- To standardize risk estimation across different PICUs.
Important limitations
Not a stand-alone clinical decision tool
PIM3 is a statistical model. It does not capture every factor influencing an individual patient’s prognosis. Clinical judgment, bedside trends, imaging, comorbidities, and team context remain essential.
Calibration varies by setting
Performance can change between countries, institutions, and time periods. Always use local governance, current validation, and the official definitions for each variable.
Data quality matters
Small input errors (especially blood gas or category coding) can shift results significantly. Standardized data collection procedures are crucial.
Practical tips for better accuracy
- Enter values measured as early as possible in PICU admission.
- Confirm unit consistency (FiO₂ as fraction, not percent).
- Use strict local definitions for diagnosis and procedure categories.
- Re-check extreme values before interpreting outputs.