Abstract illustration of pediatric mortality risk assessment

Decoding Mortality: How Well Do Pediatric Scoring Systems Work?

"A deep dive into the Paediatric Index of Mortality (PIM) scores and their effectiveness in assessing risk in intensive care units."


In pediatric intensive care units (PICUs), accurately assessing a child's risk of mortality is crucial for guiding treatment decisions and evaluating the quality of care. Various mortality risk assessment scores have been developed to aid in this process, with the Paediatric Index of Mortality (PIM) and its updated version, PIM 2, being among the most widely used.

These scores, initially created and validated in specific populations and timeframes, need to be carefully evaluated before being applied in different environments. A recent study examined the utility of PIM and PIM 2 in the Red Cross War Memorial Children's Hospital (RCWMCH) in South Africa, the only children's hospital in sub-Saharan Africa providing exclusive tertiary and quaternary services for children.

This article delves into the findings of the study, comparing the performance of PIM and PIM 2 in the RCWMCH PICU with their performance in the units where they were initially derived. By exploring the scores' discrimination and calibration, this analysis sheds light on their effectiveness as mortality risk assessment tools in a unique healthcare setting.

How Accurate Are PIM and PIM 2 Scores?

Abstract illustration of pediatric mortality risk assessment

The study retrospectively audited case records and prospectively collected patient data from all admissions to the RCWMCH PICU during 2000 (for PIM) and 2006 (for PIM 2), excluding premature infants, children who died within 2 hours of admission, and those transferred to other PICUs. Researchers then analyzed this data to assess how well the PIM and PIM 2 scores predicted mortality in this specific population.

Discrimination refers to the ability of the score to differentiate between those who will survive and those who will not. Calibration, on the other hand, refers to how well the predicted mortality rates align with the actual observed mortality rates. The study assessed both of these aspects to determine the overall accuracy and reliability of the PIM and PIM 2 scores.

  • Discrimination: Both PIM and PIM 2 demonstrated good discrimination, with AUC values of 0.849 and 0.841, respectively. This indicates that both scores are reasonably effective at distinguishing between patients who will survive and those who will not.
  • Calibration: PIM showed poor calibration (x²=19.74; p=0.02), while PIM 2 demonstrated acceptable calibration (x²=10.06; p=0.35). This suggests that PIM 2's predicted mortality rates were more closely aligned with the actual observed mortality rates in the RCWMCH PICU than PIM's predictions.
  • Standardized Mortality Risk Ratios (SMRs): The SMRs for age and diagnostic subgroups for both scores fell within wide confidence intervals. This makes it difficult to draw definitive conclusions about the scores' performance within specific patient subgroups.
These findings suggest that while both scores have the ability to broadly differentiate risk, PIM 2 may be more reliable in predicting actual mortality rates for the overall PICU population at RCWMCH.

Implications for Pediatric Intensive Care

The study highlights the importance of evaluating mortality risk assessment models in different healthcare settings before relying on them for clinical decision-making. While PIM and PIM 2 have been validated in various populations, their performance can vary depending on the specific characteristics of the patient population and the healthcare environment.

The finding that PIM 2 demonstrated better calibration than PIM in the RCWMCH PICU suggests that it may be a more appropriate tool for assessing mortality risk in this specific setting. However, the wide confidence intervals for SMRs in age and diagnostic subgroups indicate the need for further research to evaluate the scores' performance in specific patient populations.

Ultimately, mortality risk assessment models like PIM and PIM 2 can be valuable tools for benchmarking quality of care and identifying areas for improvement in pediatric intensive care units. By carefully evaluating and calibrating these models, healthcare professionals can ensure that they are providing the best possible care for critically ill children.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: 10.7196/sajcc.166, Alternate LINK

Title: Paediatric Index Of Mortality Scores: An Evaluation Of Function In The Paediatric Intensive Care Unit Of The Red Cross War Memorial Children’S Hospital

Subject: Critical Care and Intensive Care Medicine

Journal: Southern African Journal of Critical Care

Publisher: South African Medical Association NPC

Authors: Lincoln John Solomon, Brenda M Morrow, Andrew Charles Argent

Published: 2014-07-08

Everything You Need To Know

1

What are PIM and PIM 2 scores, and why are they used?

The Paediatric Index of Mortality (PIM) and PIM 2 scores are mortality risk assessment models used in pediatric intensive care units (PICUs). They help clinicians assess a child's risk of death, which is crucial for guiding treatment decisions and evaluating the quality of care. These scores were developed to provide a standardized way to evaluate patient risk, improving the consistency and effectiveness of care. They were evaluated in the Red Cross War Memorial Children's Hospital (RCWMCH) in South Africa.

2

What does 'discrimination' mean in the context of PIM and PIM 2?

Discrimination in the context of PIM and PIM 2 refers to the score's ability to differentiate between patients who will survive and those who will not. The study found that both PIM and PIM 2 demonstrated good discrimination, with AUC values of 0.849 and 0.841 respectively. This means both scores are reasonably effective in distinguishing between patients who will survive and those who will not. This is important because it is a fundamental aspect of a risk assessment tool, to ensure that the score can actually differentiate between patients with different outcomes.

3

What does 'calibration' mean in the context of PIM and PIM 2?

Calibration, in the context of PIM and PIM 2, refers to how well the predicted mortality rates align with the actual observed mortality rates. The study revealed that PIM showed poor calibration, while PIM 2 demonstrated acceptable calibration. This suggests that the PIM 2’s predicted mortality rates were more closely aligned with the actual observed mortality rates in the RCWMCH PICU than PIM's predictions. Good calibration is crucial for the reliability of these scores because it ensures that the predicted risk accurately reflects the real risk of mortality.

4

Where was the study on PIM and PIM 2 conducted?

The study was conducted in the Red Cross War Memorial Children's Hospital (RCWMCH) PICU in South Africa. This hospital was chosen because it is the only children's hospital in sub-Saharan Africa providing exclusive tertiary and quaternary services for children. The study retrospectively audited case records and prospectively collected patient data from all admissions to the RCWMCH PICU during 2000 (for PIM) and 2006 (for PIM 2), excluding premature infants, children who died within 2 hours of admission, and those transferred to other PICUs. This specific setting allows the researchers to evaluate the utility of PIM and PIM 2 in a unique healthcare environment and compare their performance with their original validation units.

5

What are the key implications of the study's findings for the use of PIM and PIM 2?

The implications of the study are that healthcare providers should evaluate mortality risk assessment models like PIM and PIM 2 in their specific healthcare settings. While both Paediatric Index of Mortality (PIM) and PIM 2 have been validated in various populations, their performance can vary depending on the specific characteristics of the patient population and the healthcare environment. The results suggest that while both scores can broadly differentiate risk, PIM 2 may be more reliable in predicting actual mortality rates for the overall PICU population at RCWMCH. These findings reinforce the need for local validation to ensure these tools are appropriately used for clinical decision-making, thereby potentially improving patient outcomes.

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