Scoring Systems for Organ Dysfunction and Multiple Organ Dysfunction: The PODIUM Consensus Conference

Abstract

Context:

Multiple scores exist to characterize organ dysfunction in children.

Objective:

To review the literature on multiple organ dysfunction (MOD) scoring systems to estimate severity of illness and to characterize the performance characteristics of currently used scoring tools and clinical assessments for organ dysfunction in critically ill children.

Data Sources:

Electronic searches of PubMed and EMBASE were conducted from January 1992 to January 2020.

Study Selection:

Studies were included if they evaluated critically ill children with MOD, evaluated the performance characteristics of scoring tools for MOD, and assessed outcomes related to mortality, functional status, organ-specific outcomes, or other patient-centered outcomes.

Data Extraction:

Data was abstracted into a standard data extraction form by a task force member.

Results:

Of 1152 unique abstracts screened, 156 full text studies were assessed including a total of 54 eligible studies. The most commonly reported scores were the Pediatric Logistic Organ Dysfunction Score (PELOD), pediatric Sequential Organ Failure Assessment score (pSOFA), Paediatric Index of Mortality (PIM), PRISM, and counts of organ dysfunction using the International Pediatric Sepsis Definition Consensus Conference. Cut-offs for specific organ dysfunction criteria, diagnostic elements included, and use of counts versus weighting varied substantially.

Limitations:

While scores demonstrated an increase in mortality associated with the severity and number of organ dysfunctions, the performance ranged widely.

Conclusion:

The multitude of scores on organ dysfunction to assess severity of illness indicates a need for unified and data-driven organ dysfunction criteria, derived and validated in large, heterogenous international databases of critically ill children.

Table of Contents Summary:

We reviewed the literature on organ dysfunction scoring systems characterizing the performance of currently used tools to assess organ dysfunction in critically ill children.

INTRODUCTION

Multiple organ dysfunction syndrome (MODS) in critically ill children remains associated with a high morbidity and persistently high mortality¹. A recent study utilizing the Virtual Pediatric Systems (VPS) database including nearly 200,000 PICU admissions revealed a mortality of 10.3% among children with MODS compared to 0.7% in children without MODS². In MODS survivors, the risk of survival with poor functional status as assessed by the Pediatric Overall Performance Category/Pediatric Cerebral Performance Category was increased several fold. Recent research into the pathophysiology of critical illness illustrates that different MODS phenotypes may reflect patient populations more likely to respond to distinct, targeted therapies. Reliable identification of patients with MODS is therefore required to: 1) accurately characterize epidemiology, 2) assist in prognostication, 3) select patient groups where risk/benefit of specific treatments may vary, and 4) efficiently enrol selected patients into targeted trials.

However, to date, diagnostic criteria of MODS remain a matter of debate and there is no agreement on a gold standard for MODS, which organs to include, and thresholds to define dysfunction for individual organ systems. A unified approach to MODS is further hampered by patient heterogeneity of previous studies. Some studies have focused primarily on the prediction of mortality, whereas others report on scores as a description of illness severity. Most scores for MODS have been in use for many years, but a comprehensive review of the performance of different scores is lacking.

As part of the Pediatric Organ Dysfunction Information Update Mandate (PODIUM) project, we aimed to review the literature on MODS scoring systems in order to characterize the performance characteristics of currently used scoring tools and clinical assessments for organ dysfunction in critically ill children.

METHODS

The PODIUM taskforce sought to develop evidenced-based criteria for organ dysfunctions in children. As part of this process, a subgroup on Multiple Organ Dysfunction Syndrome (SW, PL, EJ, CC, JLW, LJS) reviewed the literature on MODS scoring systems. The present manuscript reports on the systematic review on organ dysfunction scoring systems performed as part of PODIUM, and provides a critical evaluation of the available literature with recommendations for future research. Details on data sources, study selection, data extraction, data synthesis, and risk of bias assessment uttilized by the PODIUM collaborative are presented in the PODIUM Executive Summary.³

RESULTS

Overview of commonly used scores

Out of 1152 unique abstracts, 159 fulltexts were reviewed of which 54 provided data on scores for the purpose of this review, as shown in the PRISMA flowchart (Fig. 1), data tables (Data Supplement, Supplemental Tables 1, 2 and 3), and risk of bias assessment summary (Data Supplement, Supplemental Fig. 1). Many scores have been developed and reported in critically ill children (Table 1). Scores show substantial differences in their scope (predictive, descriptive, diagnostic, Fig. 2), number and type of variables assessed (Table 2 and Fig. 3), suitability to measure organ dysfunctions, time frame, and applicability to different clinical settings.

Figure 1.

Study flow diagram according to the Preferred Reporting Items for Systematic review and Meta-Analysis Protocols recommendations.

Table 1.

Comparison of the Performance of Different Multiple Organ Dysfunction Scoring Tools

Criteria	SCORES
	PIM-2/3	PRISM-III	PELOD-2 (dPELOD-2)	qPELOD	SOFA	pSOFA/mSOFA	LODS	MOSF/MODS (count)	PeRF	SICK	PEDIA	BEP	TISS	Arzeno 2015	Meyer 2005
Number of studies	5	4	8	1	4	2	1	4	1	1	1	1	1	1	1
Validation
Reference standard	Death	Death	Death	Death	Death	Death	Death	Death	Death	Death	Death	Death	Death	Death	Death
Case-mix applied to	PICU, mening	PICU, sepsis, RRT	PICU	Sepsis	PICU, RRT, GI	CICU, PICU	Hosp fever	PICU, ARDS, Sepsis	ARDS	Hosp fever, PICU	Hosp fever	Mening	PICU	PICU brain	PICU oncology
Validity
Construct (score reflects MODS?)	NO	YES	YES	NO	YES	YES	NO	YES	YES	NO	NO	NO	NO	YES	YES
Content (score includes all organs?)	NO	YES	NO	NO	YES	YES	NO	YES	YES	NO	NO	NO	NO	YES	YES
Criterion (↑score → ↑ death)	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES	YES
Discrimination
AUROC	Poor-Good	Mod-Good	Good	Good	Mod-Good	Good	Good	Good	Mod-Good	Mod-Good	Good	Mod	Mod	Mod	NR
Calibration	Good	Good	Poor to Good	Good	Mod to Good	Good	Good	Good	Poor to Good	Poor to Good	Good	Unknown	Unknown	Good	Unknown
Reliability	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown	Unknown
Ease of Use	Mod	Mod	Mod	Good	Good	Good		Good				Good
Ease of interpretation	Mod	Mod	Good	Good	Good	Good		Good				Good
External validity/generalizability	Unknown	Unkown	Unknown	Unknown	Mod	Unkown	Unkown	Good	Unknown	Mod	Unknown	Unknown	Unknown	Unknown	Unknown

Abbreviations: PIM-2/3, Pediatric Index of Mortality, versions 2 and 3; PRISM III, Pediatric Risk of Mortality, version 3; PELOD-2, Pediatric Logistic Organ Dysfunction, version 2; dPELOD-2, Pediatric Logistic Organ Dysfunction on day 1; SOFA, Sequential Organ Failure Assessment; pSOFA. Sequential Organ Failure Assessment, modified for use in children; mSOFA modified SOFA; LODS, Logistic Organ Dysfunction Score; MOSF/MODS, Multiple Organ Dysfunction Score; PeRF, Pediatric Respiratory Failure score; SICK, Signs of Inflammation in Children that can Kill score; PEDIA, _Pediatric Early Death Index for Africa Score; BEP, base excess and platelet count at presentation score; TISS; Therapeutic Intervention Scoring System; PICU, pediatric intensive care unit; RRT, renal replacement therapy; CICU, cardiac intensive care unit; Hosp fever, hospitalized patients with fever; ARDS, acute respiratory distress syndrome; Mening, meningococcal disease.

Figure 2.

Purpose of different scoring systems

Table 2.

Comparison of Characteristics of Main Organ Dysfunction Assessment Tools

Scores	PIM-3	PRISM-III and IV	PELOD-2 (dPELOD-2)	qPELOD	pSOFA	2005 IPSDCC (Goldstein)
Organ systems	Not specific to organs	Not specific to organs	CVS + metabolic (lactate), respiratory, hematological, renal, CNS	CVS, CNS	CVS, respiratory, hematological, hepatic, renal, CNS	CVS, respiratory, hematological, hepatic, renal, CNS
Main purpose (at time of design of the score)	Prediction of mortality, ICU benchmarking	Prediction of mortality, ICU benchmarking	Description of severity	Prediction of mortality in sepsis	Description of severity	Diagnosis of organ dysfunction
Number of items	11	17	10	3	8 (12 if counting SpO2 and individual inotropes)	18
Number of laboratory items (N of laboratory items available as POC, i.e. blood gas components, glucose and lactate)	2 (2)	12 (5)	6 (3)	0	3 (1)	9 (3)
Development methods	Derivation cohort Australia, New Zealand, Ireland, and the United Kingdom N= 53,112 in 2010–2011	Derivation cohort U.S. N=10,078 in 2011–2013	Derivation cohort French/Belgium N=3,671 in 2006–2007	A priori (aligned with qSOFA and PELOD-2)	A priori (aligned with SOFA and PELOD-2)	A priori (expert statement)
Validation/calibration	Multiple validations	Multiple validations	Multiple validations	N/A	Multiple validations	N/A
Time frame	Within 60min of admission including first contact outside PICU by PICU team	first 4hrs of PICU admission, minus 2hrs to 4hrs for laboratory variables	Daily every 24hrs of PICU admission	First 24hrs of PICU admission	Daily every 24hrs of PICU admission	Not specified
Patient information	Yes	Yes in PRISM-IV	No	No	No	No
Treatment information	Yes (ventilation)	No	Yes (ventilation)	No	Yes (ventilation, vasoactives)	Yes (ventilation, vasoactives)
Applicability:
outside PICU	Poor	Poor	Moderate	Very good	Moderate	Good
resource-limited setting	good	Poor	Poor	Very good	moderate	moderate

Abbreviations: PIM-3, Pediatric Index of Mortality, version 3; PRISM III, IV, Pediatric Risk of Mortality, versions III, IV; PELOD-2, Pediatric Logistic Organ Dysfunction, version 2; dPELOD-2, Pediatric Logistic Organ Dysfunction on day 1; qPELOD, Quick Pediatric Logistic Organ Dysfunction; pSOFA, Sequential Organ Failure Assessment, modified for use in children; IPSDCC, International Pediatric Sepsis Definition Consensus Conference; CVS, cardiovascular system; CNS, central nervous system

Figure 3:

Comparison of variables used to calculate commonly used organ dysfunction scores

PIM-3, Paediatric Index of Mortality-3; PRISM-IV, Pediatric Risk of Mortality-IV; PELOD-2, Pediatric Logistic Organ Dysfunction Score-2; qPELOD, quick PELOD; pSOFA, pediatric Sequential Organ Failure Assessment; IPSDCC International Pediatric Sepsis Definition Consensus Conference

In terms of predictive scores, the Paediatric Index of Mortality-3 (PIM-3)⁴ and the Pediatric Risk of Mortality-IV (PRISM IV)⁵ scores (and their predecesessors) are the most commonly used. However, because these scores are intended for PICU patients with and without organ dysfunctions, they may have limited applicability for assessment specific to patients withs MODS^{6, 7}. While PIM-3 contains information on cardiovascular (systolic blood pressure), respiratory (need for mechanical ventilation) and neurologic syfunction (dilated pupils), it does not lend itself to assessment of individual organ dysfunctions or MODS. The PRISM-IV physiological score contains information on cardiac (heart rate, systolic blood pressure, temperature), neurological (pupillary reactivity, mental status), respiratory (arterial PO₂, pH, PCO₂, total bicarbonate), hematological (white blood cell count, platelet count, prothrombin and partial thromboplastin time) and chemical score components (glucose, potassium, blood urea nitrogen, creatinine).

Commonly used descriptive scores include the Pediatric Logistic Organ Dysfunction Score-2 (PELOD-2)⁸ and, more recently, the pediatric Sequential Organ Failure Assessment (pSOFA)⁹. PELOD-2 assesses five (neurological, cardiovascular, renal, respiratory and hematological) organ dysfunctions, and pSOFA includes six (including hepatic) organ dysfunctions. While PELOD-2 was derived from a multicenter European PICU cohort, pSOFA was constructed as a modification from the adult SOFA score with application of age-specific thresholds based on PELOD-2.

Diagnostic scores are designed to the characterize presence of (multi-) organ dysfunction for the purpose of correct classification and/or selection for clinical studies. While not a score in the strict sense, the 2005 International Pediatric Sepsis Definition Consensus Conference (IPSDCC)^{10, 11} statement defined criteria for six organ dysfunctions which have been widely used, both in patients with and without sepsis.

In addition to these more commonly used scores, the literature search identified a number of manuscripts proposing other approaches to assess organ dysfunctions in both broad and specific patient populations (Table 1 and Supplemental Tables 1 and 2).

Predictive scores

Predictive scores such as PIM-3⁴ or PRISM-IV⁵ describe the severity of illness at a defined baseline time point, which is often a time window around PICU admission, or time of randomization in clinical trials. The premise of predictive scores is founded on predicting the outcome with minimal influence by therapies provided to treat the condition (i.e. is the observed severity of illness attributable to the disease that brings the patient to the PICU or to treatment given after PICU admission), and on a temporal separation between the prediction and the outcome (i.e. is the score predicting, rather than describing, death?). The reliability of a predictive score is better if the data are collected before any care is given or if the data are unresponsive to care. The discriminative value of a test is estimated by measuring its area under the receiver operating characteristics curve and the Hosmer-Lemeshow goodness of fit, with death used most commonly as the outcome. Good calibration refers to the agreement between predicted and observed rates of death across the spectrum of the score and may be measured by Cox calibration regression or other techniques. Reproducibility across different sites and healthcare settings is desirable to enable comparison of baseline risk of death for benchmarking. Predicted scores are not intended to be used in individual patients to guide treatment or to inform end-of-life decisions, because they were validated in whole PICU populations, not in single patients. These scores need to be updated regularly because the population of PICU patients changes over time and because the risk of mortality changes over time for many specific diseases.

There are no predictive scores specific to patients with MODS at PICU admission or at randomization. While PIM and PRISM represent the most frequently used predictive scores, organ dysfunction scores such as PELOD or pSOFA, obtained in a time window around PICU admission (such as day 1), also have predictive value for mortality. In addition, PELOD-2 on day of admission, and maximum and cumulative PELOD-2 scores were associated with health-related quality of life 3 months post discharge in a recent pediatric sepsis cohort¹².

Descriptive scores

Descriptive organ dysfunction scores estimate the severity of cases at defined time points or time intervals. Descriptive scores focus on the differentiation between patients with mild versus severe illness. Descriptive scores should reliably capture (un-) responsiveness to care, and disease progression or resolution, and may thereby provide additional information not reflected in baseline prediction¹³. While simplicity is desirable to facilitate clinical application, descriptive scores aim to characterize the number and severity of organ dysfunctions. For example, the final PELOD-2 score utilizes 10 out of 17 criteria assessed in the derivation^{14, 15} as these 10 were sufficient to explain the statistical variability related to the risk of death observed in the index population. The discriminative value of descriptive scores is estimated by measuring its AUROC to differentiate death and/or of severe adverse outcomes. The calibration of a descriptive score to predict the risk of adverse outcomes should be excellent in the index population used to create and validate the score. On the other hand, calibration in other populations is less important because comorbidities and medical practice can differ significantly in different PICUs and in different countries. Updating descriptive scores over time is somewhat less important compared to predictive scores. Descriptive scores, as predictive scores, have been validated in large populations, not in individual patients and all subpopulations; thus they should not be used to guide treatment or inform end-of-life decisions at the bedside. For example, the PELOD-2 score can be used in critically ill children with respiratory problems¹⁶, and children with suspected infection¹⁷, but we do not know how reliable the score is in other subpopulations of PICU patients like trauma patients.

Diagnostic criteria for MODS

MODS represents a syndrome, not a specific disease entity, as MODS reflects a group of symptoms and signs that consistently occur together, the combination of which is associated with predictable outcomes. Diagnostic criteria are important to enable correct classification for 1) selecting specific monitoring, interventions and clinical pathways, 2) prognostication, and 3) reliably characterizing epidemiology. Contrary to a syndrome like trisomy 21, where a consistent list of symptoms and signs relate to one common, genetic finding which defines the “gold standard”, the diagnosis of many conditions often depends on “the subjective interaction of an observer, and its defining boundaries are both arbitrary and a little fuzzy”¹⁸. Presently, there is no reference standard for MODS, and diagnosis is based on different approaches to physiological data, such as blood pressure, interventions (such as ventilation) and laboratory parameters (such as creatinine concentrations). Since formal criteria for pediatric organ dysfunction were first proposed in 1987 by Wilkinson¹⁹, subsequent iterations, such as criteria proposed in 1996 by Proulx²⁰ and in 2005 by Goldstein²¹, were largely independent rather than the result of a consistent, iterative revision process. Importantly, these initial criteria for MODS were not data-driven but defined by expert consensus opinion. Although there is ample evidence for the association of increasing MODS severity with risk of death in critically ill children^{1, 22}, the diagnostic performance of these (multi-) organ dysfunction criteria in terms of sensitivity and specificity has been understudied. When it was studied, results indicate substantially worse performance compared to descriptive scores^{23, 24}.

Limitations of current (multi-) organ dysfunction scores

Clinicians and researchers base management and diagnostic decisions at least partially on objective physiological parameters like blood pressure, heart rate, or neurological state. Although there is ample observational evidence to support the relevance of individual organs in relation to outcomes, a closer look reveals substantial differences in thresholds applied. For example, an adolescent with a creatinine of 100 micromol/L will score 2 points for renal dysfunction in PELOD-2 and pSOFA but not be counted as kidney dysfunction by IPSDCC. To complicate the matter further, ICUs internationally care for an increasing proportion of children with complex chronic health care conditions and only some scores incorporate changes from baseline²⁵. In addition, thresholds may vary with concomittantly administered therapy, for example Glasgow Coma Scale in presence of sedation and/or neuromuscular blockade.

Furthermore, the comparison of scores (Table 2, Fig. 3) reveals inconsistencies in terms of which organs are included – for example lactate is measured in PELOD-2 and IPSDCC only, whereas hepatic dysfunction is not included in PELOD-2. While some of these differences stem from score design methodology (a priori versus derivation), they may simply relate to whether some of the criteria were available in the databases used for derivation/validation. The issue is further accentuated as scores variably consider the level of support provided to an organ – only pSOFA and IPSDCC consider vasoactive-inotrope support for example, and none consider renal replacement therapies (RRT) or extracorporeal membrane oxygenation (ECMO). A child may thus exhibit severe MODS requiring ECMO and RRT resulting in normal blood pressure, blood gases, creatinine, yet only be scored for the mechanical ventilation component by some tools. In addition, scores often do not fully account for the evolution of critical care. For example, pSOFA includes vasoactive-inotropic support, but milrinone, vasopressin, and angiotensin-II analogues are not included²⁶. Importantly, the different approaches used to classify organ dysfunction severity (i.e. binary in IPSCC, weighted score in PELOD-2, discrete score in pSOFA) hinder direct comparisons of absolute score levels in relation to MODS. For example, a score as high as 4 in both PELOD-2 or pSOFA may either reflect severe dysfunction in a single organ system or mild dysfunction across several organ systems.

It is also important to consider that, despite the merits of the procedures applied for derivation, validation, and calibration, the patient cohorts used should be considered historic and were almost exclusively biased towards PICUs in the U.S., Canada, Western Europe, and Australia and New Zealand. Considering the expansion of PICU services over the past two decades around the world, it is imperative to ensure scores, or adapted versions, are applicable to different health care settings, some of which may have different resource levels. Finally, the focus of organ dysfunction scores has inevitably been on children admitted to PICUs that have the capacity to collect data on organ dysfunctions and severity. Yet, patient care represents a continuum, including emergency department to PICU, operating theatre to PICU, or interhospital transfer to PICU journeys; hence it would be desirable if scores could be readily applied outside the PICU environment.

Future developments

An ideal MODS reference score should be specific to MODS and fulfill the following quality criteria: 1) highly sensitive and specific performance for clinically relevant outcomes such as mortality; 2) operator-independence, 3) criteria should be met as soon as possible while MODS is developing; 4) good reproducibility; 5) readily availability in diverse PICU and non-PICU settings; and 6) good performance as well for non-mortality outcomes such as prolonged dependency on ICU support and mid- to long-term quality of life and functional status. In the era of electronic health records (EHR), the availability of multi-site, multi-national and, preferably, multi-setting granular data from initial presentation throughout intensive care stay to discharge or death is promising and will enable better data-driven rather than purely expert-based approaches²⁷. Acknowledging that developing new scores from EHR data will inherently result in a bias towards high-resource settings such as selected PICUs in the U.S., the international shift towards EHR in many countries, and the creation of high-quality databases in resource-limited settings, opens new opportunities for validation and adaptation to meet the requirements of different settings. Data-driven approaches should rigorously derive and validate criteria in large and independent databases, assess the intra-rater and inter-rater reproducibility of the new list of diagnostic criteria, and compare the discriminative capacity of any new diagnostic criteria for MODS versus existing scoring systems.

Recent developments in clinician-driven approaches from the more traditional Delphi-study are worth considering, as they have the potential to be pragmatic, and combine both clinician’s perception of the gestalt of a condition, and data collected during the course of a disease. For example, a “temporary (presumptive) diagnosis” of MODS put forward by one or more independent clinicians can be compared to a “confirmatory (post-hoc) diagnosis” of MODS, the latter diagnosis being made by an adjudicating committee^{28, 29}. The analysis can then assess the sensitivity and specificity of items used for temporary and confirmatory diagnosis. Using a Bayesian strategy and likelihood ratio to ascertain the diagnosis can further improve the reliability of the diagnosis of MODS made by the members of the adjudicating committee³⁰.

The challenge of developing one universal MODS gold standard can be partially overcome with appropriate methodologies. For example, latent class analysis may serve to identify surrogate gold standards. Supervised and unsupervised learning algorithms can identify clusters of patients with similar features and outcomes, which may serve to characterize phenotypes more likely to respond to certain interventions³¹. Importantly, computational approaches carry enormous promise to overcome the limitations of static (one assessment in a time window) score measures, as dynamic measures of change over time may be more informative on a patient`s pattern of disease, response to disease, and response to treatment.

It is important to note that even future large-scale data-derived criteria and scores for MODS are likely to fall short from a number of perspectives. First, recent developments such as cytokine and gene expression profiles profiles, proteomics, genomics or highly granular analysis of electronic health record data such as heart rate variability may lead to improved tools. However, their clinical usefulness remains to be determined, and applicability to different settings will pose major challenges due to the resources and expertise involved. Second, while it is feasible to derive best cut-offs for individual organ dysfunction based on optimal performance in terms of sensitivity and specificity, we are currently unable to delineate when organ dysfunction begins (for example, is a slightly elevated creatinine in a child with gastroenteritis receiving enteral rehydration equivalent to the same creatinine concentration in a child heading towards sepsis-related MODS?). Third, some alterations in physiology may reflect adaptive hypo- (e.g., hibernation) or hyper-function (tachycardia to meet increased cardiac output requirements) but current approaches struggle to discriminate these from dysfunction associated with worse outcomes.

Conclusions

After more than three decades of MODS research in critically ill children¹⁹, and a large body of observational data demonstrating worse short- and long-term outcomes in children with MODS, present approaches remain hampered by lack of validation, standardization, and applicability, indicating an urgent need for revised MODS criteria. The creation of large international research networks contributing high-resolution data, and the advances in computational science are expected to lead to a paradigm shift in the development and application of organ dysfunction scores. It is highly desirable to combine efforts aiming to yield data-driven criteria for organ and multi-organ dysfunction. In addition, these efforts should aim to derive parsimonious scores for easier application at an early stage even in settings where resources are limited to pave the way towards interventions more likely to improve outcomes for children with MODS globally.

Supplementary Material

Data Supplement

Supplemental Figure 1. Risk of Bias Assessment Summary for Studies Included in the PODIUM Multiple Organ Dysfunction Scores Systematic Review (n=54 studies)

Supplemental Table 1. Summary of Multiple Organ Dysfunction Scores Related to Mortality

Supplemental Table 2. Studies Included in the PODIUM Multiple Organ Dysfunction Scores Systematic Review (n=54 studies)

Supplemental Table 3. Performance Characteristics for Assessment Tools and Scores for Multiple Organ Dysfunction in Critically Ill Children (n=54 studies)

Abbreviations:

AUROC

Area under the receiver operating characteristics curve

IPSDCC

International Pediatric Sepsis Definition Consensus Conference

MODS

Multiple organ dysfunction syndrome

PELOD

Pediatric Logistic Organ Dysfunction Score (PELOD)

PIM

Paediatric Index of Mortality

PODIUM

Pediatric Organ Dysfunction Information Update Mandate

PRISM

Pediatric Risk of Mortality

pSOFA

pediatric Sequential Organ Failure Assessment