|Year : 2019 | Volume
| Issue : 1 | Page : 27-32
Prognostic scoring systems in pediatric ICUs: Pediatric Risk of Mortality III versus Pediatric Index of Mortality 2
Ragia A.M Yousef, Fady M El Gendy, Alyaa A Abd El Aziz
Department of Pediatrics, Faculty of Medicine, Menoufia University, Menoufia, Egyp
|Date of Submission||22-Nov-2018|
|Date of Acceptance||13-Feb-2019|
|Date of Web Publication||9-Sep-2019|
Ragia A.M Yousef
Iskandar Ebrahim st, Maimi, Alexandria, 21500
Source of Support: None, Conflict of Interest: None
Background Estimations of disease severity and probability of death are important elements in determining the prognosis of patients in pediatric ICU (PICU), and a more accurate prognostic assessment can lead to more appropriate monitoring, proper management, and family counseling.
Objective The aim of the study was to compare the performance of the PRISM III (Pediatric Risk of Mortality III) and the PIM2 (Pediatric Index of Mortality 2) scores at PICU and to investigate the relation between scores and mortality.
Patients and methods A prospective observational cohort study was conducted at PICU, Menoufia University Hospital, Egypt, during the period of February to October 2017. The study was approved by the Ethical Committee of Menoufia University Hospital. A total of 50 patients were included during the study period. Within the first hour of admission, PIM2 and PRISM III scores were applied. Patients were followed up for outcome, measured in the form of survivors and nonsurvivors.
Results A total 50 patients were included, of whom 35 were survivors and 15 were nonsurvivors. Most survivors and nonsurvivors were females, but there was no statistical significant influence on outcome. The area under the receiver operating characteristic curve was 0.937 (0.863–1.000) for PRISM III and 0.870 (0.759–0.99) for PIM2. There was a positive correlation between the two scores on the day of admission.
Conclusion Both PRISM III and PIM2 scores have a good discriminatory performance. PRISM III has better discrimination ability on admission in comparison with PIM2.
Keywords: Pediatric Index of Mortality, pediatric ICU, Pediatric Risk of Mortality
|How to cite this article:|
Yousef RA, El Gendy FM, Abd El Aziz AA. Prognostic scoring systems in pediatric ICUs: Pediatric Risk of Mortality III versus Pediatric Index of Mortality 2. Alex J Pediatr 2019;32:27-32
|How to cite this URL:|
Yousef RA, El Gendy FM, Abd El Aziz AA. Prognostic scoring systems in pediatric ICUs: Pediatric Risk of Mortality III versus Pediatric Index of Mortality 2. Alex J Pediatr [serial online] 2019 [cited 2020 Jan 20];32:27-32. Available from: http://www.ajp.eg.net/text.asp?2019/32/1/27/266406
| Introduction|| |
Pediatric ICU (PICU) is an ICU that provides treatment and care of critically ill children. PICU aims at promoting qualified care with the objective of achieving the best results and better progress for the critically ill children. The practice of PICU has developed dramatically throughout the past three decades. Knowledge of the pathology of life-threatening processes and the technological capacity to monitor and treat pediatric patients has advanced rapidly during this period. Therefore, the aim of PICU, which is to suppress the number of deaths (mortality) and the rate of disability (morbidity), can be achieved .
A critically ill child means a child who is in a clinical state that may result in respiratory or cardiac arrest or severe neurologic complications that may be primary cardiovascular or respiratory or secondary to neurologic, infectious, or metabolic disorder or serious injury. Infection is the most common, and septic shock is a catastrophic immune system reaction that produces organ failure .
Scoring systems are designed to evaluate the patient’s mortality risk in the ICU by assigning a score to the patient and predicting the outcome. However, patient’s mortality is not only affected by ICU performance but also depends on many other factors such as demographic and clinical characteristics of population, infrastructure and nonmedical factors (management and organization), and admission practice. Technological advances in PICU have resulted in a more sophisticated care for children, therefore making the PICU, prepared to treat cases of high complexity, at high cost. However, the technology available has not always succeeded in improving the quality of patient care and to augment life expectancy .
As a fact, we know little on the exact causes of death and the effect of risk factors that may complicate the course of critical illness irrespective of the underlying disease .
Knowledge of such determinants of outcome in the critically ill child would not only help improve prognostic evaluation of patients, but also indicates what therapy and research should focus on to improve the short-term and long-term outcomes of those patients .
Estimations of disease severity and probability of death are important elements in determining the prognosis of patients in PICU, and a more accurate prognostic assessment can lead to more appropriate monitoring, proper management, and family counseling. The most commonly measured PICU outcomes are mortality, length of stay, functional outcome, and organ dysfunction. The two most commonly used scoring systems to predict ICU mortality are the Pediatric Risk of Mortality (PRISM) and the Pediatric Index of Mortality (PIM). Pediatric Logistic Organ Dysfunction has recently been validated with good discrimination .
| Aim|| |
This study aims to compare the performance of two different prognostic clinical scoring systems (PRISM III and PIM2) which were developed to assess mortality probability in PICU.
| Patients and methods|| |
This work is a prospective observational cohort study including 50 patients. It was carried out in PICU in Menoufia University Hospital in the period from February to October 2017. The study was approved by the Ethical Committee of Menoufia University Hospital. The consents from the parents of the patients were obtained to participate in the study.
Age range of the included patients was from 1 month up to 16 years.
Patients who died in the first 24 h of admission to PICU.
All patients included in this study had been subjected to the following assessments on the first day of admission and then followed up until discharge.
- Full and detailed history: including medical and family history.
- Detailed physical examination of all systems.
- Routine investigations:
- Complete blood picture.
- Kidney function tests (blood urea, blood urea nitrogen, and serum creatinine).
- Liver function tests (alanine transaminase, aspartate transaminase, total bilirubin, and serum albumin).
- Arterial blood gases.
- Electrolytes profile (sodium, potassium, magnesium, and calcium).
- Coagulation profile (prothrombin time and partial thromboplastin time).
- Chest radiography.
- Computed tomographic scan if needed.
- MRI scan if needed.
- Assessment of the severity of morbidity and mortality risk on admission of the patients using the parameters of the following scores:
- PRISM III .
- PIM2 .
- Assessment of the outcome of the patients at the end of the PICU stay regarding survival.
- Data were fed to the computer using IBM SPSS software package, version 20.0 (Egypt).
- Qualitative data were described using number and percentage. Comparison between different groups regarding categorical variables was tested using χ2-test.
- Quantitative data were described using mean and standard deviation for normally distributed data.
- For normally distributed data, comparison between two independent population were done using independent t-test whereas more than two populations were analyzed using F-test (analysis of variance).
- Significant test results are quoted as two-tailed probabilities. Significance of the obtained results was judged at the 5% level.
- The capacity for discrimination between survivors and nonsurvivors was made using the typical area under a receiver operating characteristic (ROC) curve. An area under the curve (AUC) of more than 0.9 was considered excellent discrimination, between 0.80 to 0.89 good and 0.70–0.79 fair.
| Results|| |
A total of 50 patients admitted to PICU in Menoufia University Hospital, Egypt, from February to October 2017 were enrolled in a prospective observational cohort study.
Distribution of the studied patients regarding to the demographic data is summarized in [Table 1].
[Table 2] and [Table 3] revealed that the mortality rate was 30% (15 patients). Mortality rate was higher in infants (<1 year) than in children. Respiratory problems were the highest admission diagnoses (68%), followed by sepsis (36%) and followed by cardiovascular system findings (14%).
|Table 2 Comparison between survivors and nonsurvivors regarding age and sex|
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|Table 3 Comparison between survivors and nonsurvivors regarding the system affected on admission|
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[Table 4] shows a comparison of mean value of laboratory data between survivors and nonsurvivors who were included in the study. Mean values of hemoglobin, PO2, pH, and HCO3 were significantly lower in the nonsurvivors group when matched with the survivors. Furthermore, mean values of blood urea and serum creatinine were significantly higher in the nonsurvivors group when matched with the other group. Other laboratory data were insignificantly different when both groups were compared with each other.
|Table 4 Comparison between survivors and nonsurvivors regarding laboratory parameters used for evaluation of different systems|
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[Table 5] demonstrated that high PRISM III and PIM2 scores had statistically significant effect on the outcome, and they were strong predictors for mortality.
|Table 5 Comparison between survivors and nonsurvivors regarding the two prognostic clinical scores applied on the patients on pediatric ICU admission|
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Sensitivity, specificity, and accuracy of PRISM III and PIM2 scores are illustrated in [Table 6] using the typical AUC, which found that the most specific score in prediction of mortality was PRISM III. In addition, a correlation done using Pearson’s correlation coefficient was used to determine the most important score predicting mortality, as shown in [Table 7].
|Table 6 Cutoff, sensitivity, specificity, and accuracy of the two applied scores in prediction of mortality|
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|Table 7 Correlation between the two scores used in the study on admission|
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| Discussion|| |
There are several scoring systems used in PICUs that aim to predict morbidity and mortality. Numerous studies have been undertaken to evaluate the predictability of various severity of illness scores, and conflicting data have been reported so far .
Improvement of care for critically ill patients is a goal in all countries. Different care systems have been created to increase the quality of care for children who need special care. Efforts to decrease children’s mortality led to PICU establishment. It is necessary to develop models that predict the mortality risk in PICU to monitor the effectiveness of the care carried out. They enable us to compare different units and evaluate the associations between the severity of diseases, hospitalization duration, and the costs. The predictor model must be independent from time and place. It is important to know the accuracy of these scoring systems to estimate the mortality risk in PICUs of different groups and countries .
The aim of this study was to compare the performance of the PRISM III and the PIM2 scores at PICU and to investigate the relation between scores and mortality.
This study was a prospective observational cohort including 50 patients carried out in PICU in Menoufia University Hospital in the period from February to October 2017.
Regarding demographic characteristics, there was no statistically significant difference between survivors and nonsurvivors with respect to age, sex, and residence. This was similar to what was found by Graciano et al.  in their study, which evaluate the predictability of Pediatric Multiple Organ Dysfunction Score regarding mortality. The study population consisted of 3665 pediatric patients admitted to the PICU at Children’s Medical Center of Dallas, and they found that there were no statistically significant relation between sex, age, and mortality.
Regarding the admission diagnoses, respiratory problems were the highest admission diagnoses. Typpo et al.  in their study titled ‘day 1 multiple organ dysfunction syndrome is associated with poor functional outcome and mortality in the PICU’ found that the most frequent causes of admission were respiratory causes.
In this study, hemoglobin level was significantly lower in the nonsurvivors when matched with the other group. In contrast, Susianawati et al.  found that one of the main predictive factors of death observed in his study was white blood cell count.
Blood urea and serum creatinine were significantly higher in the nonsurvivors group, and this was consistent with the results of the study conducted by Akcan-Arikan et al. , who showed a very high incidence of significance in the relation between mortality and serum creatinine.
In this study, PRISM III and PIM2 scores, which were done on admission, had a statistically significant relation with mortality. The discriminatory power was evaluated using ROC, with PRISM III (AUC=0.937) having better discriminatory power than PIM2 (AUC=0.871), with positive and significant correlation using Pearson’s correlation coefficient (P<0.0001). Similar observations of positive correlation were seen in studies done by Qureshi et al. .
PRISM III was higher in nonsurvivors than in survivors. Rady et al.  and El-Nawawy et al.  found similar results. In many studies, PRISM III showed satisfactory performance in differentiating survivors from nonsurvivors, supporting the conclusion that higher scores are correlated with increased risk of death ,. In contrast, some authors have shown that the PRISM score overestimated mortality .
In this study, PRISM III was more sensitive than PIM2 in prediction of mortality, Raghavendra et al.  reported the same finding in their study who reported that the discriminatory power was evaluated using ROC, with PRISM III (AUC=0.892) having better discriminatory power than PIM II (AUC=0.871), with positive and significant correlation using spearman’s rank correlation (r=0.310; P<0.0001=). In contrast to our results, Gemke et al.  found that PRISM III and PIM scores are both adequate indicators of mortality probability for heterogeneous patient groups in PICU.
This study has several limitations. Further confirmation of the results is required, particularly because of the limited number of patients and the fact that it originates from a single unit. Moreover, it should be realized that scoring systems, although mandatory for assessment of PICU performance, do not suffice. Even the best scoring system cannot be used to predict individual outcome or to guide treatment in individual patients. Moreover, differences in acute physiologic stability owing to pre-existent chronic disorders are not accounted for, and they do not accommodate for limitations and/or restrictions of care for other reasons than acute physiologic instability.
| Conclusion|| |
- Both PRISM III and PIM scores have a good discriminatory performance.
- PRISM III has better discrimination ability on admission in comparison with PIM2.
- PRISM III should be used in PICU for evaluating the patients on admission and predicting the risk of mortality.
- Further studies with larger patient numbers and preferentially with prospective character are warranted to better clarify the issue and help to build up a national consensus along with PICUs from different geographical areas.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Marcin JP, Song J, Leigh JP. The impact of pediatric intensive care unit volume on mortality: A hierarchical instrumental variable analysis. Pediatr Crit Care Med 2005; 6:136–141.
Chang L, Horng CF, Huang YC, Hsieh YY. Prognostic accuracy of acute physiologic and chronic health evaluation II scores in critically ill cancer patients. Am J Crit Care 2006; 15:47–53.
De Mello MJG, Pessoa MF, de Albuquerque M, Lacerda HR, de Souza WV, Correia JB et al.
Risk factors for healthcare-associated infection in pediatric intensive care units: a systematic review. Cad Saude Publica 2009; 25(Suppl 3):S373–S391.
Khouli H, Afrasiabi A, Shibli M, Hajal R, Barrett CR, Homel P. Outcome of critically ill human immunodeficiency virus-infected patients in the era of highly active antiretroviral therapy. J Intensive Care Med 2005; 20:327–333.
Typpo KV, Larmonier CB, Deschenes J, Redford D, Kiela PR, Ghishan FK. Clinical characteristics associated with postoperative intestinal epithelial barrier dysfunction in children with congenital heart disease. Pediatr Crit Care Med 2015; 16:37–44.
Qureshi AU, Ali AS, Ahmad TM. Comparison of three prognostic scores (PRISM,PELOD and PIM 2) at pediatric intensive care unit under Pakistani circumstances. J Ayub Med Coll Abbottabad 2007; 19:49–53.
Slater A, Shann F, Pearson G, Paediatric Index of Mortality (PIM) Study Group. PI M2: a revised version of the paediatric index of mortality. Intensive Care Med 2003; 29:278–285.
Cuckle HS, Malone FD, Wright D. Contingent screening for Down syndrome − results from the Fa STER trial. Prenat Diagn 2008; 28:89–94.
Khajeh A, Noori NM, Reisi M. Mortality risk prediction by application of pediatric risk of mortality scoring system in pediatric intensive care unit. Iran J Pediatr 2013; 23:546–550.
Graciano AL, Balko JA, Rahn DS, Naveed A, Giroir BP. The Pediatric Multiple Organ Dysfunction Score (P-MODS): development and validation of an objective scale to measure the severity of multiple organ dysfunction in critically ill children. Crit Care Med 2005; 33:1484–1491.
Susianawati V, Suryantoro P, Naning R. Prognostic predictor at pediatrics intensive care unit (PICU) with Pediatric Risk of Mortality III (PRISM III) scores. J Med Sci 2014; 46:71–77.
Akcan-Arikan A, Zappitelli M, Loftis LL, Washburn KK, Jefferson LS, Goldstein SL. Modified rifle criteria in critically ill children with acute kidney injury. Kidney Int 2009; 71:1028–1035.
Rady HI, Mohssen NA. Application of different scoring systemsand their value in pediatric intensive care unit. Gaz Egypt Pediatr Assoc 2014; 62:59–64.
El-Nawawy AA, Abd El-Fattah MM, Metwally HA. One year study of bacterial and fungal nosocomial infections among patients in paediatric intensive care unit (PICU) in Alexandria. J Trop Pediatr 2006; 52:185–191.
Costa GA, Delgado AF, Ferraro A, Okay TS. Application of the pediatric risk of mortality score (PRISM) score and determination of mortality risk factors in a tertiary pediatric intensive care unit. Clinics (Sao Paulo) 2010; 65:1087–1092.
Martha VF, Garcia PCR, Piva JP, Einloft PR, Bruno F, Rampon V. Comparison of two prognostic scores (PRISM and PIM) at a pediatric intensive care unit. J Pediatr Rio J 2005; 81:259–264.
Prieto Espuñes S, López-Herce Cid J, Rey Galán C, Medina Villanueva A, Concha Torre A, Martínez Camblor P. Prognostic indexes of mortality in pediatric intensive care units. An Pediatr (Barc) 2007; 66:345–350.
Raghavendra BJ, Roopa MB, Patil VD. A prospective cohort study for the comparison of two prognostic scores-PRISM 3 and PIM 2 in a pediatric intensive care unit. J Evol Med Dent Sci 2014; 3:10954–10966.
Gemke RJ, Vught JV. Scoring systems in pediatric intensive care: PRISM III versus PIM. Intensive Care Med 2002; 28:204–207.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7]