Performance of Pediatric Risk of Mortality (PRISM), Pediatric Index of Mortality (PIM), and PIM2 in a pediatric intensive care unit in a developing country.

OBJECTIVE: To determine the discriminative ability and calibration of existing scoring systems in predicting the outcome (mortality) in children admitted to an Indian pediatric intensive care unit (PICU). DESIGN: Prospective cohort study. SETTING: Pediatric Intensive Care Unit, Department of Pediatrics, All India Institute of Medical Sciences, New Delhi, from July 1, 2002, to July 31, 2003. PATIENTS: A total of 246 patients were admitted. After exclusion of 29 neonates and two patients who stayed in the PICU for 0.8. However, all the models underpredicted mortality. The likely reasons for this could be differences in the patient profile and greater load of severity of illness being managed with lesser resources--both physical and human--and differences in the quality of care.     

Performance of PRISM (Pediatric Risk of Mortality) score and PIM (Pediatric Index of Mortality) score in a tertiary care pediatric ICU

Objective  

To validate Pediatric Risk of Mortality (PRISM) and Pediatric Index of Mortality (PIM) score.     

Assessment of the performance of the Pediatric Index of Mortality 2 (PIM2) among Egyptian pediatric patients admitted to the intensive care

BackgroundMortality prediction models are useful in pediatric intensive care units (PICUs) as risk assessment tools and as a benchmark for the quality of care.ObjectivesTo assess the performance of the Pediatric Index of Mortality 2 (PIM2) in terms of calibration and discrimination between survivors and non-survivors among pediatric patients.MethodsThis is a cohort prospective study including 317 pediatric patients admitted to two PICU settings in a tertiary care hospital in Egypt over a period of one year (from June 2012 till June 2013). Collected data included personal characteristics, hospital data, diagnosis, outcome and variables included in PIM2 scoring.ResultsNon-survivors constituted 8.5%. Most common diagnosis was respiratory diseases (47.9%). Only CNS morbidities (11.7% of survivors versus 37% of non-survivors, P = 0.001) and a higher PIM2 score (2.39 ± 5.49 in survivors versus 41.38 ± 36.06 in non-survivors, P = 0.001) were associated with increased risk of non-survival. The area under the curve (AUC) for PIM2 is 0.796 (95% CI 0.675–0.916), P < 0.001. The Hosmer–Lemeshow goodness-of-fit was 2.850, 8 df, P = 0.943. PIM2.ConclusionThe calibration and the discriminative ability of PIM2 scoring system aiming to distinguish survivors from non-survivors are satisfactory for this sample of pediatric patients. PIM2 is easily calculated and is freely available. Thus, this tool provides a good incentive for ICU settings in Egypt for admission of high risk patients in the light of the limited PICU bed complement capacity in relation to the demands.     

Reliability of PRISM and PIM scores in paediatric intensive care.

AIMS: To assess the reliability of mortality risk assessment using the Paediatric Risk of Mortality (PRISM) score and the Paediatric Index of Mortality (PIM) in daily practice. METHODS: Twenty seven physicians from eight tertiary paediatric intensive care units (PICUs) were asked to assess the severity of illness of 10 representative patients using the PRISM and PIM scores. Physicians were divided into three levels of experience: intensivists (>3 years PICU experience, n = 12), PICU fellows (6-30 months of PICU experience, n = 6), and residents (<6 months PICU experience, n = 9). This represents all large PICUs and about half of the paediatric intensivists and PICU fellows working in the Netherlands. RESULTS: Individual scores and predicted mortality risks for each patient varied widely. For PRISM scores the average intraclass correlation (ICC) was 0.51 (range 0.32-0.78), and the average kappa score 0.6 (range 0.28-0.87). For PIM scores the average ICC was 0.18 (range 0.08-0.46) and the average kappa score 0.53 (range 0.32-0.88). This variability occurred in both experienced and inexperienced physicians. The percentage of exact agreement ranged from 30% to 82% for PRISM scores and from 28 to 84% for PIM scores. CONCLUSION: In daily practice severity of illness scoring using the PRISM and PIM risk adjustment systems is associated with wide variability. These differences could not be explained by the physician's level of experience. Reliable assessment of PRISM and PIM scores requires rigorous specific training and strict adherence to guidelines. Consequently, assessment should probably be performed by a limited number of well trained professionals.     

Simplified PRISM III score and outcome in the pediatric intensive care unit

BACKGROUND: To evaluate the association of the PRISM III (pediatric risk of mortality) score with the infant outcome in the pediatric intensive care unit (PICU), and to determine if this score could be simplified. METHODS: A prospective cohort study was carried out with 170 infants who were consecutively admitted to the PICU. The PRISM III score with 17 physiologic variables was performed during the first 8 h of admission to the unit. Statistical analysis was done with logistic regression, odds ratios (OR) with 95% confidence intervals (95% CI), and receiver operating curve. The Alfa value was set at 0.05. RESULTS: There were 42 deaths (24.7%). The two main causes of death were septic shock (28.6%) and head trauma (16.7%). The PRISM III score had a sensitivity of 0.71, and a specificity of 0.64 as a mortality predictor. Out of the 17 physiologic variables only four of them were significant: abnormal pupillary reflexes OR 9.9 (95% CI, 3.5-28.4), acidosis OR 3.1 (95% CI, 2.0-4.9), blood urea nitrogen concentration OR 1.03 (95% CI, 1.01-1.04), and white blood cell count OR 1.02 (95% CI, 1.01-1.03). The whole logistic regression model had a coefficient of determination R(2) = 0.219, P < 0.001. CONCLUSIONS: In this setting, the PRISM III score had good sensitivity and specificity to predict mortality. This score could be simplified using only the four variables that were significant in this study. This modified PRISM III score could reduce the cost of patient care especially in developing countries PICU.     

The Comparison of PRISM and PIM scoring systems for mortality risk in infantile intensive care

Scoring systems that predict the risk of mortality for children in an intensive care unit (ICU) are needed for the evaluation of the effectiveness of pediatric intensive care. The Pediatric Risk of Mortality (PRISM) and the Pediatric Index of Mortality (PIM) scores have been developed to predict mortality among children in the ICU. The purpose of this study was to evaluate whether these systems are effective and population-independent. PRISM and PIM scores were calculated prospectively during a 1-year period solely on 105 non-surgical infants admitted to the ICU. Statistical analysis was performed to assess the performance of the scoring systems. There were 29 (27.6 per cent) deaths and 76 (72.4 per cent) survivors. SMR and Z scores for PIM and PRISM signified higher mortality and poor performance. Prediction of mortality by the scoring systems appeared to be underestimated in almost all risk groups. The Hosmer and Lemeshow test showed a satisfactory overall calibration of both scoring systems. Although ROC analysis showed a poor discriminatory function of both scores, a marginally acceptable performance for PIM was observed. The ROC curve also showed an acceptable performance for PIM, for patients with pre-existent chronic disorder. Although care must be taken not to overstate the importance of our results, we believe that when revised according to the characteristics of the population, PIM may perform well in predicting the mortality risk for infants in the ICU, especially in countries where the mortality rate is relatively high and pre-existent chronic disorders are more common.     

Acute lung injury in pediatric intensive care in Australia and New Zealand: a prospective, multicenter, observational study.

OBJECTIVE: Acute lung injury (ALI) is poorly defined in children. The objective of this prospective study was to clarify the incidence, demographics, management strategies, outcome, and mortality predictors of ALI in children in Australia and New Zealand. DESIGN: Multicenter prospective study during a 12-month period. SETTING: Intensive care unit. PATIENTS: All children admitted to intensive care and requiring mechanical ventilation were screened daily for development of ALI based on American-European Consensus Conference guidelines. Identified patients were followed for 28 days or until death or discharge. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: There were 117 cases of ALI during the study period, giving a population incidence of 2.95/100,000 <16 yrs. ALI accounted for 2.2% of pediatric intensive care unit admissions. Mortality was 35% for ALI, and this accounted for 30% of all pediatric intensive care unit deaths during the study period. Significant preadmission risk factors for mortality were chronic disease, older age, and immunosuppression. Predictors of mortality during admission were ventilatory requirements (peak inspiratory pressures, mean airway pressure, positive end-expiratory pressure) and indexes of respiratory severity on day 1 (Pao2/Fio2 ratio and oxygenation index). Higher maximum and median tidal volumes were associated with reduced mortality, even when corrected for severity of lung disease. Development of single and multiple organ failure was significantly associated with mortality. CONCLUSIONS: ALI in children is uncommon but has a high mortality rate. Risk factors for mortality are easily identified. Ventilatory variables and indexes of lung severity were significantly associated with mortality.     

Validation of pediatric index of mortality 2 (PIM2) in a single pediatric intensive care unit of Argentina.

OBJECTIVE: Pediatric Index of Mortality 2 (PIM2) is an up-to-date mortality prediction model in the public domain that has not yet been widely validated. We aimed to evaluate this score in the population of patients admitted to our pediatric intensive care unit. DESIGN: Prospective cohort study. SETTING: Multidisciplinary pediatric intensive care unit in a general university hospital in Buenos Aires, Argentina. PATIENTS: All consecutive patients admitted between January 1, 2004, and December 31, 2005. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: There were 1,574 patients included in the study. We observed 41 (2.6%) deaths, and PIM2 estimated 48.1 (3.06) deaths. Discrimination assessed by the area under the receiver operating characteristic curve was 0.9 (95% confidence interval, 0.89-0.92). Calibration across five conventional mortality risk intervals assessed by the Hosmer-Lemeshow goodness-of-fit test showed chi5 = 12.2 (p = .0348). The standardized mortality ratio for the whole population was 0.85 (95% confidence interval, 0.6-1.1). CONCLUSIONS: PIM2 showed an adequate discrimination between death and survival and a poor calibration assessed by the Hosmer-Lemeshow goodness-of-fit test. The standardized mortality ratio and clinical analysis of the Hosmer-Lemeshow table make us consider that PIM2 reasonably predicted the outcome of our patients.     

Evaluation of Pediatric Risk of Mortality (PRISM) scoring in African children with falciparum malaria.

OBJECTIVE: Little is known about the use of generic severity scores in severe childhood infectious diseases. The purpose of this prospective study was to evaluate the performance of the Pediatric Risk of Mortality (PRISM) scoring system in predicting the outcome of falciparum malaria in African children. DESIGN, SETTING, PATIENTS: All children admitted to a 120-bed pediatric ward in a tertiary care hospital in Dakar, Senegal, with a primary diagnosis of acute malaria were assigned a PRISM score after 24 hrs or at time of death. INTERVENTIONS: None. RESULTS: PRISM discrimination, evaluated by areas under receiver operating characteristic curves (AUC), was good both for all acute malaria cases (n = 311; lethality, 9%; AUC, 0.89; 95% confidence interval [CI], 0.85-0.92) and for severe malaria cases (n = 233; lethality, 12%; AUC, 0.86; 95% CI, 0.81-0.90). However, the number of children who died was greater than the number of deaths predicted by PRISM (standardized mortality ratio, 2.16; 95% CI, 1.46-2.87). CONCLUSION: This discrepancy observed in five classes of expected mortality (Hosmer-Lemeshow chi-square test, p < .001) may have been due to chance (sample size too small for a valid test), to a lower standard of care in Dakar than in the American hospitals where PRISM was designed, or to a failure of PRISM to classify risk in severe malaria.     

Comparison of Outcomes using Pediatric Index of Mortality (PIM)-3 and PIM-2 Models in a Pediatric Intensive Care Unit

Objectives

To compare patient outcomes using the Pediatric Index of Mortality-3 (PIM-3) model with PIM-2 model for children admitted to the intensive care unit.

Methods

We prospectively recorded the baseline characteristics, variables of PIM-3 and PIM-2 at admission, and outcomes of children ≤17 years over a period of 11 months. We used Area Under Receiver Operating Characteristics (AU-ROC) curves and Goodness-of-fit (GOF) tests to determine which of the two models had better discrimination and calibration.

Results

Out of 202 children enrolled, 69 (34%) died. Sepsis and pneumonia were the common admitting diagnoses. The AU-ROC was better for PIM-3 (0.75) as compared to PIM-2 (0.69; P=0.001). The GOF-P value was 0.001 for both models, that indicated poor calibration of both (P<0.001). The AU-ROC curves were acceptable across different age and diagnostic sub-groups.

Conclusion

PIM-3 had better discrimination when compared to PIM-2 in our unit. Both models had poor calibration across deciles of risk.

     

Prospective evaluation of the Paediatric Risk of Mortality (PRISM) score.

The performance of the admission day Paediatric Risk of Mortality (PRISM) score for outcome prediction was assessed prospectively in 270 consecutive admissions, aged 3 days to 18.6 years, to a paediatric intensive care unit. Using a cut off of r = 0.00 (expected mortality = 50%), the overall sensitivity (correct prediction of death) was 48% while specificity (correct prediction of survival) was 99%, comparable with the original validation data of the score in the USA. Outcome prediction was most accurate when the stay in the paediatric intensive care unit was between one and four days. Sensitivity was appreciably lower for operative patients (17%) compared with non-operative patients (71%) because of a failure to predict deaths after cardiac surgery. The sensitivity (41%) and specificity (99%) using five variables (systolic blood pressure, Glasgow coma scale, carbon dioxide tension, and serum bicarbonate and serum calcium concentrations) was similar to that using all 14 variables. Six variable ranges related differently with non-survival compared with the score. It is concluded that the performance of the PRISM score is institution independent and good for short stay patients. It underpredicts deaths after cardiac surgery. Only five variables may be needed for satisfactory outcome prediction. Some of the variables need reweighting for paediatric intensive care units in the UK.     

Application of the Pediatric Index of Mortality 2 in pediatric patients with complex chronic conditions

ObjectiveTo evaluate the performance of the Pediatric Index of Mortality 2 (PIM2) in a pediatric intensive care unit (PICU) with a high prevalence of patients with complex chronic conditions (CCCs), and compare the performance between patients with and without CCCs.MethodsA prospective cohort study was conducted in a PICU in Brazil, with patients admitted between 2009 and 2011. The performance was evaluated through discrimination and calibration. Discrimination was assessed by calculating the area under the ROC curve, and calibration was determined using the Hosmer-Lemeshow goodness-of-fit test.ResultsA total of 677 patients were included in the study, of which 83.9% had a CCC. Overall mortality was 9.7%, with a trend of higher mortality among patients with CCCs when compared to patients without CCCs (10.3% vs. 6.4%, p = 0.27), but with no difference in the mean probability of death estimated by PIM2 (5.9% vs. 5.6%, p = 0.5). Discrimination was considered adequate in the general population (0.840) and in patients with and without CCCs (0.826 and 0.944). Calibration was considered inadequate in the general population and in patients with CCCs (p < 0.0001 and p < 0.0001), but it was considered adequate in patients without CCCs (p = 0.527).ConclusionsPIM2 showed poor performance in patients with CCCs and in the general population. This result may be secondary to differences in the characteristics between the study samples (high prevalence of patients with CCCs); the performance of the PIM2 should not be ruled out.     

Evaluation of the outcome of patients admitted to the pediatric intensive care unit in Alexandria using the pediatric risk of mortality (PRISM) score

The aim of this prospective study was to evaluate the use of pediatric risk of mortality (PRISM) score to predict the patient outcome in Alexandria Pediatric Intensive Care Unit (PICU). The study included all admissions to a tertiary care teaching hospital for 13 months. All patients were subjected to thorough history taking and clinical examination. The PRISM score was obtained within 8 h from admission (including 14 parameters with 34 variables). The primary affected system, referral site, number of organ failure on admission, length of hospital stay (LOS) and outcome of patients were recorded. The bed occupancy rate, turnover rate, average LOS, total and adjusted death rates were also recorded. Results showed that the total and adjusted mortality rates were 50 and 38 per cent respectively (n = 205/406 and 125/326, respectively). The mean PRISM score on admission was 26. Non-survivors showed a significantly higher mean score compared with survivors (36 vs. 17). Non-survivors compared with survivors, were significantly younger (12 vs. 23 months), had shorter LOS (3.8 vs. 5.3 days), three or four organ system failure on admission (77 vs. 25 per cent, and 9 vs. 0 per cent of patients) and had significantly higher percentage of sepsis syndrome and neurological diseases, as the primary affected system (20 vs. 10 per cent and 26 vs. 16 per cent). The PRISM score showed a significant positive correlation only with the number of organ failure on admission (r = 0.8104; p < 0.001). The cut-off point of survival was a PRISM score 26 with expected/observed ratio of 1.05 for non-survivors with 91.6 per cent accuracy. Multiple logistic regression analysis revealed that PRISM score, LOS, and the primary affected system were relevant predictors of patient outcome in PICU. In conclusion, the PRISM score is proved to be a good predictor of outcome for children admitted to a PICU with a cut-off point of 26. The mortality in the PICU is affected by LOS, primary system affected, and number of organ failure on admission.