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.     

La escala pediátrica de evaluación del fallo multiorgánico secuencial (pSOFA): una nueva escala de predicción de la mortalidad en la unidad de cuidados intensivos pediátricos

ObjectivesTo assess performance of the age-adapted SOFA score in children admitted into Paediatric Intensive Care Units (PICUs) and whether the SOFA score can compete with the systemic inflammatory response syndrome (SIRS) in diagnosing sepsis, as recommended in the Sepsis-3 consensus definitions.MethodsTwo-centre prospective observational study in 281 children admitted to the PICU. We calculated the SOFA, Pediatric Risk of Mortality (PRISM), and Pediatric Index of Mortality-2 (PIM2) scores and assessed for the presence of SIRS at admission. The primary outcome was 30-day mortality.ResultsThe SOFA score was higher in nonsurvivors (P<.001) and mortality increased progressively across patient subgroups from lower to higher SOFA scores. The receiver operating characteristic (ROC) curve analysis revealed that the area under the curve (AUC) of the SOFA score for predicting 30-day mortality was 0.89, compared to AUCs of 0.84 and 0.79 for the PRISM and PIM2 scores, respectively. The AUC of the SOFA score for predicting a prolonged stay in the PICU was 0.67. The SOFA score was correlated to the PRISM score (r_s=0.59) and the PIM2 score (r_s=0.51). In children with infection, the AUC of the SOFA score for predicting mortality was 0.87 compared to an AUC of 0.60 using SIRS. The diagnosis of sepsis applying a SOFA cutoff of 3 points predicted mortality better than both the SIRS and the SOFA cutoff of 2 points recommended by the Sepsis-3 consensus.ConclusionsThe SOFA score at admission is useful for predicting outcomes in the general PICU population and is more accurate than SIRS for definition of paediatric sepsis.     

Correlation between severity of disease and reimbursement of costs in neonatal and paediatric intensive care patients

Abstract Aim: The aim of the present study was to investigate the correlation between neonatal, paediatric and adult disease severity scores and reimbursement by health insurances. Methods: The setting was a university hospital's neonatal intensive care unit (NICU) and paediatric intensive care unit (PICU). We performed a prospective study of all patients admitted over the 3-month study period. Data collected included five scoring systems to predict mortality or to quantify disease severity (Paediatric Index of Mortality [PIM], Paediatric Risk of Mortality [PRISM], Simplified Acute Physiological Score [SAPS], Score for Neonatal Acute Physiology [SNAP], Therapeutic Intervention Scoring System [TISS]) on a daily basis, the total reimbursement as calculated by the grouper according to the German diagnosis-related groups (DRG) system, age of the patient, length of stay (LOS), International Classification of Diseases (ICD)-10 and DRG diagnosis. Our intention was to determine the correlation between different neonatal, paediatric and adult scores (PIM, PRISM III, SAPS-II, SNAP, Core-10-TISS), and reimbursement by the health insurance on the basis of the German DRG system in its 2005 and 2007 version. Results: No positive correlation between any score applied and reimbursement by the health insurance could be identified. Reimbursement was positively correlated to the length of hospital stay. Positive correlations could also be shown for some of the scores among each other. Conclusion: We conclude that other scoring systems or measures of disease severity urgently need to be established to terminate the chronic underfunding of paediatric intensive care medicine in the developed countries.     

Calibration of the paediatric index of mortality in UK paediatric intensive care units

AIM—To test a paediatric intensive care mortality prediction model for UK use.
METHOD—Prospective collection of data from consecutive admissions to five UK paediatric intensive care units (PICUs), representing a broad cross section of paediatric intensive care activity. A total of 7253 admissions were analysed using tests of the discrimination and calibration of the logistic regression equation.
RESULTS—The model discriminated and calibrated well. The area under the ROC plot was 0.84 (95% CI 0.819 to 0.853). The standardised mortality ratio was 0.87 (95% CI 0.81 to 0.94). There was remarkable concordance in the performance of the paediatric index of mortality (PIM) within each PICU, and in the performance of the PICUs as assessed by PIM. Variation in the proportion of admissions that were ventilated or transported from another hospital did not affect the results.
CONCLUSION—We recommend that UK PICUs use PIM for their routine audit needs. PIM is not affected by the standard of therapy after admission to PICU, the information needed to calculate PIM is easy to collect, and the model is free.

     

A comparison of three scoring systems for mortality risk among retrieved intensive care patients

Aims: To assess the impact of two paediatric intensive care unit retrieval teams on the performance of three mortality risk scoring systems: pre-ICU PRISM, PIM, and PRISM II. Methods: A total of 928 critically ill children retrieved for intensive care from district general hospitals in the south east of England (crude mortality 7.8%) were studied. Results: Risk stratification was similar between the two retrieval teams for scores utilising data primarily prior to ICU admission (pre-ICU PRISM, PIM), despite differences in case mix. The fewer variables required for calculation of PIM resulted in complete data collection in 88% of patients, compared to pre-ICU PRISM (24%) and PRISM II (60%). Overall, all scoring systems discriminated well between survival and non-survival (area under receiver operating characteristic curve 0.83–0.87), with no differences between the two hospitals. There was a tendency towards better discrimination in all scores for children compared to infants and neonates, and a poor discrimination for respiratory disease using pre-ICU PRISM and PRISM II but not PIM. All showed suboptimal calibration, primarily as a consequence of mortality over prediction among the medium (10–30%) mortality risk bands. Conclusions: PIM appears to offer advantages over the other two scores in terms of being less affected by the retrieval process and easier to collect. Recalibration of all scoring systems is needed.     

Calibration of the paediatric index of mortality in UK paediatric intensive care units.

AIM: To test a paediatric intensive care mortality prediction model for UK use. METHOD: Prospective collection of data from consecutive admissions to five UK paediatric intensive care units (PICUs), representing a broad cross section of paediatric intensive care activity. A total of 7253 admissions were analysed using tests of the discrimination and calibration of the logistic regression equation. RESULTS: The model discriminated and calibrated well. The area under the ROC plot was 0.84 (95% CI 0.819 to 0.853). The standardised mortality ratio was 0.87 (95% CI 0.81 to 0.94). There was remarkable concordance in the performance of the paediatric index of mortality (PIM) within each PICU, and in the performance of the PICUs as assessed by PIM. Variation in the proportion of admissions that were ventilated or transported from another hospital did not affect the results. CONCLUSION: We recommend that UK PICUs use PIM for their routine audit needs. PIM is not affected by the standard of therapy after admission to PICU, the information needed to calculate PIM is easy to collect, and the model is free.     

The impact of pediatric intensive care unit volume on mortality: a hierarchical instrumental variable analysis.

OBJECTIVE: To evaluate the relation between annual pediatric intensive care unit (PICU) admission volume and mortality. DESIGN: Nonconcurrent cohort design. SETTING: Pediatric patients included in the most currently available research database from the Pediatric Intensive Care Unit Evaluations (PICUEs). PATIENTS: A total of 34,880 consecutive pediatric admissions to a contemporary volunteer sample of 15 U.S. PICUs. MEASUREMENTS AND MAIN RESULTS: We conducted an instrumental variable analysis and adjusted for similarities between patients admitted to different PICUs using mixed-effects, hierarchical techniques. Case mix and severity of illness was adjusted for using patient-level data and the Pediatric Risk of Mortality, version III (PRISM III). On average, admission to higher-volume PICUs was associated with lower severity-adjusted mortality (odds ratio = 0.68 per 100 patient increase in volume; 95% confidence interval: 0.52-0.89) when volume was analyzed as a linear term; however, when PICU volume was analyzed as a quadratic term, we found the lowest severity-adjusted mortality rates among PICUs with annual admission volumes between 992 and 1,491. Furthermore, lower severity-adjusted mortality rates were primarily found among patients with less than a 10% PRISM III predicted risk of mortality. CONCLUSIONS: Although there is an association between lower severity-adjusted mortality among higher volume PICUs, our data suggest that best outcomes are among mid- to large-sized PICUs. These data support minimum annual admission criteria for PICUs but raise the concern that PICUs with very high annual admission volumes may operate beyond an ideal capacity.     

Application of different scoring systems and their value in pediatric intensive care unit

BackgroundLittle is known on the impact of risk factors that may complicate the course of critical illness. Scoring systems in ICUs allow assessment of the severity of diseases and predicting mortality.ObjectivesApply commonly used scores for assessment of illness severity and identify the combination of factors predicting patient’s outcome.MethodsWe included 231 patients admitted to PICU of Cairo University, Pediatric Hospital. PRISM III, PIM2, PEMOD, PELOD, TISS and SOFA scores were applied on the day of admission. Follow up was done using SOFA score and TISS.ResultsThere were positive correlations between PRISM III, PIM2, PELOD, PEMOD, SOFA and TISS on the day of admission, and the mortality rate (p < 0.0001). TISS and SOFA score had the highest discrimination ability (AUC: 0.81, 0.765, respectively). Significant positive correlations were found between SOFA score and TISS scores on days 1, 3 and 7 and PICU mortality rate (p < 0.0001). TISS had more ability of discrimination than SOFA score on day 1 (AUC: 0.843, 0.787, respectively).ConclusionScoring systems applied in PICU had good discrimination ability. TISS was a good tool for follow up. LOS, mechanical ventilation and inotropes were risk factors of mortality.     

Use of the Pediatric Risk of Mortality Score as predictor of death and serious neurologic damage in children after submersion.

OBJECTIVE: To evaluate the Pediatric Risk of Mortality score (PRISM score) as a tool to evaluate the vital and neurologic prognosis of patients after submersion. METHODS: We conducted a retrospective analysis of the clinical histories of patients admitted to a tertiary pediatric hospital, Hospital Sant Joan de Déu, Barcelona, Spain from December 1977 to December 1999 as a consequence of near-drowning. PRISM score was calculated for each patient with data obtained upon arrival at the hospital. The probability of death was calculated using this score. RESULTS: There were 60 patients, divided into two groups as they were admitted to the Pediatric Intensive Care Unit (PICU group, n = 41) or to the Short Stay Unit (SSU group, n = 19). All patients in the SSU group survived without impairments, with PRISM scores or=24 or with probability of death >or=42% either died or had serious neurologic impairment. One third of patients with PRISM scores between 17 and 23 and/or probability of death between 16 and 42% either presented serious neurologic impairment or died. CONCLUSIONS: PRISM score enables the determination of either absence or presence of serious impairment or death in pediatric patients after submersion, if they present extreme values on this scale. However, in patients with intermediate PRISM scores, it is not possible to establish a reliable prognosis.     

Early application of generic mortality risk scores in presumed meningococcal disease.

OBJECTIVE: Mortality from meningococcal disease typically occurs within 24 hrs of intensive care unit (ICU) admission. An early, accurate mortality-risk tool may aid in trial design for novel therapies. We assessed the performance of two generic scores that assign mortality risk within 1 hr of ICU admission: the Preintensive Care Pediatric Risk of Mortality (Pre-ICU PRISM) and Pediatric Index of Mortality (PIM). DESIGN: Prospective, observational study over 21 months. SETTING: Two tertiary pediatric ICUs accepting referrals from southeast England. PATIENTS: Patients were 165 consecutive children with meningococcal disease. Ages ranged from 0.1 to 17 yrs (median 2.3 yrs). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: PIM demonstrated greater sensibility, with complete data collected in 93% of cases, compared with 35% for the pre-ICU PRISM. Both scores discriminated well. The area under the receiver operating characteristic curve was 0.90 (95% confidence interval, 0.81-1.00) for PIM and 0.94 (95% confidence interval, 0.88-0.98) for Pre-ICU PRISM; this did not change when applied to the subgroup of patients with complete data. Both scores calibrated poorly, overestimating mortality in the medium-risk strata (and also in the high-risk stratum in the case of Pre-ICU PRISM). When used as a stratification tool for a hypothetical trial (60% reduction in mortality, 80% power), the scores allowed for a reduction in study size by 50% (PIM) and 43% (pre-ICU PRISM). CONCLUSIONS: Pre-ICU PRISM and PIM both discriminate well but calibrate poorly when applied to a cohort of children with meningococcal sepsis. Both scores provide an effective means of stratification for clinical trial purposes. The main advantage for PIM appears to be ease of data collection.     

Review of Staphylococcus aureus infections requiring admission to a paediatric intensive care unit

Aims: To review clinical features and outcome of children with severe Staphylococcus aureus sepsis (SAS) presenting to a paediatric intensive care unit (PICU) with particular focus on ethnicity, clinical presentation, cardiac involvement, and outcome. Methods: Retrospective chart review of patients coded for SAS over 10 years (October 1993 to April 2004). Results: There were 58 patients identified with SAS over the 10 year study period; 55 were community acquired. This accounted for 4% of hospital admissions for SAS over this time; children with staphylococcal illness comprised 1% of all admissions to the PICU. Maori and Pacific children with SAS were overly represented in the PICU (81%) from a paediatric population where they contribute 21.6%. Musculoskeletal symptoms (79%) dominated presentation rather than isolated pneumonia (10%). An aggressive search for foci and surgical drainage of infective foci was required in 50% of children. Most children had multifocal disease (67%) and normal cardiac valves (95%); the few children (12%) presenting with methicillin resistant S aureus (MRSA) had community acquired infection. The median length of stay in the PICU was 3 (mean 5.8, SD 7.6, range 1–44) days. The median length of stay in hospital was 15 (mean 21, SD 22.7, range 2–149) days. Mortality due to SAS was 8.6% (95% CI 1.4–15.8%) compared with the overall mortality for the PICU of 6% (95% CI 5.3–6.7%). Ten children had significant morbidity after discharge. Conclusions: Community acquired SAS affects healthy children, is multifocal, and has high morbidity and mortality, in keeping with the high severity of illness scores on admission. It is imperative to look for sites of dissemination and to drain and debride foci. Routine echocardiography had low yield in the absence of pre-existing cardiac lesions, persisting fever, or persisting bacteraemia.     

Risk adjusted mortality of critical illness in a defined geographical region.

AIMS: To evaluate the performance of the Paediatric Risk of Mortality (PRISM) score in a population of UK children and to use this score to examine severity of illness adjusted mortality of critically ill children <16 years old in a defined geographical region. METHODS: Observational study of a defined population of critically ill children (<16 years old) admitted to hospitals in the South West Region between 1 December 1996 and 30 November 1998. RESULTS: Data were collected from 1148 eligible admissions. PRISM was found to perform acceptably in this population. There was no significant difference between the overall number of observed deaths and those predicted by PRISM. Admissions with mortality risk 30% or greater had significantly greater odds ratio for death in general intensive care units compared with the tertiary paediatric intensive care unit. CONCLUSIONS: Children with a high initial risk of mortality based on PRISM score were significantly more likely to survive in a tertiary paediatric intensive care unit than in general intensive care units in this region. However, there was no evidence from this study that admissions with lower mortality risk than 30% had significantly worse mortality in non-tertiary general units than in tertiary paediatric intensive care units.     

Assessing the risk of mortality in paediatric cancer patients admitted to the paediatric intensive care unit: a novel risk score?

Intensive front-line protocols have improved survival in children with malignancies; however, intensive multimodal therapy of paediatric malignancies can be associated with a significant risk of serious adverse events. Common risk scores (PRISM, PRISM III, APACHE-II) fail to predict mortality in these patients. A retrospective chart analysis of 32 paediatric cancer patients admitted to the Paediatric Intensive Care Unit (PICU) at the University Hospital of Saarland between January 2001 and December 2003 for life-threatening complications was performed. The aim of this study was to assess risk factors for short-term outcome (survival vs. non-survival when leaving the PICU) and to develop a risk score to estimate outcome in these patients. Overall survival was good (25 of 32 patients). Mortality rate was significantly related to leukaemia/lymphoma ( P =0.029), to the number of organ failures ( P <0.0001), neutropenia ( P =0.001), septic shock ( P =0.025), mechanical ventilation ( P =0.01) and inotropic support ( P =0.01). Employing multiple logistic regression, the strongest predictor for poor outcome was the number of organ failures ( P <0.05). A risk score (cut-off value: >3 points for non-survival) which included the following risk factors (non-solid tumour, number of organ failures ( n >2), neutropenia, septic shock, mechanical ventilation, and inotropic medication) yielded a sensitivity of 7/7 (95% CI: 4.56–7.00), a specificity of 23/25 (95% CI: 18.49–24.75), a positive predictive value of 23/23 (95% CI: 19.80–23.00), and a negative predictive value of 7/9 (95% CI: 3.60–8.74) for the time of admission to the PICU. Conclusion:Although our risk of mortality score is of prognostic value in assessing short-term outcome in these patients, prospective validation in a larger study cohort is mandatory. Furthermore, it must be emphasised that this risk score must not be used for decision-making in an individual patient.     

Outcome of children with neuromuscular disease admitted to paediatric intensive care

Aims: To determine the outcome of children with neuromuscular disease (NMD) following admission to a tertiary referral paediatric intensive care (PICU). Methods: All children with chronic NMD whose first PICU admission was between July 1986 and June 2001 were followed up from their first PICU admission to time of study. The outcomes recorded were death in or outside of PICU, duration of PICU admission, artificial ventilation during admission and following discharge from PICU, and readmission to PICU. Results: Over 15 years, 28 children were admitted on 69 occasions. Sixteen (57%) children had more than one admission. The median duration of PICU admission was 4 days (range 0.5–42). Twenty three per cent of unplanned admissions resulted in the commencement of respiratory support that was continued after discharge from the PICU. Severity of functional impairment was not associated with longer duration of stay or higher PRISM scores. Ten children (36%) died, with four (14%) deaths in the PICU. A higher proportion of children with severe limitation of function were among children that died compared to survivors. Conclusion: Most children with NMD admitted to the PICU recover and are discharged without the need for prolonged invasive ventilation. However, in this group of children, the use of non-invasive home based ventilation is common and they are likely to require further PICU admission.     

Risk adjusted mortality of critical illness in a defined geographical region

Aims: To evaluate the performance of the Paediatric Risk of Mortality (PRISM) score in a population of UK children and to use this score to examine severity of illness adjusted mortality of critically ill children <16 years old in a defined geographical region. Methods: Observational study of a defined population of critically ill children (<16 years old) admitted to hospitals in the South West Region between 1 December 1996 and 30 November 1998. Results: Data were collected from 1148 eligible admissions. PRISM was found to perform acceptably in this population. There was no significant difference between the overall number of observed deaths and those predicted by PRISM. Admissions with mortality risk 30% or greater had significantly greater odds ratio for death in general intensive care units compared with the tertiary paediatric intensive care unit. Conclusions: Children with a high initial risk of mortality based on PRISM score were significantly more likely to survive in a tertiary paediatric intensive care unit than in general intensive care units in this region. However, there was no evidence from this study that admissions with lower mortality risk than 30% had significantly worse mortality in non-tertiary general units than in tertiary paediatric intensive care units.     

No resuscitation orders and withdrawal of therapy in French paediatric intensive care units

Objective: To determine the incidence of different modes of death in French paediatric intensive care units and to compare patients' characteristics, including a severity of illness score (Paediatric Risk of Mortality: PRISM score) and prior health status (Paediatric Overall Performance Category scale), according to the mode of death. Design: A 4-month prospective cohort study. Setting: Nine French multidisciplinary paediatric intensive care units. Patients: All patients who died in PICUs, except premature babies. Main results: Among 712 admissions, 13% patients died. Brain death was declared in 20%, failure of cardiopulmonary resuscitation occurred in 26%, do-not-resuscitate status was identified in 27%, and withdrawal of supportive therapy was noted in 27%. The PRISM score and the baseline Paediatric Overall Performance Category were not different between the four groups. Brain-dead patients were older than those in whom a do-not-resuscitate order and withdrawal of therapy were made (median age 81 vs 7 and 4 months). Conclusions: Decisions to limit or to withdraw supportive care were made for a majority of patients dying in French paediatric intensive care units. Chronic health evaluation and severity of illness index are not sufficient to describe dead-patient populations.     

Short‐term and long‐term mortality following pediatric intensive care

Background: The aim of the present study was to examine short‐term and long‐term mortality following discharge from the pediatric intensive care unit (PICU). Methods: This was a prospective observational study. Data collected consisted of demographics, severity scores, procedures, treatment, need for and duration of mechanical ventilation (MV), length of PICU and hospital stay, and mortality at PICU and hospital discharge, at 3 and 6 months and at 1 and 2 years. Results: A total of 300 patients (196 boys and 104 girls), aged 54.26 ± 49.93 months, were included in the study. Median (interquartile range) Pediatric Risk of Mortality (PRISM III‐24) score was 7 (3–11) and predicted mortality rate was 11.16%. MV rate was 67.3% (58.3% at admission) for 6.54 ± 14.15 days, and length of PICU and hospital stay was 8.85 ± 23.28 days and 20.69 ± 28.64 days, respectively. Mortality rate at discharge was 9.7% and cumulative mortality rate thereafter was 12.7%, 15.0%, 16.7%, 19.0%, and 19.0% at hospital discharge, 3 months, 6 months, 1 year and 2 years, respectively. Significant risk factors of PICU mortality were inotrope use, PRISM III‐24 score >8, MV, arterial and central venous catheterization, nosocomial infection, complications, and cancer. Independent predictors of mortality at discharge were inotrope use and PRISM III‐24 score, whereas predictors of mortality at 2 years were comorbidity and cancer. Conclusions: A 2 year follow‐up period seems sufficient for a comprehensive mortality analysis of PICU patients. Severity of critical illness is the key factor of short‐term mortality, whereas comorbidity is the major determinant of long‐term mortality.     

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.     

Evaluation of the Paediatric Index of Mortality in children managed on adult intensive care units

Objective: To evaluate the performance of the Paediatric Index of Mortality (PIM) in children cared for in adult intensive care units (ICUs) in district general hospitals in the South West Region of England. Design and setting: An observational survey of all children admitted to adult ICUs in 15 district general hospitals between November 2000 and August 2002. For comparison, data were also collected from the regional paediatric ICUs between November 2000 and March 2002. Results: Data were collected from 374 children admitted to adult ICUs and 850 children admitted to the regional paediatric ICU. There were significant differences in the patient characteristics between the two groups. In the adult ICU paediatric population, PIM discriminated well between death and survival (Az ROC = 0.96 (95% confidence interval, 0.93 to 0.99)) and calibrated well across deciles of risk (goodness of fit χ² = 4.55 (8 df), p = 0.8). Conclusions: PIM performs well as a risk adjustment method in children whose entire care remains in the adult ICU of a district general hospital. This is important should the Paediatric Intensive Care Audit Network (PICAnet) decide to extend its data collection beyond paediatric intensive care units to other units caring for critically ill children.     

Mortality Risk Prediction by Application of Pediatric Risk of Mortality Scoring System in Pediatric Intensive Care Unit

Objective

The Pediatric Risk of Mortality (PRISM) score is one of the scores used by many pediatricians for prediction of the mortality risk in the pediatric intensive care unit (PICU). Herein, we intend to evaluate the efficacy of PRISM score in prediction of mortality rate in PICU.

Methods

In this cohort study, 221 children admitted during an 18-month period to PICU, were enrolled. PRISM score and mortality risk were calculated. Follow up was noted as death or discharge. Results were analyzed by Kaplan-Meier curve, ROC curve, Log Rank (Mantel-Cox), Logistic regression model using SPSS 15.

Findings

Totally, 57% of the patients were males. Forty seven patients died during the study period. The PRISM score was 0-10 in 71%, 11-20 in 20.4% and 21-30 in 8.6%. PRISM score showed an increase of mortality from 10.2% in 0-10 score patients to 73.8% in 21-30 score ones. The survival time significantly decreased as PRISM score increased (P≤0.001). A 7.2 fold mortality risk was present in patients with score 21-30 compared with score 0-10. ROC curve analysis for mortality according to PRISM score showed an under curve area of 80.3%.

Conclusion

PRISM score is a good predictor for evaluation of mortality risk in PICU.