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.     

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.     

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.     

The suitability of the Pediatric Index of Mortality (PIM), PIM2, the Pediatric Risk of Mortality (PRISM), and PRISM III for monitoring the quality of pediatric intensive care in Australia and New Zealand.

OBJECTIVE: To compare the performance of the Pediatric Index of Mortality (PIM), PIM2, the Pediatric Risk of Mortality (PRISM), and PRISM III in Australia and New Zealand. DESIGN: A two-phase prospective observational study. Phase 1 assessed the performance of PIM, PRISM, and PRISM III between 1997 and 1999. Phase 2 assessed PIM2 in 2000 and 2001. SETTING: Ten intensive care units in Australia and New Zealand. PATIENTS: Included in the study were 26,966 patients aged <16 yrs; 1,147 patients died in the intensive care unit. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Discrimination between death and survival was assessed by calculating the area under the receiver operating characteristic plot for each model. The areas (95% confidence interval) for PIM, PIM2, PRISM, and PRISM III were 0.89 (0.88-0.90), 0.90 (0.88-0.91), 0.90 (0.89-0.91), and 0.93 (0.92-0.94). The calibration of the models was assessed by comparing the number of observed to predicted deaths in different diagnostic and risk groups. Prediction was best using PIM2 with no difference between observed and expected mortality (standardized mortality ratio [95% confidence interval] 0.97 [0.86-1.05]). PIM, PRISM III, and PRISM all overpredicted death, predicting 116%, 130%, and 189% of observed deaths, respectively. The performance of individual units was compared during phase 1, using PIM, PRISM, and PRISM III. There was agreement between the models in the identification of outlying units; two units performed better than expected and one unit worse than expected for each model. CONCLUSIONS: Of the models tested, PIM2 was the most accurate and had the best fit in different diagnostic and risk groups; therefore, it is the most suitable mortality prediction model to use for monitoring the quality of pediatric intensive care in Australia and New Zealand. More information about the performance of the models in other regions is required before these results can be generalized.     

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.     

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.     

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.     

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.     

探讨3种评分系统对儿童严重脓毒症预后的评估价值

目的 探讨儿童年龄适应性序贯器官衰竭评分（pSOFA）、儿童死亡危险评分（PRISM Ⅲ）、儿童危重病例评分（PCIS）在儿童严重脓毒症中的预测价值和使用价值,以期为临床工作提供借鉴。方法 分析收治的193例严重脓毒症患儿的临床资料,根据最终结局将患儿分为存活组（n=151）和死亡组（n=42）。根据入院24 h内各指标的最差值进行pSOFA、PRISM Ⅲ、PCIS评分。受试者工作特征曲线（ROC）分析各评分系统预测脓毒症死亡风险的效能,平滑曲线拟合分析各评分系统的相关性和阈值效应,决策曲线分析（DCA）各评分系统的使用价值。结果 ROC分析示PCIS与pSOFA预测价值相当（P=0.182）,PRISM Ⅲ与pSOFA预测价值相当（P=0.210）,但PRISM Ⅲ优于PCIS （P=0.045）。3种评分系统与预后的拟合程度为PRISM Ⅲ > pSOFA > PCIS。DCA分析显示当严重脓毒症患儿死亡风险分别为0.4和0.6时,使用3种评分系统作为紧急干预决策依据,患儿的标准净受益（SNB）为SNB （pSOFA） > SNB （PRISM Ⅲ） > SNB （PCIS）。结论 3种评分系统对严重脓毒症患儿预后均有一定的预测价值,作为临床决策辅助工具可使患儿从中受益,pSOFA优于PRISM Ⅲ和PCIS。     

Timed Pediatric Risk of Mortality Scores predict outcomes in pediatric liver transplant recipients

More reliable methods are needed to identify children at risk for poor outcomes following liver transplantation. The Pediatric Risk of Mortality (PRISM) Score is a physiology-based scoring system used to quantify risk of mortality in pediatric intensive care unit (ICU) populations. We evaluated the PRISM Score as a predictor of outcomes including survival in the pediatric liver transplant (LT) population. We retrospectively reviewed the records of 67 consecutive LTs performed between August 1997 and February 2000 at an urban, tertiary children's hospital in Chicago, IL, USA. Four PRISM Scores were calculated to determine which periods were most meaningful. A Classic PRISM Score was calculated during first 24 h of ICU admission, and three PRISM Scores were timed with the patient's transplant: a pre-LT PRISM Score (24 h prior to transplant whether in ICU or not), a 24-h post-LT PRISM Score and a 48-h post-LT PRISM Score. These PRISM Scores and other predictors including transplant number, UNOS status and PELD Score were compared with outcomes including survival using univariate methods. The pre-LT, the 24- and the 48-h PRISM Score were associated with the post-LT number of ventilated days (p < 0.05), ICU days (p < 0.05) and with 1-yr survival (p < 0.04). The PRISM Scores were not related to the post-LT hospital length of stay (LOS) or to 1-yr re-transplantation. The PELD Score correlated with the post-LT hospital LOS, but was not associated with mortality or with the ICU LOS. A patient's UNOS status and Classic PRISM Score were not associated with any of the outcomes measured. PRISM Scores are valid predictors of outcome including survival in pediatric LT recipients. These findings help to demonstrate the importance in this population of a patient's general physiologic condition and its influence on the overall hospital course and survival.     

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.     

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.     

The pediatric risk of mortality score in infants and children with fulminant liver failure

The pediatric risk of mortality (PRISM) score as a severity scoring system has never been assessed in infants and children with fulminant liver failure (FLF). A retrospective case study of 109 infants and children admitted in a 22-bed pediatric and neonatal intensive care unit of a tertiary university hospital, National Referral Center for Pediatric Liver Transplantation, from March 1986 to August 1997 was carried out. PRISM score was not significantly different within etiologic FLF categories, or between infants and children. However, PRISM score (mean +/- SD) showed significant difference (p = 0.001) between the 27 patients who spontaneously recovered with supportive care (8.8 +/- 5.0) and 82 patients who underwent emergency liver transplantation (ELT) or those who died before (14.9 +/- 7.7). PRISM score-based probability of mortality was underestimated when compared with observed mortality. A death probability higher than 20% had a 24% sensitivity and 95% specificity for severe outcome. Reciever operating characteristic curve for PRISM score showed elevated discriminative power (Az = 0.91) for discerning children with severe outcome from those who spontaneously recovered with supportive care. A PRISM score more than 10 showed an odds ratio of 2.69 for predicting severe outcome (95% CI: 1.11-6.55; p = 0.038). In conclusion, the PRISM score is an accurate means of severity assessment in pediatric FLF. However, PRISM score-based mortality was of low predictive value.     

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 chi2 = 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.     

Comparison of two different severity scores (Paediatric Risk of Mortality [PRISM] and the Glasgow Meningococcal Sepsis Prognostic Score [GMSPS]) in meningococcal disease: preliminary analysis

Two different illness severity scores, Pediatric Risk of Mortality (PRISM) and the Glasgow Meningococcal Sepsis Prognostic Score (GMSPS), were evaluated and compared in meningococcal disease in two paediatric intensive care units. Forty-nine children with a median age of 36 months who had meningococcal sepsis confirmed by laboratory data were evaluated. Overall mortality was 18%. The median GMSPS was 3 in survivors and 8 in non-survivors. A GMSPS > or = 8 was significantly associated with death (p = 0.0001) with a mortality predictivity and specificity of 70% and 92.5%, respectively. The median PRISM score in survivors was 5.5 and 23 in non-survivors. A PRISM score of > or = 11 was significantly related to death (p < 0.0001). The Kendal correlation co-efficient between GMSPS and PRISM showed tau = 0.6859 (p = 0.0000). It is concluded that GMSPS and PRISM are useful methods for identifying and classifying children into low and high risk categories. GMSPS > or = 8 or a PRISM score > or = 11 are significantly predictive of mortality.     

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.     

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.     

Use of telemedicine to provide pediatric critical care inpatient consultations to underserved rural Northern California

OBJECTIVE: To report a novel application of telemedicine and to assess the resulting quality and satisfaction of care.Study design An existing telemedicine program was evaluated through the use of a nonconcurrent cohort design. Cohorts of patients were compared by means of the Pediatric Risk of Mortality, version III (PRISM III), to adjust for severity of illness and assess risk-adjusted mortality rates. Satisfaction and quality of care surveys administered to the pediatric patient's parents and providers were also analyzed. RESULTS: Telemedicine consultations (n=70) were conducted on 47 patients during a 2-year period. Patients receiving telemedicine consultations were sicker than the average pediatric patient cared for in the adult intensive care unit (ICU) (n=180) and compared with historic control pediatric patients (n=116) (mean PRISM III score of 9.6 versus 7.7 and 7.5, respectively). PRISM III-standardized mortality ratios were consistent among the same cohorts of patients (0.24, 0.36, and 0.37, respectively). Overall satisfaction and perception of quality of care was high among parents and rural health care providers. CONCLUSIONS: This study demonstrates that a regional pediatric ICU-based telemedicine program providing live interactive consultations to a rural adult ICU can provide quality care that is considered highly satisfactory to a select group of critically ill pediatric patients.     

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.     

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.