小儿死亡危险评分的临床应用

目的观察小儿死亡危险评分(PRISM评分)与PICU急性危重症患儿预后的关系。方法对2003年2-10月PICU收治急性危重症45例,回顾性评定PRISM评分,并依据评分分组,记录患儿临床资料和住院时间、预后。结果PRISM 评分<15分24例,>15分21例。两组年龄、体质量和院内感染率均无显著差异(P均>0.05)。两组死亡率分别为8.1%(2/ 24例)和38.1%(8/21例),PRISM评分<15分组死亡率明显低于>15分组(x2=4.14 P<0.05)。PRISM>15分组存活病例住院天数(13.2±6.1)d显著长于PRISM<15分组(9.7±8.5)d(t=1.74.P<0.05)。结论PRISM评分越高,死亡率随之增加。PRISM评分增高,患儿住院时间越长。PRISM评分能够准确评估急性危重症病人的严重程度和预后。     

Emergency Care Connect: Extending Pediatric Emergency Care Expertise to General Emergency Departments Through Telemedicine

Increasingly, children with common and lower-acuity conditions are being transferred from general emergency departments (EDs) to pediatric centers for subspecialty care. While transferring children with high-risk conditions has benefit, transferring children with common conditions may expose them to redundant care and added costs. Emergency Care Connect (ECC) is a novel telemedicine program that uses videoconferencing to connect general ED and urgent care providers to pediatric emergency medicine physicians with the goal of keeping children in their communities for definitive care, when safe and feasible. ECC objectives are to: 1) facilitate transfer decision-making for children receiving care in general ED and urgent care sites and 2) increase access to pediatric providers for real-time management, regardless of disposition. In its first 20 months, ECC partnered with 4 general EDs and 1 urgent care location, which together made 1327 contacts with our pediatric center, of which 202 (15%) became ECC consultations for 200 unique patients. Of those consultations, 71% patients remained locally for treatment and 25% experienced a care plan change. Overall, ECC was rated highly by surveyed families and providers. Barriers to implementation, such as lack of familiarity with telemedicine and fears of changes in workflow, were overcome with strong institutional support and frequent, sustained stakeholder engagement. With greater adoption of this model, ECC and programs like it have the potential to allow more children to be treated in their communities, minimize preventable transfers, and reserve beds in children's hospitals for those with potentially higher risk and more medically complex conditions.     

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.     

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.     

Prediction of mortality by application of PRISM score in intensive care unit.

OBJECTIVE: Prediction of mortality by application of Pediatric Risk of Mortality (PRISM) score in Pediatric Intensive Care Unit (PICU) patients under Indian circumstances. DESIGN: Prospective study. SETTING: PICU of a tertiary care multi-specialty hospital. METHODS: 100 sick pediatric patients admitted consecutively in PICU were taken for this study. PRISM score was calculated. Hospital outcome was recorded as (died/survived). The predicted death was calculated by the formula: RESULTS: Of 100 patients, 18 died and 82 survived. By PRISM score 49 children had the score of 1-9. The expected death in this group was 10.3% (n = 5.03) and the observed death was 8.2% (n = 4). Among 45 children with the score of 10-19, the expected mortality was 21.2% (n = 9.6) and observed was 24.4% (n = 11). There were 3 patients with the score of 20-29, the expected mortality in this group was 39.3% (n = 1.18) and observed mortality 33.3% (n = 1). There were 3 patients with score > or = 30, observed death 66.3% (n = 2) and expected mortality was 74.7% (n = 2.24). There was no significant difference between expected and observed mortality in any group. (p > 0.5). ROC analysis showed area under the curve of 72%. CONCLUSION: PRISM score has good predictive value in assessing the probability of mortality in relation to children admitted to a PICU under Indian circumstances.     

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.     

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.     

小儿危重评分和死亡危险评分在监护室中的应用

目的 通过对PICU危重患儿小儿危重评分(PCIS)和小儿死亡危险评分(PRISM)的比较判断两种评分的临床应用价值.方法 对580例PICU住院患儿按照小儿危重评分标准、死亡及器官衰竭情况进行分组,根据各组PRISM评分分析比较各组问的差异性.结果 危重组、极危重组与非危重组各组间的PRISM评分差异有显著性(P<0.01);死亡组与存活组的PRISM评分值的差异也有显著性(P<0.01);PRISM评分随器官衰竭数增加而增高(P<0.05).结论 小儿危重评分和死亡危险评分对临床危重患儿的病情危重程度、死亡危险程度的判断有指导价值.     

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 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.     

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.     

Intensive care management after pediatric liver transplantation: a single-center experience

A retrospective study was conducted to determine the significance of intensive care management on outcome after liver transplantation (LTx) in children. Of 195 transplants performed in 162 children, factors affecting morbidity and mortality were documented during the post-operative intensive care unit (ICU) stay. To assess the gain in experience of ICU management, we compared mean ventilation time and stay in the ICU as well as mortality, incidence of surgical complications, infections, and rejection episodes, during three different time-periods (October 1991-August 1994, September 1994-July 1996, and August 1996-February 1998). The time spent by patients in the ICU (9.7 days vs. 7.9 days vs. 4.7 days, p < 0.001) and time on ventilation (5.2 days vs. 3.1 days vs. 1.2 days, p < 0.001) were significantly reduced over the duration of the study. The overall mortality was 18.0% (n = 30) and 76.7% (n = 23) of these deaths occurred during the early post-operative period in the ICU. The incidence of severe surgical complications decreased significantly over time, and the application of intra-operative Doppler ultrasound since 1994 led to detection of 27 correctable vascular complications. The overall incidence of acute cellular rejection episodes in our center was 64.1%: 43.5% of the infectious episodes occurred in the ICU (bacterial 70.2%, viral 12.3%, and fungal 17.5%). The main side-effect from immunosuppressive drugs was arterial hypertension in 29% of the patients. We conclude that our efforts to improve intensive care management and monitoring were the key elements in reducing morbidity and mortality after pediatric LTx.     

Case management and quality assurance to improve care of inner-city children with asthma

Case management and quality assurance techniques were used in a program designed to improve the process and outcomes of care for inner-city children with asthma. The program had three major elements: assessment of the care of individual patients and feedback to their primary care providers, periodic contact with parents, and provision of educational materials about asthma to parents. Telephone interviews with parents were used to assess knowledge of home asthma care and the type of care prescribed by the child's physician. Medicaid and hospital records were used to measure acute care utilization. Eighty-eight children (aged 0 to 5 years) who had made more than two emergency room visits for asthma were recruited by telephone. Fifty-six prescribing errors were identified, 24 being failure to prescribe an additional drug for short-term use by children receiving continuous therapy. Acute care use dropped 50% compared with a control period. This type of program is feasible but may require in-person recruiting to reach high-risk families without telephones.     

Telemedicine Visits to Children During the Pandemic: Practice-Based Telemedicine Versus Telemedicine-Only Providers

ObjectiveIn March 2020, regulatory and payment changes allowed “brick and mortar” pediatric practices to offer practice-based telemedicine for the first time, joining direct-to-consumer (DTC) telemedicine vendors in the ability to offer visits for common acute pediatric concerns via telemedicine. We sought to characterize the relative contribution of practice-based telemedicine versus commercial DTC telemedicine models in provision of children's telemedicine from 2018 through 2021.MethodsUsing January 2018 to September 2021 data from Optum's de-identified Clinformatics® Data Mart Database, we identified telemedicine visits by children ≤17, excluding preventive visits and visits to specialists, emergency departments, and urgent care. Among included visits, we defined “telemedicine-only” providers as those with ≥80% of visits via telemedicine and practice-based telemedicine providers as those with ≤50% of visits via telemedicine. We then described the telemedicine visit volume and diagnoses for these categories overall and per 1000 children per month.ResultsFrom January 2018 to February 2020, telemedicine-only providers accounted for 57,815 telemedicine visits (90.8%), while practice-based telemedicine accounted for 4192 telemedicine visits (6.6%). From March 2020 to September 2021, telemedicine-only providers accounted for 38,282 telemedicine visits (6.1%), while practice-based telemedicine accounted for 555,125 telemedicine visits (88.2%). Per month, telemedicine visits to practice-based telemedicine providers increased from pre-pandemic to pandemic periods (0.1 vs 12.9 visits per 1000 children/month), while telemedicine visits to telemedicine-only providers occurred at a similar rate from pre-pandemic to pandemic periods (0.92 vs 0.96 visits per 1000 children/month).ConclusionsWe observed a large increase in telemedicine visits during the pandemic, with the growth in visits exclusively occurring among visits to practice-based telemedicine providers as opposed to telemedicine-only providers.     

重症监护室免疫抑制和免疫健全脓毒症患儿28天内死亡因素的病例对照研究

目的评估伴免疫抑制相关基础疾病的儿童重症监护室脓毒症患儿入PICU 28 d内死亡及其危险因素。方法病例对照研究。回顾性收集复旦大学附属儿科医院（我院）因脓毒症/脓毒性休克收入PICU的患儿临床资料,分为免疫抑制组和免疫健全组,考察免疫抑制患儿入PICU 28 d内死亡的危险因素。结果2015年12月1日至2018年12月31日我院PICU出院诊断脓毒症连续病例385例,排除入科后24 h内死亡和PICU获得性脓毒症病例,251例PICU脓毒症/脓毒性休克患儿进入本文分析,免疫抑制组110例 (43.8%),免疫健全组141例。与免疫健全组比较,免疫抑制组以住院转入患儿（70%）为主,PICU维持治疗需求（血管活性药物、有创/无创机械通气）高、24 h PRISM评分高,不明确感染部位比例高,免疫抑制组接受ECMO治疗者全部死亡,持续肾脏代替治疗（CRRT）存活率为17.4%,入PICU第28 d病死率69.1%。免疫健全组和免疫抑制组28 d内存活和死亡患儿比较,除脓毒性休克、有创机械通气、CRRT、PRISM Ⅲ评分、乳酸>2 mmol·L-1比例、PICU住院时间、总住院时间、脱离PICU时间、24 h内放弃治疗、总放弃治疗差异有统计学意义外,应用血管活性药物在免疫抑制组入PICU 28 d内存活和死亡因素比较中差异有统计学意义。多因素COX比例风险模型分析显示,PRISM Ⅲ评分、有创机械通气、乳酸>2 mmol·L-1是免疫抑制组和免疫健全组入PICU 28 d内病死率的共同危险因素,休克是免疫抑制组入PICU 28 d内病死率的危险因素。结论重症监护室脓毒症患儿病死率较高;伴免疫抑制相关基础疾病的脓毒症患儿病死率更高;PRISMⅢ评分、48 h内有创机械通气和入院乳酸值(>2 mmol·L-1)是其预后的重要危险因素。应建立早期预警指标,对免疫抑制患儿进行早期识别,早期干预,可能改善预后。     

Transition of pediatric liver transplant recipients to adult care: patient and parent perspectives

The need to prepare pediatric transplant recipients for the transfer to adult-centered transplant care has received increased attention. This study aimed to determine adolescent and young adult LTR and parent perceptions and attitudes about the transition process. LTR and their parents completed a survey assessing level of prior thought and interest in learning about transferring care, knowledge of the transition process, perceived importance of self-management skills, concerns about moving to the adult clinic, and responsibility for health management tasks. Responses were analyzed by age, gender, and time since transplantation. Participants included 46 LTR (mean age = 16.6 yr; range 12-21), and 31 parents. Recipients and parents reported moderate concern about transition, with leaving pediatric providers being a primary worry. LTR ≥16 yr reported greater health care responsibility and increased thought, interest, and knowledge about transition. There were significant differences between parent and LTR perceptions of health care responsibility, indicating that LTR perceive having more independence than what their parents report. Overall, results suggest that adolescent and young adult LTR and their parents perceive the importance of transitional care, but demonstrate poor knowledge of the process. There remains a need for improved transition planning for both adolescents and parents.     

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.     

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.