Comparison of Pediatric Risk of Mortality III, Pediatric Index of Mortality 2, and Pediatric Index of Mortality 3 in Predicting Mortality in a Pediatric Intensive Care Unit

Bedside clinical prediction tool for mortality in critically ill children

INTRODUCTION

Mortality rates among critically ill pediatric patients remain a persistent challenge. It is imperative to identify patients at higher risk to effectively allocate appropriate resources. Our study aimed to develop a prediction score based on clinical parameters and hemogram to predict pediatric intensive care unit (PICU) mortality.

METHODS

We conducted a retrospective study to develop a clinical prediction score using data from children aged 1 month to 18 years admitted for at least 24 hours to the PICU at Chiang Mai University between January 2018 and December 2022. PICU mortality was defined as death within 28 days of admission. The score was developed using multivariable logistic regression and assessed for calibration and discrimination.

RESULTS

There were 29 deaths in 330 children (8.8%). Our model for predicting 28-day ICU mortality uses four key predictors: male gender, use of vasoactive drugs, red blood cell distribution width (RDW) ≥15.9%, and platelet distribution width (PDW), categorized as follows: <10% (0 points), 10-14.9% (2 points), and ≥15% (4 points). Scores range from 0 to 8, with a cutoff value of 5 to differentiate low-risk (<5) from high-risk (≥5) groups. The tool demonstrates excellent performance with an AuROC curve of 0.86 (95% CI: 0.80-0.91, p<0.001) showing excellent discrimination and calibration, 82.8% sensitivity, and 73.1% specificity, respectively.

CONCLUSIONS

The score, developed from clinical data and hemogram, demonstrated potential in predicting ICU mortality among critically ill children. However, further studies are necessary to externally validate the score before it can be confidentially implemented in clinical practices.

Post hematopoietic stem cell transplant (HSCT) outcomes in pediatric intensive care unit, experience from a referral center for cellular therapy and hematopoietic stem cell transplantation

BACKGROUND

Patients who underwent hematopoietic stem cell transplantation (HSCT) are considered at high risk for pediatric intensive care unit (PICU) admission. Therefore, this study aimed to assess outcomes and mortality-related risk factors among pediatric HSCT recipients admitted to the PICU.

METHODS

This retrospective cohort study was conducted at a Saudi Arabian tertiary care center and involved pediatric patients (aged 4 weeks to 14 years) who underwent HSCTs between January 2015 and December 2019 and were admitted to the PICU.

RESULTS

Of the 173 pediatric HSCT recipients admitted to the PICU, 65.3% were admitted for respiratory failure. Graft-versus-host disease and chronic infections affected 48.6% and 71.7% of the cases, respectively. Pulmonary hemorrhage and veno-occlusive disease occurred in 15.0% and 32.4% of the patients, respectively. Ventilation and inotropic support were administered to 79.8% and 41.0%, respectively. Acute kidney injury (AKI) occurred in 47.4% of the patients, of which 23.2% required continuous renal replacement therapy/hemodialysis. The PICU survival rate was 59.0% (102/173), and the mortality rate was 41.0% (71/173). In the univariate analysis, chronic infection, pulmonary hemorrhage, ventilation, inotropic support, AKI, higher PRISM III score, and prolonged PICU stay were associated with mortality (P < 0.05). In the multivariable analysis, only prolonged PICU stay (P = 0.016), AKI (P = 0.040), inotropic support (P < 0.001), and ventilation (P = 0.017) showed potential association with mortality.

CONCLUSION

Early recognition and targeted interventions for these complications are crucial for improving outcomes in this vulnerable population. More research is needed to validate these findings and optimize care practices for HSCT recipients in the PICU setting.

Oncological pediatric early warning score: a dedicated tool to predict patient's clinical deterioration and need for pediatric intensive care treatment

Pediatric oncohematological patients frequently require PICU admission during their clinical history. The O-PEWS is a specific score developed to predict the need for PICU admission of oncohematological children. This study aimed at i) describing the trend of the O-PEWS in a cohort of patients hospitalized in the Pediatric Oncohematology ward and transferred to the PICU of Padua University Hospital, measured at different time-points in the 24 hours before PICU admission and to evaluate its association with mortality and presence of organ failure; ii) investigating the association between the recorded O-PEWS, and PIM3, number of organ failure and the need for ventilation, dialysis and inotropes.

This retrospective single-center study enrolled oncohematological children admitted to the PICU between 2017 and 2021. The O-PEWS, ranging between 0 and 15, was calculated on the available medical records and the TIPNet-Network database at 24 (T-24), 12 (T-12), 6 (T-6) and 0 (T0) hours before PICU admission.

RESULTS: 101 PICU admissions, related to 80 children, were registered. During the 24 hours prior to PICU admission, the O-PEWS progressively increased in all the patients. At T-24 the median O-PEWS was 3 (IQR 1-5), increasing to a median value of 6 (IQR 4-8) at T0. The O-PEWS was positively associated with mortality, organ failure and the need for ventilation at all the analyzed time-points and with the need for dialysis at T-6.

The O-PEWS appears as a useful tool for predicting early clinical deterioration in oncohematological patients and for anticipating the initiation of life-support treatments.

Performance of Pediatric Index of Mortality PIM-3 in a Tertiary Care PICU in India

Pediatric index of mortality-3 (PIM-3) is the latest update of one of the commonly used scoring systems in pediatric intensive care. It has free accessibility and is easy to use. However, there are some skepticisms regarding its practical usefulness in resource-limited settings. Hence, there is a need to generate region-specific data to evaluate its performance in different case mixes and resource constraints. The aim of the study is to evaluate the performance of the PIM-3 score in predicting mortality in a tertiary care PICU of a developing country. This is a retrospective cohort study. All children aged 1 month to 18 years admitted to the PICU during the study period from July 2016 to December 2018 were included. We reviewed the patient admission details and the case records of the enrolled. patients. Patient demographics, disease profile, co-morbidities, and PIM-3 scores were recorded along with the outcome. Area under receiver operating characteristics (AUROC) curves was used to determine discrimination. Standardized mortality ratio (SMR) and Hosmer Lemeshow goodness of fit were used to assess the calibration. Out of 282 children enrolled, 62 (21.9%) died. 58.5% of the patients were males, and 60% were less than 5 years of age. The principal diagnoses included respiratory and neurological conditions. The AUROC for PIM-3 was 0.961 (95% CI [0.93, 0.98]) and overall SMR was 1.28 (95% CI [0.96, 1.59]). Hosmer-Lemeshow goodness-of-fit was suggestive of poor calibration ( χ 2  = 11.7, p  < 0.05). We concluded that PIM-3 had good discrimination but poor calibration in our PICU setting.

Comparison of pSOFA with PRISM III and PIM 2 as Predictors of Outcome in a Tertiary Care Pediatric ICU: A Prospective Cross-sectional Study

Aims and background

Severity scores are used to predict the outcome of children admitted to the intensive care unit. A descriptive score such as the pediatric sequential organ failure assessment (pSOFA) may be useful for prediction of outcome. This study was planned to compare the pSOFA score with these well-studied scores for prediction of mortality.

Materials and methods

This prospective cross-sectional study was conducted at the pediatric intensive care units (PICU) of a tertiary care hospital. Children aged from 1 month to 12 years were enrolled sequentially. The pediatric index of mortality (PIM 2) score was calculated within 1 hour, and pediatric risk of mortality (PRISM) III and pSOFA scores were calculated within 24 hours of PICU admission. The pediatric sequential organ failure assessment score was recalculated after 72 hours. The primary outcome variable was hospital mortality, and secondary outcome variables were duration of PICU stay, need for mechanical ventilation, and occurrence of acute kidney injury (AKI). Appropriate statistical tests were used.

Results

About 151 children with median (IQR) age of 36 (6, 84) months were enrolled. Mechanical ventilation was required in 87 (57.6%) children. Mortality was 21.2% at 28 days. The median (IQR) predicted mortality using PRISM III and PIM 2 score were 3.4 (1.5%, 11%) and 8.2 (3.1%, 16.6%) respectively. Area under ROC for prediction of mortality was highest for pSOFA 72 with a cut-off of 6.5 having sensitivity of 83.3% and specificity of 76.9%.

Conclusion

The pSOFA score calculated at admission and at 72 hours had a better predictive ability for the PICU mortality compared to PRISM III and PIM 2 score.

How to cite this article

Agrwal S, Saxena R, Jha M, Jhamb U, Pallavi. Comparison of pSOFA with PRISM III and PIM 2 as Predictors of Outcome in a Tertiary Care Pediatric ICU: A Prospective Cross-sectional Study. Indian J Crit Care Med 2024;28(8):796-801.

Prognostic Markers in Pediatric Acute Liver Failure

Introduction

Acute liver failure (ALF), although rare in children, is a complex progressive pathology, with multisystem involvement and high mortality. Isolated variables or those included in prognostic scores have been studied, to optimize organ allocation. However, its validation is challenging. This study aimed to assess the accuracy of several biomarkers and scores as predictors of prognosis in pediatric ALF (PALF).

Methods

An observational study with retrospective data collection, including all cases of ALF, was defined according to the criteria of the Pediatric Acute Liver Failure Study Group, admitted to a pediatric intensive care unit (PICU) for 28 years. Two groups were defined: spontaneous recovery (SR) and non-SR (NSR) - submitted to liver transplantation (LT) or death at PICU discharge.

Results

Fifty-nine patients were included, with a median age of 24 months, and 54% were female. The most frequent etiologies were metabolic (25.4%) and infectious (18.6%); 32.2% were undetermined. SR occurred in 21 patients (35.6%). In NSR group (N = 38, 64.4%), 25 required LT (42.4%) and 19 died (32.2%), 6 (15.7%) of whom after LT. The accuracy to predict NSR was acceptable for lactate at admission (AUC 0.72; 95% CI: 0.57-0.86; p = 0.006), ammonia peak (AUC 0.72; 95% CI: 0.58-0.86; p = 0.006), and INR peak (AUC 0.70; 95% CI: 0.56-0.85; p = 0.01). The cut-off value for lactate at admission was 1.95 mmol/L (sensitivity 78.4% and specificity 61.9%), ammonia peak was 64 μmol/L (sensitivity 100% and specificity 38.1%), and INR peak was 4.8 (sensitivity 61.1% and specificity 76.2%). Lactate on admission was shown to be an independent predictor of NSR on logistic regression model. Two prognostic scores had acceptable discrimination for NSR, LIU (AUC 0.73; 95% CI: 0.59-0.87; p = 0.004) and PRISM (AUC 0.71; 95% CI: 0.56-0.86; p = 0.03). In our study, the PALF delta score (PALF-ds) had lower discrimination capacity (AUC 0.63; 95% CI: 0.47-0.78; p = 0.11).

Conclusions

The lactate at admission, an easily obtained parameter, had a similar capacity than the more complex scores, LIU and PRISM, to predict NSR. The prognostic value in our population of the promising dynamic score, PALF-ds, was lower than expected.

A Single-Center Retrospective Evaluation of Unplanned Pediatric Critical Care Upgrades

Background  Inappropriate triage of critically ill pediatric patients can lead to poor outcomes and suboptimal resource utilization. This study aimed to determine and describe the demographic characteristics, diagnostic categories, and timing of unplanned upgrades to the pediatric intensive care unit (PICU) that required short (< 24 hours of care) and extended (≥ 24 hours of care) stays. In this article, we hypothesized that we will identify demographic characteristics, diagnostic categories, and frequent upgrade timing periods in both of these groups that may justify more optimal triage strategies. Methods  This was a single-institution retrospective study of unplanned PICU upgrades between 2012 and 2018. The cohort was divided into two groups (short and extended PICU stay). We reviewed the electronic health record and evaluated for: demographics, mortality scores, upgrade timing (7a-3p, 3p-11p, 11p-7a), lead-in time (time spent on clinical service before upgrade), patient origin, and diagnostic category. Results  Four hundred and ninety-eight patients' unplanned PICU upgrades were included. One hundred and nine patients (21.9%) required a short and 389 (78.1%) required an extended PICU stay. Lead-in time (mean, standard deviation) was significantly lower in the short group (0.65 ± 0.66 vs. 0.91 ± 0.82) ( p  = 0.0006). A higher proportion of short group patients (59, 46.1%) were upgraded during the 3p-11p shift ( p  = 0.0077). Conclusion  We found that approximately one-fifth of PICU upgrades required less than 24 hours of critical care services, were more likely to be transferred between 3p-11p, and had lower lead-in times. In institutions where ill pediatric patients can be admitted to either a PICU or a monitored step-down unit, this study highlights quality improvement opportunities, particularly in recognizing which pediatric patients truly need critical care.

Infant Intensive Care Unit: Is it Time to Change?

OBJECTIVES

To assess the effect of the Infant intensive care unit (InICU), a specialized unit for critically ill infants established in 2016 in authors' hospital, on infant mortality and compare the outcome with the current Pediatric intensive care units (PICU).

METHODS

In this retrospective cross-sectional study, two groups were defined; the first included expired patients aged 1 mo to 2 y admitted to PICU before the establishment of the InICU (the PICU group). The second included age-matched expired patients admitted to the InICU (the InICU group). Data were recorded using a questionnaire.

RESULTS

The authors found that the age, sex, underlying diseases, the leading cause of admission to the ICU, time of death, hospital and ICU length of stay, and the pediatric index of mortality 2 (PIM 2) score were same between the two groups. The incidence of mortality in the PICU group was 10.66 in 1000 person-month. This value was 6.37 for the InICU group (P-value <0.001). The relative risk of mortality of patients admitted to the PICU group compared to the InICU group was 1.67 (P-value <0.001).

CONCLUSIONS

Establishment of age specific InICU for infants may be beneficial in reducing infant mortality.

Performance of Platelet Mass Index as a Marker of Severity for Sepsis and Septic Shock in Children

Platelet mass index (PMI) as a prognostic indicator in pediatric sepsis has not been previously reported. In this retrospective observational study, we evaluated PMI's performance as a prognostic indicator in children aged younger than 18 years with sepsis and septic shock in relationship with survival. Over 5 years, we collected data from 122 children admitted to our pediatric intensive care unit (PICU). PMI accuracy was assessed with sensitivity and specificity and its discrimination was assessed using the area under the receiver operating characteristic curve (AUC). Median PMI values on days 1 and 3 of PICU admission were lower among nonsurvivors. On day 1 of PICU admission, a cutoff PMI value of 1,450 fL/nL resulted in a sensitivity of 72% and a specificity of 69%, and the AUC was 0.70 (95% confidence interval [CI]: 0.55-0.86). Similarly, on day 3, a cutoff of 900 fL/nL resulted in a sensitivity of 71% and a specificity of 70%, and the AUC was 0.76 (95% CI: 0.59-0.92). Our exploratory study suggests that low PMI in children with septic shock is associated with increased mortality. Considering the PMI's fair performance, further studies should be performed to assess its clinical value.

The outcome of high-frequency oscillatory ventilation in pediatric patients with acute respiratory distress syndrome in an intensive care unit

BACKGROUND

In adults with acute respiratory distress syndrome (ARDS), high-frequency oscillatory ventilation (HFOV) has been associated with higher mortality rates. Therefore, its use in children with ARDS is still controversial.

OBJECTIVES

Evaluate the overall mortality of HFOV in children with ARDS and explore mortality-related risk factors; compare the outcome of using HFOV post-endotracheal intubation early (≤24 hours) versus late (≤24 hours).

DESIGN

Retrospective (medical record review) SETTING: Pediatric intensive care unit in a tertiary care center in Saudi Arabia.

PATIENTS AND METHODS

Data were collected from medical records of all pediatric patients with ARDS aged one week to 14 years, who were admitted to the pediatric intensive care unit (PICU) from January 2016-June 2019 and who required HFOV.

MAIN OUTCOME MEASURES

PICU mortality.

SAMPLE SIZE AND CHARACTERISTICS

135 ARDS patients including 74 females (54.8%), and 61 males (45.2%), with a median age (interquar-tile range) of 35 (72) months.

RESULTS

The overall mortality rate was 60.0% (81/135), and most died in the first 28 days in the PICU (91.3%, 74/8). Of non-survivors, 75.3% (61/81) were immunocompromised, and 24.7% (20/81) were immuno-competent patients, 52 (64.2%) received inotropic support, 40 (49.4%) had a bone-marrow transplant (BMT) before HFOV initiation. Although the prone position was used in 20.7% (28/135) to improve the survival rate post-HFOV ventilation, only 28.6% (8/28) survived. In addition, altered code status or chemotherapy reported a significant association with mortality (P<.05). Interestingly, early HFOV initiation (≤24 hours) did not seem to have a high impact on survival compared to late initiation (>24 hours); (57.4% vs. 42.6%, P=.721).

CONCLUSION

Immunocompromised and oncology patients, including post-BMT, reported poorer outcomes, and neither the prone position nor early use of HFOV improved outcomes. However, it is recommended to replicate the study in a larger cohort to generalize the results.

LIMITATIONS

Retrospective single-center study.

Characterization of Pediatric Patients with Rheumatological Diseases Admitted to a Single Tertiary Health Hospital's Pediatric Intensive Care Unit in Latin America

Most autoimmune diseases (AIDs) during childhood debut with more severe and aggressive forms, with life-threatening conditions that increase the need for intensive care therapy. This study describes the clinical, laboratory, and health outcome features of pediatric patients with AIDs admitted to the pediatric intensive care unit (PICU). This is a retrospective cross-sectional study that included the clinical records of all pediatric patients with AIDs admitted to the PICU between 2011 and 2020 in Cali, Colombia. In total, 225 PICU admissions from 136 patients were evaluated. Median age was 13 (11–15) years, and the median disease duration was 15 (5–38.5) months. Systemic lupus erythematosus was the most prevalent disease (91, 66.9%), followed by vasculitis (27, 19.8%). The leading cause of PICU admission was AID activity (95, 44.3%). C-reactive-protein levels were associated with infections (p <0.0394). Mortality occurred in 12 (8.8%) patients secondary to AID activity, primarily, diffuse alveolar hemorrhage (6, 50%). A longer disease duration was associated with mortality (p <0.00398). AID activity was the leading cause of PICU admission and mortality. Pulse steroid therapy, mechanical ventilation, and inotropic and vasopressor support were associated with nonsurvival.

Performance and analysis of four pediatric mortality prediction scores among critically ill children: A multicenter prospective observational study in four PICUs

OBJECTIVE

We aimed to evaluate and compare the prognostic performance of common pediatric mortality scoring systems (the Pediatric Index of Mortality 2 [PIM2], PIM3, Pediatric Risk of Mortality [PRISM], and PRISM4 scores) to determine which is the most applicable score in our pediatric study cohort.

METHODS

This prospective observational multicenter cohort study was conducted in four tertiary-care pediatric intensive care units (PICUs) in Turkey. All children, between 1 month and 16 years old, admitted to the participating PICUs between October 1, 2019, and March 31, 2020, were included in the study. Discrimination between death and survival was assessed by area under the receiver operating characteristic plot (AUC) for each model. The Hosmer-Lemeshow goodness-of-fit (GOF) test was used to assess the calibration of the models, RESULTS: A total of 570 patients (median age 35 months) were enrolled in the study. The observed mortality rate was 8.2% (47/570). The standardized mortality ratio (SMR) of PIM2, PIM3, PRISM, and PRISM4 with 95% confidence interval (CI) were 0.94 (0.68-1.23), 1.27 (0.93-1.68), 0.86 (0.63-1.13), and 1.5 (1.10-1.97), respectively. The AUC with 95% CI was 0.934 (0.91-0.96) for PIM2, 0.934 (0.91-0.96) for PIM3, 0.917 (0.88-0.95) for PRISM, and 0.926 (0.88-0.97) for PRISM4 models. The Hosmer-Lemeshow test showed that the difference between observed and predicted mortality by PIM3 (p = 0.003) and PRISM4 (p = 0.008) was statistically significant whereas PIM2 (p = 0.28) and PRISM (p = 0.62) showed good calibration.

CONCLUSION

The overall performance of (both discrimination and calibration) PRISM and PIM2 scoring systems in Turkish pediatric patients aged 1 month to 16 years was accurate and had the best fit for risk groups according to our study. Although PIM3 and PRISM4 have good discriminatory power, their calibration was very poor in our study cohort.

Internal validation and evaluation of the predictive performance of models based on the PRISM-3 (Pediatric Risk of Mortality) and PIM-3 (Pediatric Index of Mortality) scoring systems for predicting mortality in Pediatric Intensive Care Units (PICUs)

PURPOSE

The study was aimed to assess the prognostic power The Pediatric Risk of Mortality-3 (PRISM-3) and the Pediatric Index of Mortality-3 (PIM-3) to predict in-hospital mortality in a sample of patients admitted to the PICUs.

DESIGN AND METHODS

The study was performed to include all children younger than 18 years of age admitted to receive critical care in two hospitals, Mashhad, northeast of Iran from December 2017 to November 2018. The predictive performance was quantified in terms of the overall performance by measuring the Brier Score (BS) and standardized mortality ratio (SMR), discrimination by assessing the AUC, and calibration by applying the Hosmer-Lemeshow test.

RESULTS

A total of 2446 patients with the median age of 4.2 months (56% male) were included in the study. The PICU and in-hospital mortality were 12.4 and 16.14%, respectively. The BS of the PRISM-3 and PIM-3 was 0.088 and 0.093 for PICU mortality and 0.108 and 0.113 for in-hospital mortality. For the entire sample, the SMR of the PRISM-3 and PIM-3 were 1.34 and 1.37 for PICU mortality and 1.73 and 1.78 for in-hospital mortality, respectively. The PRISM-3 demonstrated significantly higher discrimination power in comparison with the PIM-3 (AUC = 0.829 vs 0.745) for in-hospital mortality. (AUC = 0.779 vs 0.739) for in-hospital mortality. The HL test revealed poor calibration for both models in both outcomes.

CONCLUSIONS

The performance measures of PRISM-3 were better than PIM-3 in both PICU and in-hospital mortality. However, further recalibration and modification studies are required to improve the predictive power to a clinically acceptable level before daily clinical use.

PRACTICE IMPLICATIONS

The calibration of the PRISM-3 model is more satisfactory than PIM-3, however both models have fair discrimination power.

Performance of Pediatric Risk of Mortality III and Pediatric Index of Mortality III Scores in Tertiary Pediatric Intensive Unit in Saudi Arabia

OBJECTIVE

To assess the performance of the Pediatric Risk of Mortality III (PRISM III) and Pediatric Index of Mortality III (PIM III) indices in a tertiary pediatric intensive care unit (PICU) in Saudi Arabia and to identify the factors affecting the observed performance.

DESIGN

Retrospective, single-center study using data collected from the Virtual Pediatric Systems web-based database.

SETTING

King Fahad Medical City PICU, Saudi Arabia.

PATIENTS

All pediatric patients <14 years of age admitted between 1 January 2015, and 31 December 2019.

INTERVENTIONS

Comparison of PRISM III and PIM III performances in predicting mortality across different age groups, disease categories, and resuscitation decision statuses.

MEASUREMENTS

Normality of distribution was assessed using the Kolmogorov-Smirnov and Shapiro-Wilk tests. Patient characteristics were compared between survivors and non-survivors. The medians and ranges were calculated for continuous data, whereas frequencies and percentages were used for nominal data. The Mann-Whitney U test, Kruskal-Wallis test, and Chi-square test were used to compare the characteristics of survivors and non-survivors.

MAIN RESULTS

There was a significant difference between the predicted mortality and observed mortality in both the PRISM III and PIM III. Better discrimination was found after excluding do-not-resuscitate (DNR) patients. The worst calibration and discrimination were recorded for infants <12 months of age. The PRISM III performed significantly better in patients with metabolic/genetic and central nervous system illnesses. Non-DNR patients had a lower standardized mortality rate using the PRISM III and PIM III. The PRISM III and PIM III indices performed better in patients who died within the first week of admission.

CONCLUSION

These models had sufficient discrimination ability and poor calibration. Since they were designed for particular patient characteristics and PICUs, further testing in different environments is necessary before utilization for planning and assessing performance. Alternatively, new models could be developed which are suitable for local PICUs.

Multicenter validation of PIM3 and PIM2 in Brazilian pediatric intensive care units

OBJECTIVE

To validate the PIM3 score in Brazilian PICUs and compare its performance with the PIM2.

METHODS

Observational, retrospective, multicenter study, including patients younger than 16 years old admitted consecutively from October 2013 to September 2019. We assessed the Standardized Mortality Ratio (SMR), the discrimination capability (using the area under the receiver operating characteristic curve - AUROC), and the calibration. To assess the calibration, we used the calibration belt, which is a curve that represents the correlation of predicted and observed values and their 95% Confidence Interval (CI) through all the risk ranges. We also analyzed the performance of both scores in three periods: 2013-2015, 2015-2017, and 2017-2019.

RESULTS

41,541 patients from 22 PICUs were included. Most patients aged less than 24 months (58.4%) and were admitted for medical conditions (88.6%) (respiratory conditions = 53.8%). Invasive mechanical ventilation was used in 5.8%. The median PICU length of stay was three days (IQR, 2-5), and the observed mortality was 1.8% (763 deaths). The predicted mortality by PIM3 was 1.8% (SMR 1.00; 95% CI 0.94-1.08) and by PIM2 was 2.1% (SMR 0.90; 95% CI 0.83-0.96). Both scores had good discrimination (PIM3 AUROC = 0.88 and PIM2 AUROC = 0.89). In calibration analysis, both scores overestimated mortality in the 0%-3% risk range, PIM3 tended to underestimate mortality in medium-risk patients (9%-46% risk range), and PIM2 also overestimated mortality in high-risk patients (70%-100% mortality risk).

CONCLUSIONS

Both scores had a good discrimination ability but poor calibration in different ranges, which deteriorated over time in the population studied.

Clinical and Laboratory Predictors for the Development of Low Cardiac Output Syndrome in Infants Undergoing Cardiopulmonary Bypass: A Pilot Study

Cardiac surgery employing cardiopulmonary bypass exposes infants to a high risk of morbidity and mortality. The objective of this study was to assess the utility of clinical and laboratory variables to predict the development of low cardiac output syndrome, a frequent complication following cardiac surgery in infants. We performed a prospective observational study in the pediatric cardiovascular ICU in an academic children’s hospital. Thirty-one patients with congenital heart disease were included. Serum levels of nucleosomes and a panel of 20 cytokines were measured at six time points in the perioperative period. Cardiopulmonary bypass patients were characterized by increased levels of interleukin-10, -6, and -1α upon admission to the ICU compared to non-bypass cardiac patients. Patients developing low cardiac output syndrome endured longer aortic cross-clamp time and required greater inotropic support at 12 h postoperatively compared to bypass patients not developing the condition. Higher preoperative interleukin-10 levels and 24 h postoperative interleukin-8 levels were associated with low cardiac output syndrome. Receiver operating characteristic curve analysis demonstrated a moderate capability of aortic cross-clamp duration to predict low cardiac output syndrome but not IL-8. In conclusion, low cardiac output syndrome was best predicted in our patient population by the surgical metric of aortic cross-clamp duration.

Validity of Pediatric Index of Mortality 2 score as an Outcome Predictor in Pediatric ICU of a Public Sector Tertiary Care Hospital in Pakistan

Pediatric Index of Mortality 2 (PIM-2) is one of the leading mortality scores used in intensive care units all around the world. We assessed its validity as an outcome predictor in a pediatric intensive care unit (PICU) of Mayo Hospital/King Edward Medical University Lahore, Pakistan. We enrolled 154 consecutive admissions, aged 1 month to 13 years, requiring intensive care from January to June of 2019. Patient demographics along with PIM-2 data were collected; PIM-2 score and mortality risk was calculated; and the outcome recorded as death or survival. The median age at admission was 0.50 years (interquartile range [IQR]: 0.24–1.78) and the median weight was 5.0 kg (IQR: 3.08–10.0) with females constituting 54%; malnutrition was also common (66%). Observed mortality was 29.9% (46 out of 154) and expected mortality (cut-off ≥ 99.8%) was 27.9% with a standardized mortality ratio of 1.07 (95% confidence interval [CI]: 0.79–1.41). Sepsis was the most common diagnosis at admission (27.9%) with the highest mortality (52.2%). Chi-square analysis revealed a sensitivity of 54.3% and a specificity of 83.3% (p-value 0.00). PIM-2 score showed acceptable discrimination between survivors and nonsurvivors with an area under the receiver operating characteristic curve of 0.75 (95% CI: 0.67–0.84) (p-value = 0.00); however, poor calibration according to Hosmer–Lemeshow goodness of fit test (Chi-square = 15.80, df = 7, and p-value of 0.027 [< 0.1]), thus requiring recalibration according to local population characteristics.

Meta-Analysis for the Prediction of Mortality Rates in a Pediatric Intensive Care Unit Using Different Scores: PRISM-III/IV, PIM-3, and PELOD-2

Introduction: The risk of mortality is higher in pediatric intensive care units (PICU). To prevent mortality in critically ill infants, optimal clinical management and risk stratification are required. Aims and Objectives: To assess the accuracy of PELOD-2, PIM-3, and PRISM-III/IV scores to predict outcomes in pediatric patients. Results: A total of 29 studies were included for quantitative synthesis in meta-analysis. PRISM-III/IV scoring showed pooled sensitivity of 0.78; 95% CI: 0.72-0.83 and pooled specificity of 0.75; 95% CI: 0.68-0.81 with 84% discrimination performance (SROC 0.84, 95% CI: 0.80-0.87). In the case of PIM-3, pooled sensivity 0.75; 95% CI 0.71-0.79 and pooled specificity 0.76; 95% CI 0.73-0.79 were observed with good discrimination power (SROC, 0.82, 95% CI 0.78-0.85). PELOD-2 scoring system had pooled sensitivity of 0.78 (95% CI: 0.71-0.83) and combined specificity of 0.75 (95% CI: 0.68-0.81), as well as good discriminating ability (SROC 0.83, 95% CI: 0.80-0.86) for mortality prediction in PICU patients. Conclusion: PRISM-III/IV, PIM-3, and PELOD-2 had good performance for mortality prediction in PICU but with low to moderate certainty of evidence. More well-designed studies are needed for the validation of the study results.

Comparison of pediatric scoring systems for mortality in septic patients and the impact of missing information on their predictive power: a retrospective analysis

Background

Scores can assess the severity and course of disease and predict outcome in an objective manner. This information is needed for proper risk assessment and stratification. Furthermore, scoring systems support optimal patient care, resource management and are gaining in importance in terms of artificial intelligence.

Objective

This study evaluated and compared the prognostic ability of various common pediatric scoring systems (PRISM, PRISM III, PRISM IV, PIM, PIM2, PIM3, PELOD, PELOD 2) in order to determine which is the most applicable score for pediatric sepsis patients in terms of timing of disease survey and insensitivity to missing data.

Methods

We retrospectively examined data from 398 patients under 18 years of age, who were diagnosed with sepsis. Scores were assessed at ICU admission and re-evaluated on the day of peak C-reactive protein. The scores were compared for their ability to predict mortality in this specific patient population and for their impairment due to missing data.

Results

PIM (AUC 0.76 (0.68-0.76)), PIM2 (AUC 0.78 (0.72-0.78)) and PIM3 (AUC 0.76 (0.68-0.76)) scores together with PRSIM III (AUC 0.75 (0.68-0.75)) and PELOD 2 (AUC 0.75 (0.66-0.75)) are the most suitable scores for determining patient prognosis at ICU admission. Once sepsis is pronounced, PELOD 2 (AUC 0.84 (0.77-0.91)) and PRISM IV (AUC 0.8 (0.72-0.88)) become significantly better in their performance and count among the best prognostic scores for use at this time together with PRISM III (AUC 0.81 (0.73-0.89)). PELOD 2 is good for monitoring and, like the PIM scores, is also largely insensitive to missing values.

Conclusion

Overall, PIM scores show comparatively good performance, are stable as far as timing of the disease survey is concerned, and they are also relatively stable in terms of missing parameters. PELOD 2 is best suitable for monitoring clinical course.

Dynamic Electronic Tracking and Escalation to reduce Critical care Transfers (DETECT): the protocol for a stepped wedge mixed method study to explore the clinical effectiveness, clinical utility and cost-effectiveness of an electronic physiological surveillance system for use in children

Background

Active monitoring of hospitalised adults, using handheld electronic physiological surveillance systems, is associated with reduced in-patient mortality in the UK. Potential also exists to improve the recognition and response to deterioration in hospitalised children. However, the clinical effectiveness, the clinical utility, and the cost-effectiveness of this technology to reduce paediatric critical deterioration, have not been evaluated in an NHS environment.

Method

This is a non-randomised stepped-wedge prospective mixed methods study. Participants will be in-patients under the age of 18 years, at a tertiary children’s hospital. Day-case, neonatal surgery and Paediatric Intensive Care Unit (PICU) patients will be excluded.

The intervention is the implementation of Careflow Vitals and Connect (System C) to document vital signs and sepsis screening. The underpinning age-specific Paediatric Early Warning Score (PEWS) risk model calculates PEWS and provides associated clinical decision support. Real-time data of deterioration risk are immediately visible to the entire clinical team to optimise situation awareness, the chronology of the escalation and response are captured with automated reporting of the organisational safety profile.

Baseline data will be collected prospectively for 1 year preceding the intervention. Following a 3 month implementation period, 1 year of post-intervention data will be collected.

The primary outcome is unplanned transfers to critical care (HDU and/or PICU). The secondary outcomes are critical deterioration events (CDE), the timeliness of critical care transfer, the critical care interventions required, critical care length of stay and outcome.

The clinical effectiveness will be measured by prevalence of CDE per 1000 hospital admissions and per 1000 non-PICU bed days.

Observation, field notes, e-surveys and focused interviews will be used to establish the clinical utility of the technology to healthcare professionals and the acceptability to in-patient families. The cost-effectiveness will be analysed using Health Related Group costs per day for the critical care and hospital stay for up to 90 days post CDE.

Discussion

If the technology is effective at reducing CDE in hospitalised children it could be deployed widely, to reduce morbidity and mortality, and associated costs.

Trial registration

Current Controlled Trials ISRCTN61279068, date of registration 03.06.19, retrospectively registered.