Introduction: Sepsis-associated acute kidney injury (AKI) is a common diagnosis in children that is associated with poor outcomes. The lack of therapeutic options once present makes early identification of at-risk patients essential. The renal angina index (RAI) has been previously validated to predict severe AKI in heterogeneous populations of critically ill children. The performance of this score specifically in children with septic shock is unknown. Methods: A secondary analysis of a multicenter, prospective, observational study of 379 children with septic shock to determine the ability of the RAI to predict severe AKI at day 3, and to assess for the potential need for recalibration of the RAI in this unique subset of patients. Results: At the original cutoff of ≥8, the RAI predicted day 3 severe AKI with an area under the receiving operating characteristic (AUROC) curve 0.90 (95% confidence interval [CI]: 0.86 to 93), 95% sensitivity, and 54% specificity. A Youden's index identified a higher optimal cutoff of ≥20 (sensitivity 83%, specificity 80%), and day 1 platelet count <150 × 103/μl was an independent predictor of severe AKI (adjusted odds ratio: 3.2; 95% CI: 1.7 to 6.3; P < 0.001). Recalibration of the RAI to include platelet count and this new threshold restored the sensitivity of the original ≥8 threshold (95%), while improving its specificity (69%). Conclusions: The RAI appears to be a sensitive and reliable tool for prediction of severe AKI in children with septic shock, although the use of a recalibrated sepsis-specific RAI using a higher cutoff and platelet count may be beneficial.

Secretory phospholipase 2 (sPLA2) acts as a mediator between proximal and distal events of the inflammatory cascade. Its role in SARS-CoV-2 infection is unknown, but could contribute to COVID-19 inflammasome activation and cellular damage. We present the first report of plasma sPLA2 levels in adults and children with COVID-19 compared with controls. Currently asymptomatic adults with a history of recent COVID-19 infection (≥4 weeks before) identified by SARS-CoV-2 IgG antibodies had sPLA2 levels similar to those who were seronegative (9 ± 6 vs.17 ± 28 ng/mL, P = 0.26). In contrast, children hospitalized with severe COVID-19 had significantly elevated sPLA2 compared with those with mild or asymptomatic SARS-CoV-2 infection (269 ± 137 vs. 2 ± 3 ng/mL, P = 0.01). Among children hospitalized with multisystem inflammatory syndrome in children (MIS-C), all had severe disease requiring pediatric intensive care unit (PICU) admission. sPLA2 levels were significantly higher in those with acute illness <10 days versus convalescent disease ≥10 days (540 ± 510 vs. 2 ± 1, P = 0.04). Thus, sPLA2 levels correlated with COVID-19 severity and acute MIS-C in children, implicating a role in inflammasome activation and disease pathogenesis. sPLA2 may be a useful biomarker to stratify risk and guide patient management for children with acute COVID-19 and MIS-C. Therapeutic compounds targeting sPLA2 and inflammasome activation warrant consideration.

Background: Acute kidney injury occurs in one in four children admitted to an intensive care unit (ICU) and its severity is independently associated with increased patient morbidity and mortality. Early prediction of acute kidney injury has the potential to improve outcomes. In smaller, single-centre trial populations, we have previously derived and validated the performance of a renal angina index, a context-driven risk stratification system, to predict severe acute kidney injury in children and adolescents. Here, we tested the predictive accuracy of this index for severe acute kidney injury in a large heterogeneous population. Methods: We did a prospective, observational study (AWARE) that recruited patients in the ICUs of 32 hospitals in nine countries across Asia, Australia, Europe, and North America. All patients aged between 3 months and 25 years who were admitted to an ICU at least 48 h previously were eligible. Exclusion criteria were a history of stage 5 chronic kidney disease (ie, estimated glomerular filtration rate <15 mL/min per 1·73m 2 or on maintenance dialysis) or kidney transplantation in the preceding 90 days. Patients' medical records were reviewed to collect data up to 3 months before (serum creatinine only), daily during the first 7 days, and on day 28 after ICU admission. For the assessment of the renal angina index, we included patients from the AWARE study who had full data from the day of ICU admission, day 3, and day 28, including serum creatinine concentrations and urine output measurements. The primary outcome was the presence of severe acute kidney injury (stage 2–3 acute kidney injury, according to Kidney Disease Improving Global Outcomes [KDIGO] guidelines) on the third day after ICU admission. We compared the performance of the renal angina index with changes in serum creatinine relative to baseline for prediction of the primary outcome. A score of eight points or more on the renal angina index defined fulfilment of renal angina; serum creatinine concentration relative to baseline was calculated using maximum serum creatinine concentration in the first 12 h of ICU admission). This trial is registered with ClinicalTrials.gov, number NCT01987921. Findings: Between Jan 1 and Dec 31, 2014, we obtained data for 1590 patients. 286 patients (18%) had fulfilment of renal angina. At day 3, severe acute kidney injury occurred in 121 (42%) patients positive for renal angina and 247 (19%) patients negative for renal angina (relative risk [RR] 2·23, 95% CI 1·87–2.66, p<0·0001). Of 368 (23%) patients with severe acute kidney injury, more had increased use of renal replacement and increased mortality than of the 1222 (77%) patients without severe acute kidney injury (40 [11%] vs 18 [2%], p<0.0001; and 28 [8%] vs 53 [4%], p=0·01). Fulfilment of renal angina showed better prediction for severe acute kidney injury than serum creatinine greater than baseline (RR 1.61, 95% CI 1·33–1·93; p<0·0001), which was maintained on multivariate regression (independent odds ratio for fulfilment of renal angina 3·21, 95% CI 2·20–4·67 vs serum creatinine greater than baseline 0·68, 0·49–4·94). Interpretation: Earlier and better prediction of severe acute kidney injury has the potential to improve patient outcomes associated with acute kidney injury. Compared with isolated, context-free changes in serum creatinine, renal angina risk assessment improved accuracy for prediction of severe acute kidney injury in critically ill children and young people. Funding: US National Institutes of Health.

Background: The prevalence of continuous renal replacement therapy (CRRT) utilization in critically ill patients with acute kidney is increasing. In comparison to published and on-going trials attempting to answer questions surrounding the optimal timing of CRRT initiation, anticoagulation, and modality, a paucity of literature describes the quality of the therapy delivered. Methods: We conducted a single-center process improvement project to determine if a methodology to assess the quality of CRRT delivery could lead to improvement in CRRT delivery outcomes. We developed three broad categories of objective CRRT metrics to assess longitudinally, enabling creation of a CRRT Dashboard. Following the objective categories of "filter", "prescription", and "fluid balance" over time allowed us to perform quarterly analyses, target provider based CRRT education, and address variation from our standard of care. From 2012 to 2017, 184 critically ill patients received CRRT. Results: We report a mean filter life of 56 + 28.4 h, a 60-h filter life of 62%, and unplanned filter changes of 15%. Compared to a minimum target prescription of 2000 ml/1.73 m2/hour, we report the mean prescribed dose (2300 ml/1.73 m2/hour) and the rate of patients receiving at least the minimum prescription (98%). Finally, using a 10% deviation in the acceptable range of desired daily patient fluid balance, we report 83% CRRT patient days achieving an acceptable stipulated fluid goal. Conclusion: We report the implementation of a quality dashboard and adopting quality improvement strategies provided a platform for measuring adherence to our institutional standards and the delivery of CRRT, specifically on the process of the care.

Prior criteria for organ dysfunction in critically ill children were based mainly on expert opinion. We convened the Pediatric Organ Dysfunction Information Update Mandate (PODIUM) expert panel to summarize data characterizing single and multiple organ dysfunction and to derive contemporary criteria for pediatric organ dysfunction. The panel was composed of 88 members representing 47 institutions and 7 countries. We conducted systematic reviews of the literature to derive evidence-based criteria for single organ dysfunction for neurologic, cardiovascular, respiratory, gastrointestinal, acute liver, renal, hematologic, coagulation, endocrine, endothelial, and immune system dysfunction. We searched PubMed and Embase from January 1992 to January 2020. Study identification was accomplished using a combination of medical subject headings terms and keywords related to concepts of pediatric organ dysfunction. Electronic searches were performed by medical librarians. Studies were eligible for inclusion if the authors reported original data collected in critically ill children; evaluated performance characteristics of scoring tools or clinical assessments for organ dysfunction; and assessed a patient-centered, clinically meaningful outcome. Data were abstracted from each included study into an electronic data extraction form. Risk of bias was assessed using the Quality in Prognosis Studies tool. Consensus was achieved for a final set of 43 criteria for pediatric organ dysfunction through iterative voting and discussion. Although the PODIUM criteria for organ dysfunction were limited by available evidence and will require validation, they provide a contemporary foundation for researchers to identify and study single and multiple organ dysfunction in critically ill children.

Background: Acute kidney injury is a common complication following the Norwood operation. Most neonatal studies report acute kidney injury peaking within the first 48 hours after cardiac surgery. The aim of this study was to evaluate if persistent acute kidney injury (>48 postoperative hours) after the Norwood operation was associated with clinically relevant outcomes. Methods: Two-centre retrospective study among neonates undergoing the Norwood operation. Acute kidney injury was initially identified as developing within the first 48 hours after cardiac surgery and stratified into transient (≤48 hours) and persistent (>48 hours) using the neonatal modification of the Kidney Disease: Improving Global Outcomes serum creatinine criteria. Severe was defined as stage ≥2. Primary and secondary outcomes were mortality and duration of ventilation and hospital length of stay. Results: One hundred sixty-eight patients were included. Transient and persistent acute kidney injuries occurred in 24 and 17%, respectively. Cardiopulmonary bypass and aortic cross clamp duration, and incidence of cardiac arrest were greater among those with persistent kidney injury. Mortality was four times higher (41 versus 12%, p < 0.001) and mechanical ventilation duration 50 hours longer in persistent acute kidney injury patients (158 versus 107 hours; p < 0.001). In multivariable analysis, persistent acute kidney injury was not associated with mortality, duration of ventilation or length of stay. Severe persistent acute kidney injury was associated with a 59% increase in expected ventilation duration (aIRR:1.59, 95% CI:1.16, 2.18; p = 0.004). Conclusions: Future large studies are needed to determine if risk factors and outcomes change by delineating acute kidney injury into discrete timing phenotypes.

Background: Fluid overload and acute kidney injury are common and associated with poor outcomes among critically ill children. The prodrome of renal angina stratifies patients by risk for severe acute kidney injury, but the predictive discrimination for fluid overload is unknown. Methods: Post-hoc analysis of patients admitted to a tertiary care pediatric intensive care unit (PICU). The primary outcome was the performance of renal angina fulfillment on day of ICU admission to predict fluid overload ≥15% on Day 3. Results: 77/139 children (55%) fulfilled renal angina (RA+). After adjusting for covariates, RA+ was associated with increased odds of fluid overload on Day 3 (adjusted odds ratio (aOR) 5.1, 95% CI 1.23–21.2, p = 0.025, versus RA-). RA- resulted in a 90% negative predictive value for fluid overload on Day 3. Median fluid overload was significantly higher in RA+ patients with severe acute kidney injury compared to RA+ patients without severe acute kidney injury (% fluid overload on Day 3: 8.8% vs. 0.73%, p = 0.002). Conclusion: Among critically ill children, fulfillment of renal angina was associated with increased odds of fluid overload versus the absence of renal angina and a higher fluid overload among patients who developed acute kidney injury. Renal angina directed risk classification may identify patients at highest risk for fluid accumulation. Expanded study in larger populations is warranted.

Objective: Predict the onset of presumed serious infection, defined as a positive blood culture drawn and new antibiotic course of at least 4 days (PSI*), among pediatric patients with Central Venous Lines (CVLs). Design: Retrospective cohort study. Setting: Single academic children's hospital. Patients: All hospital encounters from January 2013 to December 2018, excluding the ones without a CVL or with a length-of-stay shorter than 24 h. Measurements and Main Results: Clinical features including demographics, laboratory results, vital signs, characteristics of the CVLs and medications used were extracted retrospectively from electronic medical records. Data were aggregated across all hospitals within a single pediatric health system and used to train a deep learning model to predict the occurrence of PSI* during the next 48 h of hospitalization. The proposed model prediction was compared to prediction of PSI* by a marker of illness severity (PELOD-2). The baseline prevalence of line infections was 0.34% over all segmented 48-h time windows. Events were identified among cases using onset time. All data from admission till the onset was used for cases and among controls we used all data from admission till discharge. The benchmarks were aggregated over all 48 h time windows [N=748,380 associated with 27,137 patient encounters]. The model achieved an area under the receiver operating characteristic curve of 0.993 (95% CI = [0.990, 0.996]), the enriched positive predictive value (PPV) was 23 times greater than the base prevalence. Conversely, prediction by PELOD-2 achieved a lower PPV of 1.5% [0.9%, 2.1%] which was 5 times the baseline prevalence. Conclusion: A deep learning model that employs common clinical features in the electronic health record can help predict the onset of CLABSI in hospitalized children with central venous line 48 hours prior to the time of specimen collection.

Low plasma arginine bioavailability has been implicated in endothelial dysfunction and immune dysregulation. The role of arginine in COVID-19 is unknown, but could contribute to cellular damage if low. Our objective was to determine arginine bioavailability in adults and children with COVID-19 vs. healthy controls. We hypothesized that arginine bioavailability would be low in patients with COVID-19 and multisystem inflammatory syndrome in children (MIS-C). We conducted a prospective observational study of three patient cohorts; arginine bioavailability was determined in asymptomatic healthy controls, adults hospitalized with COVID-19, and hospitalized children/adolescents <21 y old with COVID-19, MIS-C, or asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection identified on admission screen. Mean patient plasma amino acids were compared to controls using the Student’s t test. Arginine-to-ornithine ratio, a biomarker of arginase activity, and global arginine bioavailability ratio (GABR, arginine/[ornithine+citrulline]) were assessed in all three groups. A total of 80 patients were included (28 controls, 32 adults with COVID-19, and 20 pediatric patients with COVID-19/MIS-C). Mean plasma arginine and arginine bioavailability ratios were lower among adult and pediatric patients with COVID-19/MIS-C compared to controls. There was no difference between arginine bioavailability in children with COVID-19 vs. MIS-C. Adults and children with COVID-19 and MIS-C in our cohort had low arginine bioavailability compared to healthy adult controls. This may contribute to immune dysregulation and endothelial dysfunction in COVID-19. Low arginine-to-ornithine ratio in patients with COVID-19 or MIS-C suggests an elevation of arginase activity. Further study is merited to explore the role of arginine dysregulation in COVID-19.

Background: Presumed serious infection (PSI) is defined as a blood culture drawn and new antibiotic course of at least 4 days among pediatric patients with Central Venous Lines (CVLs). Early PSI prediction and use of medical interventions can prevent adverse outcomes and improve the quality of care. Methods: Clinical features including demographics, laboratory results, vital signs, characteristics of the CVLs and medications used were extracted retrospectively from electronic medical records. Data were aggregated across all hospitals within a single pediatric health system and used to train machine learning models (XGBoost and ElasticNet) to predict the occurrence of PSI 8 h prior to clinical suspicion. Prediction for PSI was benchmarked against PRISM-III. Results: Our model achieved an area under the receiver operating characteristic curve of 0.84 (95% CI = [0.82, 0.85]), sensitivity of 0.73 [0.69, 0.74], and positive predictive value (PPV) of 0.36 [0.34, 0.36]. The PRISM-III conversely achieved a lower sensitivity of 0.19 [0.16, 0.22] and PPV of 0.30 [0.26, 0.34] at a cut-off of ≥ 10. The features with the most impact on the PSI prediction were maximum diastolic blood pressure prior to PSI prediction (mean SHAP = 3.4), height (mean SHAP = 3.2), and maximum temperature prior to PSI prediction (mean SHAP = 2.6). Conclusion: A machine learning model using common features in the electronic medical records can predict the onset of serious infections in children with central venous lines at least 8 h prior to when a clinical team drew a blood culture.