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Predictive models are mathematical functions that take input variable(s), process the input variable(s) and produce an output. The mathematical definition of processing the input variable(s) to produce an output is an algorithm. Describing the relation between the variables in a dataset can be feasible by linear equations in some datasets. For instance, linear regression models aim to fit a linear line that relates input variable(s) to output variable(s). However, when there are a large number of variables, or their relation to the output variable is too complex, or non-linear to be described by linear lines, or even there is no obvious output variable to be predicted in the dataset, then the classic linear regression models fail. In such cases, a different approach is needed. This alternative strategy is called ML. In ML, algorithms are developed to discover unknown complex relations between variables from a large dataset, and these algorithms produce outputs based on what they discovered or ‘learnt’ from the dataset.

Streptococcus pneumoniae-associated hemolytic uremic syndrome (Sp-HUS) is a serious complication of invasive pneumococcal disease that is associated with increased mortality in the acute phase and morbidity in the long term. Recently, Sp-HUS definition has undergone revision and cases are categorized as definite, probable, and possible, based on less invasive serological investigations that evaluate Thomsen-Friedenreich crypt antigen (T-antigen) activation. In comparison to the pre-vaccine era, Sp-HUS incidence seems to be decreasing after the introduction of 7-serotype valence and 13-serotype valence pneumococcal vaccines in 2000 and 2010, respectively. However, Sp-HUS cases continue to occur secondary to vaccine failure and emergence of non-vaccine/replacement serotypes. No single hypothesis elucidates the molecular basis for Sp-HUS occurrence, although pneumococcal neuraminidase production and formation of T-antigen antibody complexes on susceptible endothelial and red blood cells continues to remain the most acceptable explanation. Management of Sp-HUS patients remains supportive in nature and better outcomes are being reported secondary to earlier recognition, better diagnostic tools and improved medical care. Recently, the addition of eculizumab therapy in the management of Sp-HUS for control of dysregulated complement activity has demonstrated good outcomes, although randomized clinical trials are awaited. A sustained pneumococcal vaccination program and vigilance for replacement serotypes will be the key for persistent reduction in Sp-HUS cases worldwide.

To study association of enteral feeds in bronchiolitis patients supported by different levels of high flow nasal cannula (HFNC) with adverse events, nutritional goals, and clinical outcomes. Bronchiolitis patients ≤ 24 months of age treated with < 1 L/kg/min, 1–2 L/kg/min and > 2 L/kg/min of HFNC between January 2014 and December 2021 were studied retrospectively at a tertiary care children’s hospital. Adverse events (aspiration pneumonia, emesis, and respiratory support escalation), nutritional goals (initiation of enteral feeds, achievement of nutritional goal volume and goal calories, percentage weight change during hospital stay) and clinical outcomes (HFNC duration, oxygen supplementation duration after HFNC, length of hospital stay following HFNC support, total length of hospital stay and follow-up for 1 month after hospital discharge) were compared between fed and non-fed patients on HFNC. Six hundred thirty-six (489 fed and 147 not-fed) bronchiolitis patients on HFNC studied. 260 patients, 317 patients and 59 patients were supported by < 1 L/kg/min, 1–2 L/kg/min and > 2 L/kg/min of HFNC, respectively. Enterally fed patients had significantly less adverse events (OR = 0.14, 95% CI 0.083 – 0.23, p < 0.001), significantly better nutritional goals: earlier initiation of enteral feeds by 65% in time (mean ratio = 0.35, 95% CI 0.28 – 0.43, p < 0.001), earlier achievement of goal volume and goal calorie needs by 14% in time (mean ratio = 0.86, 95% CI 0.78 to 0.96, p = 0.005) and significantly better clinical outcomes: shorter HFNC duration by 29.75 h (95% CI 20.19 -39.31, p < 0.001), shorter oxygen supplementation duration after HFNC by 12.14 h (95% CI 6.70 -17.59, p < 0.001), shorter length of hospital stay after HFNC support by 21.35 h (95% CI 14.71–27.98, p < 0.001) and shorter total length of hospital stay by 51.10 h (95% CI 38.65 -63.55, p < 0.001), as compared to non-fed patients, after adjusting for age, weight, prematurity, comorbidities, admission time, admission bronchiolitis score, admission respiratory rate, and HFNC levels. The number of revisits and readmissions at 7 and 30 days after hospital discharge were not significantly different (p > 0.05) between the fed and non-fed groups.     Conclusion : Enteral feeding of bronchiolitis patients supported by different levels of HFNC is associated with less adverse events and better nutrition goals and clinical outcomes. What is Known: •There is general apprehension to feed critically ill bronchiolitis patients supported by high flow nasal cannula. What is New: •Our study reveals that enteral feeding of critically ill bronchiolitis patients supported by different levels of high flow nasal cannula is associated with minimal adverse events, better nutritional goals and improved clinical outcomes as compared to non-fed patients.

Background This study aims to externally validate a clinical mathematical model designed to predict urine output (UOP) during the initial post-operative period in pediatric patients who underwent cardiac surgery with cardiopulmonary bypass (CPB). Methods Children aged 0–18 years admitted to the pediatric cardiac intensive care unit at Cleveland Clinic Children’s from April 2018 to April 2023, who underwent cardiac surgery with CPB were included. Patients were excluded if they had pre-operative kidney failure requiring kidney replacement therapy (KRT), re-operation or extracorporeal membrane oxygenation or KRT requirement within the first 32 post-operative hours or had indwelling urinary catheter for fewer than the initial 32 post-operative hours, or had vasoactive-inotrope score of 0, or those with missing data in the electronic health records. Results A total of 213 encounters were analyzed; median age (days): 172 (IQR 25–75th%: 51–1655), weight (kg): 6.1 (IQR 25–75th%: 3.8–15.5), median UOP ml/kg/hr in the first 32 post-operative hours: 2.59 (IQR 25–75th%: 1.93–3.26) and post-operative 30-day mortality: 1, (0.4%). The mathematical model achieved the following metrics in the entire dataset: mean absolute error (95th% Confidence Interval (CI)): 0.70 (0.67–0.73), median absolute error (95th% CI): 0.54 (0.52–0.56), mean squared error (95th% CI): 0.97 (0.89–1.05), root mean squared error (95th% CI): 0.99 (0.95–1.03) and R2 Score (95th% CI): 0.29 (0.24–0.34). Conclusions This study provides encouraging external validation results of a mathematical model predicting post-operative UOP in pediatric cardiac surgery patients. Further multicenter studies must explore its broader applicability. Graphical abstract A higher resolution version of the Graphical abstract is available as Supplementary information

Purpose: To develop and validate machine learning models for predicting the length of stay (LOS) in the Pediatric Intensive Care Unit (PICU) using data from the Virtual Pediatric Systems (VPS) database. Methods: A retrospective study was conducted utilizing machine learning (ML) algorithms to analyze and predict PICU LOS based on historical patient data from the VPS database. The study included data from over 100 North American PICUs spanning the years 2015–2020. After excluding entries with missing variables and those indicating recovery from cardiac surgery, the dataset comprised 123,354 patient encounters. Various ML models, including Support Vector Machine, Stochastic Gradient Descent Classifier, K-Nearest Neighbors, Decision Tree, Gradient Boosting, CatBoost, and Recurrent Neural Networks (RNNs), were evaluated for their accuracy in predicting PICU LOS at thresholds of 24 h, 36 h, 48 h, 72 h, 5 days, and 7 days. Results: Gradient Boosting, CatBoost, and RNN models demonstrated the highest accuracy, particularly at the 36 h and 48 h thresholds, with accuracy rates between 70 and 73%. These results far outperform traditional statistical and existing prediction methods that report accuracy of only around 50%, which is effectively unusable in the practical setting. These models also exhibited balanced performance between sensitivity (up to 74%) and specificity (up to 82%) at these thresholds. Conclusions: ML models, particularly Gradient Boosting, CatBoost, and RNNs, show moderate effectiveness in predicting PICU LOS with accuracy slightly over 70%, outperforming previously reported human predictions. This suggests potential utility in enhancing resource and staffing management in PICUs. However, further improvements through training on specialized databases can potentially achieve better accuracy and clinical applicability.

Optimal treatment for non-critically ill multisystem inflammatory syndrome in children (MIS-C) remains unclear. We evaluated short-term outcomes in mild to moderately ill hospitalized MIS-C patients fulfilling CDC 2020 and CDC/CTSE 2023 criteria and treated between April 2020 and March 2022 with either intravenous immunoglobulin (IVIG) monotherapy (Group A, n = 17) or IVIG plus corticosteroids (GC) (Group B, n = 22). Cardiovascular clinical parameters, inflammatory markers, and cardiac imaging were compared on days 1, 3, and 5 relative to day 0. The two groups had no significant differences in demographics or illness severity. Group B showed improvement in heart rate (17.8; 95% CI [9.74, 25.8]), mean blood pressure (5.63 [1.61, 9.64]), and body temperature (1.45 [0.94, 1.95]) by day 1, followed by improvement in albumin (0.43 [0.2, 0.84]), CRP (7.56 [3.0, 12.11]), D-dimer (2344 [488.7, 4200.2]), ferritin (1448 [−609.4, 3505.5]), fibrinogen (110 [44.4, 176]), lymphocyte count (1006 [63.5, 1948]), and NT-proBNP (2901 [−349.3, 6153]) by day 3 and left ventricular ejection fraction by day 4–5 (3.84 [0.55, 8.23]). All results were statistically significant (p < 0.05). Group A required more additional therapies, with no difference in hospital stay. Our study concludes that combined IVIG and GC therapy yielded better short-term outcomes than IVIG monotherapy in this patient population, with improvement in cardiovascular clinical parameters preceding changes in inflammatory markers and cardiac imaging.

Two paediatric congenital heart disease patients presented with a brief history of low-grade fever without any focal symptoms. Their clinical features and laboratory tests were unremarkable; however, their blood cultures were positive that prompted further work-up. Infective endocarditis should be considered in any paediatric congenital heart disease patient who presents with fever without any other associated clinical features.

Purpose of review Cardiac output (CO) is a fundamental physiological parameter that measures the volume of blood that is pumped by the heart per unit of time, and helps define how oxygen is delivered to the tissues of the human body. In this paper, we discuss current methods of continuous CO monitoring while defining low CO syndrome (LCOS) and how analytical tools may help improve CO management in the subpopulation of patients with congenital heart disease (CHD). Recent findings Non-invasive methods of measuring CO have become increasingly available in recent years. Advantages of non-invasive over invasive techniques include decreased risk of procedural complications, decreased exposure to sedative and/or anesthetic agents, and increased patient comfort. Pediatric patient populations are particularly sensitive to the risks and complications of invasive techniques given the relative size of current technologies to pediatric vascular and cardiac dimensions. Summary Novel device technologies, combined with emerging analytical techniques, may help improve measurement of CO in children and those with CHD, and allow earlier detection of LCOS.

Context: Lung transplantation is limited by donor lung availability with ∼20% of deceased donor lungs transplanted. Diagnostic testing identifying pulmonary derangements guide donor management strategies to maximize lung transplantation. Lung ultrasound (LUS) identifies pathology in critically ill patients equivalent or superior to chest radiograph (CXR) or computed tomography (CT) scans. No published studies have reported on LUS in neurologically deceased donors (DNDDs). Objective: We evaluated LUS in identifying abnormal lung pathology in DNDDs and related these findings to the standard approach. Design: Prospective pilot study. Setting: Intensive care units, university-associated teaching hospital. Participants: Six DNDDs evaluated during donor management. Interventions: Deceased donors were enrolled based on the availability of ultrasound operators (USOs). Bedside LUS was performed using Lichtenstein 3- or Volpicelli 4-zone method based on the operator preference. Lungs were evaluated for sliding, A/B profile, consolidation, or pleural fluid. Ultrasound operators were blinded to donor management data. Lung ultrasound interpretations were compared for interindividual variability. Ultrasound and anteroposterior portable CXR (AP-CXR) results were compared by Organ Procurement Organization medical directors. Measurements and Main Results: Bedside LUS compared well to AP-CXRs during donor management. There was no interindividual variability noted among USOs. Lung ultrasound identified all findings on AP-CXR and additional clinical pathology not reported on AP-CXR. Reports on AP-CXRs took a median 202 (13-696) minutes to occur, with LUS results available immediately. Conclusions: Lung ultrasound may play a significant role in donor management providing real-time clinical data, allowing for rapid identification of abnormalities, and leading to management interventions that may increase the number of transplanted lungs.

BackgroundThe rates, outcomes, and long-term trends of stroke complicating the use of extracorporeal membrane oxygenation (ECMO) have been inconsistently reported. We compared the outcomes of pediatric ECMO patients with and without stroke and described the frequency trends between 2000 and 2017.MethodsUsing the National Inpatient Sample (NIS) database, pediatric patients (age ≤18 years) who received ECMO were identified using ICD-9&10 codes. Binary, regression, and trend analyses were performed to compare patients with and without stroke.ResultsA total of 114,477,997 records were reviewed. Overall, 28,695 (0.025%) ECMO patients were identified of which 2982 (10.4%) had stroke, which were further classified as hemorrhagic (n = 1464), ischemic (n = 1280), or combined (n = 238). Mortality was higher in the hemorrhagic and combined groups compared to patients with ischemic stroke and patients without stroke. Length of stay (LOS) was significantly longer in stroke vs. no-stroke patients. Hypertension and septicemia were more encountered in the hemorrhagic group, whereas the combined group demonstrated higher frequency of cardiac arrest and seizures.ConclusionsOver the years, there is an apparent increase in the diagnosis of stroke. All types of stroke in ECMO patients are associated with increased LOS, although mortality is increased in hemorrhagic and combined stroke only.ImpactStroke is a commonly seen complication in pediatric patients supported by ECMO.Understanding the trends will help in identifying modifiable risk factors that predict poor outcomes in this patient population.