The effect of excessive gas to blood ratios in an ECMO oxygenator.

INTRODUCTION: Oxygenators for paediatric Extracorporeal Membrane Oxygenation (ECMO) are required to operate over a wide range of flow rates, in a patient group ranging from neonates through to fully grown adolescents. ECMO oxygenators typically have a manufacturer's stated maximum gas: blood flow rate (GBFR) ratio of 2:1, however, many patients require greater ratios than this for adequate CO2 removal. Mismatches in GBFR in theory could result in high gas phase pressures. These increased pressures in theory could cause the formation of gross gaseous microemboli (GME) placing the child at higher risk of neurological injury. METHODS: We evaluated 6 paediatric and 6 adult A.L.ONE™ ECMO oxygenators and assessed their gas phase pressures and GME release, in an ex vivo setting, in GBFR ratios up to greater than 2, across a range of gas flow (1L - 10 L/min) rates with a fraction of inspired oxygen (FiO2) content of 50% and 100%. RESULTS: There were no increases above 10 mmHg observed in gas phase pressures in GBFR >= 2:1 in either adult or paediatric oxygenators. Laboratory examination of GME activity demonstrated a small increase in post-membrane GME release over the study period. GME release was unaffected by FiO2 setting or gas flow rate, with a maximum volume of < 6 µL in both paediatric and adult oxygenators. CONCLUSIONS: In an ex vivo setting, increasing GBFR above 2:1 in a paediatric oxygenator, and to a GBFR of 2:1 in an adult oxygenator did not significantly increase gas phase pressures, and no oxygenator membrane rupture was observed. There were no associations between gas flow rates and GME production.

Rapid desensitization through immunoadsorption during cardiopulmonary bypass. A novel method to facilitate human leukocyte antigen incompatible heart transplantation.

BACKGROUND: Anti-human leukocyte antigen (HLA)-antibody production represents a major barrier to heart transplantation, limiting recipient compatibility with potential donors and increasing the risk of complications with poor waiting-list outcomes. Currently there is no consensus to when desensitization should take place, and through what mechanism, meaning that sensitized patients must wait for a compatible donor for many months, if not years. We aimed to determine if intraoperative immunoadsorption could provide a potential desensitization methodology. METHODS: Anti-HLA antibody-containing whole blood was added to a Cardiopulmonary bypass (CPB) circuit set up to mimic a 20 kg patient undergoing heart transplantation. Plasma was separated and diverted to a standalone, secondary immunoadsorption system, with antibody-depleted plasma returned to the CPB circuit. Samples for anti-HLA antibody definition were taken at baseline, when combined with the CPB prime (on bypass), and then every 20 min for the duration of treatment (total 180 min). RESULTS: A reduction in individual allele median fluorescence intensity (MFI) to below clinically relevant levels (<1000 MFI), and in the majority of cases below the lower positive detection limit (<500 MFI), even in alleles with a baseline MFI >4000 was demonstrated. Reduction occurred in all cases within 120 min, demonstrating efficacy in a time period usual for heart transplantation. Flowcytometric crossmatching of suitable pseudo-donor lymphocytes demonstrated a change from T cell and B cell positive channel shifts to negative, demonstrating a reduction in binding capacity. CONCLUSIONS: Intraoperative immunoadsorption in an ex vivo setting demonstrates clinically relevant reductions in anti-HLA antibodies within the normal timeframe for heart transplantation. This method represents a potential desensitization technique that could enable sensitized children to accept a donor organ earlier, even in the presence of donor-specific anti-HLA antibodies.

Clinical phenotypes and outcomes in children with multisystem inflammatory syndrome across SARS-CoV-2 variant eras: a multinational study from the 4CE consortium.

Background: Multisystem inflammatory syndrome in children (MIS-C) is a severe complication of SARS-CoV-2 infection. It remains unclear how MIS-C phenotypes vary across SARS-CoV-2 variants. We aimed to investigate clinical characteristics and outcomes of MIS-C across SARS-CoV-2 eras. Methods: We performed a multicentre observational retrospective study including seven paediatric hospitals in four countries (France, Spain, U.K., and U.S.). All consecutive confirmed patients with MIS-C hospitalised between February 1st, 2020, and May 31st, 2022, were included. Electronic Health Records (EHR) data were used to calculate pooled risk differences (RD) and effect sizes (ES) at site level, using Alpha as reference. Meta-analysis was used to pool data across sites. Findings: Of 598 patients with MIS-C (61% male, 39% female; mean age 9.7 years [SD 4.5]), 383 (64%) were admitted in the Alpha era, 111 (19%) in the Delta era, and 104 (17%) in the Omicron era. Compared with patients admitted in the Alpha era, those admitted in the Delta era were younger (ES -1.18 years [95% CI -2.05, -0.32]), had fewer respiratory symptoms (RD -0.15 [95% CI -0.33, -0.04]), less frequent non-cardiogenic shock or systemic inflammatory response syndrome (SIRS) (RD -0.35 [95% CI -0.64, -0.07]), lower lymphocyte count (ES -0.16 × 109/uL [95% CI -0.30, -0.01]), lower C-reactive protein (ES -28.5 mg/L [95% CI -46.3, -10.7]), and lower troponin (ES -0.14 ng/mL [95% CI -0.26, -0.03]). Patients admitted in the Omicron versus Alpha eras were younger (ES -1.6 years [95% CI -2.5, -0.8]), had less frequent SIRS (RD -0.18 [95% CI -0.30, -0.05]), lower lymphocyte count (ES -0.39 × 109/uL [95% CI -0.52, -0.25]), lower troponin (ES -0.16 ng/mL [95% CI -0.30, -0.01]) and less frequently received anticoagulation therapy (RD -0.19 [95% CI -0.37, -0.04]). Length of hospitalization was shorter in the Delta versus Alpha eras (-1.3 days [95% CI -2.3, -0.4]). Interpretation: Our study suggested that MIS-C clinical phenotypes varied across SARS-CoV-2 eras, with patients in Delta and Omicron eras being younger and less sick. EHR data can be effectively leveraged to identify rare complications of pandemic diseases and their variation over time. Funding: None.

Oxygen delivery in pediatric cardiac surgery and its association with acute kidney injury using machine learning.

OBJECTIVE: Acute kidney injury (AKI) after pediatric cardiac surgery with cardiopulmonary bypass (CPB) is a frequently reported complication. In this study we aimed to determine the oxygen delivery indexed to body surface area (Do2i) threshold associated with postoperative AKI in pediatric patients during CPB, and whether it remains clinically important in the context of other known independent risk factors. METHODS: A single-institution, retrospective study, encompassing 396 pediatric patients, who underwent heart surgery between April 2019 and April 2021 was undertaken. Time spent below Do2i thresholds were compared to determine the critical value for all stages of AKI occurring within 48 hours of surgery. Do2i threshold was then included in a classification analysis with known risk factors including nephrotoxic drug usage, surgical complexity, intraoperative data, comorbidities and ventricular function data, and vasoactive inotrope requirement to determine Do2i predictive importance. RESULTS: Logistic regression models showed cumulative time spent below a Do2i value of 350 mL/min/m2 was associated with AKI. Random forest models, incorporating established risk factors, showed Do2i threshold still maintained predictive importance. Patients who developed post-CPB AKI were younger, had longer CPB and ischemic times, and required higher inotrope support postsurgery. CONCLUSIONS: The present data support previous findings that Do2i during CPB is an independent risk factor for AKI development in pediatric patients. Furthermore, the data support previous suggestions of a higher threshold value in children compared with that in adults and indicate that adjustments in Do2i management might reduce incidence of postoperative AKI in the pediatric cardiac surgery population.

International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality.

Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory values and standard demographic and clinical covariates across healthcare systems, countries, and continents. Specifically, we trained a Cox regression model with nine measured laboratory test values, standard demographics at admission, and comorbidity burden pre-admission. These models were compared at site, country, and continent level. Of the 39,969 hospitalized patients with COVID-19 (68.6% male), 5717 (14.3%) died. In the Cox model, age, albumin, AST, creatine, CRP, and white blood cell count are most predictive of mortality. The baseline covariates are more predictive of mortality during the early days of COVID-19 hospitalization. Models trained at healthcare systems with larger cohort size largely retain good transportability performance when porting to different sites. The combination of routine laboratory test values at admission along with basic demographic features can predict mortality in patients hospitalized with COVID-19. Importantly, this potentially deployable model differs from prior work by demonstrating not only consistent performance but also reliable transportability across healthcare systems in the US and Europe, highlighting the generalizability of this model and the overall approach.

Classification Performance of Neural Networks Versus Logistic Regression Models: Evidence From Healthcare Practice.

Machine learning encompasses statistical approaches such as logistic regression (LR) through to more computationally complex models such as neural networks (NN). The aim of this study is to review current published evidence for performance from studies directly comparing logistic regression, and neural network classification approaches in medicine. A literature review was carried out to identify primary research studies which provided information regarding comparative area under the curve (AUC) values for the overall performance of both LR and NN for a defined clinical healthcare-related problem. Following an initial search, articles were reviewed to remove those that did not meet the criteria and performance metrics were extracted from the included articles. Teh initial search revealed 114 articles; 21 studies were included in the study. In 13/21 (62%) of cases, NN had a greater AUC compared to LR, but in most the difference was small and unlikely to be of clinical significance; (unweighted mean difference in AUC 0.03 (95% CI 0-0.06) in favour of NN versus LR. In the majority of cases examined across a range of clinical settings, LR models provide reasonable performance that is only marginally improved using more complex methods such as NN. In many circumstances, the use of a relatively simple LR model is likely to be adequate for real-world needs but in specific circumstances in which large amounts of data are available, and where even small increases in performance would provide significant management value, the application of advanced analytic tools such as NNs may be indicated.

International Analysis of Electronic Health Records of Children and Youth Hospitalized With COVID-19 Infection in 6 Countries.

Importance: Additional sources of pediatric epidemiological and clinical data are needed to efficiently study COVID-19 in children and youth and inform infection prevention and clinical treatment of pediatric patients. Objective: To describe international hospitalization trends and key epidemiological and clinical features of children and youth with COVID-19. Design, Setting, and Participants: This retrospective cohort study included pediatric patients hospitalized between February 2 and October 10, 2020. Patient-level electronic health record (EHR) data were collected across 27 hospitals in France, Germany, Spain, Singapore, the UK, and the US. Patients younger than 21 years who tested positive for COVID-19 and were hospitalized at an institution participating in the Consortium for Clinical Characterization of COVID-19 by EHR were included in the study. Main Outcomes and Measures: Patient characteristics, clinical features, and medication use. Results: There were 347 males (52%; 95% CI, 48.5-55.3) and 324 females (48%; 95% CI, 44.4-51.3) in this study's cohort. There was a bimodal age distribution, with the greatest proportion of patients in the 0- to 2-year (199 patients [30%]) and 12- to 17-year (170 patients [25%]) age range. Trends in hospitalizations for 671 children and youth found discrete surges with variable timing across 6 countries. Data from this cohort mirrored national-level pediatric hospitalization trends for most countries with available data, with peaks in hospitalizations during the initial spring surge occurring within 23 days in the national-level and 4CE data. A total of 27 364 laboratory values for 16 laboratory tests were analyzed, with mean values indicating elevations in markers of inflammation (C-reactive protein, 83 mg/L; 95% CI, 53-112 mg/L; ferritin, 417 ng/mL; 95% CI, 228-607 ng/mL; and procalcitonin, 1.45 ng/mL; 95% CI, 0.13-2.77 ng/mL). Abnormalities in coagulation were also evident (D-dimer, 0.78 ug/mL; 95% CI, 0.35-1.21 ug/mL; and fibrinogen, 477 mg/dL; 95% CI, 385-569 mg/dL). Cardiac troponin, when checked (n = 59), was elevated (0.032 ng/mL; 95% CI, 0.000-0.080 ng/mL). Common complications included cardiac arrhythmias (15.0%; 95% CI, 8.1%-21.7%), viral pneumonia (13.3%; 95% CI, 6.5%-20.1%), and respiratory failure (10.5%; 95% CI, 5.8%-15.3%). Few children were treated with COVID-19-directed medications. Conclusions and Relevance: This study of EHRs of children and youth hospitalized for COVID-19 in 6 countries demonstrated variability in hospitalization trends across countries and identified common complications and laboratory abnormalities in children and youth with COVID-19 infection. Large-scale informatics-based approaches to integrate and analyze data across health care systems complement methods of disease surveillance and advance understanding of epidemiological and clinical features associated with COVID-19 in children and youth.

International Comparisons of Harmonized Laboratory Value Trajectories to Predict Severe COVID-19: Leveraging the 4CE Collaborative Across 342 Hospitals and 6 Countries: A Retrospective Cohort Study.

Objectives: To perform an international comparison of the trajectory of laboratory values among hospitalized patients with COVID-19 who develop severe disease and identify optimal timing of laboratory value collection to predict severity across hospitals and regions. Design: Retrospective cohort study. Setting: The Consortium for Clinical Characterization of COVID-19 by EHR (4CE), an international multi-site data-sharing collaborative of 342 hospitals in the US and in Europe. Participants: Patients hospitalized with COVID-19, admitted before or after PCR-confirmed result for SARS-CoV-2. Primary and secondary outcome measures: Patients were categorized as "ever-severe" or "never-severe" using the validated 4CE severity criteria. Eighteen laboratory tests associated with poor COVID-19-related outcomes were evaluated for predictive accuracy by area under the curve (AUC), compared between the severity categories. Subgroup analysis was performed to validate a subset of laboratory values as predictive of severity against a published algorithm. A subset of laboratory values (CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin) was compared between North American and European sites for severity prediction. Results: Of 36,447 patients with COVID-19, 19,953 (43.7%) were categorized as ever-severe. Most patients (78.7%) were 50 years of age or older and male (60.5%). Longitudinal trajectories of CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin showed association with disease severity. Significant differences of laboratory values at admission were found between the two groups. With the exception of D-dimer, predictive discrimination of laboratory values did not improve after admission. Sub-group analysis using age, D-dimer, CRP, and lymphocyte count as predictive of severity at admission showed similar discrimination to a published algorithm (AUC=0.88 and 0.91, respectively). Both models deteriorated in predictive accuracy as the disease progressed. On average, no difference in severity prediction was found between North American and European sites. Conclusions: Laboratory test values at admission can be used to predict severity in patients with COVID-19. Prediction models show consistency across international sites highlighting the potential generalizability of these models.

Quantification of Lipid Filtration and the Effects on Cerebral Injury During Cardiopulmonary Bypass.

BACKGROUND: Lipid microemboli (LME) are formed in pericardial suction blood which, when returned to the cardiopulmonary bypass (CPB) circuit, can pass through filter materials and are returned to the arterial cannula. LME have been observed to enter all major organs and have been associated with small capillary arteriolar dilatations in the brains of patients who have died after CPB. However, a causal relationship showing correlation between LME and organ dysfunction has not been demonstrated, or whether removal of LME results in improved organ function. METHODS: A prospective, single center, randomized controlled trial examined 30 patients (15 per group) undergoing coronary artery bypass grafting using CPB with or without a lipid-depleting filter. The effects of LME filtration on neurocognitive injury were assessed using neuron-specific enolase (NSE). RESULTS: The study group showed a significant reduction in LME after filtration of the pericardial suction blood (p < 0.001), whereas the control group exhibited a significant rise in LME (p < 0.001). There was a significant reduction in peak NSE release (p = 0.013) and significant attenuation throughout the postoperative period (p = 0.002). Correlation and regression analyses showed a significant relationship between the number of LME post-CPB and peak NSE release (r = 0.42, p = 0.02). CONCLUSIONS: Several methods of LME filtration have been proposed, but none provided a suitable, efficacious method for use within the clinical setting. The RemoweLL CPB system removes significant numbers of LME from the cardiotomy suction. Furthermore, LME correlate to the release of a known marker of neurologic injury.

Aortic surgery using total miniaturized cardiopulmonary bypass.

PURPOSE: Few centers have attempted aortic surgery using miniaturized cardiopulmonary bypass (MCPB) systems due to concerns of air handling. The extra corporeal circuit optimized (ECCO) total MCPB system uses a venous air removal device and a parallel soft-shell reservoir that allows for venting of the heart. At our institution, total MCPB is used for all coronary artery bypass graft patients. Our objective was to assess the suitability of the ECCO total MCPB system during aortic surgery. DESCRIPTION: Fifty consecutive and unselected aortic procedures using the ECCO system were undertaken. Surgical feasibility, air removal ability, and blood transfusion requirements were audited to determine the efficacy of this technique. EVALUATION: The bypass time was 81.6 +/- 28.0 minutes and the ischemic time was 56.7 +/- 18.9 minutes. Total MCPB handled 1,910 +/- 404 mL of vented blood with 96 venous air removal device activations noted. The blood product transfusion rate was 12%, which was below the surgical transfusion rate for our unit. There were no complications. CONCLUSIONS: Aortic surgery can be undertaken safely and effectively using the ECCO total MCPB system.