Specialized interferon action in COVID-19.

The impacts of interferon (IFN) signaling on COVID-19 pathology are multiple, with both protective and harmful effects being documented. We report here a multiomics investigation of systemic IFN signaling in hospitalized COVID-19 patients, defining the multiomics biosignatures associated with varying levels of 12 different type I, II, and III IFNs. The antiviral transcriptional response in circulating immune cells is strongly associated with a specific subset of IFNs, most prominently IFNA2 and IFNG. In contrast, proteomics signatures indicative of endothelial damage and platelet activation associate with high levels of IFNB1 and IFNA6. Seroconversion and time since hospitalization associate with a significant decrease in a specific subset of IFNs. Additionally, differential IFN subtype production is linked to distinct constellations of circulating myeloid and lymphoid immune cell types. Each IFN has a unique metabolic signature, with IFNG being the most associated with activation of the kynurenine pathway. IFNs also show differential relationships with clinical markers of poor prognosis and disease severity. For example, whereas IFNG has the strongest association with C-reactive protein and other immune markers of poor prognosis, IFNB1 associates with increased neutrophil to lymphocyte ratio, a marker of late severe disease. Altogether, these results reveal specialized IFN action in COVID-19, with potential diagnostic and therapeutic implications.

Recovery Trajectories in Children Requiring 3 or More Days of Invasive Ventilation.

OBJECTIVES: To characterize health-related quality of life (HRQL) and functional recovery trajectories and risk factors for prolonged impairments among critically ill children receiving greater than or equal to 3 days of invasive ventilation. DESIGN: Prospective cohort study. SETTING: Quaternary children's hospital PICU. PATIENTS: Children without a preexisting tracheostomy who received greater than or equal to 3 days of invasive ventilation, survived hospitalization, and completed greater than or equal to 1 postdischarge data collection. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We evaluated 144 children measuring HRQL using proxy-report Pediatric Quality of Life Inventory and functional status using the Functional Status Scale (FSS) reflecting preillness baseline, PICU and hospital discharge, and 1, 3, 6, and 12 months after hospital discharge. They had a median age of 5.3 years (interquartile range, 1.1-13.0 yr), 58 (40%) were female, 45 (31%) had a complex chronic condition, and 110 (76%) had normal preillness FSS scores. Respiratory failure etiologies included lung disease ( n = 49; 34%), neurologic failure ( n = 23; 16%), and septic shock ( n = 22; 15%). At 1-month postdischarge, 68 of 122 (56%) reported worsened HRQL and 35 (29%) had a new functional impairment compared with preillness baseline. This improved at 3 months to 54 (46%) and 24 (20%), respectively, and remained stable through the remaining 9 months of follow-up. We used interaction forests to evaluate relative variable importance including pairwise interactions and found that therapy consultation within 3 days of intubation was associated with better HRQL recovery in older patients and those with better preillness physical HRQL. During the postdischarge year, 76 patients (53%) had an emergency department visit or hospitalization, and 62 (43%) newly received physical, occupational, or speech therapy. CONCLUSIONS: Impairments in HRQL and functional status as well as health resource use were common among children with acute respiratory failure. Early therapy consultation was a modifiable characteristic associated with shorter duration of worsened HRQL in older patients.

Association between monoclonal antibody therapy, vaccination, and longer-term symptom resolution after acute COVID-19.

Effective therapies for reducing post-acute sequelae of COVID-19 (PASC) symptoms are lacking. Evaluate the association between monoclonal antibody (mAb) treatment or COVID-19 vaccination with symptom recovery in COVID-19 participants. The longitudinal survey-based cohort study was conducted from April 2021 to January 2022 across a multihospital Colorado health system. Adults ≥18 years with a positive SARS-CoV-2 test were included. Primary exposures were mAb treatment and COVID-19 vaccination. The primary outcome was time to symptom resolution after SARS-CoV-2 positive test date. The secondary outcome was hospitalization within 28 days of a positive SARS-CoV-2 test. Analysis included 1612 participants, 539 mAb treated, and 486 with ≥2 vaccinations. Time to symptom resolution was similar between mAb treated versus untreated patients (adjusted hazard ratio (aHR): 0.90, 95% CI: 0.77-1.04). Time to symptom resolution was shorter for patients who received ≥2 vaccinations compared to those unvaccinated (aHR: 1.56, 95% CI: 1.31-1.88). 28-day hospitalization risk was lower for patients receiving mAb therapy (adjusted odds ratio [aOR]: 0.31, 95% CI: 0.19-0.50) and ≥2 vaccinations (aOR: 0.33, 95% CI: 0.20-0.55), compared with untreated or unvaccinated status. Analysis included 1612 participants, 539 mAb treated, and 486 with ≥2 vaccinations. Time to symptom resolution was similar between mAb treated versus untreated patients (adjusted hazard ratio (aHR): 0.90, 95% CI: 0.77-1.04). Time to symptom resolution was shorter for patients who received ≥2 vaccinations compared to those unvaccinated (aHR: 1.56, 95% CI: 1.31-1.88). 28-day hospitalization risk was lower for patients receiving mAb therapy (adjusted odds ratio [aOR]: 0.31, 95% CI: 0.19-0.50) and ≥2 vaccinations (aOR: 0.33, 95% CI: 0.20-0.55), compared with untreated or unvaccinated status. COVID-19 vaccination, but not mAb therapy, was associated with a shorter time to symptom resolution. Both were associated with lower 28-day hospitalization.

Real-world evaluation of early remdesivir in high-risk COVID-19 outpatients during Omicron including BQ.1/BQ.1.1/XBB.1.5.

BACKGROUND: A trial performed among unvaccinated, high-risk outpatients with COVID-19 during the delta period showed remdesivir reduced hospitalization. We used our real-world data platform to determine the effectiveness of remdesivir on reducing 28-day hospitalization among outpatients with mild-moderate COVID-19 during an Omicron period including BQ.1/BQ.1.1/XBB.1.5. METHODS: We did a propensity-matched, retrospective cohort study of non-hospitalized adults with SARS-CoV-2 infection between April 7, 2022, and February 7, 2023. Electronic healthcare record data from a large health system in Colorado were linked to statewide vaccination and mortality data. We included patients with a positive SARS-CoV-2 test or outpatient remdesivir administration. Exclusion criteria were other SARS-CoV-2 treatments or positive SARS-CoV-2 test more than seven days before remdesivir. The primary outcome was all-cause hospitalization up to day 28. Secondary outcomes included 28-day COVID-related hospitalization and 28-day all-cause mortality. RESULTS: Among 29,270 patients with SARS-CoV-2 infection, 1,252 remdesivir-treated patients were matched to 2,499 untreated patients. Remdesivir was associated with lower 28-day all-cause hospitalization (1.3% vs. 3.3%, adjusted hazard ratio (aHR) 0.39 [95% CI 0.23-0.67], p < 0.001) than no treatment. All-cause mortality at 28 days was numerically lower among remdesivir-treated patients (0.1% vs. 0.4%; aOR 0.32 [95% CI 0.03-1.40]). Similar benefit of RDV treatment on 28-day all-cause hospitalization was observed across Omicron periods, aOR (95% CI): BA.2/BA2.12.1 (0.77[0.19-2.41]), BA.4/5 (0.50[95% CI 0.50-1.01]), BQ.1/BQ.1.1/XBB.1.5 (0.21[95% CI 0.08-0.57]. CONCLUSION: Among outpatients with SARS-CoV-2 during recent Omicron surges, remdesivir was associated with lower hospitalization than no treatment, supporting current National Institutes of Health Guidelines.

Association of an In-Hospital Desirability of Outcomes Ranking Scale With Postdischarge Health-Related Quality of Life: A Secondary Analysis of the Life After Pediatric Sepsis Evaluation.

OBJECTIVES: To develop a desirability of outcome ranking (DOOR) scale for use in children with septic shock and determine its correlation with a decrease in 3-month postadmission health-related quality of life (HRQL) or death. DESIGN: Secondary analysis of the Life After Pediatric Sepsis Evaluation prospective study. SETTING: Twelve U.S. PICUs, 2013-2017. PATIENTS: Children (1 mo-18 yr) with septic shock. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We applied a 7-point pediatric critical care (PCC) DOOR scale: 7: death; 6: extracorporeal life support; 5: supported by life-sustaining therapies (continuous renal replacement therapy, vasoactive, or invasive ventilation); 4: hospitalized with or 3: without organ dysfunction; 2: discharged with or 1: without new morbidity to patients by assigning the highest applicable score on specific days post-PICU admission. We analyzed Spearman rank-order correlations (95% CIs) between proximal outcomes (PCC-DOOR scale on days 7, 14, and 21, ventilator-free days, cumulative 28-day Pediatric Logistic Organ Dysfunction-2 (PELOD-2) scores, and PICU-free days) and 3-month decrease in HRQL or death. HRQL was measured by Pediatric Quality of Life Inventory 4.0 or Functional Status II-R for patients with developmental delay. Patients who died were assigned the worst possible HRQL score. PCC-DOOR scores were applied to 385 patients, median age 6 years (interquartile range 2, 13) and 177 (46%) with a complex chronic condition(s). Three-month outcomes were available for 245 patients (64%) and 42 patients (17%) died. PCC-DOOR scale on days 7, 14, and 21 demonstrated fair correlation with the primary outcome (-0.42 [-0.52, -0.31], -0.47 [-0.56, -0.36], and -0.52 [-0.61, -0.42]), similar to the correlations for cumulative 28-day PELOD-2 scores (-0.51 [-0.59, -0.41]), ventilator-free days (0.43 [0.32, 0.53]), and PICU-free days (0.46 [0.35, 0.55]). CONCLUSIONS: The PCC-DOOR scale is a feasible, practical outcome for pediatric sepsis trials and demonstrates fair correlation with decrease in HRQL or death at 3 months.

Biomarker Assessment of a High-Risk, Data-Driven Pediatric Sepsis Phenotype Characterized by Persistent Hypoxemia, Encephalopathy, and Shock.

OBJECTIVES: Identification of children with sepsis-associated multiple organ dysfunction syndrome (MODS) at risk for poor outcomes remains a challenge. We sought to the determine reproducibility of the data-driven "persistent hypoxemia, encephalopathy, and shock" (PHES) phenotype and determine its association with inflammatory and endothelial biomarkers, as well as biomarker-based pediatric risk strata. DESIGN: We retrained and validated a random forest classifier using organ dysfunction subscores in the 2012-2018 electronic health record (EHR) dataset used to derive the PHES phenotype. We used this classifier to assign phenotype membership in a test set consisting of prospectively (2003-2023) enrolled pediatric septic shock patients. We compared profiles of the PERSEVERE family of biomarkers among those with and without the PHES phenotype and determined the association with established biomarker-based mortality and MODS risk strata. SETTING: Twenty-five PICUs across the United States. PATIENTS: EHR data from 15,246 critically ill patients with sepsis-associated MODS split into derivation and validation sets and 1,270 pediatric septic shock patients in the test set of whom 615 had complete biomarker data. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The area under the receiver operator characteristic curve of the modified classifier to predict PHES phenotype membership was 0.91 (95% CI, 0.90-0.92) in the EHR validation set. In the test set, PHES phenotype membership was associated with both increased adjusted odds of complicated course (adjusted odds ratio [aOR] 4.1; 95% CI, 3.2-5.4) and 28-day mortality (aOR of 4.8; 95% CI, 3.11-7.25) after controlling for age, severity of illness, and immunocompromised status. Patients belonging to the PHES phenotype were characterized by greater degree of systemic inflammation and endothelial activation, and were more likely to be stratified as high risk based on PERSEVERE biomarkers predictive of death and persistent MODS. CONCLUSIONS: The PHES trajectory-based phenotype is reproducible, independently associated with poor clinical outcomes, and overlapped with higher risk strata based on prospectively validated biomarker approaches.

The Pediatric Data Science and Analytics Subgroup of the Pediatric Acute Lung Injury and Sepsis Investigators Network: Use of Supervised Machine Learning Applications in Pediatric Critical Care Medicine Research.

OBJECTIVE: Perform a scoping review of supervised machine learning in pediatric critical care to identify published applications, methodologies, and implementation frequency to inform best practices for the development, validation, and reporting of predictive models in pediatric critical care. DESIGN: Scoping review and expert opinion. SETTING: We queried CINAHL Plus with Full Text (EBSCO), Cochrane Library (Wiley), Embase (Elsevier), Ovid Medline, and PubMed for articles published between 2000 and 2022 related to machine learning concepts and pediatric critical illness. Articles were excluded if the majority of patients were adults or neonates, if unsupervised machine learning was the primary methodology, or if information related to the development, validation, and/or implementation of the model was not reported. Article selection and data extraction were performed using dual review in the Covidence tool, with discrepancies resolved by consensus. SUBJECTS: Articles reporting on the development, validation, or implementation of supervised machine learning models in the field of pediatric critical care medicine. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 5075 identified studies, 141 articles were included. Studies were primarily (57%) performed at a single site. The majority took place in the United States (70%). Most were retrospective observational cohort studies. More than three-quarters of the articles were published between 2018 and 2022. The most common algorithms included logistic regression and random forest. Predicted events were most commonly death, transfer to ICU, and sepsis. Only 14% of articles reported external validation, and only a single model was implemented at publication. Reporting of validation methods, performance assessments, and implementation varied widely. Follow-up with authors suggests that implementation remains uncommon after model publication. CONCLUSIONS: Publication of supervised machine learning models to address clinical challenges in pediatric critical care medicine has increased dramatically in the last 5 years. While these approaches have the potential to benefit children with critical illness, the literature demonstrates incomplete reporting, absence of external validation, and infrequent clinical implementation.

International Consensus Criteria for Pediatric Sepsis and Septic Shock.

Importance: Sepsis is a leading cause of death among children worldwide. Current pediatric-specific criteria for sepsis were published in 2005 based on expert opinion. In 2016, the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) defined sepsis as life-threatening organ dysfunction caused by a dysregulated host response to infection, but it excluded children. Objective: To update and evaluate criteria for sepsis and septic shock in children. Evidence Review: The Society of Critical Care Medicine (SCCM) convened a task force of 35 pediatric experts in critical care, emergency medicine, infectious diseases, general pediatrics, nursing, public health, and neonatology from 6 continents. Using evidence from an international survey, systematic review and meta-analysis, and a new organ dysfunction score developed based on more than 3 million electronic health record encounters from 10 sites on 4 continents, a modified Delphi consensus process was employed to develop criteria. Findings: Based on survey data, most pediatric clinicians used sepsis to refer to infection with life-threatening organ dysfunction, which differed from prior pediatric sepsis criteria that used systemic inflammatory response syndrome (SIRS) criteria, which have poor predictive properties, and included the redundant term, severe sepsis. The SCCM task force recommends that sepsis in children be identified by a Phoenix Sepsis Score of at least 2 points in children with suspected infection, which indicates potentially life-threatening dysfunction of the respiratory, cardiovascular, coagulation, and/or neurological systems. Children with a Phoenix Sepsis Score of at least 2 points had in-hospital mortality of 7.1% in higher-resource settings and 28.5% in lower-resource settings, more than 8 times that of children with suspected infection not meeting these criteria. Mortality was higher in children who had organ dysfunction in at least 1 of 4-respiratory, cardiovascular, coagulation, and/or neurological-organ systems that was not the primary site of infection. Septic shock was defined as children with sepsis who had cardiovascular dysfunction, indicated by at least 1 cardiovascular point in the Phoenix Sepsis Score, which included severe hypotension for age, blood lactate exceeding 5 mmol/L, or need for vasoactive medication. Children with septic shock had an in-hospital mortality rate of 10.8% and 33.5% in higher- and lower-resource settings, respectively. Conclusions and Relevance: The Phoenix sepsis criteria for sepsis and septic shock in children were derived and validated by the international SCCM Pediatric Sepsis Definition Task Force using a large international database and survey, systematic review and meta-analysis, and modified Delphi consensus approach. A Phoenix Sepsis Score of at least 2 identified potentially life-threatening organ dysfunction in children younger than 18 years with infection, and its use has the potential to improve clinical care, epidemiological assessment, and research in pediatric sepsis and septic shock around the world.

Development and Validation of the Phoenix Criteria for Pediatric Sepsis and Septic Shock.

Importance: The Society of Critical Care Medicine Pediatric Sepsis Definition Task Force sought to develop and validate new clinical criteria for pediatric sepsis and septic shock using measures of organ dysfunction through a data-driven approach. Objective: To derive and validate novel criteria for pediatric sepsis and septic shock across differently resourced settings. Design, Setting, and Participants: Multicenter, international, retrospective cohort study in 10 health systems in the US, Colombia, Bangladesh, China, and Kenya, 3 of which were used as external validation sites. Data were collected from emergency and inpatient encounters for children (aged <18 years) from 2010 to 2019: 3 049 699 in the development (including derivation and internal validation) set and 581 317 in the external validation set. Exposure: Stacked regression models to predict mortality in children with suspected infection were derived and validated using the best-performing organ dysfunction subscores from 8 existing scores. The final model was then translated into an integer-based score used to establish binary criteria for sepsis and septic shock. Main Outcomes and Measures: The primary outcome for all analyses was in-hospital mortality. Model- and integer-based score performance measures included the area under the precision recall curve (AUPRC; primary) and area under the receiver operating characteristic curve (AUROC; secondary). For binary criteria, primary performance measures were positive predictive value and sensitivity. Results: Among the 172 984 children with suspected infection in the first 24 hours (development set; 1.2% mortality), a 4-organ-system model performed best. The integer version of that model, the Phoenix Sepsis Score, had AUPRCs of 0.23 to 0.38 (95% CI range, 0.20-0.39) and AUROCs of 0.71 to 0.92 (95% CI range, 0.70-0.92) to predict mortality in the validation sets. Using a Phoenix Sepsis Score of 2 points or higher in children with suspected infection as criteria for sepsis and sepsis plus 1 or more cardiovascular point as criteria for septic shock resulted in a higher positive predictive value and higher or similar sensitivity compared with the 2005 International Pediatric Sepsis Consensus Conference (IPSCC) criteria across differently resourced settings. Conclusions and Relevance: The novel Phoenix sepsis criteria, which were derived and validated using data from higher- and lower-resource settings, had improved performance for the diagnosis of pediatric sepsis and septic shock compared with the existing IPSCC criteria.

Coding long COVID: characterizing a new disease through an ICD-10 lens.

BACKGROUND: Naming a newly discovered disease is a difficult process; in the context of the COVID-19 pandemic and the existence of post-acute sequelae of SARS-CoV-2 infection (PASC), which includes long COVID, it has proven especially challenging. Disease definitions and assignment of a diagnosis code are often asynchronous and iterative. The clinical definition and our understanding of the underlying mechanisms of long COVID are still in flux, and the deployment of an ICD-10-CM code for long COVID in the USA took nearly 2 years after patients had begun to describe their condition. Here, we leverage the largest publicly available HIPAA-limited dataset about patients with COVID-19 in the US to examine the heterogeneity of adoption and use of U09.9, the ICD-10-CM code for "Post COVID-19 condition, unspecified." METHODS: We undertook a number of analyses to characterize the N3C population with a U09.9 diagnosis code (n = 33,782), including assessing person-level demographics and a number of area-level social determinants of health; diagnoses commonly co-occurring with U09.9, clustered using the Louvain algorithm; and quantifying medications and procedures recorded within 60 days of U09.9 diagnosis. We stratified all analyses by age group in order to discern differing patterns of care across the lifespan. RESULTS: We established the diagnoses most commonly co-occurring with U09.9 and algorithmically clustered them into four major categories: cardiopulmonary, neurological, gastrointestinal, and comorbid conditions. Importantly, we discovered that the population of patients diagnosed with U09.9 is demographically skewed toward female, White, non-Hispanic individuals, as well as individuals living in areas with low poverty and low unemployment. Our results also include a characterization of common procedures and medications associated with U09.9-coded patients. CONCLUSIONS: This work offers insight into potential subtypes and current practice patterns around long COVID and speaks to the existence of disparities in the diagnosis of patients with long COVID. This latter finding in particular requires further research and urgent remediation.

Leveraging Serologic Testing to Identify Children at Risk For Post-Acute Sequelae of SARS-CoV-2 Infection: An Electronic Health Record-Based Cohort Study from the RECOVER Program.

Using an electronic health record-based algorithm, we identified children with Coronavirus disease 2019 (COVID-19) based exclusively on serologic testing between March 2020 and April 2022. Compared with the 131 537 polymerase chain reaction-positive children, the 2714 serology-positive children were more likely to be inpatients (24% vs 2%), to have a chronic condition (37% vs 24%), and to have a diagnosis of multisystem inflammatory syndrome in children (23% vs <1%). Identification of children who could have been asymptomatic or paucisymptomatic and not tested is critical to define the burden of post-acute sequelae of severe acute respiratory syndrome coronavirus 2 infection in children.

A methodology of phenotyping ICU patients from EHR data: High-fidelity, personalized, and interpretable phenotypes estimation.

OBJECTIVE: Computing phenotypes that provide high-fidelity, time-dependent characterizations and yield personalized interpretations is challenging, especially given the complexity of physiological and healthcare systems and clinical data quality. This paper develops a methodological pipeline to estimate unmeasured physiological parameters and produce high-fidelity, personalized phenotypes anchored to physiological mechanics from electronic health record (EHR). METHODS: A methodological phenotyping pipeline is developed that computes new phenotypes defined with unmeasurable computational biomarkers quantifying specific physiological properties in real time. Working within the inverse problem framework, this pipeline is applied to the glucose-insulin system for ICU patients using data assimilation to estimate an established mathematical physiological model with stochastic optimization. This produces physiological model parameter vectors of clinically unmeasured endocrine properties, here insulin secretion, clearance, and resistance, estimated for individual patient. These physiological parameter vectors are used as inputs to unsupervised machine learning methods to produce phenotypic labels and discrete physiological phenotypes. These phenotypes are inherently interpretable because they are based on parametric physiological descriptors. To establish potential clinical utility, the computed phenotypes are evaluated with external EHR data for consistency and reliability and with clinician face validation. RESULTS: The phenotype computation was performed on a cohort of 109 ICU patients who received no or short-acting insulin therapy, rendering continuous and discrete physiological phenotypes as specific computational biomarkers of unmeasured insulin secretion, clearance, and resistance on time windows of three days. Six, six, and five discrete phenotypes were found in the first, middle, and last three-day periods of ICU stays, respectively. Computed phenotypic labels were predictive with an average accuracy of 89%. External validation of discrete phenotypes showed coherence and consistency in clinically observable differences based on laboratory measurements and ICD 9/10 codes and clinical concordance from face validity. A particularly clinically impactful parameter, insulin secretion, had a concordance accuracy of 83%±27%. CONCLUSION: The new physiological phenotypes computed with individual patient ICU data and defined by estimates of mechanistic model parameters have high physiological fidelity, are continuous, time-specific, personalized, interpretable, and predictive. This methodology is generalizable to other clinical and physiological settings and opens the door for discovering deeper physiological information to personalize medical care.

Reporting of Social Determinants of Health in Pediatric Sepsis Studies.

OBJECTIVE: Standardized, consistent reporting of social determinants of health (SDOH) in studies on children with sepsis would allow for: 1) understanding the association of SDOH with illness severity and outcomes, 2) comparing populations and extrapolating study results, and 3) identification of potentially modifiable socioeconomic factors for policy makers. We, therefore, sought to determine how frequently data on SDOH were reported, which factors were collected and how these factors were defined in studies of sepsis in children. DATA SOURCES AND SELECTION: We reviewed 106 articles (published between 2005 and 2020) utilized in a recent systematic review on physiologic criteria for pediatric sepsis. DATA EXTRACTION: Data were extracted by two reviewers on variables that fell within the World Health Organization's SDOH categories. DATA SYNTHESIS: SDOH were not the primary outcome in any of the included studies. Seventeen percent of articles (18/106) did not report on any SDOH, and a further 36.8% (39/106) only reported on gender/sex. Of the remaining 46.2% of articles, the most reported SDOH categories were preadmission nutritional status (35.8%, 38/106) and race/ethnicity (18.9%, 20/106). However, no two studies used the same definition of the variables reported within each of these categories. Six studies reported on socioeconomic status (3.8%, 6/106), including two from upper-middle-income and four from lower middle-income countries. Only three studies reported on parental education levels (2.8%, 3/106). No study reported on parental job security or structural conflict. CONCLUSIONS: We found overall low reporting of SDOH and marked variability in categorizations and definitions of SDOH variables. Consistent and standardized reporting of SDOH in pediatric sepsis studies is needed to understand the role these factors play in the development and severity of sepsis, to compare and extrapolate study results between settings and to implement policies aimed at improving socioeconomic conditions related to sepsis.

Operationalizing Appropriate Sepsis Definitions in Children Worldwide: Considerations for the Pediatric Sepsis Definition Taskforce.

Sepsis is a leading cause of global mortality in children, yet definitions for pediatric sepsis are outdated and lack global applicability and validity. In adults, the Sepsis-3 Definition Taskforce queried databases from high-income countries to develop and validate the criteria. The merit of this definition has been widely acknowledged; however, important considerations about less-resourced and more diverse settings pose challenges to its use globally. To improve applicability and relevance globally, the Pediatric Sepsis Definition Taskforce sought to develop a conceptual framework and rationale of the critical aspects and context-specific factors that must be considered for the optimal operationalization of future pediatric sepsis definitions. It is important to address challenges in developing a set of pediatric sepsis criteria which capture manifestations of illnesses with vastly different etiologies and underlying mechanisms. Ideal criteria need to be unambiguous, and capable of adapting to the different contexts in which children with suspected infections are present around the globe. Additionally, criteria need to facilitate early recognition and timely escalation of treatment to prevent progression and limit life-threatening organ dysfunction. To address these challenges, locally adaptable solutions are required, which permit individualized care based on available resources and the pretest probability of sepsis. This should facilitate affordable diagnostics which support risk stratification and prediction of likely treatment responses, and solutions for locally relevant outcome measures. For this purpose, global collaborative databases need to be established, using minimum variable datasets from routinely collected data. In summary, a "Think globally, act locally" approach is required.

Derivation, Validation, and Clinical Relevance of a Pediatric Sepsis Phenotype With Persistent Hypoxemia, Encephalopathy, and Shock.

OBJECTIVES: Untangling the heterogeneity of sepsis in children and identifying clinically relevant phenotypes could lead to the development of targeted therapies. Our aim was to analyze the organ dysfunction trajectories of children with sepsis-associated multiple organ dysfunction syndrome (MODS) to identify reproducible and clinically relevant sepsis phenotypes and determine if they are associated with heterogeneity of treatment effect (HTE) to common therapies. DESIGN: Multicenter observational cohort study. SETTING: Thirteen PICUs in the United States. PATIENTS: Patients admitted with suspected infections to the PICU between 2012 and 2018. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We used subgraph-augmented nonnegative matrix factorization to identify candidate trajectory-based phenotypes based on the type, severity, and progression of organ dysfunction in the first 72 hours. We analyzed the candidate phenotypes to determine reproducibility as well as prognostic, therapeutic, and biological relevance. Overall, 38,732 children had suspected infection, of which 15,246 (39.4%) had sepsis-associated MODS with an in-hospital mortality of 10.1%. We identified an organ dysfunction trajectory-based phenotype (which we termed persistent hypoxemia, encephalopathy, and shock) that was highly reproducible, had features of systemic inflammation and coagulopathy, and was independently associated with higher mortality. In a propensity score-matched analysis, patients with persistent hypoxemia, encephalopathy, and shock phenotype appeared to have HTE and benefit from adjuvant therapy with hydrocortisone and albumin. When compared with other high-risk clinical syndromes, the persistent hypoxemia, encephalopathy, and shock phenotype only overlapped with 50%-60% of patients with septic shock, moderate-to-severe pediatric acute respiratory distress syndrome, or those in the top tier of organ dysfunction burden, suggesting that it represents a nonsynonymous clinical phenotype of sepsis-associated MODS. CONCLUSIONS: We derived and validated the persistent hypoxemia, encephalopathy, and shock phenotype, which is highly reproducible, clinically relevant, and associated with HTE to common adjuvant therapies in children with sepsis.

Risk factors associated with post-acute sequelae of SARS-CoV-2: an N3C and NIH RECOVER study.

BACKGROUND: More than one-third of individuals experience post-acute sequelae of SARS-CoV-2 infection (PASC, which includes long-COVID). The objective is to identify risk factors associated with PASC/long-COVID diagnosis. METHODS: This was a retrospective case-control study including 31 health systems in the United States from the National COVID Cohort Collaborative (N3C). 8,325 individuals with PASC (defined by the presence of the International Classification of Diseases, version 10 code U09.9 or a long-COVID clinic visit) matched to 41,625 controls within the same health system and COVID index date within ± 45 days of the corresponding case's earliest COVID index date. Measurements of risk factors included demographics, comorbidities, treatment and acute characteristics related to COVID-19. Multivariable logistic regression, random forest, and XGBoost were used to determine the associations between risk factors and PASC. RESULTS: Among 8,325 individuals with PASC, the majority were > 50 years of age (56.6%), female (62.8%), and non-Hispanic White (68.6%). In logistic regression, middle-age categories (40 to 69 years; OR ranging from 2.32 to 2.58), female sex (OR 1.4, 95% CI 1.33-1.48), hospitalization associated with COVID-19 (OR 3.8, 95% CI 3.05-4.73), long (8-30 days, OR 1.69, 95% CI 1.31-2.17) or extended hospital stay (30 + days, OR 3.38, 95% CI 2.45-4.67), receipt of mechanical ventilation (OR 1.44, 95% CI 1.18-1.74), and several comorbidities including depression (OR 1.50, 95% CI 1.40-1.60), chronic lung disease (OR 1.63, 95% CI 1.53-1.74), and obesity (OR 1.23, 95% CI 1.16-1.3) were associated with increased likelihood of PASC diagnosis or care at a long-COVID clinic. Characteristics associated with a lower likelihood of PASC diagnosis or care at a long-COVID clinic included younger age (18 to 29 years), male sex, non-Hispanic Black race, and comorbidities such as substance abuse, cardiomyopathy, psychosis, and dementia. More doctors per capita in the county of residence was associated with an increased likelihood of PASC diagnosis or care at a long-COVID clinic. Our findings were consistent in sensitivity analyses using a variety of analytic techniques and approaches to select controls. CONCLUSIONS: This national study identified important risk factors for PASC diagnosis such as middle age, severe COVID-19 disease, and specific comorbidities. Further clinical and epidemiological research is needed to better understand underlying mechanisms and the potential role of vaccines and therapeutics in altering PASC course.

Real-World Evidence of the Neutralizing Monoclonal Antibody Sotrovimab for Preventing Hospitalization and Mortality in COVID-19 Outpatients.

BACKGROUND: It is not known whether sotrovimab, a neutralizing monoclonal antibody (mAb) treatment authorized for early symptomatic coronavirus disease 2019 (COVID-19) patients, is also effective in preventing the progression of severe disease and mortality following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant infection. METHODS: In an observational cohort study of nonhospitalized adult patients with SARS-CoV-2 infection, 1 October 2021-11 December 2021, using electronic health records from a statewide health system plus state-level vaccine and mortality data, we used propensity matching to select 3 patients not receiving mAbs for each patient who received outpatient sotrovimab treatment. The primary outcome was 28-day hospitalization; secondary outcomes included mortality and severity of hospitalization. RESULTS: Of 10 036 patients with SARS-CoV-2 infection, 522 receiving sotrovimab were matched to 1563 not receiving mAbs. Compared to mAb-untreated patients, sotrovimab treatment was associated with a 63% decrease in the odds of all-cause hospitalization (raw rate 2.1% vs 5.7%; adjusted odds ratio [aOR], 0.37; 95% confidence interval [CI], .19-.66) and an 89% decrease in the odds of all-cause 28-day mortality (raw rate 0% vs 1.0%; aOR, 0.11; 95% CI, .0-.79), and may reduce respiratory disease severity among those hospitalized. CONCLUSIONS: Real-world evidence demonstrated sotrovimab effectiveness in reducing hospitalization and all-cause 28-day mortality among COVID-19 outpatients during the Delta variant phase.

A Multicenter, Prospective, Observational, Cohort-Controlled Study of Clinical Outcomes Following Coronavirus Disease 2019 (COVID-19) Convalescent Plasma Therapy in Hospitalized Patients With COVID-19.

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has caused high inpatient mortality and morbidity throughout the world. COVID-19 convalescent plasma (CCP) has been utilized as a potential therapy for patients hospitalized with coronavirus disease 2019 (COVID-19) pneumonia. This study evaluated the outcomes of hospitalized patients with COVID-19 treated with CCP in a prospective, observational, multicenter trial. METHODS: From April through August 2020, hospitalized patients with COVID-19 at 16 participating hospitals in Colorado were enrolled and treated with CCP and compared with hospitalized patients with COVID-19 who were not treated with convalescent plasma. Plasma antibody levels were determined following the trial, given that antibody tests were not approved at the initiation of the trial. CCP-treated and untreated hospitalized patients with COVID-19 were matched using propensity scores followed by analysis for length of hospitalization and inpatient mortality. RESULTS: A total of 542 hospitalized patients with COVID-19 were enrolled at 16 hospitals across the region. A total of 468 hospitalized patients with COVID-19 were entered into propensity score matching with 188 patients matched for analysis in the CCP-treatment and control arms. Fine-Gray models revealed increased length of hospital stay in CCP-treated patients and no change in inpatient mortality compared with controls. In subgroup analysis of CCP-treated patients within 7 days of admission, there was no difference in length of hospitalization and inpatient mortality. CONCLUSIONS: These data show that treatment of hospitalized patients with COVID-19 treated with CCP did not significantly improve patient hospitalization length of stay or inpatient mortality.

Association between treatment failure and hospitalization after receipt of neutralizing monoclonal antibody treatment for COVID-19 outpatients.

BACKGROUND: Neutralizing monoclonal antibodies (mAbs) are highly effective in reducing hospitalization and mortality among early symptomatic COVID-19 patients in clinical trials and real-world data. While resistance to some mAbs has since emerged among new variants, characteristics associated with treatment failure of mAbs remain unknown. METHODS: This multicenter, observational cohort study included patients with COVID-19 who received mAb treatment between November 20, 2020, and December 9, 2021. We utilized electronic health records from a statewide health system plus state-level vaccine and mortality data. The primary outcome was mAb treatment failure, defined as hospitalization or death within 28 days of a positive SARS-CoV-2 test. RESULTS: COVID-19 mAb was administered to 7406 patients. Hospitalization within 28 days of positive SARS-CoV-2 test occurred in 258 (3.5%) of all patients who received mAb treatment. Ten patients (0.1%) died within 28 days, and all but one were hospitalized prior to death. Characteristics associated with treatment failure included having two or more comorbidities excluding obesity and immunocompromised status (adjusted odds ratio [OR] 3.71, 95% confidence interval [CI] 2.52-5.56), lack of SARS-CoV-2 vaccination (OR 2.73, 95% CI 2.01-3.77), non-Hispanic black race/ethnicity (OR 2.21, 95% CI 1.20-3.82), obesity (OR 1.79, 95% CI 1.36-2.34), one comorbidity (OR 1.68, 95% CI 1.11-2.57), age ≥ 65 years (OR 1.62, 95% CI 1.13-2.35), and male sex (OR 1.56, 95% CI 1.21-2.02). Immunocompromised status (none, mild, or moderate/severe), pandemic phase, and type of mAb received were not associated with treatment failure (all p > 0.05). CONCLUSIONS: Comorbidities, lack of prior SARS-CoV-2 vaccination, non-Hispanic black race/ethnicity, obesity, age ≥ 65 years, and male sex are associated with treatment failure of mAbs.

Identifying Long-Term Morbidities and Health Trajectories After Prolonged Mechanical Ventilation in Children Using State All Payer Claims Data.

OBJECTIVES: To identify postdischarge outcome phenotypes and risk factors for poor outcomes using insurance claims data. DESIGN: Retrospective cohort study. SETTING: Single quaternary center. PATIENTS: Children without preexisting tracheostomy who required greater than or equal to 3 days of invasive mechanical ventilation, survived the hospitalization, and had postdischarge insurance eligibility in Colorado's All Payer Claims Database. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We used unsupervised machine learning to identify functional outcome phenotypes based on claims data representative of postdischarge morbidities. We assessed health trajectory by comparing change in the number of insurance claims between quarters 1 and 4 of the postdischarge year. Regression analyses identified variables associated with unfavorable outcomes. The 381 subjects had median age 3.3 years (interquartile range, 0.9-12 yr), and 147 (39%) had a complex chronic condition. Primary diagnoses were respiratory (41%), injury (23%), and neurologic (11%). We identified three phenotypes: lower morbidity (n = 300), higher morbidity (n = 62), and 1-year nonsurvivors (n = 19). Complex chronic conditions most strongly predicted the nonsurvivor phenotype. Longer PICU stays and tracheostomy placement most strongly predicted the higher morbidity phenotype. Patients with high but improving postdischarge resource use were differentiated by high illness severity and long PICU stays. Patients with persistently high or increasing resource use were differentiated by complex chronic conditions and tracheostomy placement. CONCLUSIONS: New morbidities are common after prolonged mechanical ventilation. Identifying phenotypes at high risk of postdischarge morbidity may facilitate prognostic enrichment in clinical trials.