Can Multisystem Inflammatory Syndrome in Children Be Managed in the Outpatient Setting? An EHR-Based Cohort Study From the RECOVER Program.

Using electronic health record data combined with primary chart review, we identified seven children across nine participant pediatric medical centers with a diagnosis of Multisystem Inflammatory Syndrome in Children (MIS-C) managed exclusively as outpatients. These findings should raise awareness of mild presentations of MIS-C and the option of outpatient management.

Real-world use of nirmatrelvir-ritonavir in outpatients with COVID-19 during the era of omicron variants including BA.4 and BA.5 in Colorado, USA: a retrospective cohort study.

BACKGROUND: Nirmatrelvir is a protease inhibitor with in-vitro activity against SARS-CoV-2, and ritonavir-boosted nirmatrelvir can reduce the risk of progression to severe COVID-19 among individuals at high risk infected with delta and early omicron variants. However, less is known about the effectiveness of nirmatrelvir-ritonavir during more recent BA.2, BA2.12.1, BA.4, and BA.5 omicron variant surges. We used our real-world data platform to evaluate the effect of nirmatrelvir-ritonavir treatment on 28-day hospitalisation, mortality, and emergency department visits among outpatients with early symptomatic COVID-19 during a SARS-CoV-2 omicron (BA.2, BA2.12.1, BA.4, and BA.5) predominant period in Colorado, USA. METHODS: We did a propensity-matched, retrospective, observational cohort study of non-hospitalised adult patients infected with SARS-CoV-2 between March 26 and Aug 25, 2022, using records from a statewide health system in Colorado. We obtained data from the electronic health records of University of Colorado Health, the largest health system in Colorado, with 13 hospitals and 141 000 annual hospital admissions, and with numerous ambulatory sites and affiliated pharmacies around the state. Included patients had a positive SARS-CoV-2 test or nirmatrelvir-ritonavir medication order. Exclusion criteria were an order for or administration of other SARS-CoV-2 treatments within 10 days of a positive SARS-CoV-2 test, hospitalisation at the time of positive SARS-CoV-2 test, and positive SARS-CoV-2 test more than 10 days before a nirmatrelvir-ritonavir order. We propensity score matched patients treated with nirmatrelvir-ritonavir with untreated patients. The primary outcome was 28-day all-cause hospitalisation. FINDINGS: Among 28 167 patients infected with SARS-CoV-2 between March 26 and Aug 25, 2022, 21 493 met the study inclusion criteria. 9881 patients received treatment with nirmatrelvir-ritonavir and 11 612 were untreated. Nirmatrelvir-ritonavir treatment was associated with reduced 28-day all-cause hospitalisation compared with no antiviral treatment (61 [0·9%] of 7168 patients vs 135 [1·4%] of 9361 patients, adjusted odds ratio (OR) 0·45 [95% CI 0·33-0·62]; p<0·0001). Nirmatrelvir-ritonavir treatment was also associated with reduced 28-day all-cause mortality (two [<0·1%] of 7168 patients vs 15 [0·2%] of 9361 patients; adjusted OR 0·15 [95% CI 0·03-0·50]; p=0·0010). Using subsequent emergency department visits as a surrogate for clinically significant relapse, we observed a decrease after nirmatrelvir-ritonavir treatment (283 [3·9%] of 7168 patients vs 437 [4·7%] of 9361 patients; adjusted OR 0·74 [95% CI 0·63-0·87]; p=0·0002). INTERPRETATION: Real-world evidence reported during a BA.2, BA2.12.1, BA.4, and BA.5 omicron surge showed an association between nirmatrelvir-ritonavir treatment and reduced 28-day all-cause hospitalisation, all-cause mortality, and visits to the emergency department. With results that are among the first to suggest effectiveness of nirmatrelvir-ritonavir for non-hospitalised patients during an omicron period inclusive of BA.4 and BA.5 subvariants, these data support nirmatrelvir-ritonavir as an ongoing first-line treatment for adults acutely infected with SARS-CoV-2. FUNDING: US National Institutes of Health.

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.

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.

Clinical Features and Burden of Postacute Sequelae of SARS-CoV-2 Infection in Children and Adolescents.

Importance: The postacute sequelae of SARS-CoV-2 infection (PASC) has emerged as a long-term complication in adults, but current understanding of the clinical presentation of PASC in children is limited. Objective: To identify diagnosed symptoms, diagnosed health conditions, and medications associated with PASC in children. Design, Setting and Participants: This retrospective cohort study used electronic health records from 9 US children's hospitals for individuals younger than 21 years who underwent antigen or reverse transcriptase-polymerase chain reaction (RT-PCR) testing for SARS-CoV-2 between March 1, 2020, and October 31, 2021, and had at least 1 encounter in the 3 years before testing. Exposures: SARS-CoV-2 positivity by viral test (antigen or RT-PCR). Main Outcomes and Measures: Syndromic (symptoms), systemic (conditions), and medication PASC features were identified in the 28 to 179 days following the initial test date. Adjusted hazard ratios (aHRs) were obtained for 151 clinically predicted PASC features by contrasting viral test-positive groups with viral test-negative groups using proportional hazards models, adjusting for site, age, sex, testing location, race and ethnicity, and time period of cohort entrance. The incidence proportion for any syndromic, systemic, or medication PASC feature was estimated in the 2 groups to obtain a burden of PASC estimate. Results: Among 659 286 children in the study sample, 348 091 (52.8%) were male, and the mean (SD) age was 8.1 (5.7) years. A total of 59 893 (9.1%) tested positive by viral test for SARS-CoV-2, and 599 393 (90.9%) tested negative. Most were tested in outpatient testing facility settings (322 813 [50.3%]) or office settings (162 138 [24.6%]). The most common syndromic, systemic, and medication features were loss of taste or smell (aHR, 1.96; 95% CI, 1.16-3.32), myocarditis (aHR, 3.10; 95% CI, 1.94-4.96), and cough and cold preparations (aHR, 1.52; 95% CI, 1.18-1.96), respectively. The incidence of at least 1 systemic, syndromic, or medication feature of PASC was 41.9% (95% CI, 41.4-42.4) among viral test-positive children vs 38.2% (95% CI, 38.1-38.4) among viral test-negative children, with an incidence proportion difference of 3.7% (95% CI, 3.2-4.2). A higher strength of association for PASC was identified in those cared for in the intensive care unit during the acute illness phase, children younger than 5 years, and individuals with complex chronic conditions. Conclusions and Relevance: In this large-scale, exploratory study, the burden of pediatric PASC that presented to health systems was low. Myocarditis was the most commonly diagnosed PASC-associated condition. Acute illness severity, young age, and comorbid complex chronic disease increased the risk of PASC.

Acute Upper Airway Disease in Children With the Omicron (B.1.1.529) Variant of SARS-CoV-2-A Report From the US National COVID Cohort Collaborative.

This cohort study uses data from the US National COVID Cohort Collaborative to evaluate upper airway infections in children during the surge of the Omicron (B.1.1.529) variant of SARS-CoV-2 in the US.

Harmonizing units and values of quantitative data elements in a very large nationally pooled electronic health record (EHR) dataset.

OBJECTIVE: The goals of this study were to harmonize data from electronic health records (EHRs) into common units, and impute units that were missing. MATERIALS AND METHODS: The National COVID Cohort Collaborative (N3C) table of laboratory measurement data-over 3.1 billion patient records and over 19 000 unique measurement concepts in the Observational Medical Outcomes Partnership (OMOP) common-data-model format from 55 data partners. We grouped ontologically similar OMOP concepts together for 52 variables relevant to COVID-19 research, and developed a unit-harmonization pipeline comprised of (1) selecting a canonical unit for each measurement variable, (2) arriving at a formula for conversion, (3) obtaining clinical review of each formula, (4) applying the formula to convert data values in each unit into the target canonical unit, and (5) removing any harmonized value that fell outside of accepted value ranges for the variable. For data with missing units for all the results within a lab test for a data partner, we compared values with pooled values of all data partners, using the Kolmogorov-Smirnov test. RESULTS: Of the concepts without missing values, we harmonized 88.1% of the values, and imputed units for 78.2% of records where units were absent (41% of contributors' records lacked units). DISCUSSION: The harmonization and inference methods developed herein can serve as a resource for initiatives aiming to extract insight from heterogeneous EHR collections. Unique properties of centralized data are harnessed to enable unit inference. CONCLUSION: The pipeline we developed for the pooled N3C data enables use of measurements that would otherwise be unavailable for analysis.

The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers. MATERIALS AND METHODS: The Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics. RESULTS: Organized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access. CONCLUSIONS: The N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19.