Finding Long-COVID: Temporal Topic Modeling of Electronic Health Records from the N3C and RECOVER Programs.

Post-Acute Sequelae of SARS-CoV-2 infection (PASC), also known as Long-COVID, encompasses a variety of complex and varied outcomes following COVID-19 infection that are still poorly understood. We clustered over 600 million condition diagnoses from 14 million patients available through the National COVID Cohort Collaborative (N3C), generating hundreds of highly detailed clinical phenotypes. Assessing patient clinical trajectories using these clusters allowed us to identify individual conditions and phenotypes strongly increased after acute infection. We found many conditions increased in COVID-19 patients compared to controls, and using a novel method to associate patients with clusters over time, we additionally found phenotypes specific to patient sex, age, wave of infection, and PASC diagnosis status. While many of these results reflect known PASC symptoms, the resolution provided by this unprecedented data scale suggests avenues for improved diagnostics and mechanistic understanding of this multifaceted disease.

Long COVID incidence in adults and children between 2020 and 2023: a real-world data study from the RECOVER Initiative.

Estimates of post-acute sequelae of SARS-CoV-2 infection (PASC) incidence, also known as Long COVID, have varied across studies and changed over time. We estimated PASC incidence among adult and pediatric populations in three nationwide research networks of electronic health records (EHR) participating in the RECOVER Initiative using different classification algorithms (computable phenotypes). Overall, 7% of children and 8.5%-26.4% of adults developed PASC, depending on computable phenotype used. Excess incidence among SARS-CoV-2 patients was 4% in children and ranged from 4-7% among adults, representing a lower-bound incidence estimation based on two control groups - contemporary COVID-19 negative and historical patients (2019). Temporal patterns were consistent across networks, with peaks associated with introduction of new viral variants. Our findings indicate that preventing and mitigating Long COVID remains a public health priority. Examining temporal patterns and risk factors of PASC incidence informs our understanding of etiology and can improve prevention and management.

Supervised diagnostic classification of cognitive attributes using data augmentation.

Over recent decades, machine learning, an integral subfield of artificial intelligence, has revolutionized diverse sectors, enabling data-driven decisions with minimal human intervention. In particular, the field of educational assessment emerges as a promising area for machine learning applications, where students can be classified and diagnosed using their performance data. The objectives of Diagnostic Classification Models (DCMs), which provide a suite of methods for diagnosing students' cognitive states in relation to the mastery of necessary cognitive attributes for solving problems in a test, can be effectively addressed through machine learning techniques. However, the challenge lies in the latent nature of cognitive status, which makes it difficult to obtain labels for the training dataset. Consequently, the application of machine learning methods to DCMs often assumes smaller training sets with labels derived either from theoretical considerations or human experts. In this study, the authors propose a supervised diagnostic classification model with data augmentation (SDCM-DA). This method is designed to utilize the augmented data using a data generation model constructed by leveraging the probability of correct responses for each attribute mastery pattern derived from the expert-labeled dataset. To explore the benefits of data augmentation, a simulation study is carried out, contrasting it with classification methods that rely solely on the expert-labeled dataset for training. The findings reveal that utilizing data augmentation with the estimated probabilities of correct responses substantially enhances classification accuracy. This holds true even when the augmentation originates from a small labeled sample with occasional labeling errors, and when the tests contain lower-quality items that may inaccurately measure students' true cognitive status. Moreover, the study demonstrates that leveraging augmented data for learning can enable the successful classification of students, thereby eliminating the necessity for specifying an underlying response model.

Coordinated single-cell tumor microenvironment dynamics reinforce pancreatic cancer subtype.

Bulk analyses of pancreatic ductal adenocarcinoma (PDAC) samples are complicated by the tumor microenvironment (TME), i.e. signals from fibroblasts, endocrine, exocrine, and immune cells. Despite this, we and others have established tumor and stroma subtypes with prognostic significance. However, understanding of underlying signals driving distinct immune and stromal landscapes is still incomplete. Here we integrate 92 single cell RNA-seq samples from seven independent studies to build a reproducible PDAC atlas with a focus on tumor-TME interdependence. Patients with activated stroma are synonymous with higher myofibroblastic and immunogenic fibroblasts, and furthermore show increased M2-like macrophages and regulatory T-cells. Contrastingly, patients with 'normal' stroma show M1-like recruitment, elevated effector and exhausted T-cells. To aid interoperability of future studies, we provide a pretrained cell type classifier and an atlas of subtype-based signaling factors that we also validate in mouse data. Ultimately, this work leverages the heterogeneity among single-cell studies to create a comprehensive view of the orchestra of signaling interactions governing PDAC.

TRPC expression in human periodontal ligament cells and the periodontal tissue of periodontitis mice: a preliminary study.

BACKGROUND: Transient receptor potential canonical (TRPC) channels are non-selective cationic channels with permeability to Ca2+ and Na+. Despite their importance, there are currently few studies on TRPC in the periodontal ligament (PDL) and bone cells in the dental field. To provide biological information regarding TRPC in PDL cells and periodontal tissue, we evaluated TRPC channels expression in the osteoblast differentiation of PDL cells and periodontitis-induced tissue. Human PDL cells were cultured in osteogenic differentiation media for 28 days, and the expression of Runx2, osteocalcin (OCN), and TRPC1, 3, 4, and 6 was evaluated by real-time PCR. In ligature-induced periodontitis mice, the alveolar bone and osteoid areas, the osteoclast number, and the expression of Runx2, OCN, TRPC3, and TRPC6 was evaluated by H&E staining, TRAP staining, and immunohistochemistry, respectively. RESULTS: In the PDL cell differentiation group, TRPC6 expression peaked on day 7 and TRPC3 expression generally increased during differentiation. During the 28 days of periodontitis progression, alveolar bone loss and osteoclast numbers increased compared to the control group during the experimental period and the osteoid area increased from day 14. TRPC6 expression in the periodontitis group increased in the PDL area and in the osteoblasts compared to the control group, whereas TRPC3 expression increased only in the PDL area on days 7 and 28. CONCLUSIONS: These results indicate changes of TRPC3 and TRPC6 expression in PDL cells that were differentiating into osteoblasts and in periodontitis-induced tissue, suggesting the need for research on the role of TRPC in osteoblast differentiation or periodontitis progression.

Enhancement of the Anticancer Ability of Natural Killer Cells through Allogeneic Mitochondrial Transfer.

An in vitro culture period of at least 2 weeks is required to produce sufficient natural killer (NK) cells for immunotherapy, which are the key effectors in hematological malignancy treatment. Mitochondrial damage and fragmentation reduce the NK cell immune surveillance capacity. Thus, we hypothesized that the transfer of healthy mitochondria to NK cells could enhance their anticancer effects. Allogeneic healthy mitochondria isolated from WRL-68 cells were transferred to NK cells. We evaluated NK cells' proliferative capacity, cell cycle, and cytotoxic capacity against various cancer cell types by analyzing specific lysis and the cytotoxic granules released. The relationship between the transferred allogenic mitochondrial residues and NK cell function was determined. After mitochondrial transfer, the NK cell proliferation rate was 1.2-fold higher than that of control cells. The mitochondria-treated NK cells secreted a 2.7-, 4.1-, and 5-fold higher amount of granzyme B, perforin, and IFN-γ, respectively, when co-cultured with K562 cells. The specific lysis of various solid cancer cells increased 1.3-1.6-fold. However, once allogeneic mitochondria were eliminated, the NK cell activity returned to the pre-mitochondrial transfer level. Mitochondria-enriched NK cells have the potential to be used as a novel solid cancer treatment agent, without the need for in vitro cytokine-induced culture.

Geographic and Temporal Trends in COVID-Associated Acute Kidney Injury in the National COVID Cohort Collaborative.

BACKGROUND: AKI is associated with mortality in patients hospitalized with coronavirus disease 2019 (COVID-19); however, its incidence, geographic distribution, and temporal trends since the start of the pandemic are understudied. METHODS: Electronic health record data were obtained from 53 health systems in the United States in the National COVID Cohort Collaborative. We selected hospitalized adults diagnosed with COVID-19 between March 6, 2020, and January 6, 2022. AKI was determined with serum creatinine and diagnosis codes. Time was divided into 16-week periods (P1-6) and geographical regions into Northeast, Midwest, South, and West. Multivariable models were used to analyze the risk factors for AKI or mortality. RESULTS: Of a total cohort of 336,473, 129,176 (38%) patients had AKI. Fifty-six thousand three hundred and twenty-two (17%) lacked a diagnosis code but had AKI based on the change in serum creatinine. Similar to patients coded for AKI, these patients had higher mortality compared with those without AKI. The incidence of AKI was highest in P1 (47%; 23,097/48,947), lower in P2 (37%; 12,102/32,513), and relatively stable thereafter. Compared with the Midwest, the Northeast, South, and West had higher adjusted odds of AKI in P1. Subsequently, the South and West regions continued to have the highest relative AKI odds. In multivariable models, AKI defined by either serum creatinine or diagnostic code and the severity of AKI was associated with mortality. CONCLUSIONS: The incidence and distribution of COVID-19-associated AKI changed since the first wave of the pandemic in the United States. PODCAST: This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/CJASN/2023_08_08_CJN0000000000000192.mp3.

Risk of post-acute sequelae of SARS-CoV-2 infection associated with pre-coronavirus disease obstructive sleep apnea diagnoses: an electronic health record-based analysis from the RECOVER initiative.

STUDY OBJECTIVES: Obstructive sleep apnea (OSA) has been associated with more severe acute coronavirus disease-2019 (COVID-19) outcomes. We assessed OSA as a potential risk factor for Post-Acute Sequelae of SARS-CoV-2 (PASC). METHODS: We assessed the impact of preexisting OSA on the risk for probable PASC in adults and children using electronic health record data from multiple research networks. Three research networks within the REsearching COVID to Enhance Recovery initiative (PCORnet Adult, PCORnet Pediatric, and the National COVID Cohort Collaborative [N3C]) employed a harmonized analytic approach to examine the risk of probable PASC in COVID-19-positive patients with and without a diagnosis of OSA prior to pandemic onset. Unadjusted odds ratios (ORs) were calculated as well as ORs adjusted for age group, sex, race/ethnicity, hospitalization status, obesity, and preexisting comorbidities. RESULTS: Across networks, the unadjusted OR for probable PASC associated with a preexisting OSA diagnosis in adults and children ranged from 1.41 to 3.93. Adjusted analyses found an attenuated association that remained significant among adults only. Multiple sensitivity analyses with expanded inclusion criteria and covariates yielded results consistent with the primary analysis. CONCLUSIONS: Adults with preexisting OSA were found to have significantly elevated odds of probable PASC. This finding was consistent across data sources, approaches for identifying COVID-19-positive patients, and definitions of PASC. Patients with OSA may be at elevated risk for PASC after SARS-CoV-2 infection and should be monitored for post-acute sequelae.

New Accelerated Corrosion Test Method Simulating Atmospheric Corrosion of Complex Phase Steel Combining Cyclic Corrosion Test and Electrochemically Accelerated Corrosion Test.

The automobile industry commonly uses cyclic corrosion tests (CCTs) to evaluate the durability of materials. However, the extended evaluation period required by CCTs can pose challenges in this fast-paced industry. To address this issue, a new approach that combines a CCT with an electrochemically accelerated corrosion test has been explored, to shorten the evaluation period. This method involves the formation of a corrosion product layer through a CCT, which leads to localized corrosion, followed by applying an electrochemically accelerated corrosion test using an agar gel electrolyte to preserve the corrosion product layer as much as possible. The results indicate that this approach can achieve comparable localized corrosion resistance, with similar localized corrosion area ratios and maximum localized corrosion depths to those obtained through a conventional CCT in half the time.

Clinical encounter heterogeneity and methods for resolving in networked EHR data: a study from N3C and RECOVER programs.

OBJECTIVE: Clinical encounter data are heterogeneous and vary greatly from institution to institution. These problems of variance affect interpretability and usability of clinical encounter data for analysis. These problems are magnified when multisite electronic health record (EHR) data are networked together. This article presents a novel, generalizable method for resolving encounter heterogeneity for analysis by combining related atomic encounters into composite "macrovisits." MATERIALS AND METHODS: Encounters were composed of data from 75 partner sites harmonized to a common data model as part of the NIH Researching COVID to Enhance Recovery Initiative, a project of the National Covid Cohort Collaborative. Summary statistics were computed for overall and site-level data to assess issues and identify modifications. Two algorithms were developed to refine atomic encounters into cleaner, analyzable longitudinal clinical visits. RESULTS: Atomic inpatient encounters data were found to be widely disparate between sites in terms of length-of-stay (LOS) and numbers of OMOP CDM measurements per encounter. After aggregating encounters to macrovisits, LOS and measurement variance decreased. A subsequent algorithm to identify hospitalized macrovisits further reduced data variability. DISCUSSION: Encounters are a complex and heterogeneous component of EHR data and native data issues are not addressed by existing methods. These types of complex and poorly studied issues contribute to the difficulty of deriving value from EHR data, and these types of foundational, large-scale explorations, and developments are necessary to realize the full potential of modern real-world data. CONCLUSION: This article presents method developments to manipulate and resolve EHR encounter data issues in a generalizable way as a foundation for future research and analysis.

Periodontitis deteriorates renal fibrosis and macrophage infiltration in rats with chronic kidney disease.

OBJECTIVE: The objective of this study was to examine the effect of periodontitis on renal function and morphology in rats with or without nephrectomy (Nx)-induced chronic kidney disease (CKD). METHODS: Rats were divided into sham surgery (Sham), Sham with tooth ligation (ShamL), Nx, and NxL groups. Periodontitis was induced by tooth ligation at 16-week olds. Creatinine, alveolar bone area, and renal histopathology were analyzed at 20-week olds. RESULTS: Creatinine did not differ between the Sham and ShamL groups or between the Nx and NxL groups. The ShamL and NxL groups (both p = 0.002) had less alveolar bone area than the Sham group. The NxL group had fewer glomeruli than the Nx group (p < 0.000). The periodontitis groups demonstrated more tubulointerstitial fibrosis (Sham vs. ShamL p = 0.002, Nx vs. NxL p < 0.000) and macrophage infiltration (Sham vs. ShamL p = 0.002, Nx vs. NxL p = 0.006) than the groups without periodontitis. Only the NxL group had greater renal TNFα expression than the Sham group (p < 0.003). CONCLUSIONS: These suggest that periodontitis increases renal fibrosis and inflammation in the presence or absence of CKD but does not affect renal function. Periodontitis also increases TNFα expression in the presence of CKD.

SARS-CoV-2 Reinfection is Preceded by Unique Biomarkers and Related to Initial Infection Timing and Severity: an N3C RECOVER EHR-Based Cohort Study.

Although the COVID-19 pandemic has persisted for over 2 years, reinfections with SARS-CoV-2 are not well understood. We use the electronic health record (EHR)-based study cohort from the National COVID Cohort Collaborative (N3C) as part of the NIH Researching COVID to Enhance Recovery (RECOVER) Initiative to characterize reinfection, understand development of Long COVID after reinfection, and compare severity of reinfection with initial infection. We validate previous findings of reinfection incidence (5.9%), the occurrence of most reinfections during the Omicron epoch, and evidence of multiple reinfections. We present novel findings that Long COVID diagnoses occur closer to the index date for infection or reinfection in the Omicron BA epoch. We report lower albumin levels leading up to reinfection and a statistically significant association of severity between first infection and reinfection (chi-squared value: 9446.2, p-value: 0) with a medium effect size (Cramer's V: 0.18, DoF = 4).

Alveolar bone and tibia responses to hormonal and mineral abnormalities in rats with chronic kidney disease: A pilot study.

OBJECTIVES: As the impact of chronic kidney disease (CKD) severity on different bone types remains unclear, we induced increasing levels of CKD severity in a rat model and investigated hormone and mineral levels as well as alveolar and tibia bone histomorphology. METHODS: Rats were divided into sham operation (sham), 4/6 nephrectomy (4/6Nx), 5/6Nx, and 4/6Nx with hyperphosphorous (HP) diet (4/6NxHP). At week 20, BUN, FGF23, PTH, and P were estimated in plasma. Bone parameters were evaluated by microCT, and osteoclasts and osteoid areas were evaluated by TRAP and H&E stains, respectively. RESULTS: The 4/6NxHP and 5/6Nx groups had elevated PTH, and the 4/6NxHP group alone had elevated P. Compared to the 4/6Nx group, the 4/6NxHP group demonstrated increased FGF23 and P. In the alveolar bone, the 4/6NxHP group had reduced bone volume and BMD compared to the sham and 4/6Nx groups. In the tibia cortical bone, bone surface density was higher in the 4/6NxHP group compared to the sham group. Tibia cortical bone volume was negatively correlated with FGF23 and P. Moreover, alveolar bone volume was negatively correlated with FGF23, PTH, and P. CONCLUSIONS: Our results demonstrate that hormone and mineral levels vary with CKD severity, and alveolar bone loss strongly correlates with these hormone and mineral alterations.

COVID-19-associated AKI in hospitalized US patients: incidence, temporal trends, geographical distribution, risk factors and mortality.

Background: Acute kidney injury (AKI) is associated with mortality in patients hospitalized with COVID-19, however, its incidence, geographic distribution, and temporal trends since the start of the pandemic are understudied. Methods: Electronic health record data were obtained from 53 health systems in the United States (US) in the National COVID Cohort Collaborative (N3C). We selected hospitalized adults diagnosed with COVID-19 between March 6th, 2020, and January 6th, 2022. AKI was determined with serum creatinine (SCr) and diagnosis codes. Time were divided into 16-weeks (P1-6) periods and geographical regions into Northeast, Midwest, South, and West. Multivariable models were used to analyze the risk factors for AKI or mortality. Results: Out of a total cohort of 306,061, 126,478 (41.0 %) patients had AKI. Among these, 17.9% lacked a diagnosis code but had AKI based on the change in SCr. Similar to patients coded for AKI, these patients had higher mortality compared to those without AKI. The incidence of AKI was highest in P1 (49.3%), reduced in P2 (40.6%), and relatively stable thereafter. Compared to the Midwest, the Northeast, South, and West had higher adjusted AKI incidence in P1, subsequently, the South and West regions continued to have the highest relative incidence. In multivariable models, AKI defined by either SCr or diagnostic code, and the severity of AKI was associated with mortality. Conclusions: Uncoded cases of COVID-19-associated AKI are common and associated with mortality. The incidence and distribution of COVID-19-associated AKI have changed since the first wave of the pandemic in the US.

Comparison of Hydrogen Embrittlement Susceptibility of Different Types of Advanced High-Strength Steels.

This study investigated the hydrogen embrittlement (HE) characteristics of advanced high-strength steels (AHSSs). Two different types of AHSSs with a tensile strength of 1.2 GPa were investigated. Slow strain rate tests (SSRTs) were performed under various applied potentials (Eapp) to identify the mechanism with the greatest effect on the embrittlement of the specimens. The SSRT results revealed that, as the Eapp increased, the elongation tended to increase, even when a potential exceeding the corrosion potential was applied. Both types of AHSSs exhibited embrittled fracture behavior that was dominated by HE. The fractured SSRT specimens were subjected to a thermal desorption spectroscopy analysis, revealing that diffusible hydrogen was trapped mainly at the grain boundaries and dislocations (i.e., reversible hydrogen-trapping sites). The micro-analysis results revealed that the poor HE resistance of the specimens was attributed to the more reversible hydrogen-trapping sites.

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.

Glycemic Control and Clinical Outcomes in U.S. Patients With COVID-19: Data From the National COVID Cohort Collaborative (N3C) Database.

OBJECTIVE: The purpose of the study is to evaluate the relationship between HbA1c and severity of coronavirus disease 2019 (COVID-19) outcomes in patients with type 2 diabetes (T2D) with acute COVID-19 infection. RESEARCH DESIGN AND METHODS: We conducted a retrospective study using observational data from the National COVID Cohort Collaborative (N3C), a longitudinal, multicenter U.S. cohort of patients with COVID-19 infection. Patients were ≥18 years old with T2D and confirmed COVID-19 infection by laboratory testing or diagnosis code. The primary outcome was 30-day mortality following the date of COVID-19 diagnosis. Secondary outcomes included need for invasive ventilation or extracorporeal membrane oxygenation (ECMO), hospitalization within 7 days before or 30 days after COVID-19 diagnosis, and length of stay (LOS) for patients who were hospitalized. RESULTS: The study included 39,616 patients (50.9% female, 55.4% White, 26.4% Black or African American, and 16.1% Hispanic or Latino, with mean ± SD age 62.1 ± 13.9 years and mean ± SD HbA1c 7.6% ± 2.0). There was an increasing risk of hospitalization with incrementally higher HbA1c levels, but risk of death plateaued at HbA1c >8%, and risk of invasive ventilation or ECMO plateaued >9%. There was no significant difference in LOS across HbA1c levels. CONCLUSIONS: In a large, multicenter cohort of patients in the U.S. with T2D and COVID-19 infection, risk of hospitalization increased with incrementally higher HbA1c levels. Risk of death and invasive ventilation also increased but plateaued at different levels of glycemic control.

Characteristics, Outcomes, and Severity Risk Factors Associated With SARS-CoV-2 Infection Among Children in the US National COVID Cohort Collaborative.

Importance: Understanding of SARS-CoV-2 infection in US children has been limited by the lack of large, multicenter studies with granular data. Objective: To examine the characteristics, changes over time, outcomes, and severity risk factors of children with SARS-CoV-2 within the National COVID Cohort Collaborative (N3C). Design, Setting, and Participants: A prospective cohort study of encounters with end dates before September 24, 2021, was conducted at 56 N3C facilities throughout the US. Participants included children younger than 19 years at initial SARS-CoV-2 testing. Main Outcomes and Measures: Case incidence and severity over time, demographic and comorbidity severity risk factors, vital sign and laboratory trajectories, clinical outcomes, and acute COVID-19 vs multisystem inflammatory syndrome in children (MIS-C), and Delta vs pre-Delta variant differences for children with SARS-CoV-2. Results: A total of 1 068 410 children were tested for SARS-CoV-2 and 167 262 test results (15.6%) were positive (82 882 [49.6%] girls; median age, 11.9 [IQR, 6.0-16.1] years). Among the 10 245 children (6.1%) who were hospitalized, 1423 (13.9%) met the criteria for severe disease: mechanical ventilation (796 [7.8%]), vasopressor-inotropic support (868 [8.5%]), extracorporeal membrane oxygenation (42 [0.4%]), or death (131 [1.3%]). Male sex (odds ratio [OR], 1.37; 95% CI, 1.21-1.56), Black/African American race (OR, 1.25; 95% CI, 1.06-1.47), obesity (OR, 1.19; 95% CI, 1.01-1.41), and several pediatric complex chronic condition (PCCC) subcategories were associated with higher severity disease. Vital signs and many laboratory test values from the day of admission were predictive of peak disease severity. Variables associated with increased odds for MIS-C vs acute COVID-19 included male sex (OR, 1.59; 95% CI, 1.33-1.90), Black/African American race (OR, 1.44; 95% CI, 1.17-1.77), younger than 12 years (OR, 1.81; 95% CI, 1.51-2.18), obesity (OR, 1.76; 95% CI, 1.40-2.22), and not having a pediatric complex chronic condition (OR, 0.72; 95% CI, 0.65-0.80). The children with MIS-C had a more inflammatory laboratory profile and severe clinical phenotype, with higher rates of invasive ventilation (117 of 707 [16.5%] vs 514 of 8241 [6.2%]; P < .001) and need for vasoactive-inotropic support (191 of 707 [27.0%] vs 426 of 8241 [5.2%]; P < .001) compared with those who had acute COVID-19. Comparing children during the Delta vs pre-Delta eras, there was no significant change in hospitalization rate (1738 [6.0%] vs 8507 [6.2%]; P = .18) and lower odds for severe disease (179 [10.3%] vs 1242 [14.6%]) (decreased by a factor of 0.67; 95% CI, 0.57-0.79; P < .001). Conclusions and Relevance: In this cohort study of US children with SARS-CoV-2, there were observed differences in demographic characteristics, preexisting comorbidities, and initial vital sign and laboratory values between severity subgroups. Taken together, these results suggest that early identification of children likely to progress to severe disease could be achieved using readily available data elements from the day of admission. Further work is needed to translate this knowledge into improved outcomes.

Distribution of neutrophil and monocyte/macrophage populations induced by the CXCR4 inhibitor AMD3100 in blood and periodontal tissue early after periodontitis induction.

CXCR4, a CXCL12 receptor, is expressed on epithelial cells, fibroblasts, and inflammatory cells. The CXCR4-CXCL12 interaction is related to the migration of neutrophils and monocytes/macrophages. Periodontitis, an inflammatory disease mainly caused by gram-negative bacteria, is characterized by infiltration of circulating inflammatory cells and alveolar bone (AB) loss. To investigate whether CXCR4 is involved in the distribution of neutrophils and monocytes/macrophages early after periodontitis induction, we examined the effects of AMD3100 (AMD), a CXCR4 antagonist, in ligature-induced periodontitis mice and LPS-injected air pouch mice. The periodontitis study was accomplished in control (C), periodontitis (P), and P + AMD groups. Periodontitis was induced by ligation of the mandibular first molar. AMD was intraperitoneally administered daily beginning the day before ligation until sacrifice on the third day after ligation. The air pouch study was accomplished in C, lipopolysaccharide (LPS), and LPS + AMD groups. Air pouches on mice backs were formed by subcutaneous injection of sterilized air. AMD was administered and then LPS was injected into the air pouch. For the detection of neutrophils and monocytes/macrophages in blood and air pouch exudates, flow cytometry was performed with anti-Ly6G/anti-CD11b antibodies (Abs) and anti-CD115 Ab, respectively. In periodontal tissue, Ly6G+ cells and CD115+ cells were counted by immunohistological analysis. AB loss was estimated by the periodontal ligament area in the furcation. In the periodontitis study, the P group showed higher numbers of Ly6G+ cells and CD115+ cells in blood and periodontal tissue than the C group. The P + AMD group showed a greater number of Ly6G+ cells and CD115+ cells in blood, but not in periodontal tissue compared to the P group. There was no difference in AB loss between the P and P + AMD groups. In the air pouch study, the LPS group had higher levels of Ly6G+ CD11b+ cells and CD115+ cells in both blood and exudates than the C group. The number of these cells in the LPS + AMD group was higher in blood than in the LPS group, but not in the exudates. The CXCR4 antagonist further increased neutrophil and monocyte/macrophage populations in the blood, but did not alter the levels in the periodontal tissue and exudates in mice with periodontitis and LPS-injected air pouches. These results suggest that during inflammatory conditions such as periodontitis, CXCR4 is involved in the distribution of neutrophils and monocytes/macrophages in the blood, but not in inflamed peripheral tissues.

Children with SARS-CoV-2 in the National COVID Cohort Collaborative (N3C).

IMPORTANCE: SARS-CoV-2. OBJECTIVE: To determine the characteristics, changes over time, outcomes, and severity risk factors of SARS-CoV-2 affected children within the National COVID Cohort Collaborative (N3C). DESIGN: Prospective cohort study of patient encounters with end dates before May 27th, 2021. SETTING: 45 N3C institutions. PARTICIPANTS: Children <19-years-old at initial SARS-CoV-2 testing. MAIN OUTCOMES AND MEASURES: Case incidence and severity over time, demographic and comorbidity severity risk factors, vital sign and laboratory trajectories, clinical outcomes, and acute COVID-19 vs MIS-C contrasts for children infected with SARS-CoV-2. RESULTS: 728,047 children in the N3C were tested for SARS-CoV-2; of these, 91,865 (12.6%) were positive. Among the 5,213 (6%) hospitalized children, 685 (13%) met criteria for severe disease: mechanical ventilation (7%), vasopressor/inotropic support (7%), ECMO (0.6%), or death/discharge to hospice (1.1%). Male gender, African American race, older age, and several pediatric complex chronic condition (PCCC) subcategories were associated with higher clinical severity (p ≤ 0.05). Vital signs (all p≤0.002) and many laboratory tests from the first day of hospitalization were predictive of peak disease severity. Children with severe (vs moderate) disease were more likely to receive antimicrobials (71% vs 32%, p<0.001) and immunomodulatory medications (53% vs 16%, p<0.001). Compared to those with acute COVID-19, children with MIS-C were more likely to be male, Black/African American, 1-to-12-years-old, and less likely to have asthma, diabetes, or a PCCC (p < 0.04). MIS-C cases demonstrated a more inflammatory laboratory profile and more severe clinical phenotype with higher rates of invasive ventilation (12% vs 6%) and need for vasoactive-inotropic support (31% vs 6%) compared to acute COVID-19 cases, respectively (p<0.03). CONCLUSIONS: In the largest U.S. SARS-CoV-2-positive pediatric cohort to date, we observed differences in demographics, pre-existing comorbidities, and initial vital sign and laboratory test values between severity subgroups. Taken together, these results suggest that early identification of children likely to progress to severe disease could be achieved using readily available data elements from the day of admission. Further work is needed to translate this knowledge into improved outcomes.