Precision symptom phenotyping identifies early clinical and proteomic predictors of distinct COVID-19 sequelae.

BACKGROUND: Post-COVID conditions (PCC) are difficult to characterize, diagnose, predict, and treat due to overlapping symptoms and poorly understood pathology. Identifying inflammatory profiles may improve clinical prognostication and trial endpoints. METHODS: 1,988 SARS-CoV-2 positive U.S. Military Health System beneficiaries with quantitative post-COVID symptom scores were included in this analysis. Among participants who reported moderate-to-severe symptoms on surveys collected 6-months post-SARS-CoV-2 infection, principal component analysis (PCA) followed by K-means clustering identified distinct clusters of symptoms. RESULTS: Three symptom-based clusters were identified: a sensory cluster (loss of smell and/or taste), a fatigue/difficulty thinking cluster, and a difficulty breathing/exercise intolerance cluster. Individuals within the sensory cluster were all outpatients during their initial COVID-19 presentation. The difficulty breathing cluster had a higher likelihood of obesity and COVID-19 hospitalization compared to those with no/mild symptoms at 6-months post-infection. Multinomial regression linked early post-infection D-dimer and IL-1RA elevation to fatigue/difficulty thinking, and elevated ICAM-1 concentrations to sensory symptoms. CONCLUSIONS: We identified three distinct symptom-based PCC phenotypes with specific clinical risk factors and early post-infection inflammatory predictors. With further validation and characterization, this framework may allow more precise classification of PCC cases and potentially improve the diagnosis, prognostication, and treatment of PCC.

Understanding "Hybrid Immunity": Comparison and Predictors of Humoral Immune Responses to Severe Acute Respiratory Syndrome Coronavirus 2 Infection (SARS-CoV-2) and Coronavirus Disease 2019 (COVID-19) Vaccines.

BACKGROUND: Comparison of humoral responses in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccinees, those with SARS-CoV-2 infection, or combinations of vaccine/ infection ("hybrid immunity") may clarify predictors of vaccine immunogenicity. METHODS: We studied 2660 US Military Health System beneficiaries with a history of SARS-CoV-2 infection-alone (n = 705), vaccination-alone (n = 932), vaccine-after-infection (n = 869), and vaccine-breakthrough-infection (n = 154). Peak anti-spike-immunoglobulin G (IgG) responses through 183 days were compared, with adjustment for vaccine product, demography, and comorbidities. We excluded those with evidence of clinical or subclinical SARS-CoV-2 reinfection from all groups. RESULTS: Multivariable regression results indicated that vaccine-after-infection anti-spike-IgG responses were higher than infection-alone (P < .01), regardless of prior infection severity. An increased time between infection and vaccination was associated with greater post-vaccination IgG response (P < .01). Vaccination-alone elicited a greater IgG response but more rapid waning of IgG (P < .01) compared with infection-alone (P < .01). BNT162b2 and mRNA-1273 vaccine-receipt was associated with greater IgG responses compared with JNJ-78436735 vaccine-receipt (P < .01), regardless of infection history. Those with vaccine-after-infection or vaccine-breakthrough-infection had a more durable anti-spike-IgG response compared to infection-alone (P < .01). CONCLUSIONS: Vaccine-receipt elicited higher anti-spike-IgG responses than infection-alone, although IgG levels waned faster in those vaccinated (compared to infection-alone). Vaccine-after-infection elicits a greater humoral response compared with vaccine or infection alone; and the timing, but not disease severity, of prior infection predicted these post-vaccination IgG responses. While differences between groups were small in magnitude, these results offer insights into vaccine immunogenicity variations that may help inform vaccination timing strategies.

Temporal Improvements in COVID-19 Outcomes for Hospitalized Adults: A Post Hoc Observational Study of Remdesivir Group Participants in the Adaptive COVID-19 Treatment Trial.

BACKGROUND: The COVID-19 standard of care (SOC) evolved rapidly during 2020 and 2021, but its cumulative effect over time is unclear. OBJECTIVE: To evaluate whether recovery and mortality improved as SOC evolved, using data from ACTT (Adaptive COVID-19 Treatment Trial). DESIGN: ACTT is a series of phase 3, randomized, double-blind, placebo-controlled trials that evaluated COVID-19 therapeutics from February 2020 through May 2021. ACTT-1 compared remdesivir plus SOC to placebo plus SOC, and in ACTT-2 and ACTT-3, remdesivir plus SOC was the control group. This post hoc analysis compared recovery and mortality between these comparable sequential cohorts of patients who received remdesivir plus SOC, adjusting for baseline characteristics with propensity score weighting. The analysis was repeated for participants in ACTT-3 and ACTT-4 who received remdesivir plus dexamethasone plus SOC. Trends in SOC that could explain outcome improvements were analyzed. (ClinicalTrials.gov: NCT04280705 [ACTT-1], NCT04401579 [ACTT-2], NCT04492475 [ACTT-3], and NCT04640168 [ACTT-4]). SETTING: 94 hospitals in 10 countries (86% U.S. participants). PARTICIPANTS: Adults hospitalized with COVID-19. INTERVENTION: SOC. MEASUREMENTS: 28-day mortality and recovery. RESULTS: Although outcomes were better in ACTT-2 than in ACTT-1, adjusted hazard ratios (HRs) were close to 1 (HR for recovery, 1.04 [95% CI, 0.92 to 1.17]; HR for mortality, 0.90 [CI, 0.56 to 1.40]). Comparable patients were less likely to be intubated in ACTT-2 than in ACTT-1 (odds ratio, 0.75 [CI, 0.53 to 0.97]), and hydroxychloroquine use decreased. Outcomes improved from ACTT-2 to ACTT-3 (HR for recovery, 1.43 [CI, 1.24 to 1.64]; HR for mortality, 0.45 [CI, 0.21 to 0.97]). Potential explanatory factors (SOC trends, case surges, and variant trends) were similar between ACTT-2 and ACTT-3, except for increased dexamethasone use (11% to 77%). Outcomes were similar in ACTT-3 and ACTT-4. Antibiotic use decreased gradually across all stages. LIMITATION: Unmeasured confounding. CONCLUSION: Changes in patient composition explained improved outcomes from ACTT-1 to ACTT-2 but not from ACTT-2 to ACTT-3, suggesting improved SOC. These results support excluding nonconcurrent controls from analysis of platform trials in rapidly changing therapeutic areas. PRIMARY FUNDING SOURCE: National Institute of Allergy and Infectious Diseases.

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) mRNA Vaccine-Breakthrough Infection Phenotype Includes Significant Symptoms, Live Virus Shedding, and Viral Genetic Diversity.

Little is known about severe acute respiratory syndrome coronavirus 2 "vaccine-breakthrough" infections (VBIs). Here we characterize 24 VBIs in predominantly young healthy persons. While none required hospitalization, a proportion endorsed severe symptoms and shed live virus as high as 4.13 × 103 plaque-forming units/mL. Infecting genotypes included both variant-of-concern (VOC) and non-VOC strains.

Clinical, Immunological, and Virological SARS-CoV-2 Phenotypes in Obese and Nonobese Military Health System Beneficiaries.

BACKGROUND: The mechanisms underlying the association between obesity and coronavirus disease 2019 (COVID-19) severity remain unclear. After verifying that obesity was a correlate of severe COVID-19 in US Military Health System (MHS) beneficiaries, we compared immunological and virological phenotypes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in both obese and nonobese participants. METHODS: COVID-19-infected MHS beneficiaries were enrolled, and anthropometric, clinical, and demographic data were collected. We compared the SARS-CoV-2 peak IgG humoral response and reverse-transcription polymerase chain reaction viral load in obese and nonobese patients, stratified by hospitalization, utilizing logistic regression models. RESULTS: Data from 511 COVID-19 patients were analyzed, among whom 24% were obese and 14% severely obese. Obesity was independently associated with hospitalization (adjusted odds ratio [aOR], 1.91; 95% confidence interval [CI], 1.15-3.18) and need for oxygen therapy (aOR, 3.39; 95% CI, 1.61-7.11). In outpatients, severely obese had a log10 (1.89) higher nucleocapsid (N1) genome equivalents (GE)/reaction and log10 (2.62) higher N2 GE/reaction than nonobese (P = 0.03 and P < .001, respectively). We noted a correlation between body mass index and peak anti-spike protein IgG in inpatients and outpatients (coefficient = 5.48, P < .001). CONCLUSIONS: Obesity is a strong correlate of COVID-19 severity in MHS beneficiaries. These findings offer new pathophysiological insights into the relationship between obesity and COVID-19 severity.

Durability of SARS-CoV-2-Specific T-Cell Responses at 12 Months Postinfection.

BACKGROUND: Characterizing the longevity and quality of cellular immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enhances understanding of coronavirus disease 2019 (COVID-19) immunity that influences clinical outcomes. Prior studies suggest SARS-CoV-2-specific T cells are present in peripheral blood 10 months after infection. Analysis of the function, durability, and diversity of cellular response long after natural infection, over a range of ages and disease phenotypes, is needed to identify preventative and therapeutic interventions. METHODS: We identified participants in our multisite longitudinal, prospective cohort study 12 months after SARS-CoV-2 infection representing a range of disease severity. We investigated function, phenotypes, and frequency of T cells specific for SARS-CoV-2 using intracellular cytokine staining and spectral flow cytometry, and compared magnitude of SARS-CoV-2-specific antibodies. RESULTS: SARS-CoV-2-specific antibodies and T cells were detected 12 months postinfection. Severe acute illness was associated with higher frequencies of SARS-CoV-2-specific CD4 T cells and antibodies at 12 months. In contrast, polyfunctional and cytotoxic T cells responsive to SARS-CoV-2 were identified in participants over a wide spectrum of disease severity. CONCLUSIONS: SARS-CoV-2 infection induces polyfunctional memory T cells detectable at 12 months postinfection, with higher frequency noted in those who experienced severe disease.

National Emergency Tele-Critical Care in a Pandemic: Barriers and Solutions.

The COVID-19 pandemic caused tremendous disruption to the U.S. healthcare system and nearly crippled some hospitals during large patient surges. Limited ICU beds across the country further exacerbated these challenges. Telemedicine, specifically tele-critical care (TCC), can expand a hospital's clinical capabilities through remote expertise and increase capacity by offloading some monitoring to remote teams. Unfortunately, the rapid deployment of telemedicine, especially TCC, is constrained by multiple barriers. In the summer of 2020, to support the National Emergency Tele-Critical Care Network (NETCCN) deployment, more than 50 national leaders in applying telemedicine technologies to critical care assembled to provide their opinions about barriers to NETCCN implementation and strategies to overcome them. Through consensus, these experts developed white papers that formed the basis of this article. Herein, the authors share their experience and propose multiple solutions to barriers presented by laws, local policies and cultures, and individual perspectives according to a minimum, better, best paradigm for TCC delivery in the setting of a national disaster. Cross-state licensure and local privileging of virtual experts were identified as the most significant barriers to rapid deployment of services, whereas refining the model of TCC to achieve the best outcomes and defining the best financial model is the most significant for long-term success. Ultimately, we conclude that a rapidly deployable national telemedicine response system is achievable.

Randomized Controlled Trial of Telementoring During Resource-Limited Patient Care Simulation Improves Caregiver Performance and Patient Survival.

OBJECTIVES: To determine the impact of telementoring on caregiver performance during a high-fidelity medical simulation model (HFMSM) of a critically ill patient in a resource-limited setting. DESIGN: A two-center, randomized, controlled study using a HFMSM of a patient with community-acquired pneumonia complicated by acute respiratory distress syndrome. SETTING: A notional clinic in a remote location staffed by a single clinician and nonmedical assistant. PARTICIPANTS: Clinicians with limited experience managing critically ill patients. INTERVENTIONS: Telemedicine (TM) support. MEASUREMENTS: The primary outcome was clinical performance as measured by accuracy, reliability, and efficiency of care. Secondary outcomes were patient survival, procedural quality, subjective assessment of the HFMSM, and perceived workload. MAIN RESULTS: TM participants (N = 11) performed better than non-TM (NTM, N = 12) in providing expected care (accuracy), delivering care more consistently (reliability), and without consistent differences in efficiency (timeliness of care). Accuracy: TM completed 91% and NTM 42% of expected tasks and procedures. Efficiency: groups did not differ in the mean (± sd) minutes it took to obtain an advanced airway successfully (TM 15.2 ± 10.5 vs. NTM 22.8 ± 8.4, p = 0.10) or decompress a tension pneumothorax with a needle (TM 0.7 ± 0.5 vs. NTM 0.6 ± 0.9, p = 0.65). TM was slower than NTM in completing thoracostomy (22.3 ± 10.2 vs. 12.3 ± 4.8, p = 0.03). Reliability: TM performed 13 of 17 (76%) tasks with more consistent timing than NTM. TM completed 68% and NTM 29% of procedural quality metrics. Eighty-two percent of the TM participants versus 17% of the NTM participants simulated patients survived (p = 0.003). The groups similarly perceived the HFMSM as realistic, managed their patients with personal ownership, and experienced comparable workload and stress. CONCLUSIONS: Remote expertise provided with TM to caregivers in resource-limited settings improves caregiver performance, quality of care, and potentially real patient survival. HFMSM can be used to study interventions in ways not possible with real patients.

SARS-CoV-2 infection is associated with self-reported post-acute neuropsychological symptoms within six months of follow-up.

BACKGROUND: Chronic neuropsychological sequelae following SARS-CoV-2 infection, including depression, anxiety, fatigue, and general cognitive difficulties, are a major public health concern. Given the potential impact of long-term neuropsychological impairment, it is important to characterize the frequency and predictors of this post-infection phenotype. METHODS: The Epidemiology, Immunology, and Clinical Characteristics of Emerging Infectious Diseases with Pandemic Potential (EPICC) study is a longitudinal study assessing the impact of SARS-CoV-2 infection in U.S. Military Healthcare System (MHS) beneficiaries, i.e. those eligible for care in the MHS including active duty servicemembers, dependents, and retirees. Four broad areas of neuropsychological symptoms were assessed cross-sectionally among subjects 1-6 months post-infection/enrollment, including: depression (Patient Health Questionnaire-9), anxiety (General Anxiety Disorder-7), fatigue (PROMIS® Fatigue 7a), and cognitive function (PROMIS® Cognitive Function 8a and PROMIS® Cognitive Function abilities 8a). Multivariable Poisson regression models compared participants with and without SARS-CoV-2 infection history on these measures, adjusting for sex, ethnicity, active-duty status, age, and months post-first positive or enrollment of questionnaire completion (MPFP/E); models for fatigue and cognitive function were also adjusted for depression and anxiety scores. RESULTS: The study population included 2383 participants who completed all five instruments within six MPFP/E, of whom 687 (28.8%) had at least one positive SARS-CoV-2 test. Compared to those who had never tested positive for SARS-CoV-2, the positive group was more likely to meet instrument-based criteria for depression (15.4% vs 10.3%, p<0.001), fatigue (20.1% vs 8.0%, p<0.001), impaired cognitive function (15.7% vs 8.6%, p<0.001), and impaired cognitive function abilities (24.3% vs 16.3%, p<0.001). In multivariable models, SARS-CoV-2 positive participants, assessed at an average of 2.7 months after infection, had increased risk of moderate to severe depression (RR: 1.44, 95% CI 1.12-1.84), fatigue (RR: 2.07, 95% CI 1.62-2.65), impaired cognitive function (RR: 1.64, 95% CI 1.27-2.11), and impaired cognitive function abilities (RR: 1.41, 95% CI 1.15-1.71); MPFP/E was not significant. CONCLUSIONS: Participants with a history of SARS-CoV-2 infection were up to twice as likely to report cognitive impairment and fatigue as the group without prior SARS-CoV-2 infection. These findings underscore the continued importance of preventing SARS-CoV-2 infection and while time since infection/enrollment was not significant through 6 months of follow-up, this highlights the need for additional research into the long-term impacts of COVID-19 to mitigate and reverse these neuropsychological outcomes.

A machine learning approach identifies distinct early-symptom cluster phenotypes which correlate with hospitalization, failure to return to activities, and prolonged COVID-19 symptoms.

BACKGROUND: Accurate COVID-19 prognosis is a critical aspect of acute and long-term clinical management. We identified discrete clusters of early stage-symptoms which may delineate groups with distinct disease severity phenotypes, including risk of developing long-term symptoms and associated inflammatory profiles. METHODS: 1,273 SARS-CoV-2 positive U.S. Military Health System beneficiaries with quantitative symptom scores (FLU-PRO Plus) were included in this analysis. We employed machine-learning approaches to identify symptom clusters and compared risk of hospitalization, long-term symptoms, as well as peak CRP and IL-6 concentrations. RESULTS: We identified three distinct clusters of participants based on their FLU-PRO Plus symptoms: cluster 1 ("Nasal cluster") is highly correlated with reporting runny/stuffy nose and sneezing, cluster 2 ("Sensory cluster") is highly correlated with loss of smell or taste, and cluster 3 ("Respiratory/Systemic cluster") is highly correlated with the respiratory (cough, trouble breathing, among others) and systemic (body aches, chills, among others) domain symptoms. Participants in the Respiratory/Systemic cluster were twice as likely as those in the Nasal cluster to have been hospitalized, and 1.5 times as likely to report that they had not returned-to-activities, which remained significant after controlling for confounding covariates (P < 0.01). Respiratory/Systemic and Sensory clusters were more likely to have symptoms at six-months post-symptom-onset (P = 0.03). We observed higher peak CRP and IL-6 in the Respiratory/Systemic cluster (P < 0.01). CONCLUSIONS: We identified early symptom profiles potentially associated with hospitalization, return-to-activities, long-term symptoms, and inflammatory profiles. These findings may assist in patient prognosis, including prediction of long COVID risk.

Persistent COVID-19 Symptoms at 6 Months After Onset and the Role of Vaccination Before or After SARS-CoV-2 Infection.

Importance: Understanding the factors associated with post-COVID conditions is important for prevention. Objective: To identify characteristics associated with persistent post-COVID-19 symptoms and to describe post-COVID-19 medical encounters. Design, Setting, and Participants: This cohort study used data from the Epidemiology, Immunology, and Clinical Characteristics of Emerging Infectious Diseases With Pandemic Potential (EPICC) study implemented in the US military health system (MHS); MHS beneficiaries aged 18 years or older who tested positive for SARS-CoV-2 from February 28, 2020, through December 31, 2021, were analyzed, with 1-year follow-up. Exposures: SARS-CoV-2 infection. Main Outcomes and Measures: The outcomes analyzed included survey-reported symptoms through 6 months after SARS-CoV-2 infection and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnosis categories reported in medical records 6 months following SARS-CoV-2 infection vs 3 months before infection. Results: More than half of the 1832 participants in these analyses were aged 18 to 44 years (1226 [66.9%]; mean [SD] age, 40.5 [13.7] years), were male (1118 [61.0%]), were unvaccinated at the time of their infection (1413 [77.1%]), and had no comorbidities (1290 [70.4%]). A total of 728 participants (39.7%) had illness that lasted 28 days or longer (28-89 days: 364 [19.9%]; ≥90 days: 364 [19.9%]). Participants who were unvaccinated prior to infection (risk ratio [RR], 1.39; 95% CI, 1.04-1.85), reported moderate (RR, 1.80; 95% CI, 1.47-2.22) or severe (RR, 2.25; 95% CI, 1.80-2.81) initial illnesses, had more hospitalized days (RR per each day of hospitalization, 1.02; 95% CI, 1.00-1.03), and had a Charlson Comorbidity Index score of 5 or greater (RR, 1.55; 95% CI, 1.01-2.37) were more likely to report 28 or more days of symptoms. Among unvaccinated participants, postinfection vaccination was associated with a 41% lower risk of reporting symptoms at 6 months (RR, 0.59; 95% CI, 0.40-0.89). Participants had higher risk of pulmonary (RR, 2.00; 95% CI, 1.40-2.84), diabetes (RR, 1.46; 95% CI, 1.00-2.13), neurological (RR, 1.29; 95% CI, 1.02-1.64), and mental health-related medical encounters (RR, 1.28; 95% CI, 1.01-1.62) at 6 months after symptom onset than at baseline (before SARS-CoV-2 infection). Conclusions and Relevance: In this cohort study, more severe acute illness, a higher Charlson Comorbidity Index score, and being unvaccinated were associated with a higher risk of reporting COVID-19 symptoms lasting 28 days or more. Participants with COVID-19 were more likely to seek medical care for diabetes, pulmonary, neurological, and mental health-related illness for at least 6 months after onset compared with their pre-COVID baseline health care use patterns. These findings may inform the risk-benefit ratio of COVID-19 vaccination policy.

Decreased Self-reported Physical Fitness Following SARS-CoV-2 Infection and the Impact of Vaccine Boosters in a Cohort Study.

Background: The long-term effects of coronavirus disease 2019 (COVID-19) on physical fitness are unclear, and the impact of vaccination on that relationship is uncertain. Methods: We compared survey responses in a 1-year study of US military service members with (n = 1923) and without (n = 1591) a history of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We fit Poisson regression models to estimate the association between history of SARS-CoV-2 infection and fitness impairment, adjusting for time since infection, demographics, and baseline health. Results: The participants in this analysis were primarily young adults aged 18-39 years (75%), and 71.5% were male. Participants with a history of SARS-CoV-2 infection were more likely to report difficulty exercising (38.7% vs 18.4%; P < .01), difficulty performing daily activities (30.4% vs 12.7%; P < .01), and decreased fitness test (FT) scores (42.7% vs 26.2%; P < .01) than those without a history of infection. SARS-CoV-2-infected participants were at higher risk of these outcomes after adjusting for other factors (unvaccinated: exercising: adjusted risk ratio [aRR], 3.99; 95% CI, 3.36-4.73; activities: aRR, 5.02; 95% CI, 4.09-6.16; FT affected: aRR, 2.55; 95% CI, 2.19-2.98). Among SARS-CoV-2-positive participants, full vaccination before infection was associated with a lower risk of post-COVID-19 fitness impairment (fully vaccinated: exercise: aRR, 0.81; 95% CI, 0.70-0.95; activities: aRR, 0.76; 95% CI, 0.64-0.91; FT: aRR, 0.87; 95% CI, 0.76-1.00; boosted: exercise: aRR, 0.62; 95% CI, 0.51-0.74; activities: aRR, 0.52; 95% CI, 0.41-0.65; FT: aRR, 0.59; 95% CI, 0.49-0.70). Conclusions: In this study of generally young, healthy military service members, SARS-CoV-2 infection was associated with lower self-reported fitness and exercise capacity; vaccination and boosting were associated with lower risk of self-reported fitness loss.

Evaluating Demographic Representation in Clinical Trials: Use of the Adaptive Coronavirus Disease 2019 Treatment Trial (ACTT) as a Test Case.

Background: Clinical trials initiated during emerging infectious disease outbreaks must quickly enroll participants to identify treatments to reduce morbidity and mortality. This may be at odds with enrolling a representative study population, especially when the population affected is undefined. Methods: We evaluated the utility of the Centers for Disease Control and Prevention's COVID-19-Associated Hospitalization Surveillance Network (COVID-NET), the COVID-19 Case Surveillance System (CCSS), and 2020 United States (US) Census data to determine demographic representation in the 4 stages of the Adaptive COVID-19 Treatment Trial (ACTT). We compared the cumulative proportion of participants by sex, race, ethnicity, and age enrolled at US ACTT sites, with respective 95% confidence intervals, to the reference data in forest plots. Results: US ACTT sites enrolled 3509 adults hospitalized with COVID-19. When compared with COVID-NET, ACTT enrolled a similar or higher proportion of Hispanic/Latino and White participants depending on the stage, and a similar proportion of African American participants in all stages. In contrast, ACTT enrolled a higher proportion of these groups when compared with US Census and CCSS. The proportion of participants aged ≥65 years was either similar or lower than COVID-NET and higher than CCSS and the US Census. The proportion of females enrolled in ACTT was lower than the proportion of females in the reference datasets. Conclusions: Although surveillance data of hospitalized cases may not be available early in an outbreak, they are a better comparator than US Census data and surveillance of all cases, which may not reflect the population affected and at higher risk of severe disease.

Urea(lly) Got Me: An Uncommon Etiology of Peripartum Liver Failure.

A 23-year-old woman presented 4 days postpartum for agitation and confusion, with initial evaluation consistent with acute fatty liver of pregnancy (AFLP). Later in her course, an amino acid panel was highly suggestive of citrullinemia type 1. She was started on arginine supplementation and glycerol phenylbutyrate and evaluated for a liver transplant. After starting the medication and diet modification, her liver failure resolved, and she was safely discharged. Urea cycle disorders may mimic AFLP with liver enzyme elevation, delirium, and hyperammonemia, but unlike AFLP, patients with urea cycle disorders will typically not recover without dietary modifications and/or medication.

Patient Self-Performed Point-of-Care Ultrasound: Using Communication Technologies to Empower Patient Self-Care.

Point-of-Care ultrasound (POCUS) is an invaluable tool permitting the understanding of critical physiologic and anatomic details wherever and whenever a patient has a medical need. Thus the application of POCUS has dramatically expanded beyond hospitals to become a portable user-friendly technology in a variety of prehospital settings. Traditional thinking holds that a trained user is required to obtain images, greatly handicapping the scale of potential improvements in individual health assessments. However, as the interpretation of ultrasound images can be accomplished remotely by experts, the paradigm wherein experts guide novices to obtain meaningful images that facilitate remote care is being embraced worldwide. The ultimate extension of this concept is for experts to guide patients to image themselves, enabling secondary disease prevention, home-focused care, and self-empowerment of the individual to manage their own health. This paradigm of remotely telementored self-performed ultrasound (RTMSPUS) was first described for supporting health care on the International Space Station. The TeleMentored Ultrasound Supported Medical Interventions (TMUSMI) Research Group has been investigating the utility of this paradigm for terrestrial use. The technique has particular attractiveness in enabling surveillance of lung health during pandemic scenarios. However, the paradigm has tremendous potential to empower and support nearly any medical question poised in a conscious individual with internet connectivity able to follow the directions of a remote expert. Further studies and development are recommended in all areas of acute and chronic health care.