Sepsis endotypes identified by host gene expression across global cohorts.

BACKGROUND: Sepsis from infection is a global health priority and clinical trials have failed to deliver effective therapeutic interventions. To address complicating heterogeneity in sepsis pathobiology, and improve outcomes, promising precision medicine approaches are helping identify disease endotypes, however, they require a more complete definition of sepsis subgroups. METHODS: Here, we use RNA sequencing from peripheral blood to interrogate the host response to sepsis from participants in a global observational study carried out in West Africa, Southeast Asia, and North America (N = 494). RESULTS: We identify four sepsis subtypes differentiated by 28-day mortality. A low mortality immunocompetent group is specified by features that describe the adaptive immune system. In contrast, the three high mortality groups show elevated clinical severity consistent with multiple organ dysfunction. The immunosuppressed group members show signs of a dysfunctional immune response, the acute-inflammation group is set apart by molecular features of the innate immune response, while the immunometabolic group is characterized by metabolic pathways such as heme biosynthesis. CONCLUSIONS: Our analysis reveals details of molecular endotypes in sepsis that support immunotherapeutic interventions and identifies biomarkers that predict outcomes in these groups.

Sepsis is a life-threatening multi-organ failure caused by the body's immune response to infection. Clinical symptoms of sepsis vary from one person to another likely due to differences in host factors, infecting pathogen, and comorbidities. This difference in clinical symptoms may contribute to the lack of effective interventions for sepsis. Therefore, approaches tailored to targeting groups of patients who present similarly are of great interest. This study analysed a large group of sepsis patients with diverse symptoms using laboratory markers and mathematical analysis. We report four patient groups that differ by risk of death and immune response profile. Targeting these defined groups with tailored interventions presents an exciting opportunity to improve the health outcomes of patients with sepsis.

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.

Evidence of Orientia spp. Endemicity among Severe Infectious Disease Cohorts, Uganda.

At 3 severe infection cohort sites in Uganda, Orientia seropositivity was common. We identified 4 seroconversion cases and 1 PCR-positive case. These results provide serologic and molecular support for Orientia spp. circulating in sub-Saharan Africa, possibly expanding its endemic range. Orientia infections could cause severe illness and hospitalizations in this region.

Gene expression signatures in blood from a West African sepsis cohort define host response phenotypes.

Our limited understanding of the pathophysiological mechanisms that operate during sepsis is an obstacle to rational treatment and clinical trial design. There is a critical lack of data from low- and middle-income countries where the sepsis burden is increased which inhibits generalized strategies for therapeutic intervention. Here we perform RNA sequencing of whole blood to investigate longitudinal host response to sepsis in a Ghanaian cohort. Data dimensional reduction reveals dynamic gene expression patterns that describe cell type-specific molecular phenotypes including a dysregulated myeloid compartment shared between sepsis and COVID-19. The gene expression signatures reported here define a landscape of host response to sepsis that supports interventions via targeting immunophenotypes to improve outcomes.

A proof of concept for a targeted enrichment approach to the simultaneous detection and characterization of rickettsial pathogens from clinical specimens.

Infection with either Rickettsia prowazekii or Orientia tsutsugamushi is common, yet diagnostic capabilities are limited due to the short window for positive identification. Until now, although targeted enrichment had been applied to increase sensitivity of sequencing-based detection for various microorganisms, it had not been applied to sequencing of R. prowazekii in clinical samples. Additionally, hybridization-based targeted enrichment strategies had only scarcely been applied to qPCR of any pathogens in clinical samples. Therefore, we tested a targeted enrichment technique as a proof of concept and found that it dramatically reduced the limits of detection of these organisms by both qPCR and high throughput sequencing. The enrichment methodology was first tested in contrived clinical samples with known spiked-in concentrations of R. prowazekii and O. tsutsugamushi DNA. This method was also evaluated using clinical samples, resulting in the simultaneous identification and characterization of O. tsutsugamushi directly from clinical specimens taken from sepsis patients. We demonstrated that the targeted enrichment technique is helpful by lowering the limit of detection, not only when applied to sequencing, but also when applied to qPCR, suggesting the technique could be applied more broadly to include other assays and/or microbes for which there are limited diagnostic or detection modalities.

Two-Year Longitudinal Study Reveals That Long COVID Symptoms Peak and Quality of Life Nadirs at 6-12 Months Postinfection.

Background: Few longitudinal studies available characterize long COVID outcomes out to 24 months, especially in people with nonsevere acute coronavirus disease 2019 (COVID-19). This study sought to prospectively characterize incidence and duration of long COVID symptoms and their association with quality of life (QoL) from 1-24 months after mild-to-moderate COVID-19 using validated tools in a diverse cohort of unvaccinated people infected with SARS-CoV-2 in 2020. Methods: At 1-3, 6, 12, 18, and 24 months post-COVID-19, 70 participants had orthostatic vital signs measured, provided blood, and completed surveys characterizing symptoms, QoL, and return to pre-COVID-19 health and activities using validated tools (FLU-PRO+, Fatigue Severity Scale, Insomnia Severity Index, General Practitioner Assessment of Cognition, Patient Health Questionnaire Depression 8-Item, Generalized Anxiety Disorder 7-Item, 36-Item Short-Form Health Survey, EuroQol EQ-5D-5L). Results: During the study period, 33% of participants experienced long COVID (had not returned to pre-COVID-19 health status and reported at least 1 symptom >90 days postinfection); 8% had not returned to their pre-COVID-19 health status 24 months postinfection. Long COVID symptoms peaked 6 months post-COVID-19, frequently causing activity limitations. Having long COVID was significantly associated with decreased QoL in multiple domains. Frequencies of orthostatic hypotension and tachycardia reflected levels reported in the general population. Within-person weight increased significantly between months 1 and 6. Long COVID was associated with pre-COVID-19 obesity and hyperlipidemia, but not with high-sensitivity C-reactive protein levels 1-3 months postinfection. Conclusions: Long COVID occurs in a significant proportion of unvaccinated people, even if the acute illness was not severe. Long COVID prevalence peaked 6-12 months post-COVID-19, and a small proportion of participants still reported not returning to their pre-COVID-19 health status 24 months post-COVID-19.

sciCSR infers B cell state transition and predicts class-switch recombination dynamics using single-cell transcriptomic data.

Class-switch recombination (CSR) is an integral part of B cell maturation. Here we present sciCSR (pronounced 'scissor', single-cell inference of class-switch recombination), a computational pipeline that analyzes CSR events and dynamics of B cells from single-cell RNA sequencing (scRNA-seq) experiments. Validated on both simulated and real data, sciCSR re-analyzes scRNA-seq alignments to differentiate productive heavy-chain immunoglobulin transcripts from germline 'sterile' transcripts. From a snapshot of B cell scRNA-seq data, a Markov state model is built to infer the dynamics and direction of CSR. Applying sciCSR on severe acute respiratory syndrome coronavirus 2 vaccination time-course scRNA-seq data, we observe that sciCSR predicts, using data from an earlier time point in the collected time-course, the isotype distribution of B cell receptor repertoires of subsequent time points with high accuracy (cosine similarity ~0.9). Using processes specific to B cells, sciCSR identifies transitions that are often missed by conventional RNA velocity analyses and can reveal insights into the dynamics of B cell CSR during immune response.

Implementation of an International Severe Infection Point-of-Care Ultrasound Research Network.

INTRODUCTION: Point-of-care ultrasound (POCUS) is a rapid, readily available, and cost-effective diagnostic and prognostic modality in a range of clinical settings. However, data to support its clinical application are limited. This project's main goal was to assess the effectiveness of standardizing lung ultrasound (LUS) training for sonographers to determine if universal LUS adoption is justified. MATERIALS AND METHODS: We describe the effectiveness of an implementation of a LUS research training program across eight international study sites in Asia, Africa, and North America as part of prospective Coronavirus Disease of 2019 (COVID-19) and sepsis study cohorts (Rapid Assessment of Infection with SONography research network). Within our network, point-of-care LUS was used to longitudinally evaluate radiographic markers of lung injury. POCUS operators were personnel from a variety of backgrounds ranging from research coordinators with no medical background to experienced clinicians. RESULTS: Following a standardized protocol, 49 study sonographers were trained and LUS images from 486 study participants were collected. After training was completed, we compared before and after image qualities for interpretation. The proportion of acceptable images improved at each site between the first 25 scans and the second 25 scans, resulting in 80% or greater acceptance at each study site. CONCLUSIONS: POCUS training and implementation proved feasible in diverse research settings among a range of providers. Standardization across ongoing cohort protocols affords opportunities for increased statistical power and generalizability of results. These results potentially support care delivery by enabling military medics to provide care at the point of injury, as well as aiding frontline clinicians in both austere and highly resourced critical care settings.

Point-of-care biomarker assay for rapid multiplexed detection of CRP and IP-10.

Rapid and accurate measurements of immune protein markers are essential for diagnosis and treatment in all clinical settings. The recent pandemic has revealed a stark need for developing new tools and assays that could be rapidly used in diverse settings and provide useful information to clinicians. Here, we describe the development and test application of a novel one-step CRP/IP-10 duplex assay for the LightDeck platform capable of delivering reproducible and accurate measurements in under eight minutes. We used the optimized assay to measure CRP and IP-10 levels in human blood and serum samples from healthy, SARS-CoV-2 (COVID-19) positive, and influenza-like illness (ILI) presenting patients. Our results agreed with previously published analyte levels and enabled us to make statistically significant comparisons relevant to multiple clinical parameters. Our duplex assay is a simple and powerful tool for aiding prognostic decision-making in diverse settings.

Additive value of lung ultrasound to clinical parameters for prognosticating COVID-19.

The inclusion of LUS with simple, point-of-care clinical parameters have potential to improve COVID-19 prognostication above that from standard clinical care delivery. https://bit.ly/3InePYK.

Long COVID brain fog and muscle pain are associated with longer time to clearance of SARS-CoV-2 RNA from the upper respiratory tract during acute infection.

Introduction: The incidence of long COVID is substantial, even in people with mild to moderate acute COVID-19. The role of early viral kinetics in the subsequent development of long COVID is largely unknown, especially in individuals who were not hospitalized for acute COVID-19. Methods: Seventy-three non-hospitalized adult participants were enrolled within approximately 48 hours of their first positive SARS-CoV-2 RT-PCR test, and mid-turbinate nasal and saliva samples were collected up to 9 times within the first 45 days after enrollment. Samples were assayed for SARS-CoV-2 using RT-PCR and additional SARS-CoV-2 test results were abstracted from the clinical record. Each participant indicated the presence and severity of 49 long COVID symptoms at 1-, 3-, 6-, 12-, and 18-months post-COVID-19 diagnosis. Time from acute COVID-19 illness onset to SARS-CoV-2 RNA clearance greater or less than 28 days was tested for association with the presence or absence of each of 49 long COVID symptoms at 90+ days from acute COVID-19 symptom onset. Results: Self-reported brain fog and muscle pain at 90+ days after acute COVID-19 onset were negatively associated with viral RNA clearance within 28 days of acute COVID-19 onset with adjustment for age, sex, BMI ≥ 25, and COVID vaccination status prior to COVID-19 (brain fog: aRR 0.46, 95% CI 0.22-0.95; muscle pain: aRR 0.28, 95% CI 0.08-0.94). Participants reporting higher severity brain fog or muscle pain at 90+ days after acute COVID-19 onset were less likely to have cleared SARS-CoV-2 RNA within 28 days. The acute viral RNA decay trajectories of participants who did and did not later go on to experience brain fog 90+ days after acute COVID-19 onset were distinct. Discussion: This work indicates that at least two long COVID symptoms - brain fog and muscle pain - at 90+ days from acute COVID-19 onset are specifically associated with prolonged time to clearance of SARS-CoV-2 RNA from the upper respiratory tract during acute COVID-19. This finding provides evidence that delayed immune clearance of SARS-CoV-2 antigen or greater amount or duration of viral antigen burden in the upper respiratory tract during acute COVID-19 are directly linked to long COVID. This work suggests that host-pathogen interactions during the first few weeks after acute COVID-19 onset have an impact on long COVID risk months later.

Screening tools for predicting mortality of adults with suspected sepsis: an international sepsis cohort validation study.

OBJECTIVES: We evaluated the performance of commonly used sepsis screening tools across prospective sepsis cohorts in the USA, Cambodia and Ghana. DESIGN: Prospective cohort studies. SETTING AND PARTICIPANTS: From 2014 to 2021, participants with two or more SIRS (Systemic Inflammatory Response Syndrome) criteria and suspected infection were enrolled in emergency departments and medical wards at hospitals in Cambodia and Ghana and hospitalised participants with suspected infection were enrolled in the USA. Cox proportional hazards regression was performed, and Harrell's C-statistic calculated to determine 28-day mortality prediction performance of the quick Sequential Organ Failure Assessment (qSOFA) score ≥2, SIRS score ≥3, National Early Warning Score (NEWS) ≥5, Modified Early Warning Score (MEWS) ≥5 or Universal Vital Assessment (UVA) score ≥2. Screening tools were compared with baseline risk (age and sex) with the Wald test. RESULTS: The cohorts included 567 participants (42.9% women) including 187 participants from Kumasi, Ghana, 200 participants from Takeo, Cambodia and 180 participants from Durham, North Carolina in the USA. The pooled mortality was 16.4% at 28 days. The mortality prediction accuracy increased from baseline risk with the MEWS (C-statistic: 0.63, 95% CI 0.58 to 0.68; p=0.002), NEWS (C-statistic: 0.68; 95% CI 0.64 to 0.73; p<0.001), qSOFA (C-statistic: 0.70, 95% CI 0.64 to 0.75; p<0.001), UVA score (C-statistic: 0.73, 95% CI 0.69 to 0.78; p<0.001), but not with SIRS (0.60; 95% CI 0.54 to 0.65; p=0.13). Within individual cohorts, only the UVA score in Ghana performed better than baseline risk (C-statistic: 0.77; 95% CI 0.71 to 0.83; p<0.001). CONCLUSIONS: Among the cohorts, MEWS, NEWS, qSOFA and UVA scores performed better than baseline risk, largely driven by accuracy improvements in Ghana, while SIRS scores did not improve prognostication accuracy. Prognostication scores should be validated within the target population prior to clinical use.

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.

Long COVID brain fog and muscle pain are associated with longer time to clearance of SARS-CoV-2 RNA from the upper respiratory tract during acute infection.

The incidence of long COVID is substantial, even in people who did not require hospitalization for acute COVID-19. The pathobiological mechanisms of long COVID and the role of early viral kinetics in its development are largely unknown. Seventy-three non-hospitalized adult participants were enrolled within approximately 48 hours of their first positive SARS-CoV-2 RT-PCR test, and mid-turbinate nasal and saliva samples were collected up to 9 times within the first 45 days after enrollment. Samples were assayed for SARS-CoV-2 using RT-PCR and additional test results were abstracted from the clinical record. Each participant indicated the presence and severity of 49 long- COVID symptoms at 1-, 3-, 6-, 12-, and 18-months post-COVID-19 diagnosis. Time from acute COVID-19 illness onset to SARS-CoV-2 RNA clearance greater or less than 28 days was tested for association with the presence or absence of each of 49 long COVID symptoms at 90+ days from acute COVID-19 symptom onset. Brain fog and muscle pain at 90+ days after acute COVID-19 onset were negatively associated with viral RNA clearance within 28 days of acute COVID-19 onset with adjustment for age, sex, BMI ≥ 25, and COVID vaccination status prior to COVID-19 (brain fog: aRR 0.46, 95% CI 0.22-0.95; muscle pain: aRR 0.28, 95% CI 0.08-0.94). This work indicates that at least two long COVID symptoms - brain fog and muscle pain - at 90+ days from acute COVID-19 onset are specifically associated with longer time to clearance of SARS-CoV-2 RNA from the upper respiratory tract.

Transfusing Convalescent Plasma as Post-Exposure Prophylaxis Against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection: A Double-Blinded, Phase 2 Randomized, Controlled Trial.

BACKGROUND: The efficacy of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) convalescent plasma (CCP) for preventing infection in exposed, uninfected individuals is unknown. CCP might prevent infection when administered before symptoms or laboratory evidence of infection. METHODS: This double-blinded, phase 2 randomized, controlled trial (RCT) compared the efficacy and safety of prophylactic high titer (≥1:320 by Euroimmun ELISA) CCP with standard plasma. Asymptomatic participants aged ≥18 years with close contact exposure to a person with confirmed coronavirus disease 2019 (COVID-19) in the previous 120 hours and negative SARS-CoV-2 test within 24 hours before transfusion were eligible. The primary outcome was new SARS-CoV-2 infection. RESULTS: In total, 180 participants were enrolled; 87 were assigned to CCP and 93 to control plasma, and 170 transfused at 19 sites across the United States from June 2020 to March 2021. Two were excluded for screening SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) positivity. Of the remaining 168 participants, 12/81 (14.8%) CCP and 13/87 (14.9%) control recipients developed SARS-CoV-2 infection; 6 (7.4%) CCP and 7 (8%) control recipients developed COVID-19 (infection with symptoms). There were no COVID-19-related hospitalizations in CCP and 2 in control recipients. Efficacy by restricted mean infection free time (RMIFT) by 28 days for all SARS-CoV-2 infections (25.3 vs 25.2 days; P = .49) and COVID-19 (26.3 vs 25.9 days; P = .35) was similar for both groups. CONCLUSIONS: Administration of high-titer CCP as post-exposure prophylaxis, although appearing safe, did not prevent SARS-CoV-2 infection. CLINICAL TRIALS REGISTRATION: NCT04323800.

Do worsening lung ultrasound scans identify severe COVID-19 trajectories?

Background: While point-of-care ultrasound (POCUS) has been used to track worsening COVID-19 disease it is unclear if there are dynamic differences between severity trajectories. Methods: We studied 12-lung zone protocol scans from 244 participants [with repeat scans obtained in 3 days (N = 114), 7 days (N = 53), and weekly (N = 9)] ≥ 18 years of age hospitalized for COVID-19 pneumonia. Differences in mean lung ultrasound (LUS) scores and percent of lung fields with A-lines over time were compared between peak severity levels (as defined by the WHO clinical progression scale) using linear mixed-effects models. Results: Mean LUS scores were elevated by 0.19 (p = 0.035) and A-lines were present in 14.7% fewer lung fields (p = 0.02) among those with ICU-level or fatal peak illness compared to less severe hospitalized illness, regardless of duration of illness. There were no differences between severity groups in the trajectories of mean LUS score 0.19 (p = 0.66) or percent A-lines (p = 0.40). Discussion: Our results do not support the use of serial LUS scans to monitor COVID-19 disease progression among hospitalized adults.

Distinct blood inflammatory biomarker clusters stratify host phenotypes during the middle phase of COVID-19.

The associations between clinical phenotypes of coronavirus disease 2019 (COVID-19) and the host inflammatory response during the transition from peak illness to convalescence are not yet well understood. Blood plasma samples were collected from 129 adult SARS-CoV-2 positive inpatient and outpatient participants between April 2020 and January 2021, in a multi-center prospective cohort study at 8 military hospitals across the United States. Plasma inflammatory protein biomarkers were measured in samples from 15 to 28 days post symptom onset. Topological Data Analysis (TDA) was used to identify patterns of inflammation, and associations with peak severity (outpatient, hospitalized, ICU admission or death), Charlson Comorbidity Index (CCI), and body mass index (BMI) were evaluated using logistic regression. The study population (n = 129, 33.3% female, median 41.3 years of age) included 77 outpatient, 31 inpatient, 16 ICU-level, and 5 fatal cases. Three distinct inflammatory biomarker clusters were identified and were associated with significant differences in peak disease severity (p < 0.001), age (p < 0.001), BMI (p < 0.001), and CCI (p = 0.001). Host-biomarker profiles stratified a heterogeneous population of COVID-19 patients during the transition from peak illness to convalescence, and these distinct inflammatory patterns were associated with comorbid disease and severe illness due to COVID-19.

Aetiology of hospitalized fever and risk of death at Arua and Mubende tertiary care hospitals in Uganda from August 2019 to August 2020.

BACKGROUND: Epidemiology of febrile illness in Uganda is shifting due to increased HIV treatment access, emerging viruses, and increased surveillance. We investigated the aetiology and outcomes of acute febrile illness in adults presenting to hospital using a standardized testing algorithm of available assays in at Arua and Mubende tertiary care hospitals in Uganda. METHODS: We recruited adults with a ≥ 38.0 °C temperature or history of fever within 48 h of presentation from August 2019 to August 2020. Medical history, demographics, and vital signs were recorded. Testing performed included a complete blood count, renal and liver function, malaria smears, blood culture, and human immunodeficiency virus (HIV). When HIV positive, testing included cryptococcal antigen, CD4 count, and urine lateral flow lipoarabinomannan assay for tuberculosis. Participants were followed during hospitalization and at a 1-month visit. A Cox proportional hazard regression was performed to evaluate for baseline clinical features and risk of death. RESULTS: Of 132 participants, the median age was 33.5 years (IQR 24 to 46) and 58.3% (n = 77) were female. Overall, 73 (55.3%) of 132 had a positive microbiologic result. Among those living with HIV, 31 (68.9%) of 45 had at least one positive assay; 16 (35.6%) had malaria, 14 (31.1%) tuberculosis, and 4 (8.9%) cryptococcal antigenemia. The majority (65.9%) were HIV-negative; 42 (48.3%) of 87 had at least one diagnostic assay positive; 24 (27.6%) had positive malaria smears and 1 was Xpert MTB/RIF Ultra positive. Overall, 16 (12.1%) of 132 died; 9 (56.3%) of 16 were HIV-negative, 6 died after discharge. High respiratory rate (≥ 22 breaths per minute) (hazard ratio [HR] 8.05; 95% CI 1.81 to 35.69) and low (i.e., < 92%) oxygen saturation (HR 4.33; 95% CI 1.38 to 13.61) were identified to be associated with increased risk of death. CONCLUSION: In those with hospitalized fever, malaria and tuberculosis were common causes of febrile illness, but most deaths were non-malarial, and most HIV-negative participants did not have a positive diagnostic result. Those with respiratory failure had a high risk of death.

Post-acute sequelae of SARS-CoV-2 (PASC) impact quality of life at 6, 12 and 18 months post-infection.

Little data exist on long COVID outcomes beyond one year. In a cohort enrolled with mild-moderate acute COVID-19, a wide range of symptoms manifest at 6, 12, and 18 months. Endorsing over 3 symptoms associates with poorer quality of life in 5 domains: physical, social, fatigue, pain, and general health.

Point-of-Care Lung Ultrasound Predicts Severe Disease and Death Due to COVID-19: A Prospective Cohort Study.

The clinical utility of point-of-care lung ultrasound (LUS) among hospitalized patients with COVID-19 is unclear. DESIGN: Prospective cohort study. SETTING: A large tertiary care center in Maryland, between April 2020 and September 2021. PATIENTS: Hospitalized adults (≥ 18 yr old) with positive severe acute respiratory syndrome coronavirus 2 reverse transcriptase-polymerase chain reaction results. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: All patients were scanned using a standardized protocol including 12 lung zones and followed to determine clinical outcomes until hospital discharge and vital status at 28 days. Ultrasounds were independently reviewed for lung and pleural line artifacts and abnormalities, and the mean LUS Score (mLUSS) (ranging from 0 to 3) across lung zones was determined. The primary outcome was time to ICU-level care, defined as high-flow oxygen, noninvasive, or invasive mechanical ventilation, within 28 days of the initial ultrasound. Cox proportional hazards regression models adjusted for age and sex were fit for mLUSS and each ultrasound covariate. A total of 264 participants were enrolled in the study; the median age was 61 years and 114 participants (43.2%) were female. The median mLUSS was 1.0 (interquartile range, 0.5-1.3). Following enrollment, 27 participants (10.0%) went on to require ICU-level care, and 14 (5.3%) subsequently died by 28 days. Each increase in mLUSS at enrollment was associated with disease progression to ICU-level care (adjusted hazard ratio [aHR], 3.61; 95% CI, 1.27-10.2) and 28-day mortality (aHR, 3.10; 95% CI, 1.29-7.50). Pleural line abnormalities were independently associated with disease progression to death (aHR, 20.93; CI, 3.33-131.30). CONCLUSIONS: Participants with a mLUSS greater than or equal to 1 or pleural line changes on LUS had an increased likelihood of subsequent requirement of high-flow oxygen or greater. LUS is a promising tool for assessing risk of COVID-19 progression at the bedside.