Dysregulated naive B cells and de novo autoreactivity in severe COVID-19.

Severe SARS-CoV-2 infection1 has been associated with highly inflammatory immune activation since the earliest days of the COVID-19 pandemic2-5. More recently, these responses have been associated with the emergence of self-reactive antibodies with pathologic potential6-10, although their origins and resolution have remained unclear11. Previously, we and others have identified extrafollicular B cell activation, a pathway associated with the formation of new autoreactive antibodies in chronic autoimmunity12,13, as a dominant feature of severe and critical COVID-19 (refs. 14-18). Here, using single-cell B cell repertoire analysis of patients with mild and severe disease, we identify the expansion of a naive-derived, low-mutation IgG1 population of antibody-secreting cells (ASCs) reflecting features of low selective pressure. These features correlate with progressive, broad, clinically relevant autoreactivity, particularly directed against nuclear antigens and carbamylated proteins, emerging 10-15 days after the onset of symptoms. Detailed analysis of the low-selection compartment shows a high frequency of clonotypes specific for both SARS-CoV-2 and autoantigens, including pathogenic autoantibodies against the glomerular basement membrane. We further identify the contraction of this pathway on recovery, re-establishment of tolerance standards and concomitant loss of acute-derived ASCs irrespective of antigen specificity. However, serological autoreactivity persists in a subset of patients with postacute sequelae, raising important questions as to the contribution of emerging autoreactivity to continuing symptomology on recovery. In summary, this study demonstrates the origins, breadth and resolution of autoreactivity in severe COVID-19, with implications for early intervention and the treatment of patients with post-COVID sequelae.

2024 Focused Update: Guidelines on Use of Corticosteroids in Sepsis, Acute Respiratory Distress Syndrome, and Community-Acquired Pneumonia.

RATIONALE: New evidence is available examining the use of corticosteroids in sepsis, acute respiratory distress syndrome (ARDS) and community-acquired pneumonia (CAP), warranting a focused update of the 2017 guideline on critical illness-related corticosteroid insufficiency. OBJECTIVES: To develop evidence-based recommendations for use of corticosteroids in hospitalized adults and children with sepsis, ARDS, and CAP. PANEL DESIGN: The 22-member panel included diverse representation from medicine, including adult and pediatric intensivists, pulmonologists, endocrinologists, nurses, pharmacists, and clinician-methodologists with expertise in developing evidence-based Clinical Practice Guidelines. We followed Society of Critical Care Medicine conflict of interest policies in all phases of the guideline development, including task force selection and voting. METHODS: After development of five focused Population, Intervention, Control, and Outcomes (PICO) questions, we conducted systematic reviews to identify the best available evidence addressing each question. We evaluated the certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation approach and formulated recommendations using the evidence-to-decision framework. RESULTS: In response to the five PICOs, the panel issued four recommendations addressing the use of corticosteroids in patients with sepsis, ARDS, and CAP. These included a conditional recommendation to administer corticosteroids for patients with septic shock and critically ill patients with ARDS and a strong recommendation for use in hospitalized patients with severe CAP. The panel also recommended against high dose/short duration administration of corticosteroids for septic shock. In response to the final PICO regarding type of corticosteroid molecule in ARDS, the panel was unable to provide specific recommendations addressing corticosteroid molecule, dose, and duration of therapy, based on currently available evidence. CONCLUSIONS: The panel provided updated recommendations based on current evidence to inform clinicians, patients, and other stakeholders on the use of corticosteroids for sepsis, ARDS, and CAP.

Systematized and efficient: organization of critical care in the future.

Since the advent of critical care in the twentieth century, the core elements that are the foundation for critical care systems, namely to care for critically ill and injured patients and to save lives, have evolved enormously. The past half-century has seen dramatic advancements in diagnostic, organ support, and treatment modalities in critical care, with further improvements now needed to achieve personalized critical care of the highest quality. For critical care to be even higher quality in the future, advancements in the following areas are key: the physical ICU space; the people that care for critically ill patients; the equipment and technologies; the information systems and data; and the research systems that impact critically ill patients and families. With acutely and critically ill patients and their families as the absolute focal point, advancements across these areas will hopefully transform care and outcomes over the coming years.

Validation of a Host Response Assay, SeptiCyte LAB, for Discriminating Sepsis from Systemic Inflammatory Response Syndrome in the ICU.

RATIONALE: A molecular test to distinguish between sepsis and systemic inflammation of noninfectious etiology could potentially have clinical utility. OBJECTIVES: This study evaluated the diagnostic performance of a molecular host response assay (SeptiCyte LAB) designed to distinguish between sepsis and noninfectious systemic inflammation in critically ill adults. METHODS: The study employed a prospective, observational, noninterventional design and recruited a heterogeneous cohort of adult critical care patients from seven sites in the United States (n = 249). An additional group of 198 patients, recruited in the large MARS (Molecular Diagnosis and Risk Stratification of Sepsis) consortium trial in the Netherlands ( www.clinicaltrials.gov identifier NCT01905033), was also tested and analyzed, making a grand total of 447 patients in our study. The performance of SeptiCyte LAB was compared with retrospective physician diagnosis by a panel of three experts. MEASUREMENTS AND MAIN RESULTS: In receiver operating characteristic curve analysis, SeptiCyte LAB had an estimated area under the curve of 0.82-0.89 for discriminating sepsis from noninfectious systemic inflammation. The relative likelihood of sepsis versus noninfectious systemic inflammation was found to increase with increasing test score (range, 0-10). In a forward logistic regression analysis, the diagnostic performance of the assay was improved only marginally when used in combination with other clinical and laboratory variables, including procalcitonin. The performance of the assay was not significantly affected by demographic variables, including age, sex, or race/ethnicity. CONCLUSIONS: SeptiCyte LAB appears to be a promising diagnostic tool to complement physician assessment of infection likelihood in critically ill adult patients with systemic inflammation. Clinical trial registered with www.clinicaltrials.gov (NCT01905033 and NCT02127502).

Racial Differences in Accuracy of Predictive Models for High-Flow Nasal Cannula Failure in COVID-19.

OBJECTIVES: To develop and validate machine learning (ML) models to predict high-flow nasal cannula (HFNC) failure in COVID-19, compare their performance to the respiratory rate-oxygenation (ROX) index, and evaluate model accuracy by self-reported race. DESIGN: Retrospective cohort study. SETTING: Four Emory University Hospitals in Atlanta, GA. PATIENTS: Adult patients hospitalized with COVID-19 between March 2020 and April 2022 who received HFNC therapy within 24 hours of ICU admission were included. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Four types of supervised ML models were developed for predicting HFNC failure (defined as intubation or death within 7 d of HFNC initiation), using routine clinical variables from the first 24 hours of ICU admission. Models were trained on the first 60% (n = 594) of admissions and validated on the latter 40% (n = 390) of admissions to simulate prospective implementation. Among 984 patients included, 317 patients (32.2%) developed HFNC failure. eXtreme Gradient Boosting (XGB) model had the highest area under the receiver-operator characteristic curve (AUROC) for predicting HFNC failure (0.707), and was the only model with significantly better performance than the ROX index (AUROC 0.616). XGB model had significantly worse performance in Black patients compared with White patients (AUROC 0.663 vs. 0.808, p = 0.02). Racial differences in the XGB model were reduced and no longer statistically significant when restricted to patients with nonmissing arterial blood gas data, and when XGB model was developed to predict mortality (rather than the composite outcome of failure, which could be influenced by biased clinical decisions for intubation). CONCLUSIONS: Our XGB model had better discrimination for predicting HFNC failure in COVID-19 than the ROX index, but had racial differences in accuracy of predictions. Further studies are needed to understand and mitigate potential sources of biases in clinical ML models and to improve their equitability.

Validation of SeptiCyte RAPID to Discriminate Sepsis from Non-Infectious Systemic Inflammation.

(1) Background: SeptiCyte RAPID is a molecular test for discriminating sepsis from non-infectious systemic inflammation, and for estimating sepsis probabilities. The objective of this study was the clinical validation of SeptiCyte RAPID, based on testing retrospectively banked and prospectively collected patient samples. (2) Methods: The cartridge-based SeptiCyte RAPID test accepts a PAXgene blood RNA sample and provides sample-to-answer processing in ~1 h. The test output (SeptiScore, range 0-15) falls into four interpretation bands, with higher scores indicating higher probabilities of sepsis. Retrospective (N = 356) and prospective (N = 63) samples were tested from adult patients in ICU who either had the systemic inflammatory response syndrome (SIRS), or were suspected of having/diagnosed with sepsis. Patients were clinically evaluated by a panel of three expert physicians blinded to the SeptiCyte test results. Results were interpreted under either the Sepsis-2 or Sepsis-3 framework. (3) Results: Under the Sepsis-2 framework, SeptiCyte RAPID performance for the combined retrospective and prospective cohorts had Areas Under the ROC Curve (AUCs) ranging from 0.82 to 0.85, a negative predictive value of 0.91 (sensitivity 0.94) for SeptiScore Band 1 (score range 0.1-5.0; lowest risk of sepsis), and a positive predictive value of 0.81 (specificity 0.90) for SeptiScore Band 4 (score range 7.4-15; highest risk of sepsis). Performance estimates for the prospective cohort ranged from AUC 0.86-0.95. For physician-adjudicated sepsis cases that were blood culture (+) or blood, urine culture (+)(+), 43/48 (90%) of SeptiCyte scores fell in Bands 3 or 4. In multivariable analysis with up to 14 additional clinical variables, SeptiScore was the most important variable for sepsis diagnosis. A comparable performance was obtained for the majority of patients reanalyzed under the Sepsis-3 definition, although a subgroup of 16 patients was identified that was called septic under Sepsis-2 but not under Sepsis-3. (4) Conclusions: This study validates SeptiCyte RAPID for estimating sepsis probability, under both the Sepsis-2 and Sepsis-3 frameworks, for hospitalized patients on their first day of ICU admission.

Airway TGF-ß1 and oxidant stress in children with severe asthma: association with airflow limitation.

BACKGROUND: TGF-ß1 is thought to play a role in airway remodeling in asthmatic subjects. TGF-ß1 expression might be mediated by an excessive burden of reactive oxygen species and oxidant stress. OBJECTIVE: Given the profound airway oxidant stress we have previously observed in children with severe asthma, we sought to (1) quantify TGF-ß1 protein and mRNA gene expression in the airways of children with mild-to-moderate and severe atopic asthma and (2) determine the relationship of airway TGF-ß1 concentrations to oxidant burden (ie, lipid peroxidation), T(H)2-mediated eosinophilic inflammation, and airflow limitation. METHODS: Bronchoalveolar lavage fluid was collected from 68 atopic children with asthma (severe asthma, n = 28) and 12 atopic adult control subjects. Airway TGF-ß1 expression and activation were assessed in relation to airway IL-13, 8-isoprostane, and malondialdehyde concentrations. The relationship of airway TGF-ß1 expression to airflow limitation in children with asthma was also assessed. RESULTS: Children with severe asthma had higher total airway concentrations of TGF-ß1 that were associated with increased protein and mRNA expression of TGF-ß1 in airway macrophages and an increase in concentrations of the lipid peroxidation biomarkers 8-isoprostanes and malondialdehyde. TGF-ß1 activation was also greater in children with severe asthma and was associated with higher airway 8-isoprostane, malondialdehyde, and IL-13 concentrations. Total airway TGF-ß1 concentrations were further associated with airflow limitation. CONCLUSIONS: Children with severe asthma have increased airway TGF-ß1 expression and activation associated with an increased airway oxidant burden. Oxidant stress might mediate the effects of TGF-ß1 and promote airway remodeling in children with severe asthma.

HIRA: Heart Rate Interval based Rapid Alert score to characterize autonomic dysfunction among patients with sepsis-related acute respiratory failure (ARF).

Objective. To examine whether heart rate interval based rapid alert (HIRA) score derived from a combination model of heart rate variability (HRV) and modified early warning score (MEWS) is a surrogate for the detection of acute respiratory failure (ARF) in critically ill sepsis patients.Approach. Retrospective HRV analysis of sepsis patients admitted to Emory healthcare intensive care unit (ICU) was performed between sepsis-related ARF and sepsis controls without ARF. HRV measures such as time domain, frequency domain, and nonlinear measures were analyzed up to 24 h after patient admission, 1 h before the onset of ARF, and a random event time in the sepsis controls. Statistical significance was computed by the Wilcoxon Rank Sum test. Machine learning algorithms such as eXtreme Gradient Boosting and logistic regression were developed to validate the HIRA score model. The performance of HIRA and early warning score models were evaluated using the area under the receiver operating characteristic (AUROC).Main Results. A total of 89 (ICU) patients with sepsis were included in this retrospective cohort study, of whom 31 (34%) developed sepsis-related ARF and 58 (65%) were sepsis controls without ARF. Time-domain HRV for Electrocardiogram (ECG) Beat-to-Beat RR intervals strongly distinguished ARF patients from controls. HRV measures for nonlinear and frequency domains were significantly altered (p< 0.05) among ARF compared to controls. The HIRA score AUC: 0.93; 95% confidence interval (CI): 0.88-0.98) showed a higher predictive ability to detect ARF when compared to MEWS (AUC: 0.71; 95% CI: 0.50-0.90).Significance. HRV was significantly impaired across patients who developed ARF when compared to controls. The HIRA score uses non-invasively derived HRV and may be used to inform diagnostic and therapeutic decisions regarding the severity of sepsis and earlier identification of the need for mechanical ventilation.

Study on the relationship between selenium and cadmium in diseased human lungs.

Cadmium (Cd) is a toxic environmental metal that interacts with selenium (Se) and contributes to many lung diseases. Humans have widespread exposures to Cd through diet and cigarette smoking, and studies in rodent models show that Se can protect against Cd toxicities. We sought to identify whether an antagonistic relationship existed between Se and Cd burdens and determine whether this relationship may associate with metabolic variation within human lungs. We performed metabolomics of 31 human lungs, including 25 with end-stage lung disease due to idiopathic pulmonary fibrosis, cystic fibrosis, chronic obstructive lung disease (COPD)/emphysema and other causes, and 6 non-diseased lungs. Results showed pathway associations with Cd including amino acid, lipid and energy-related pathways. Metabolic pathways varying with Se had considerable overlap with these pathways. Hierarchical cluster analysis (HCA) of individuals according to metabolites associated with Cd showed partial separation of disease types, with COPD/emphysema in the cluster with highest Cd, and non-diseased lungs in the cluster with the lowest Cd. When compared to HCA of metabolites associated with Se, the results showed that the cluster containing COPD/emphysema had the lowest Se, and the non-diseased lungs had the highest Se. A greater number of pathway associations occurred for Cd to Se ratio than either Cd or Se alone, indicating that metabolic patterns were more dependent on Cd to Se ratio than on either alone. Network analysis of interactions of Cd and Se showed network centrality was associated with pathways linked to polyunsaturated fatty acids involved in inflammatory signaling. Overall, the data show that metabolic pathway responses in human lung vary with Cd and Se in a pattern suggesting that Se is antagonistic to Cd toxicity in humans.

Early identification of patients at risk of acute lung injury: evaluation of lung injury prediction score in a multicenter cohort study.

RATIONALE: Accurate, early identification of patients at risk for developing acute lung injury (ALI) provides the opportunity to test and implement secondary prevention strategies. OBJECTIVES: To determine the frequency and outcome of ALI development in patients at risk and validate a lung injury prediction score (LIPS). METHODS: In this prospective multicenter observational cohort study, predisposing conditions and risk modifiers predictive of ALI development were identified from routine clinical data available during initial evaluation. The discrimination of the model was assessed with area under receiver operating curve (AUC). The risk of death from ALI was determined after adjustment for severity of illness and predisposing conditions. MEASUREMENTS AND MAIN RESULTS: Twenty-two hospitals enrolled 5,584 patients at risk. ALI developed a median of 2 (interquartile range 1-4) days after initial evaluation in 377 (6.8%; 148 ALI-only, 229 adult respiratory distress syndrome) patients. The frequency of ALI varied according to predisposing conditions (from 3% in pancreatitis to 26% after smoke inhalation). LIPS discriminated patients who developed ALI from those who did not with an AUC of 0.80 (95% confidence interval, 0.78-0.82). When adjusted for severity of illness and predisposing conditions, development of ALI increased the risk of in-hospital death (odds ratio, 4.1; 95% confidence interval, 2.9-5.7). CONCLUSIONS: ALI occurrence varies according to predisposing conditions and carries an independently poor prognosis. Using routinely available clinical data, LIPS identifies patients at high risk for ALI early in the course of their illness. This model will alert clinicians about the risk of ALI and facilitate testing and implementation of ALI prevention strategies. Clinical trial registered with www.clinicaltrials.gov (NCT00889772).

Serial Measurements of Protein Biomarkers in Sepsis-Induced Acute Respiratory Distress Syndrome.

The role of early, serial measurements of protein biomarkers in sepsis-induced acute respiratory distress syndrome (ARDS) is not clear. OBJECTIVES: To determine the differences in soluble receptor for advanced glycation end-products (sRAGEs), angiopoietin-2, and surfactant protein-D (SP-D) levels and their changes over time between sepsis patients with and without ARDS. DESIGN SETTING AND PARTICIPANTS: Prospective observational cohort study of adult patients admitted to the medical ICU at Grady Memorial Hospital within 72 hours of sepsis diagnosis. MAIN OUTCOMES AND MEASURES: Plasma sRAGE, angiopoietin-2, and SP-D levels were measured for 3 consecutive days after enrollment. The primary outcome was ARDS development, and the secondary outcome of 28-day mortality. The biomarker levels and their changes over time were compared between ARDS and non-ARDS patients and between nonsurvivors and survivors. RESULTS: We enrolled 111 patients, and 21 patients (18.9%) developed ARDS. The three biomarker levels were not significantly different between ARDS and non-ARDS patients on all 3 days of measurement. Nonsurvivors had higher levels of all three biomarkers than did survivors on multiple days. The changes of the biomarker levels over time were not different between the outcome groups. Logistic regression analyses showed association between day 1 SP-D level and mortality (odds ratio, 1.52; 95% CI, 1.03-2.24; p = 0.03), and generalized estimating equation analyses showed association between angiopoietin-2 levels and mortality (estimate 0.0002; se 0.0001; p = 0.04). CONCLUSIONS AND RELEVANCE: Among critically ill patients with sepsis, sRAGE, angiopoietin-2, and SP-D levels were not significantly different between ARDS and non-ARDS patients but were higher in nonsurvivors compared with survivors. The trend toward higher levels of sRAGE and SP-D, but not of angiopoietin-2, in ARDS patients may indicate the importance of epithelial injury in sepsis-induced ARDS. Changes of the biomarker levels over time were not different between the outcome groups.

Machine Learning Approaches to Identify Discriminative Signatures of Volatile Organic Compounds (VOCs) from Bacteria and Fungi Using SPME-DART-MS.

Point-of-care screening tools are essential to expedite patient care and decrease reliance on slow diagnostic tools (e.g., microbial cultures) to identify pathogens and their associated antibiotic resistance. Analysis of volatile organic compounds (VOC) emitted from biological media has seen increased attention in recent years as a potential non-invasive diagnostic procedure. This work explores the use of solid phase micro-extraction (SPME) and ambient plasma ionization mass spectrometry (MS) to rapidly acquire VOC signatures of bacteria and fungi. The MS spectrum of each pathogen goes through a preprocessing and feature extraction pipeline. Various supervised and unsupervised machine learning (ML) classification algorithms are trained and evaluated on the extracted feature set. These are able to classify the type of pathogen as bacteria or fungi with high accuracy, while marked progress is also made in identifying specific strains of bacteria. This study presents a new approach for the identification of pathogens from VOC signatures collected using SPME and ambient ionization MS by training classifiers on just a few samples of data. This ambient plasma ionization and ML approach is robust, rapid, precise, and can potentially be used as a non-invasive clinical diagnostic tool for point-of-care applications.

Severe acute respiratory syndrome coronavirus 2 vaccine breakthrough infections: A single metro-based testing network experience.

Objectives: Understanding the incidence and characteristics that influence severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine breakthrough infections (VBIs) is imperative for developing public health policies to mitigate the coronavirus disease of 2019 (COVID-19) pandemic. We examined these factors and post-vaccination mitigation practices in individuals partially and fully vaccinated against SARS-CoV-2. Materials and methods: Adults >18 years old were voluntarily enrolled from a single metro-based SARS-CoV-2 testing network from January to July 2021. Participants were categorized as asymptomatic or symptomatic, and as unvaccinated, partially vaccinated, or fully vaccinated. All participants had confirmed SARS-CoV-2 infection based on standard of care (SOC) testing with nasopharyngeal swabs. Variant analysis by rRT-PCR was performed in a subset of time-matched vaccinated and unvaccinated individuals. A subgroup of partially and fully vaccinated individuals with a positive SARS-CoV-2 rRT-PCR was contacted to assess disease severity and post-vaccination mitigation practices. Results: Participants (n = 1,317) voluntarily underwent testing for SARS-CoV-2 during the enrollment period. A total of 29.5% of the population received at least one SARS-CoV-2 vaccine (n = 389), 12.8% partially vaccinated (n = 169); 16.1% fully vaccinated (n = 213). A total of 21.3% of partially vaccinated individuals tested positive (n = 36) and 9.4% of fully vaccinated individuals tested positive (n = 20) for SARS-CoV-2. Pfizer/BioNTech mRNA-1273 was the predominant vaccine received (1st dose = 66.8%, 2nd dose = 67.9%). Chronic liver disease and immunosuppression were more prevalent in the vaccinated (partially/fully) group compared to the unvaccinated group (p = 0.003, p = 0.021, respectively). There were more asymptomatic individuals in the vaccinated group compared to the unvaccinated group [n = 6 (10.7%), n = 16 (4.1%), p = 0.045]. CT values were lower for the unvaccinated group (median 24.3, IQR 19.1-30.5) compared to the vaccinated group (29.4, 22.0-33.7, p = 0.004). In the vaccinated group (n = 56), 18 participants were successfully contacted, 7 were lost to follow-up, and 2 were deceased. A total of 50% (n = 9) required hospitalization due to COVID-19 illness. Adherence to nationally endorsed mitigation strategies varied post-vaccination. Conclusion: The incidence of SARS-CoV-2 infection at this center was 21.3% in the partially vaccinated group and 9.4% in the fully vaccinated group. Chronic liver disease and immunosuppression were more prevalent in the vaccinated SARS-CoV-2 positive group, suggesting that these may be risk factors for VBIs. Partially and fully vaccinated individuals had a higher incidence of asymptomatic SARS-CoV-2 and higher CT values compared to unvaccinated SARS-CoV-2 positive individuals.

Clinical evaluation of the Diagnostic Analyzer for Selective Hybridization (DASH): A point-of-care PCR test for rapid detection of SARS-CoV-2 infection.

BACKGROUND: An ideal test for COVID-19 would combine the sensitivity of laboratory-based PCR with the speed and ease of use of point-of-care (POC) or home-based rapid antigen testing. We evaluated clinical performance of the Diagnostic Analyzer for Selective Hybridization (DASH) SARS-CoV-2 POC rapid PCR test. METHODS: We conducted a cross-sectional study of adults with and without symptoms of COVID-19 at four clinical sites where we collected two bilateral anterior nasal swabs and information on COVID-19 symptoms, vaccination, and exposure. One swab was tested with the DASH SARS-CoV-2 POC PCR and the second in a central laboratory using Cepheid Xpert Xpress SARS-CoV-2 PCR. We assessed test concordance and calculated sensitivity, specificity, negative and positive predictive values using Xpert as the "gold standard". RESULTS: We enrolled 315 and analyzed 313 participants with median age 42 years; 65% were female, 62% symptomatic, 75% had received ≥2 doses of mRNA COVID-19 vaccine, and 16% currently SARS-CoV-2 positive. There were concordant results for 307 tests indicating an overall agreement for DASH of 0.98 [95% CI 0.96, 0.99] compared to Xpert. DASH performed at 0.96 [95% CI 0.86, 1.00] sensitivity and 0.98 [95% CI 0.96, 1.00] specificity, with a positive predictive value of 0.85 [95% CI 0.73, 0.96] and negative predictive value of 0.996 [95% CI 0.99, 1.00]. The six discordant tests between DASH and Xpert all had high Ct values (>30) on the respective positive assay. DASH and Xpert Ct values were highly correlated (R = 0.89 [95% CI 0.81, 0.94]). CONCLUSIONS: DASH POC SARS-CoV-2 PCR was accurate, easy to use, and provided fast results (approximately 15 minutes) in real-life clinical settings with an overall performance similar to an EUA-approved laboratory-based PCR.

Clinical evaluation of the Diagnostic Analyzer for Selective Hybridization (DASH): a point-of-care PCR test for rapid detection of SARS-CoV-2 infection.

BACKGROUND: Rapid and accurate testing for SARS-CoV-2 is an essential tool in the medical and public health response to the COVID-19 pandemic. An ideal test for COVID-19 would combine the sensitivity of laboratory-based PCR combined with the speed and ease of use of point-of-care (POC) or home-based rapid antigen testing. METHODS: To evaluate the performance of the Diagnostic Analyzer for Selective Hybridization (DASH) SARS-CoV-2 POC PCR (sample insertion to result time of 16 minutes), we conducted a cross-sectional study of adults with and without symptoms of COVID-19 at four clinical sites. We collected two bilateral anterior nasal swabs from each participant and information on COVID-19 symptoms, vaccination, and exposure. One swab was tested with the DASH SARS-CoV-2 POC PCR and the second in a central laboratory using Cepheid Xpert Xpress SARS-CoV-2 PCR. We assessed test concordance and calculated sensitivity, specificity, negative and positive predictive values using Xpert as the "gold standard." RESULTS: We enrolled 315 and analyzed 313 participants with median age 42 years; 65% were female, 62% symptomatic, 75% had received ≥2 doses of mRNA COVID-19 vaccine, and 16% currently COVID-19 positive. There were concordant results for 307 tests indicating an overall agreement for DASH of 0.98 [95% CI 0.96, 0.99] compared to Xpert. DASH performed at 0.96 [95% CI 0.86, 1.00] sensitivity and 0.98 [95% CI 0.96, 1.00] specificity, with a positive predictive value of 0.85 [95% CI 0.73, 0.96] and negative predictive value of 0.996 [95% CI 0.99, 1.00]. The six discordant tests between DASH and Xpert all had high Ct values (>30) on the respective positive assay. DASH and Xpert Ct values were highly correlated (R=0.89 [95% CI 0.81, 0.94]). CONCLUSIONS: DASH POC SARS-CoV-2 PCR was accurate, easy to use, and provided fast results in real-life clinical settings with an overall performance similar to an EUA-approved laboratory-based PCR. Its compact design and ease of use are optimal for a variety of healthcare, and potentially community settings, including areas with lack of access to central laboratory-based PCR testing. SUMMARY: DASH is an accurate, easy to use, and fast point-of-care test with applications for diagnosis and screening of SARS-CoV-2 infection.

Pulmonary and Critical Care Considerations for e-Cigarette, or Vaping, Product Use-Associated Lung Injury.

BACKGROUND: In 2019, the United States experienced a nationwide outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI). More than one-half of these patients required admission to an ICU. RESEARCH QUESTION: What are the recent literature and expert opinions which inform the diagnosis and management of patients with critical illness with EVALI? STUDY DESIGN AND METHODS: To synthesize information critical to pulmonary/critical care specialists in the care of patients with EVALI, this study examined data available from patients hospitalized with EVALI between August 2019 and January 2020; reviewed the clinical course and critical care experience with those patients admitted to the ICU; and compiled opinion of national experts. RESULTS: Of the 2,708 patients with confirmed or probable EVALI requiring hospitalization as of January 21, 2020, a total of 1,604 (59.2%) had data available on ICU admission; of these, 705 (44.0%) were admitted to the ICU and are included in this analysis. The majority of ICU patients required respiratory support (88.5%) and in severe cases required intubation (36.1%) or extracorporeal membrane oxygenation (6.7%). The majority (93.0%) of these ICU patients survived to discharge. Review of the clinical course and expert opinion provided insight into: imaging; considerations for bronchoscopy; medical treatment, including use of empiric antibiotics, antiviral agents, and corticosteroids; respiratory support, including considerations for intubation, positioning maneuvers, and extracorporeal membrane oxygenation; and patient outcomes. INTERPRETATION: Review of the clinical course of patients with EVALI requiring ICU admission and compilation of expert opinion provided critical insight into pulmonary/critical care-specific considerations for this patient population. Because a large proportion of patients hospitalized with EVALI required ICU admission, it is important to remain prepared to care for patients with EVALI.

Don't forget about human factors: Lessons learned from COVID-19 point-of-care testing.

During the COVID-19 pandemic, the development of point-of-care (POC) diagnostic testing accelerated in an unparalleled fashion. As a result, there has been an increased need for accurate, robust, and easy-to-use POC testing in a variety of non-traditional settings (i.e., pharmacies, drive-thru sites, schools). While stakeholders often express the desire for POC technologies that are "as simple as digital pregnancy tests," there is little discussion of what this means in regards to device design, development, and assessment. The design of POC technologies and systems should take into account the capabilities and limitations of the users and their environments. Such "human factors" are important tenets that can help technology developers create POC technologies that are effective for end-users in a multitude of settings. Here, we review the core principles of human factors and discuss lessons learned during the evaluation process of SARS-CoV-2 POC testing.

The impact of comorbid [corrected] conditions on critical illness.

OBJECTIVE: To review the current knowledge of common comorbidities in the intensive care unit, including diabetes mellitus, chronic obstructive pulmonary disease, cancer, end-stage renal disease, end-stage liver disease, HIV infection, and obesity, with specific attention to epidemiology, contribution to diseases and outcomes, and the impact on treatments in these patients. DATA SOURCE: Review of the relevant medical literature for specific common comorbidities in the critically ill. RESULTS: Critically ill patients are admitted to the intensive care unit for various reasons, and often the admission diagnosis is accompanied by a chronic comorbidity. Chronic comorbid conditions commonly seen in critically ill patients may influence the decision to provide intensive care unit care, decisions regarding types and intensity of intensive care unit treatment options, and outcomes. The presence of comorbid conditions may predispose patients to specific complications or forms of organ dysfunction. The impact of specific comorbidities varies among critically ill medical, surgical, and other populations, and outcomes associated with certain comorbidities have changed over time. Specifically, outcomes for patients with cancer and HIV have improved, likely related to advances in therapy. Overall, the negative impact of chronic comorbidity on survival in critical illness may be primarily influenced by the degree of organ dysfunction or the cumulative severity of multiple comorbidities. CONCLUSION: Chronic comorbid conditions are common in critically ill patients. Both the acute illness and the chronic conditions influence prognosis and optimal care delivery for these patients, particularly for adverse outcomes and complications influenced by comorbidities. Further work is needed to fully determine the individual and combined impact of chronic comorbidities on intensive care unit outcomes.