Using a targeted metabolomics approach to explore differences in ARDS associated with COVID-19 compared to ARDS caused by H1N1 influenza and bacterial pneumonia.

RATIONALE: Acute respiratory distress syndrome (ARDS) is a life-threatening critical care syndrome commonly associated with infections such as COVID-19, influenza, and bacterial pneumonia. Ongoing research aims to improve our understanding of ARDS, including its molecular mechanisms, individualized treatment options, and potential interventions to reduce inflammation and promote lung repair. OBJECTIVE: To map and compare metabolic phenotypes of different infectious causes of ARDS to better understand the metabolic pathways involved in the underlying pathogenesis. METHODS: We analyzed metabolic phenotypes of 3 ARDS cohorts caused by COVID-19, H1N1 influenza, and bacterial pneumonia compared to non-ARDS COVID-19-infected patients and ICU-ventilated controls. Targeted metabolomics was performed on plasma samples from a total of 150 patients using quantitative LC-MS/MS and DI-MS/MS analytical platforms. RESULTS: Distinct metabolic phenotypes were detected between different infectious causes of ARDS. There were metabolomics differences between ARDSs associated with COVID-19 and H1N1, which include metabolic pathways involving taurine and hypotaurine, pyruvate, TCA cycle metabolites, lysine, and glycerophospholipids. ARDSs associated with bacterial pneumonia and COVID-19 differed in the metabolism of D-glutamine and D-glutamate, arginine, proline, histidine, and pyruvate. The metabolic profile of COVID-19 ARDS (C19/A) patients admitted to the ICU differed from COVID-19 pneumonia (C19/P) patients who were not admitted to the ICU in metabolisms of phenylalanine, tryptophan, lysine, and tyrosine. Metabolomics analysis revealed significant differences between C19/A, H1N1/A, and PNA/A vs ICU-ventilated controls, reflecting potentially different disease mechanisms. CONCLUSION: Different metabolic phenotypes characterize ARDS associated with different viral and bacterial infections.

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.

Proteomic Evolution from Acute to Post-COVID-19 Conditions.

Many COVID-19 survivors have post-COVID-19 conditions, and females are at a higher risk. We sought to determine (1) how protein levels change from acute to post-COVID-19 conditions, (2) whether females have a plasma protein signature different from that of males, and (3) which biological pathways are associated with COVID-19 when compared to restrictive lung disease. We measured protein levels in 74 patients on the day of admission and at 3 and 6 months after diagnosis. We determined protein concentrations by multiple reaction monitoring (MRM) using a panel of 269 heavy-labeled peptides. The predicted forced vital capacity (FVC) and diffusing capacity of the lungs for carbon monoxide (DLCO) were measured by routine pulmonary function testing. Proteins associated with six key lipid-related pathways increased from admission to 3 and 6 months; conversely, proteins related to innate immune responses and vasoconstriction-related proteins decreased. Multiple biological functions were regulated differentially between females and males. Concentrations of eight proteins were associated with FVC, %, and they together had c-statistics of 0.751 (CI:0.732-0.779); similarly, concentrations of five proteins had c-statistics of 0.707 (CI:0.676-0.737) for DLCO, %. Lipid biology may drive evolution from acute to post-COVID-19 conditions, while activation of innate immunity and vascular regulation pathways decreased over that period. (ProteomeXchange identifiers: PXD041762, PXD029437).

Distorted correlations among censored data: causes, effects, and correction.

Data censoring occurs when researchers do not know precise values of data points (e.g., age is 55+ or concentration ≤ .001). Censoring is frequent within psychology but typically unrecognized outside of longitudinal studies. We describe five circumstances when censoring may occur, demonstrate censoring distorts correlations, and discuss how censoring can create spurious factors. Next, we explain how to use R package lava to calculate maximum likelihood estimates (Holst and Budtz-Jørgensen Computational Statistics, 28(4), 1385-1452, 2013) of correlations between uncensored variables based upon censored variables. Previous research demonstrated these estimates were more accurate than Muthén's (1984) estimate for one particular model, but no research has systematically examined their accuracy. We therefore conducted a simulation study exploring the effects of the correlation, sample size, and censoring on point and interval estimates of correlations. Based upon 80 cells in which low values of normally distributed variables were censored, we recommend the constrained regression model with Wald confidence intervals. These methods were precise and unbiased unless both variables had 70% censoring and the correlation was large and negative (e.g., -.9), in which case estimates were closer to -1 than they should be. Opposite results would occur if low values of one variable and high values of the other were censored: Estimates would be precise and unbiased unless censoring was extreme and correlations were large and positive. To estimate large correlations accurately, we recommend researchers reduce censoring by using longer longitudinal studies, using scales with more response options, and matching measures to populations to reduce floor and ceiling effects.

Impact of the COVID-19 pandemic on non-COVID-19 community-acquired pneumonia: a retrospective cohort study.

BACKGROUND: The COVID-19 pandemic could impact frequency and mortality of non-COVID-19 community-acquired pneumonia (CAP). Changes in frequency, patient mix, treatment and organ dysfunction could cascade together to increase mortality of CAP during compared with pre-COVID-19. METHODS: Hospitalised CAP patients at St. Paul's Hospital, Vancouver, Canada pre-COVID-19 (fiscal years 2018/2019 and 2019/2020) and during COVID-19 pandemic (2020/2021 and 2021/2022) were evaluated. RESULTS: In 5219 CAP patients, there was no significant difference prepandemic versus during pandemic in mean age, gender and Charlson Comorbidity Score. However, hospital mortality increased significantly from pre-COVID-19 versus during COVID-19 (7.5% vs 12.1% respectively, (95% CI for difference: 3.0% to 6.3%), p<0.001), a 61% relative increase, coincident with increases in ICU admission (18.3% vs 25.5%, respectively, (95% CI for difference: 5.0% to 9.5%) p<0.001, 39% relative increase) and ventilation (12.7% vs 17.5%, respectively, (95% CI for difference: 2.8% to 6.7%) p<0.001, 38% relative increase). Results remained the same after regression adjustment for age, sex and Charlson score. CAP hospital admissions decreased 27% from pre-COVID-19 (n=1349 and 1433, 2018/2019 and 2019/2020, respectively) versus the first COVID-19 pandemic year (n=1047 in 2020/2021) then rose to prepandemic number (n=1390 in 2021/2022). During prepandemic years, CAP admissions peaked in winter; during COVID-19, the CAP admissions peaked every 6 months. CONCLUSIONS AND RELEVANCE: This is the first study to show that the COVID-19 pandemic was associated with increases in hospital mortality, ICU admission and invasive mechanical ventilation rates of non-COVID-19 CAP and a transient, 1-year frequency decrease. There was no winter seasonality of CAP during the COVID-19 pandemic era. These novel findings could be used to guide future pandemic planning for CAP hospital care.

Purity is not a distinct moral domain.

Purity violations overlap with other moral domains. They are not uniquely characterized by hypothesized markers of purity - the witness's emotion of disgust, taint to perpetrator's soul, or the diminished role of intention in moral judgment. Thus, Fitouchi et al.'s proposition that puritanical morality (a subset of violations in the purity domain) is part of cooperation-based morality is an important advance.

Identifying molecular phenotypes in sepsis: an analysis of two prospective observational cohorts and secondary analysis of two randomised controlled trials.

BACKGROUND: In sepsis and acute respiratory distress syndrome (ARDS), heterogeneity has contributed to difficulty identifying effective pharmacotherapies. In ARDS, two molecular phenotypes (hypoinflammatory and hyperinflammatory) have consistently been identified, with divergent outcomes and treatment responses. In this study, we sought to derive molecular phenotypes in critically ill adults with sepsis, determine their overlap with previous ARDS phenotypes, and evaluate whether they respond differently to treatment in completed sepsis trials. METHODS: We used clinical data and plasma biomarkers from two prospective sepsis cohorts, the Validating Acute Lung Injury biomarkers for Diagnosis (VALID) study (N=1140) and the Early Assessment of Renal and Lung Injury (EARLI) study (N=818), in latent class analysis (LCA) to identify the optimal number of classes in each cohort independently. We used validated models trained to classify ARDS phenotypes to evaluate concordance of sepsis and ARDS phenotypes. We applied these models retrospectively to the previously published Prospective Recombinant Human Activated Protein C Worldwide Evaluation in Severe Sepsis and Septic Shock (PROWESS-SHOCK) trial and Vasopressin and Septic Shock Trial (VASST) to assign phenotypes and evaluate heterogeneity of treatment effect. FINDINGS: A two-class model best fit both VALID and EARLI (p<0·0001). In VALID, 804 (70·5%) of the 1140 patients were classified as hypoinflammatory and 336 (29·5%) as hyperinflammatory; in EARLI, 530 (64·8%) of 818 were hypoinflammatory and 288 (35·2%) hyperinflammatory. We observed higher plasma pro-inflammatory cytokines, more vasopressor use, more bacteraemia, lower protein C, and higher mortality in the hyperinflammatory than in the hypoinflammatory phenotype (p<0·0001 for all). Classifier models indicated strong concordance between sepsis phenotypes and previously identified ARDS phenotypes (area under the curve 0·87-0·96, depending on the model). Findings were similar excluding participants with both sepsis and ARDS. In PROWESS-SHOCK, 1142 (68·0%) of 1680 patients had the hypoinflammatory phenotype and 538 (32·0%) had the hyperinflammatory phenotype, and response to activated protein C differed by phenotype (p=0·0043). In VASST, phenotype proportions were similar to other cohorts; however, no treatment interaction with the type of vasopressor was observed (p=0·72). INTERPRETATION: Molecular phenotypes previously identified in ARDS are also identifiable in multiple sepsis cohorts and respond differently to activated protein C. Molecular phenotypes could represent a treatable trait in critical illness beyond the patient's syndromic diagnosis. FUNDING: US National Institutes of Health.

Outcomes and characteristics of patients hospitalized for COVID-19 in British Columbia, Ontario and Quebec during the Omicron wave.

BACKGROUND: Omicron is the current predominant variant of concern of SARS-CoV-2. We hypothesized that vaccination alters outcomes of patients hospitalized with COVID-19 during the Omicron wave and that these patients have different characteristics and outcomes than in previous waves. METHODS: This is a substudy of the Host Response Mediators in Coronavirus (COVID-19) Infection (ARBs CORONA I) trial, which included adults admitted to hospital with acute COVID-19 up to July 2022 from 9 hospitals in British Columbia, Ontario and Quebec. We excluded emergency department visits without hospital admission, readmissions and admissions for another reason. Using adjusted regression analysis, we compared mortality and organ dysfunction between vaccinated (≥ 2 doses) and unvaccinated patients during the Omicron wave, as well as between all patients in the Omicron and first 3 waves of the COVID-19 pandemic. RESULTS: During the Omicron wave, 28-day mortality was significantly lower in vaccinated (n = 19/237) than unvaccinated hospitalized patients (n = 12/127) (adjusted odds ratio [OR] 0.36, 95% confidence interval [CI] 0.15-0.89); vaccinated patients had lower risk of admission to the intensive care unit, invasive ventilation and acute respiratory distress syndrome and shorter hospital length of stay. Patients hospitalized during the Omicron wave had more comorbidities than in previous waves, and lower 28-day mortality than in waves 1 and 2 (adjusted OR 0.38, 95% CI 0.24-0.59; and 0.42, 95% CI 0.26-0.65) but not wave 3 (adjusted OR 0.81, 95% CI 0.43-1.51) and had less organ dysfunction than in the first 2 waves. INTERPRETATION: Patients who were at least double vaccinated had lower mortality than unvaccinated patients hospitalized during the Omicron wave. Patients hospitalized during the Omicron wave had more chronic disease and lower mortality than in the first 2 waves, but not wave 3. Changes in vaccination, treatments and predominant SARS-CoV-2 variant may have decreased mortality in patients hospitalized during the Omicron wave.

Use of latent class analysis and patient reported outcome measures to identify distinct long COVID phenotypes: A longitudinal cohort study.

OBJECTIVES: We sought to 1) identify long COVID phenotypes based on patient reported outcome measures (PROMs) and 2) determine whether the phenotypes were associated with quality of life (QoL) and/or lung function. METHODS: This was a longitudinal cohort study of hospitalized and non-hospitalized patients from March 2020 to January 2022 that was conducted across 4 Post-COVID Recovery Clinics in British Columbia, Canada. Latent class analysis was used to identify long COVID phenotypes using baseline PROMs (fatigue, dyspnea, cough, anxiety, depression, and post-traumatic stress disorder). We then explored the association between the phenotypes and QoL (using the EuroQoL 5 dimensions visual analogue scale [EQ5D VAS]) and lung function (using the diffusing capacity of the lung for carbon monoxide [DLCO]). RESULTS: There were 1,344 patients enrolled in the study (mean age 51 ±15 years; 780 [58%] were females; 769 (57%) were of a non-White race). Three distinct long COVID phenotypes were identified: Class 1) fatigue and dyspnea, Class 2) anxiety and depression, and Class 3) fatigue, dyspnea, anxiety, and depression. Class 3 had a significantly lower EQ5D VAS at 3 (50±19) and 6 months (54 ± 22) compared to Classes 1 and 2 (p<0.001). The EQ5D VAS significantly improved between 3 and 6 months for Class 1 (median difference of 6.0 [95% CI, 4.0 to 8.0]) and Class 3 (median difference of 5.0 [95% CI, 0 to 8.5]). There were no differences in DLCO between the classes. CONCLUSIONS: There were 3 distinct long COVID phenotypes with different outcomes in QoL between 3 and 6 months after symptom onset. These phenotypes suggest that long COVID is a heterogeneous condition with distinct subpopulations who may have different outcomes and warrant tailored therapeutic approaches.

Single institution experience with death by neurological criteria/brain death guideline adherence.

OBJECTIVE: To determine the effect on adherence to an institutional death by neurological criteria/brain death (DNC/BD) policy of implementation of a standardized DNC/BD checklist in the electronic medical record (EMR). METHODS: The retrospective study cohort included all patients admitted to our institution who were declared dead by neurologic criteria determined by ICD code (G93.82) between June 2015 and October 2019. Two investigators independently reviewed each case for adherence with institutional policy, and agreement was assessed using unweighted kappa statistics. Patient data and adherence to institutional policy before and after implementation of a standardized DNC/BD checklist were compared. RESULTS: There were 66 patients identified by the initial search and 38 were included in the final analysis, with 19 cases in both the pre- and post- checklist periods. There were no significant differences in age, cause of DNC/BD, time to DNC/BD determination, potential toxic, metabolic, physiologic confounders, or use of ancillary testing. The pre-checklist period adherence was 47.4% (n = 9/19) versus 94.6% (n = 18/19; p = 0.001) in the post-checklist EMR DNC/BD period. CONCLUSION: Implementation of a standardized EMR checklist substantially improved DNC/BD policy adherence in our institution. CLASSIFICATION OF EVIDENCE: This study provides Class IV evidence on the use of standardized EMR checklist to improve death by neurologic criteria/brain death policy adherence.

On the set of emotions with facial signals.

Which, if any, emotions have a facial signal? Studies from AI to Zoology sometimes presuppose an answer to this question. According to one important and influential research program, the basic (fundamental and discrete) emotions can be identified by their possession of a biologically based unique and universally recognized facial signal. To the classic set of six such emotions, researchers recently advanced 12 new candidates, which were examined in the present study with a standard free-labeling procedure in three samples: English-speaking Americans (n = 200), Mandarin-speaking Chinese (n = 101), and Malayalam-speaking Indians (n = 200). In the three samples, respectively, a majority of respondents chose the predicted label for only one, one, and none of the 12 faces. That is, a majority of respondents failed to choose the predicted label for 11 of the 12 faces in the English-speaking (proportion of respondents range for the 11: .04 to .45) and Mandarin-speaking (proportion of respondents range for the 11: .00 to .44) samples; a majority of respondents failed to choose the predicted label for any of the 12 faces in the Malayalam-speaking sample (proportion of respondents range: .00 to .42). The modal choice in the three samples was the predicted label for five, six, and one, respectively, of the 12 faces. "Recognition" of the predicted emotion was negligible (< 15% of respondents) for five, eight (two of which were modal), and 10, respectively, of the 12 faces. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Is purity a distinct and homogeneous domain in moral psychology?

"No" is our answer to the question in our title. In moral psychology, a purity violation (defined as an immoral act committed against one's own body or soul) was theorized to be a homogeneous moral domain qualitatively distinct from other moral domains. In contrast, we hypothesized heterogeneity rather than homogeneity, overlapping rather than distinct domains, and quantitative rather than qualitative differences from other hypothesized domains (specifically, autonomy, which is harm to others). Purity has been said to consist of norms violations of which elicit disgust and taint the soul. Here we empirically examined homogeneity: whether violations of body (e.g., eating putrid food) belong in the same moral domain as violations of the soul unrelated to bodily health (e.g., selling one's soul, desecrating sacred books). We examined distinctness: whether reactions to purity violations differ in predicted ways from those to violations of autonomy. In four studies (the last preregistered), American Internet users (in Studies 2 and 4, classified as politically conservative or liberal; Ns = 80, 96, 1,312, 376) were given stories about violations based on prior studies. Nonhealth purity violations were rated as relatively more disgusting, but less gross (the lay term for the reaction to putrid things) and more likely to taint the soul than were health-related ones. Surprisingly, both health and nonhealth purity violations were typically judged as only slightly immoral if at all. Autonomy violations were rated as more disgusting and tainting of the soul than were purity violations. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Evaluating fatigue in patients recovering from COVID-19: validation of the fatigue severity scale and single item screening questions.

BACKGROUND: Fatigue is a common symptom in hospitalized and non-hospitalized patients recovering from COVID-19, but no fatigue measurement scales or questions have been validated in these populations. The objective of this study was to perform validity assessments of the fatigue severity scale (FSS) and two single-item screening questions (SISQs) for fatigue in patients recovering from COVID-19. METHODS: We examined patients ≥ 28 days after their first SARS-CoV-2 infection who were hospitalized for their acute illness, as well as non-hospitalized patients referred for persistent symptoms. Patients completed questionnaires through 1 of 4 Post COVID-19 Recovery Clinics in British Columbia, Canada. Construct validity was assessed by comparing FSS scores to quality of life and depression measures. Two SISQs were evaluated based on the ability to classify fatigue (FSS score ≥ 4). RESULTS: Questionnaires were returned in 548 hospitalized and 546 non-hospitalized patients, with scores computable in 96.4% and 98.2% of patients respectively. Cronbach's alpha was 0.96 in both groups. The mean ± SD FSS score was 4.4 ± 1.8 in the hospitalized and 5.2 ± 1.6 in the non-hospitalized group, with 62.5% hospitalized and 78.9% non-hospitalized patients classified as fatigued. Ceiling effects were 7.6% in the hospitalized and 16.1% in non-hospitalized patients. FSS scores negatively correlated with EQ-5D scores in both groups (Spearman's rho - 0.6 in both hospitalized and non-hospitalized; p < 0.001) and were higher among patients with a positive PHQ-2 depression screen (5.4 vs. 4.0 in hospitalized and 5.9 vs. 4.9 in non-hospitalized; p < 0.001). An SISQ asking whether there was "fatigue present" had a sensitivity of 70.6% in hospitalized and 83.2% in non-hospitalized patients; the "always feeling tired" SISQ, had a sensitivity of 70.5% and 89.6% respectively. CONCLUSIONS: Fatigue was common and severe in patients referred for post COVID-19 assessment. Overall, the FSS is suitable for measuring fatigue in these patients, as there was excellent data quality, strong internal consistency, and construct validity. However, ceiling effects may be a limitation in the non-hospitalized group. SISQs had good sensitivity for identifying clinically relevant fatigue in non-hospitalized patients but only moderate sensitivity in the hospitalized group, indicating that there were more false negatives.

Modulation of vascular endothelial inflammatory response by proprotein convertase subtilisin-kexin type 9.

BACKGROUND AND AIMS: Endotoxins carried within LDL are cleared from the circulation via hepatic LDL receptor (LDLR)-mediated endocytosis. Proprotein convertase subtilisin-kexin type 9 (PCSK9) reduces this clearance by down-regulating LDLR density on hepatocytes. In addition to hepatocytes, vascular endothelial cells also express receptor targets of PCSK9, including LDLR. Therefore, we hypothesized that PCSK9 may regulate vascular endothelial cell uptake of lipopolysaccharide (LPS) and alter the vascular endothelial cell inflammatory response. METHODS AND RESULTS: We found that LPS is internalized by human umbilical vein vascular endothelial cells (HUVECs) and LPS uptake dose-dependently increased with increasing LDL concentration. Intracellular LPS co-localized with LDL. PCSK9 and, separately, blocking antibodies against LDLR, dose-dependently decreased the vascular endothelial cell uptake of LPS and, furthermore, inhibition of endocytosis using Dynasore blocked LPS uptake. In contrast, blocking antibodies against TLR4 did not alter LPS uptake. PCSK9 decreased the LPS-induced proinflammatory response (IL-6 and IL-8 gene expression and protein secretion, and VCAM-1/ICAM-1 expression) in vascular endothelial cells. In addition, a decrease in PCSK9 and increase in LDLR, mediated by triciribine or siPCSK9, increased LPS uptake and the LPS-induced proinflammatory response. Similar results were also found in aortic vascular tissue from Pcsk9-/- mice after LPS injection. CONCLUSIONS: Our data suggest that, similar to PCSK9 treatment in hepatocytes, PCSK9 reduces vascular endothelial cell uptake of LPS via LDLR-mediated endocytosis. Consequently, PCSK9 decreases the LPS-induced proinflammatory response in vascular endothelial cells. These results raise the possibility that PCSK9 inhibition may have additional effects on vascular endothelial inflammation via this alternative pathway, beyond the known effects of PCSK9 inhibition on LDL lowering and hepatic endotoxin clearance.