Search

Critical illness, such as severe COVID-19, is heterogenous in presentation and treatment response. However, it remains possible that clinical course may be influenced by dynamic and/or random events such that similar patients subject to similar injuries may yet follow different trajectories. We deployed a mechanistic mathematical model of COVID-19 to determine the range of possible clinical courses after SARS-CoV-2 infection, which may follow from specific changes in viral properties, immune properties, treatment modality and random external factors such as initial viral load. We find that treatment efficacy and baseline patient or viral features are not the sole determinant of outcome. We found patients with enhanced innate or adaptive immune responses can experience poor viral control, resolution of infection or non-infectious inflammatory injury depending on treatment efficacy and initial viral load. Hypoxemia may result from poor viral control or ongoing inflammation despite effective viral control. Adaptive immune responses may be inhibited by very early effective therapy, resulting in viral load rebound after cessation of therapy. Our model suggests individual disease course may be influenced by the interaction between external and patient-intrinsic factors. These data have implications for the reproducibility of clinical trial cohorts and timing of optimal treatment., Competing Interests: JFG has served as a compensated consultant or received honoraria from Bristol-Myers Squibb, Genentech/Roche, Ariad/Takeda, Loxo/Lilly, Blueprint, Oncorus, Regeneron, Gilead, Moderna, Mirati, AstraZeneca, Pfizer, Novartis, iTeos, Nuvalent, Karyopharm, Beigene, Silverback Therapeutics, Merck, and GlydeBio; research support from Novartis, Genentech/Roche, and Ariad/Takeda; institutional research support from Bristol-Myers Squibb, Tesaro, Moderna, Blueprint, Jounce, Array Biopharma, Merck, Adaptimmune, Novartis, and Alexo; and has an immediate family member who is an employee with equity at Ironwood Pharmaceuticals. LLM owns equity in Bayer AG and is a consultant for SimBiosys. RKJ received consultant fees from Elpis, Innocoll, SPARC, SynDevRx; owns equity in Accurius, Enlight, Ophthotech, SynDevRx; and serves on the Boards of Trustees of Tekla Healthcare Investors, Tekla Life Sciences Investors, Tekla Healthcare Opportunities Fund, Tekla World Healthcare Fund; and received a grant from Boehringer Ingelheim. Neither any reagent nor any funding from these organizations was used in this study. Other co-authors have no conflict of interests to declare. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2024 Voutouri et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This study introduces a tailored COVID-19 model for patients with cancer, incorporating viral variants and immune-response dynamics. The model aims to optimize vaccination strategies, contributing to personalized healthcare for vulnerable groups., Competing Interests: Declaration of interests J.F.G. has served as a compensated consultant or received honoraria from Bristol-Myers Squibb, Genentech/Roche, Takeda, Loxo/Lilly, Blueprint Medicine, Gilead, Moderna, AstraZeneca, Curie Therapeutics, Mirati, Merus Pharmacueticals, Nuvalent, Pfizer, Novartis, Merck, iTeos, Karyopharm, and Silverback Therapeutics; has received research support from Novartis, Genentech/Roche, and Takeda; has received institutional research support from Bristol-Myers Squibb, Tesaro, Moderna, Blueprint, Jounce, Array Biopharma, Merck, Adaptimmune, Novartis, and Alexo; and has an immediate family member who is an employee with equity at Ironwood Pharmaceuticals. R.K.J. received consultant fees from Cur, DynamiCure, Elpis, SPARC, SynDevRx; owns equity in Accurius, Enlight, SynDevRx; served on Board of Trustees of Tekla Healthcare Investors, Tekla Life Sciences Investors, Tekla Healthcare Opportunities Fund, and Tekla World Healthcare Fund; and received research grants from Boehringer Ingelheim and Sanofi. No funding or reagents from these organizations were used in this study., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

How Treatment Effect Heterogeneity WorksThis Stats, STAT! animated video explores the concept of treatment effect heterogeneity. Differences in the effectiveness of treatments across participants in a clinical trial is important to understand when deciding how to apply clinical trial results to clinical practice.

How Statistical Power WorksThis Stats, STAT! animated video explores the concept of statistical power and explains how clinical investigators determine how many participants to enroll in a randomized trial.

How Censoring WorksA common challenge in clinical research is determining the time to occurrence of a given event. This animated video explores the concept of censoring in survival analysis and how investigators deal with ambiguity in the time of an event's occurrence.

Large Language ModelsIn the latest edition of Stats, STAT!, Fralick and colleagues explain the statistics behind large language models - used in chat bots like ChatGPT and Bard. While these new tools may seem remarkably intelligent, at their core they just assemble sentences based on statistics from large amounts of text.

As the pandemic has progressed, our understanding of hypoxemia in coronavirus disease 2019 (COVID-19) lung disease has become more nuanced, although much remains to be understood. In this article, we review ventilation-perfusion mismatching in COVID-19 and the evidence to support various biologic theories offered in explanation. In addition, the relationship between hypoxemia and other features of severe COVID-19 lung disease such as respiratory symptoms, radiographic abnormalities, and pulmonary mechanics is explored. Recognizing and understanding hypoxemia in COVID-19 lung disease remains essential for risk stratification, prognostication, and choice of appropriate treatments in severe COVID-19., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Bayesian WayThis animated video explores two possible approaches to analyzing data in a randomized controlled trial: "Frequentist" versus "Bayesian."

Good Intentions to Treat This Stats, STAT! animated video explores common approaches to analyzing data from randomized controlled trials, including intention-to-treat, per-protocol, and as-treated analyses.

Background: Prone position ventilation (PPV) is resource-intensive, yet the optimal strategy for PPV in intubated patients with COVID-19 is unclear., Research Question: Does a prolonged (24 or more h) PPV strategy improve mortality in intubated COVID-19 patients compared with intermittent (∼16 h with daily supination) PPV?, Study Design and Methods: Multicenter, retrospective cohort study of consecutively admitted intubated COVID-19 patients treated with PPV between March 11 and May 31, 2020. The primary outcome was 30-day all-cause mortality. Secondary outcomes included 90-day all-cause mortality and prone-related complications. Inverse probability treatment weights (IPTW) were used to control for potential treatment selection bias., Results: Of the COVID-19 patients who received PPV, 157 underwent prolonged and 110 underwent intermittent PPV. Patients undergoing prolonged PPV had reduced 30-day (adjusted hazard ratio [aHR], 0.475; 95% CI, 0.336-0.670; P < .001) and 90-day (aHR, 0.638; 95% CI, 0.461-0.883; P = .006) mortality compared with intermittent PPV. In patients with Pao 2 /Fio 2  ≤ 150 at the time of pronation, prolonged PPV was associated with reduced 30-day (aHR, 0.357; 95% CI, 0.213-0.597; P < .001) and 90-day mortality (aHR, 0.562; 95% CI, 0.357-0.884; P = .008). Patients treated with prolonged PPV underwent fewer pronation and supination events (median, 1; 95% CI, 1-2 vs 3; 95% CI, 1-4; P < .001). PPV strategy was not associated with overall PPV-related complications, although patients receiving prolonged PPV had increased rates of facial edema and lower rates of peri-proning hypotension., Interpretation: Among intubated COVID-19 patients who received PPV, prolonged PPV was associated with reduced mortality. Prolonged PPV was associated with fewer pronation and supination events and a small increase in rates of facial edema. These findings suggest that prolonged PPV is a safe, effective strategy for mortality reduction in intubated COVID-19 patients., (Copyright © 2022 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.)

(1) The use of high-flow nasal cannula (HFNC) combined with frequent respiratory monitoring in patients with acute hypoxic respiratory failure due to COVID-19 has been shown to reduce intubation and mechanical ventilation. (2) This prospective, single-center, observational study included consecutive adult patients with COVID-19 pneumonia treated with a high-flow nasal cannula. Hemodynamic parameters, respiratory rate, inspiratory fraction of oxygen (F i O 2 ), saturation of oxygen (S p O 2 ), and the ratio of oxygen saturation to respiratory rate (ROX) were recorded prior to treatment initiation and every 2 h for 24 h. A 6-month follow-up questionnaire was also conducted. (3) Over the study period, 153 of 187 patients were eligible for HFNC. Of these patients, 80% required intubation and 37% of the intubated patients died in hospital. Male sex (OR = 4.65; 95% CI [1.28; 20.6], p = 0.03) and higher BMI (OR = 2.63; 95% CI [1.14; 6.76], p = 0.03) were associated with an increased risk for new limitations at 6-months after hospital discharge. (4) 20% of patients who received HFNC did not require intubation and were discharged alive from the hospital. Male sex and higher BMI were associated with poor long-term functional outcomes.

SARS-CoV-2 vaccines are effective at limiting disease severity, but effectiveness is lower among patients with cancer or immunosuppression. Effectiveness wanes with time and varies by vaccine type. Moreover, previously prescribed vaccines were based on the ancestral SARS-CoV-2 spike-protein that emerging variants may evade. Here, we describe a mechanistic mathematical model for vaccination-induced immunity. We validate it with available clinical data and use it to simulate the effectiveness of vaccines against viral variants with lower antigenicity, increased virulence, or enhanced cell binding for various vaccine platforms. The analysis includes the omicron variant as well as hypothetical future variants with even greater immune evasion of vaccine-induced antibodies and addresses the potential benefits of the new bivalent vaccines. We further account for concurrent cancer or underlying immunosuppression. The model confirms enhanced immunogenicity following booster vaccination in immunosuppressed patients but predicts ongoing booster requirements for these individuals to maintain protection. We further studied the impact of variants on immunosuppressed individuals as a function of the interval between multiple booster doses. Our model suggests possible strategies for future vaccinations and suggests tailored strategies for high-risk groups.

Of Climate Change and Competing Risks This Stats, STAT! animated video explores the concept of competing risks - and discusses why it is so important for investigators to consider whether the occurrence of one event can prevent or change the likelihood of the occurrence of another.

Blinding is a critical strategy used to limit certain types of bias in randomized controlled trials. This animated video explores the rationale and examines potential threats to keeping group allocation concealed - from study participants and investigators.

Rationale: The leading cause of death in coronavirus disease 2019 (COVID-19) is severe pneumonia, with many patients developing acute respiratory distress syndrome (ARDS) and diffuse alveolar damage (DAD). Whether DAD in fatal COVID-19 is distinct from other causes of DAD remains unknown. Objective: To compare lung parenchymal and vascular alterations between patients with fatal COVID-19 pneumonia and other DAD-causing etiologies using a multidimensional approach. Methods: This autopsy cohort consisted of consecutive patients with COVID-19 pneumonia ( n  = 20) and with respiratory failure and histologic DAD ( n  = 21; non-COVID-19 viral and nonviral etiologies). Premortem chest computed tomography (CT) scans were evaluated for vascular changes. Postmortem lung tissues were compared using histopathological and computational analyses. Machine-learning-derived morphometric analysis of the microvasculature was performed, with a random forest classifier quantifying vascular congestion (C Vasc ) in different microscopic compartments. Respiratory mechanics and gas-exchange parameters were evaluated longitudinally in patients with ARDS. Measurements and Main Results: In premortem CT, patients with COVID-19 showed more dilated vasculature when all lung segments were evaluated ( P  = 0.001) compared with controls with DAD. Histopathology revealed vasculopathic changes, including hemangiomatosis-like changes ( P  = 0.043), thromboemboli ( P  = 0.0038), pulmonary infarcts ( P  = 0.047), and perivascular inflammation ( P  < 0.001). Generalized estimating equations revealed significant regional differences in the lung microarchitecture among all DAD-causing entities. COVID-19 showed a larger overall C Vasc range ( P  = 0.002). Alveolar-septal congestion was associated with a significantly shorter time to death from symptom onset ( P  = 0.03), length of hospital stay ( P  = 0.02), and increased ventilatory ratio [an estimate for pulmonary dead space fraction ( V d ); p  = 0.043] in all cases of ARDS. Conclusions: Severe COVID-19 pneumonia is characterized by significant vasculopathy and aberrant alveolar-septal congestion. Our findings also highlight the role that vascular alterations may play in V d and clinical outcomes in ARDS in general.

Subgroup Analyses: Subpar or Sublime?This animated video explores some of the potential pitfalls of performing subgroup analyses in randomized controlled trials and explains how to approach potential findings with caution.

The Problem of Multiple Comparisons This animated video reviews the problem of multiple comparisons in research studies and explains how performing multiple statistical hypothesis tests can produce associations simply by chance.

The Case of the Missing DataThis animated video explores how investigators approach missing data in clinical trials.

Background: Mathematical modelling may aid in understanding the complex interactions between injury and immune response in critical illness., Methods: We utilize a system biology model of COVID-19 to analyze the effect of altering baseline patient characteristics on the outcome of immunomodulatory therapies. We create example parameter sets meant to mimic diverse patient types. For each patient type, we define the optimal treatment, identify biologic programs responsible for clinical responses, and predict biomarkers of those programs., Findings: Model states representing older and hyperinflamed patients respond better to immunomodulation than those representing obese and diabetic patients. The disparate clinical responses are driven by distinct biologic programs. Optimal treatment initiation time is determined by neutrophil recruitment, systemic cytokine expression, systemic microthrombosis and the renin-angiotensin system (RAS) in older patients, and by RAS, systemic microthrombosis and trans IL6 signalling for hyperinflamed patients. For older and hyperinflamed patients, IL6 modulating therapy is predicted to be optimal when initiated very early (<4 th day of infection) and broad immunosuppression therapy (corticosteroids) is predicted to be optimally initiated later in the disease (7 th - 9 th day of infection). We show that markers of biologic programs identified by the model correspond to clinically identified markers of disease severity., Interpretation: We demonstrate that modelling of COVID-19 pathobiology can suggest biomarkers that predict optimal response to a given immunomodulatory treatment. Mathematical modelling thus constitutes a novel adjunct to predictive enrichment and may aid in the reduction of heterogeneity in critical care trials., Funding: C.V. received a Marie Skłodowska Curie Actions Individual Fellowship (MSCA-IF-GF-2020-101028945). R.K.J.'s research is supported by R01-CA208205, and U01-CA 224348, R35-CA197743 and grants from the National Foundation for Cancer Research, Jane's Trust Foundation, Advanced Medical Research Foundation and Harvard Ludwig Cancer Center. No funder had a role in production or approval of this manuscript., Competing Interests: Declaration of interests LLM owns equity in Bayer AG and is a consultant for SimBiosys. R.K.J. received honorarium from Amgen; consultant fees from Chugai, Elpis, Merck, Ophthotech, Pfizer, SPARC, SynDevRx, XTuit; owns equity in Accurius, Enlight, Ophthotech, SynDevRx; and serves on the Boards of Trustees of Tekla Healthcare Investors, Tekla Life Sciences Investors, Tekla Healthcare Opportunities Fund, Tekla World Healthcare Fund; and received a grant from Boehringer Ingelheim. Neither any reagent nor any funding from these organizations was used in this study. Other coauthors have no conflict of interests to declare., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

Is Noninferior Not Inferior? What is a non-inferiority trial margin? To answer this, ask whether you have ever weighed a tradeoff between the best version of something and an acceptable alternative. Restated, in a choice between two decisions, is one option not inferior to the other? Watch an animated video that explores the basis for non-inferiority trials, the meaning of non-inferiority margins, and the interpretation of a non-inferiority trial's results.

Background: Dyspnea and exercise intolerance are commonly reported post-acute sequelae of SARS-CoV-2 infection (PASC), but routine diagnostic testing is often normal. Cardiopulmonary exercise testing (CPET) offers comprehensive assessment of dyspnea to characterize pulmonary PASC., Methods: We performed a retrospective cohort study of CPET performed on patients reporting dyspnea and/or exercise intolerance following confirmed Covid-19 between August 1, 2020 and March 1, 2021, and compared them to age- and sex-matched patients with unexplained dyspnea referred for CPET at the same center in the pre-Covid-19 era., Findings: Compared to matched unexplained dyspnea comparators, PASC patients shared similar medical comorbidities and subjective dyspnea at referral (mMRC score 1.6 ± 0.9 vs. 1.4 ± 0.9, P  = 0.5). Fifteen (83.3%) PASC patients underwent high resolution computed tomography of the chest, of which half (46.7%) were normal, and 17 (94.4%) patients had pulmonary function testing, of which the majority (76.5%) were normal. All patients underwent CPET, and 12 (67%) had normal findings. Compared to matched comparators, PASC patients had similar peak oxygen consumption, oxygen consumption at ventilatory anaerobic threshold, and ventilatory efficiency measured by the minute ventilation to carbon dioxide production (VE/VCO 2 ) slope., Interpretation: Despite prominent dyspnea, physiological abnormalities on CPET were mild across a range of initial Covid-19 severity and similar to matched comparators referred for dyspnea without antecedent SARS-CoV-2., Funding: The project was supported by the NHLBI (R01HL131029, R01HL151841, U10HL110337, T32HL116275) and a KL2 award (5KL2TR002542-02) from Harvard Catalyst., Competing Interests: LPH receives consulting fees from Plaint Therapeutics and Boehringer Ingelheim and serves on the medical advisory board Boehringer Ingelheim, all unrelated to the content of this manuscript. BDM is a data safety monitoring board member for a clinical trial (Multicenter, Randomized, Double-Blinded, Placebo-Controlled Study to Assess Safety and Efficacy of SIR1–365 in Patients with Severe COVID-19) funded by Sironax, USA, unrelated to the content of this manuscript; received payment from Abbvie for providing a presentation on severe COVID-19. GDL serves on the steering committee for clinical trials related to CPET for Amgen, AstraZeneca, Cyclerion, and Cytokinetics, all unrelated to the content of this manuscript; and Cardiopulmonary Exercise Testing Core Laboratory Projects with NHLBI, Amgen, AstraZeneca, Cyclerion, Cytokinetics, Applied Therapeutics, and Abbott, that are not directly related to this work., (© 2021 The Authors.)

Importance: Prone positioning improves clinical outcomes in moderate-to-severe acute respiratory distress syndrome and has been widely adopted for the treatment of patients with acute respiratory distress syndrome due to coronavirus disease 2019. Little is known about the effects of prone positioning among patients with less severe acute respiratory distress syndrome, obesity, or those treated with pulmonary vasodilators., Objectives: We characterize the change in oxygenation, respiratory system compliance, and dead-space-to-tidal-volume ratio in response to prone positioning in patients with coronavirus disease 2019 acute respiratory distress syndrome with a range of severities. A subset analysis of patients treated with inhaled nitric oxide and subsequent prone positioning explored the influence of pulmonary vasodilation on the physiology of prone positioning., Design Setting and Participants: Retrospective cohort study of all consecutively admitted adult patients with acute respiratory distress syndrome due to coronavirus disease 2019 treated with mechanical ventilation and prone positioning in the ICUs of an academic hospital between March 11, 2020, and May 1, 2020., Main Outcomes and Measures: Respiratory system mechanics and gas exchange during the first episode of prone positioning., Results: Among 122 patients, median (interquartile range) age was 60 years (51-71 yr), median body mass index was 31.5 kg/m 2 (27-35 kg/m 2 ), and 50 patients (41%) were female. The ratio of Pao 2 to Fio 2 improved with prone positioning in 90% of patients. Prone positioning was associated with a significant increase in the ratio of Pao 2 to Fio 2 (from median 149 [123-170] to 226 [169-268], p < 0.001) but no change in dead-space-to-tidal-volume ratio or respiratory system compliance. Supine ratio of Pao 2 to Fio 2 , respiratory system compliance, positive end-expiratory pressure, and body mass index did not correlate with absolute change in the ratio of Pao 2 to Fio 2 with prone positioning. However, patients with ratio of Pao 2 to Fio 2 less than 150 experienced a greater relative improvement in oxygenation with prone positioning than patients with ratio of Pao 2 to Fio 2 greater than or equal to 150 (median percent change in ratio of Pao 2 to Fio 2 62 [29-107] vs 30 [10-70], p = 0.002). Among 12 patients, inhaled nitric oxide prior to prone positioning was associated with a significant increase in the ratio of Pao 2 to Fio 2 (from median 136 [77-168] to 170 [138-213], p = 0.003) and decrease in dead-space-to-tidal-volume ratio (0.54 [0.49-0.58] to 0.46 [0.44-0.53], p = 0.001). Subsequent prone positioning in this subgroup further improved the ratio of Pao 2 to Fio 2 (from 145 [122-183] to 205 [150-232], p = 0.017) but did not change dead-space-to-tidal-volume ratio., Conclusions and Relevance: Prone positioning improves oxygenation across the acute respiratory distress syndrome severity spectrum, irrespective of supine respiratory system compliance, positive end-expiratory pressure, or body mass index. There was a greater relative benefit among patients with more severe disease. Prone positioning confers an additive benefit in oxygenation among patients treated with inhaled nitric oxide., Competing Interests: Dr. Hardin reports receiving research funding from AstraZeneca. Dr. Malhotra reports income from Equillium, Corvus, and Livanova related to medical education. ResMed provided a philanthropic donation to University of California, San Diego. Dr. Berra reports receiving funding from “Fast Grants for COVID-19 Research” from the Mercatus Center of George Mason University and from iNO Therapeutics LLC. He also reports receiving technologies and devices from iNO Therapeutics LLC, Praxair, and Masimo. Dr. Ziehr is supported by National Institutes of Health (NIH) T32 HL116275. Dr. Malhotra is supported by NIH R01 AG063925, R01 HL085188, and R01 HL148436. Dr. Berra is supported by NIH K23 HL128882. The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2021 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine.)

As predicting the trajectory of COVID-19 is challenging, machine learning models could assist physicians in identifying high-risk individuals. This study compares the performance of 18 machine learning algorithms for predicting ICU admission and mortality among COVID-19 patients. Using COVID-19 patient data from the Mass General Brigham (MGB) Healthcare database, we developed and internally validated models using patients presenting to the Emergency Department (ED) between March-April 2020 (n = 3597) and further validated them using temporally distinct individuals who presented to the ED between May-August 2020 (n = 1711). We show that ensemble-based models perform better than other model types at predicting both 5-day ICU admission and 28-day mortality from COVID-19. CRP, LDH, and O 2 saturation were important for ICU admission models whereas eGFR <60 ml/min/1.73 m 2 , and neutrophil and lymphocyte percentages were the most important variables for predicting mortality. Implementing such models could help in clinical decision-making for future infectious disease outbreaks including COVID-19.

The dramatic impact of the COVID-19 pandemic has resulted in an "all hands on deck" approach to find new therapies to improve outcomes in this disease. In addition to causing significant respiratory pathology, infection with SARS-CoV-2 (like infection with other respiratory viruses) directly or indirectly results in abnormal vasculature, which may contribute to hypoxemia. These vascular effects cause significant morbidity and may contribute to mortality from the disease. Given that abnormal vasculature and poor oxygenation are also hallmarks of solid tumors, lessons from the treatment of cancer may help identify drugs that can be repurposed to treat COVID-19. Although the mechanisms that result in vascular abnormalities in COVID-19 are not fully understood, it is possible that there is dysregulation of many of the same angiogenic and thrombotic pathways as seen in patients with cancer. Many anticancer therapeutics, including androgen deprivation therapy (ADT) and immune checkpoint blockers (ICB), result in vascular normalization in addition to their direct effects on tumor cells. Therefore, these therapies, which have been extensively explored in clinical trials of patients with cancer, may have beneficial effects on the vasculature of patients with COVID-19. Furthermore, these drugs may have additional effects on the disease course, as some ADTs may impact viral entry, and ICBs may accelerate T-cell-mediated viral clearance. These insights from the treatment of cancer may be leveraged to abrogate the vascular pathologies found in COVID-19 and other forms of hypoxemic respiratory failure., (©2021 American Association for Cancer Research.)

Objective: Recent cohort studies have identified obesity as a risk factor for poor outcomes in coronavirus disease 2019 (COVID-19). To further explore the relationship between obesity and critical illness in COVID-19, the association of BMI with baseline demographic and intensive care unit (ICU) parameters, laboratory values, and outcomes in a critically ill patient cohort was examined., Methods: In this retrospective study, the first 277 consecutive patients admitted to Massachusetts General Hospital ICUs with laboratory-confirmed COVID-19 were examined. BMI class, initial ICU laboratory values, physiologic characteristics including gas exchange and ventilatory mechanics, and ICU interventions as clinically available were measured. Mortality, length of ICU admission, and duration of mechanical ventilation were also measured., Results: There was no difference found in respiratory system compliance or oxygenation between patients with and without obesity. Patients without obesity had higher initial ferritin and D-dimer levels than patients with obesity. Standard acute respiratory distress syndrome management, including prone ventilation, was equally distributed between BMI groups. There was no difference found in outcomes between BMI groups, including 30- and 60-day mortality and duration of mechanical ventilation., Conclusions: In this cohort of critically ill patients with COVID-19, obesity was not associated with meaningful differences in respiratory physiology, inflammatory profile, or clinical outcomes., (© 2021 The Obesity Society.)

Coronavirus disease 2019 (COVID-19) appears to be associated with increased arterial and venous thromboembolic disease. These presumed abnormalities in hemostasis have been associated with filter clotting during continuous renal replacement therapy (CRRT). We aimed to characterize the burden of CRRT filter clotting in COVID-19 infection and to describe a CRRT anticoagulation protocol that used anti-factor Xa levels for systemic heparin dosing. Multi-center study of consecutive patients with COVID-19 receiving CRRT. Primary outcome was CRRT filter loss. Sixty-five patients were analyzed, including 17 using an anti-factor Xa protocol to guide systemic heparin dosing. Fifty-four out of 65 patients (83%) lost at least one filter. Median first filter survival time was 6.5 [2.5, 33.5] h. There was no difference in first or second filter loss between the anti-Xa protocol and standard of care anticoagulation groups, however fewer patients lost their third filter in the protocolized group (55% vs. 93%) resulting in a longer median third filter survival time (24 [15.1, 54.2] vs. 17.3 [9.5, 35.1] h, p = 0.04). The rate of CRRT filter loss is high in COVID-19 infection. An anticoagulation protocol using systemic unfractionated heparin, dosed by anti-factor Xa levels is reasonable approach to anticoagulation in this population.

Background: Acute respiratory distress syndrome (ARDS) secondary to coronavirus disease-2019 (COVID-19) is characterized by substantial heterogeneity in clinical, biochemical, and physiological characteristics. However, the pathophysiology of severe COVID-19 infection is poorly understood. Previous studies established clinical and biological phenotypes among classical ARDS cohorts, with important therapeutic implications. The phenotypic profile of COVID-19 associated ARDS remains unknown., Methods: We used latent class modeling via a multivariate mixture model to identify phenotypes from clinical and biochemical data collected from 263 patients admitted to Massachusetts General Hospital intensive care unit with COVID-19-associated ARDS between March 13 and August 2, 2020., Findings: We identified two distinct phenotypes of COVID-19-associated ARDS, with substantial differences in biochemical profiles despite minimal differences in respiratory dynamics. The minority phenotype (class 2, n  = 70, 26·6%) demonstrated increased markers of coagulopathy, with mild relative hyper-inflammation and dramatically increased markers of end-organ dysfunction (e.g., creatinine, troponin). The odds of 28-day mortality among the class 2 phenotype was more than double that of the class 1 phenotype (40·0% vs.· 23·3%, OR = 2·2, 95% CI [1·2, 3·9])., Interpretation: We identified distinct phenotypic profiles in COVID-19 associated ARDS, with little variation according to respiratory physiology but with important variation according to systemic and extra-pulmonary markers. Phenotypic identity was highly associated with short-term mortality. The class 2 phenotype exhibited prominent signatures of coagulopathy, suggesting that vascular dysfunction may play an important role in the clinical progression of severe COVID-19-related disease., Competing Interests: LB receives salary support from K23 HL128882/NHLBI NIH as principal investigator for his work on hemolysis and nitric oxide. LB receives technologies and devices from iNO Therapeutics LLC, Praxair Inc., Masimo Corp. LB receives grants from “Fast Grants for COVID-19 research” at Mercatus Center of George Mason University and from iNO Therapeutics LLC. BTT reports grants from NIH NHLBI and personal fees from Bayer, Thetis, and Novartis, outside the submitted work. CCH receives research support from AstraZeneca, outside the scope of the submitted work. The other authors have nothing to disclose., (© 2021 The Author(s).)

Understanding the underlying mechanisms of COVID-19 progression and the impact of various pharmaceutical interventions is crucial for the clinical management of the disease. We developed a comprehensive mathematical framework based on the known mechanisms of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, incorporating the renin-angiotensin system and ACE2, which the virus exploits for cellular entry, key elements of the innate and adaptive immune responses, the role of inflammatory cytokines, and the coagulation cascade for thrombus formation. The model predicts the evolution of viral load, immune cells, cytokines, thrombosis, and oxygen saturation based on patient baseline condition and the presence of comorbidities. Model predictions were validated with clinical data from healthy people and COVID-19 patients, and the results were used to gain insight into identified risk factors of disease progression including older age; comorbidities such as obesity, diabetes, and hypertension; and dysregulated immune response. We then simulated treatment with various drug classes to identify optimal therapeutic protocols. We found that the outcome of any treatment depends on the sustained response rate of activated CD8 + T cells and sufficient control of the innate immune response. Furthermore, the best treatment-or combination of treatments-depends on the preinfection health status of the patient. Our mathematical framework provides important insight into SARS-CoV-2 pathogenesis and could be used as the basis for personalized, optimal management of COVID-19., Competing Interests: Competing interest statement: R.K.J. received honorarium from Amgen; consultant fees from Chugai, Merck, Ophthotech, Pfizer, SPARC, SynDevRx, XTuit, Elpis; owns equity in Accurius, Enlight, Ophthotech, SynDevRx; and serves on the Boards of Trustees of Tekla Healthcare Investors, Tekla Life Sciences Investors, Tekla Healthcare Opportunities Fund, and Tekla World Healthcare Fund. Neither any reagent nor any funding from these organizations was used in this study. A.B.P. has received fellowship funding from Relypsa, Inc. L.L.M. owns equity in Bayer AG and is a consultant for SimBiosys. Neither any reagent nor any funding from these organizations was used in this study., (Copyright © 2021 the Author(s). Published by PNAS.)

Background: Patients with severe coronavirus disease 2019 (COVID-19) have respiratory failure with hypoxemia and acute bilateral pulmonary infiltrates, consistent with ARDS. Respiratory failure in COVID-19 might represent a novel pathologic entity., Research Question: How does the lung histopathology described in COVID-19 compare with the lung histopathology described in SARS and H1N1 influenza?, Study Design and Methods: We conducted a systematic review to characterize the lung histopathologic features of COVID-19 and compare them against findings of other recent viral pandemics, H1N1 influenza and SARS. We systematically searched MEDLINE and PubMed for studies published up to June 24, 2020, using search terms for COVID-19, H1N1 influenza, and SARS with keywords for pathology, biopsy, and autopsy. Using PRISMA-Individual Participant Data guidelines, our systematic review analysis included 26 articles representing 171 COVID-19 patients; 20 articles representing 287 H1N1 patients; and eight articles representing 64 SARS patients., Results: In COVID-19, acute-phase diffuse alveolar damage (DAD) was reported in 88% of patients, which was similar to the proportion of cases with DAD in both H1N1 (90%) and SARS (98%). Pulmonary microthrombi were reported in 57% of COVID-19 and 58% of SARS patients, as compared with 24% of H1N1 influenza patients., Interpretation: DAD, the histologic correlate of ARDS, is the predominant histopathologic pattern identified in lung pathology from patients with COVID-19, H1N1 influenza, and SARS. Microthrombi were reported more frequently in both patients with COVID-19 and SARS as compared with H1N1 influenza. Future work is needed to validate this histopathologic finding and, if confirmed, elucidate the mechanistic underpinnings and characterize any associations with clinically important outcomes., (Copyright © 2020 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.)

Background: Exercise testing plays an important role in evaluating heart failure prognosis and selecting patients for advanced therapeutic interventions. However, concern for severe acute respiratory syndrome novel coronavirus-2 transmission during exercise testing has markedly curtailed performance of exercise testing during the novel coronavirus disease-2019 pandemic., Methods and Results: To examine the feasibility to conducting exercise testing with an in-line filter, 2 healthy volunteer subjects each completed 2 incremental exercise tests, one with discrete stages of increasing resistance and one with a continuous ramp. Each subject performed 1 test with an electrostatic filter in-line with the system measuring gas exchange and air flow, and 1 test without the filter in place. Oxygen uptake and minute ventilation were highly consistent when evaluated with and without use of an electrostatic filter with a >99.9% viral efficiency., Conclusions: Deployment of a commercially available in-line electrostatic viral filter during cardiopulmonary exercise testing is feasible and provides consistent data compared with testing without a filter., (Copyright © 2020. Published by Elsevier Inc.)

Human infection by the novel viral pathogen SARS-CoV-2 results in a clinical syndrome termed Coronavirus Disease 2019 (COVID-19). Although the majority of COVID-19 cases are self-limiting, a substantial minority of patients develop disease severe enough to require intensive care. Features of critical illness associated with COVID-19 include hypoxemic respiratory failure, acute respiratory distress syndrome (ARDS), shock, and multiple organ dysfunction syndrome (MODS). In most (but not all) respects critically ill patients with COVID-19 resemble critically ill patients with ARDS due to other causes and are optimally managed with standard, evidence-based critical care protocols. However, there is naturally an intense interest in developing specific therapies for severe COVID-19. Here we synthesize the rapidly expanding literature around the pathophysiology, clinical presentation, and management of COVID-19 with a focus on those points most relevant for intensivists tasked with caring for these patients. We specifically highlight evidence-based approaches that we believe should guide the identification, triage, respiratory support, and general ICU care of critically ill patients infected with SARS-CoV-2. In addition, in light of the pressing need and growing enthusiasm for targeted COVID-19 therapies, we review the biological basis, plausibility, and clinical evidence underlying these novel treatment approaches.