key: cord-012010-5h2ox3hu
authors: Bos, Lieuwe D.J.; Sinha, Pratik; Dickson, Robert P.
title: Response to “COVID-19 conundrum: Clinical phenotyping based on pathophysiology as a promising approach to guide therapy in a novel illness” and “Strengthening the foundation of the house of CARDS by phenotyping on the fly” and “COVID-19 phenotypes: leading or misleading?”
date: 2020-08-03
journal: Eur Respir J
DOI: 10.1183/13993003.02756-2020
sha: 
doc_id: 12010
cord_uid: 5h2ox3hu

We argue that phenotyping of COVID-19 related ARDS should be done using careful, data-driven approaches.

In their letter, Drs. Cherian et al. take issue with our interpretation of the respiratory physiology of COVID-19, arguing that it is based merely on "small cohort studies," instead arguing that "a high proportion of mechanically ventilated COVID-19 patients exhibit near-normal lung compliance." [1] Yet the low respiratory compliance of COVID- 19 patients has now been extensively demonstrated by studies totaling more than 800 COVID-19 patients [2] [3] [4] [5] [6] [7] [8] , including a direct comparison with non-COVID ARDS patients that revealed no difference in respiratory compliance. [8] In contrast, the three case series cited by the correspondents in support of their claim comprise cohorts of, respectively, 16, 10 and 26 patients [9] [10] [11] . Further, even these case series report average respiratory compliance in COVID-19 of 40-45 mL/cmH 2 O, which is in fact abnormal and far from "near-normal compliance". [12, 13] As an informative comparison, the ANZICS cohort of ARDS patients used to derive the Berlin Definition of ARDS had an average respiratory compliance of 40 ± 15 ml/cmH 2 O. [14] We thus find no evidence in the authors' citations (or elsewhere) to support their empirical claim that many or most COVID-19 patients present with "normal" or "near-normal" respiratory compliance.

Drs. Cherian et al. also assume a temporal progression from "early" COVID-19 physiology (characterized by normal respiratory compliance) to "late" physiology (characterized by impaired respiratory compliance). Yet three published studies comprising nearly 350 mechanically ventilated COVID-19 patients have reported serial measurements of respiratory compliance [2, 4, 7] , and none has shown any temporal trend towards decreased compliance in the days following initiation of mechanical ventilation. Further, a recent report from Haudebourg et al. demonstrated no correlation between duration of symptoms and respiratory compliance in COVID-19 patients ( Figure   1a ) [8] . We have since validated this observation using our own clinical data ( Figure 1b ). Figure 1c , Gattinoni et al. recently published their own data countering these findings [15] . Importantly, when data from all three cohorts are combined and analysed together, no temporal trend is present (p=0.50, r 2 =0.005). Closer inspection reveals that the purported correlation in one of the cohorts is entirely attributable to two patients with low respiratory compliance and more than three weeks of symptoms, a duration of disease irrelevant to considerations of acute pathogenesis and rarely 2) the instability of statistical inferences using small, single variable, data sources; and 3) the predictable correction of initial human intuitions when more data emerge. A final, under-appreciated and unmeasurable pitfall of premature phenotyping raised in our Editorial, and one that the multitude of publications addressing these purported phenotypes are substantiating, is the opportunity cost to research resources caused by high-profile yet unsupported speculation. This factor is all the more pertinent in the face of an unforgiving pandemic in which clinical ICU workload is highly demanding and clinical research is a zero-sum game. Further, clinicians have even less time than usual to critically evaluate scientific literature. Therefore, it is incumbent as clinician-scientists that whilst our data gathering may be agile and creative, its interpretation should be cautious and deliberate.

While we agree with Drs. Cherian regarding the potential pathophysiologic importance of endothelial injury in COVID-19, the data at hand are simply insufficient to declare if this aspect of pathogenesis is a central mediator of disease progression and lung injury in COVID-19. For example, it is worth noting that while endothelial injury has been described in post-mortem histopathological evaluations, it is not ubiquitous. Epithelial injury and diffuse alveolar damage, however, are. [16, 17] Our Editorial did not take a position on the pathophysiology of COVID-19, nor do we dispute the need to identify more homogenous biological pathways. Frankly, we do not believe in "typical ARDS," as the syndrome encompasses diverse etiologic pathways with only partially intersecting clinical and histopathological "bottlenecks." We are merely arguing that the currently postulated phenotypes are unconvincing, and insufficient to justify a widespread change in clinical management (as proposed by the correspondents).

In his response to our Editorial, Dr. Rajendram reveals a curious misinterpretation of our Editorial: "Thus, whilst the net effect of the ARDSNet protocol is beneficial at the level of the study population, theoretically, it may harm select patients… contrary to the opinions of the Surviving Sepsis Campaign, and Bos and colleagues, the ARDSNet protocol is not a panacea." Putting aside the wishful thinking of a supportive intervention functioning as a "panacea" for a condition with persistent mortality of 30-40%, the correspondent (along with Drs. Cherian et al.) seems to think that we dispute the heterogeneity of ARDS, and advocate for a "one-size-fits-all" approach to its clinical management. Quite the opposite: we strongly believe that ARDS represents a pathophysiologically heterogenous syndrome and have argued the same for COVID-19 related ARDS. [18] Until well-defined biological subgroups are identified, the ceiling of effective interventions is likely to remain supportive. We also strongly suspect there are likely considerable biological differences between COVID-19 and non-COVID-19 ARDS. [19] Where we differ with our correspondents, we suspect, is in our lack of confidence that clinicians can identify meaningful subphenotypes using underpowered cohorts and bedside intuitions and then recommend effective interventions without testing them in a scientific study. This was the central point of our Editorial and is illustrated with two examples in this response (the "normal compliance" of COVID-19 and its purported temporal worsening). As a contrast, the correspondents may consider recent pre-COVID-19 research identifying hypoinflammatory and hyperinflammatory subphenotypes in ARDS (to which we have contributed). [9, 20] These ARDS subphenotypes were derived using unsupervised clustering of more than 3,000 rigorously adjudicated and extensively characterized patients. [21] The ARDS subphenotypes have been consistently validated across multiple cohorts and research groups [22] [23] [24] . In contrast, the high-compliance "L" phenotype, for the reasons detailed above, seems inherently unstable. Whereas it was initially described as constituting 70-80% of COVID-19 ARDS cases [20] , it now is defined as a rarely encountered extreme of a one-dimensional physiologic continuum. [25] In comparison, the previously identified ARDS subphenotypes represent distinct clinical "clusters" of patients, informed by measurements across organ systems and physiologic domains in secondary analyses of well curated cohorts of patients. [21] Yet despite this robustness, we would recommend that any therapeutic interventions for which benefits have been observed in these hyperinflammatory and hypoinflammatory phenotypes require testing in prospective trials before they are implemented into clinical practice, as they were derived using secondary analyses.

The objective of our editorial was to challenge the subclassification of patients with COVID-19 that frequently occurred in the early weeks of the pandemic based on "discussions" and "close observations" before they became entrenched dogmas. [1] An unintended consequence of such a challenge may be that it evokes negative emotions with the reader, especially in these troubling and polarising times. We were, therefore, saddened to learn that our Editorial caused irritation among Gattinoni et al. [25] . While we vehemently disagree that "observations of Bos and colleagues are expressed with a tone which goes beyond healthy and reasonable scientific debate," we acknowledge that our essay was interpreted as such by the correspondents and that is regrettable. We would like to clarify that the particular quoted sentences from our Editorial that prompted the authors' irritation and concern were aimed at premature phenotyping in general. It is an unfortunate misunderstanding that the authors assumed we were speaking directly and exclusively about them. For the reasons outlined above, however, we stand by our Editorial.

Drs. Gattinoni et al. state that "the 'L & H' phenotypes were not intended to be tightly descriptive nor mutually exclusive 'bins' into which each patient falls," yet this is what is usually implied by disease "subphenotypes" or "endotypes". [26] As described in our Editorial, for phenotypes to be purposeful, they should be discrete, robust, generalizable, easily-identifiable, and ideally, have an actionable intervention. Seemingly, almost none of these conditions are met in the current case. As an illustration, the problem with loosely-defined phenotypes, as described by the correspondents, emerges when we try to precisely identify, at the bedside, who the patients are that the correspondents "hoped to help prevent use of high PEEP when there is no benefit, and equally important, to avoid maintaining low pressures when higher pressures can be beneficial." It is difficult to conceive how these phenotypes would be identifiable using quantifiable variables and when precisely to intervene, given that the authors themselves concede that these phenotypes are temporally dynamic, neither mutually-exclusive nor discrete, and that "usually, there is overlap".

We agree entirely with the correspondents that ventilator management should be individualized to each patient's physiology, and have never argued otherwise. In the theoretical "limit case" of a patient with normal lung compliance and minimal lung recruitability, we would similarly discourage use of high levels of PEEP, as surely would most practicing intensivists. We merely disagree with the correspondent's conclusions regarding the prevalence of these theoretical patients based on data from 16 patients [20] , as well as their subsequent recommendations to deviate from safe ventilatory practice for COVID-19 patients based on this limited data. [27] As catalogued above, the available data show that this purported "phenotype" is rarely encountered in COVID-19 ARDS.

Unexpectedly, the correspondents request evidence from us that their efforts at phenotyping have caused harm. Basic scientific convention, however, mandates that before they implore the field to deviate from usual practice, the burden is rather on them to demonstrate the benefits and safety of their proposed phenotyping scheme and linked interventions using robust scientific studies. Thankfully for our patients, that is how best medical science works -primum non nocere. Putting aside the complete absence of efficacy data, the validity of the physiological basis for their proposed interventions for these phenotypes has also been recently questioned. [28, 29] We hope our response clarifies for the correspondents and readers that we in no way dispute the underlying heterogeneity of ARDS, nor the uniqueness of COVID-19, nor the need for patient-tailored therapy; indeed, much of our research is focused on attaining this. We merely insist that phenotyping be done using careful, data-driven approaches.

To paraphrase Dr. Rajendram, rather than strengthening a house of cards, we should instead aspire to build a foundation out of sturdier, more lasting materials: in this case agile, yet robust, scientific studies using a responsible, data-informed approach. At this stage of the pandemic, sufficient data points exist to equip us to advance from anecdotebased intuitions to evidence-informed science.

COVID-19 conundrum: Clinical phenotyping based on pathophysiology as a promising approach to guide therapy in a novel illness

Covid-19 in Critically Ill Patients in the Seattle Region -Case Series

Subphenotyping ARDS in COVID-19 Patients: Consequences for Ventilator Management

Respiratory Pathophysiology of Mechanically Ventilated Patients with COVID-19: A Cohort Study

ICU and Ventilator Mortality Among Critically Ill Adults With Coronavirus Disease

Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study

Respiratory Mechanics and Gas Exchange in COVID-19 Associated Respiratory Failure

Respiratory Mechanics of COVID-19 vs. Non-COVID-19 Associated Acute Respiratory Distress Syndrome

Does Not Lead to a "Typical" Acute Respiratory Distress Syndrome

Potential for Lung Recruitment and Ventilation-Perfusion Mismatch in Patients With the Acute Respiratory Distress Syndrome From Coronavirus Disease

Clinical phenotypes of SARS-CoV-2: Implications for clinicians and researchers

Reference values for dynamic and static pulmonary compliance in men

Pulmonary mechanics during general anaesthesia. The influence of mechanical irritation on the airway

Acute respiratory distress syndrome: the Berlin Definition

Postmortem Examination of Patients With COVID-19

Pulmonary Vascular Endothelialitis, Thrombosis, and Angiogenesis in Covid-19

COVID-19 Related Acute Respiratory Distress Syndrome: Not so Atypical

Is a "Cytokine Storm" Relevant to COVID-19?

COVID-19 pneumonia: different respiratory treatments for different phenotypes?

Subphenotypes in acute respiratory distress syndrome: latent class analysis of data from two randomised controlled trials

Acute Respiratory Distress Syndrome Subphenotypes Respond Differently to Randomized Fluid Management Strategy

Identification and validation of distinct biological phenotypes in patients with acute respiratory distress syndrome by cluster analysis

Stability of ARDS subphenotypes over time in two randomised controlled trials

COVID-19 phenotypes: leading or misleading?

Toward Smarter Lumping and Smarter Splitting: Rethinking Strategies for Sepsis and Acute Respiratory Distress Syndrome Clinical Trial Design

Management of COVID-19 Respiratory Distress

COVID-19-associated acute respiratory distress syndrome: is a different approach to management warranted?

Caution about early intubation and mechanical ventilation in COVID-19