Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area | Critical Care Medicine | JAMA | JAMA Network
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New York City coronavirus update from Mitchell Katz, MD, President and CEO of NYC Health + Hospitals, the largest municipal public health system in the United States. Recorded April 13, 2020.

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    25 Comments for this article
    COVID-19 and Endothelial Dysfunction
    Gaetano Santulli, MD, PhD | Albert Einstein College of Medicine, Montefiore University Hospital, New York, NY, USA and Federico II University, Naples, Italy.
    In their interesting article (1), Dr. Richardson and colleagues reported hypertension, cardiovascular disease, obesity, and diabetes mellitus, as frequent comorbidities in patients with COVID-19, consistent with previous studies (2, 3). A common underlying feature of all these disorders is endothelial dysfunction. Furthermore, all of the co-factors bound by SARS-CoV-2 coronavirus to access host cells, including ACE2, CD147, sialic acid receptor, and TMPRSS2, are expressed by human endothelial cells (4). Hence, we hypothesize that SARS-CoV-2 could directly affect endothelial cells (4), explaining all systemic manifestations observed in COVID-19 patients, including thrombotic complications (2, 5). If our theory is correct, drugs that have been shown to ameliorate endothelial function, such as modulators of the renin-angiotensin-aldosterone system, anti-coagulants, statins, and anti-inflammatory drugs, could be helpful in COVID-19 patients.

    The authors show in the supplementary tables some data regarding the percentage of patients who were receiving ACE inhibitors and angiotensin II receptor blocker. Can they perform a multivariate analysis to verify whether such treatment(s) had any effect on the severity of disease? Equally important, the authors show an increased average value of D-dimer in their population: do they have any data on actual coagulation disorders?


    (1) Richardson S, Hirsch JS, Narasimhan M, et al. Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area. JAMA. 2020, in press.
    (2) McMichael TM, Currie DW, Clark S, et al. Epidemiology of Covid-19 in a Long-Term Care Facility in King County, Washington. N Engl J Med. 2020; in press.
    (3) Shi S, Qin M, Shen B, et al. Association of Cardiac Injury With Mortality in Hospitalized Patients With COVID-19 in Wuhan, China. JAMA Cardiol. 2020; in press.
    (4) Sardu C, Gambardella J, Morelli MB, et al. Is COVID-19 an Endothelial Disease? Clinical and Basic Evidence. Preprints 2020, 2020040204; doi: 10.20944/preprints202004.0204.v1.
    (5) Tang N, Li D, Wang X and Sun Z. Abnormal Coagulation Parameters are Associated with Poor Prognosis in Patients with Novel Coronavirus Pneumonia. J Thromb Haemost. 2020;18:844-847.

    Jessica Gambardella, PhD
    Albert Einstein College of Medicine, New York, NY, USA and Federico II University, Naples, Italy;

    Celestino Sardu, PhD
    Vanvitelli University, Naples, Italy;

    Gaetano Santulli, MD, PhD
    Albert Einstein College of Medicine, Montefiore University Hospital, New York, NY, USA and Federico II University, Naples, Italy.
    Androgens are Key to Vulnerability
    Carlos Wambier, MD, PhD | Department of Dermatology, Warren Alpert Medical School - Brown University, RI, USA
    Richardson et al (1) bring numbers from the American epicenter and important data regarding known male gender vulnerability (2): the drastic difference of over 6 times more male fatalities in a very productive age range (40-49 years) and approximately two times more male admissions from 30-49 years.

    One biologic explanation for this vulnerability is that Transmembrane Protease, Serine 2 (TMPRSS2), the protease that primes the Spike protein of the virus for infectivity, is an androgen-expressed protein (3). TMPRSS2 is expressed in the adult lungs (4). Both TMPRSS2 and Angiotensin Converting Enzyme 2 (ACE2), the virus receptor, are expressed in
    male and female lungs (5). Interestingly, the genes of ACE2 and the Androgen Receptor are located on the X chromosome (3).

    Excess androgen activity is likely to produce excessive TMPRSS2, increasing viral infectivity. Individuals with excess androgen activity usually present with hyperandrogenic phenotypes, including a distinct, cumulative, irreversible feature: pattern scalp hair miniaturization (androgenetic alopecia) (6).

    In a preliminary study in 41 Spanish men admitted due to severe COVID-19, mean age was 58 years (range 23-79) and 71% had androgenetic alopecia (7).

    Male vulnerability to SARS-CoV-1 has well studied in murine experiments (8). Male's lungs presented more viral load/damage. Females presented resistance and ovariectomy increased their vulnerability. Prophylaxis with the anti-androgen agent flutamide improved survival: 20% of the treated vs 0% of the control group among males (8). Remdesivir failed to demonstrate benefit in experimental male mice survival (9). Anti-androgen therapy remains to be tested in humans as a possible therapy to modify this well-known host risk factor.


    1. Richardson S, Hirsch JS, Narasimhan M, et al. Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area. JAMA. 2020;10022:1-8.
    2. COVID-19 sex-disaggregated data tracker Sex, gender and COVID-19. Global Health 50/50. Published 2020. Accessed April 22, 2020.
    3. Wambier CG, Goren A. SARS-COV-2 infection is likely to be androgen mediated. J Am Acad Dermatol. April 2020. doi:10.1016/j.jaad.2020.04.032
    4. Jacquinet E, Rao N V., Rao G V., Zhengming W, Albertine KH, Hoidal JR. Cloning and characterization of the cDNA and gene for human epitheliasin. Eur J Biochem. 2001;268(9):2687-2699. doi:10.1046/j.1432-1327.2001.02165.x
    5. Wang X, Dhindsa RS, Povysil G, et al. Transcriptional inhibition of host viral entry proteins as a therapeutic strategy for SARS-CoV-2. Preprints. 2020;(2020030360). doi:10.20944/preprints202003.0360.v1
    6. Goren A, McCoy J, Wambier CG, et al. What does androgenetic alopecia have to do with COVID-19? An insight into a potential new therapy. Dermatol Ther. 2020:e13365. doi:10.1111/dth.13365
    7. Goren A, Vano‐Galvan S, Wambier C., et al. A preliminary observation: male pattern hair loss among hospitalized COVID‐19 patients in Spain – A potential clue to the role of androgens in COVID‐19 severity. J Cosmet Dermatol. 2020; doi:10.1111/jocd.13443
    8. Channappanavar R, Fett C, Mack M, Ten Eyck PP, Meyerholz DK, Perlman S. Sex-Based Differences in Susceptibility to Severe Acute Respiratory Syndrome Coronavirus Infection. J Immunol. 2017;198(10):4046-4053. doi:10.4049/jimmunol.1601896
    9. Sheahan TP, Sims AC, Leist SR, et al. Comparative therapeutic efficacy of remdesivir and combination lopinavir, ritonavir, and interferon beta against MERS-CoV. Nat Commun. 2020;11(1). doi:10.1038/s41467-019-13940-6
    Mortality of ICU admitted patients
    Ornella Piazza, MD | University of Salerno
    In this interesting paper, Richardson et Al report a very high ICU mortality rate.

    In one month, 373 cases were being treated in the ICU (14%). A total of 320 patients received mechanical ventilation and 282 died, with a mortality of 88,1%. The overall death rate for COVID-19 for patients admitted to critical care is much higher than for other viral pneumonias (about 22.2%).

    Which scenarios can be considered when interpreting deaths from COVID-19?
    What about patients with severe hyperglycemia?
    Rajeev Gupta, MD, DM (Cardiology) | Mediclinic Al-Jowhara, and Mediclinic Al Ain Hospital, Al Ain, UAE
    It is interesting to observe the pattern of illness.

    Our brief experience in the UAE is almost the same. In addition, we observed very high plasma glucose even among previously non-diabetic patients with/without acidosis. Maybe this virus affects the pancreas and blocks insulin secretion.

    Secondly, we observed that despite the clinical and radiologic picture of COVID-19, many patients had negative nasopharyngeal swab, even when done 3 times.

    Thirdly, many patients responded to hydroxychloroquine (we observed).
    Very Misleading
    John Yuill, MD | Hospitalist, Community Hospital, TN
    Several media outlets have reported the 88% mortality rate without explaining that the many patients who remained hospitalized at the time the study ended are excluded, and that therefore it is too soon to determine final mortality rate.

    See for a cogent explanation of the bias in this study.
    Mechanical Ventilation in COVID19 - Not Routine ARDS!
    Michele Nanna, Assistant Professor of Medicine | Albert Einstein Coll of Medicine
    With all the emphasis on the availability of ventilators in the current pandemic it is important to remember that ventilators are not self-driving machines. Qualified personnel are required to operate them. Injuries can derive from the improper use of the devices. In fact, each patient may require different ventilation strategies depending on the presence of coexisting lung disease on which ARDS is superimposed. Therefore all recommendations offered may not apply to an individual patient. Even in presence of ARDS without underlying lung disease injury can occur and strategies should be implemented to avoid additional damage.

    For example, PEEP
    traditionally has been used to improve oxygenation while reducing Fi02 . When trying to minimize iatrogenic complications of mechanical ventilation PEEP is a modality that can potentially minimize the injury caused by ventilation at low lung volumes by recruiting poorly ventilated lung units and keeping them open. The critical issue is how to define the ideal PEEP level in an individual patient without causing damage to other lung units. This can be monitored by CT scan or oxygenation response, both imperfect methods. PEEP levels often are estimated on the basis of a PEEP / Fi02. Higher PEEP levels have been
    associated with decreased mortality in ARDS patients with Pa02 / Fi02 < 200mm Hg but not in patients with higher Pa02 / Fi02 ratios. PEEP level can also be guided by esophageal pressure with the goal of keeping positive P1 at end expiration positive, resulting in increase PO2 levels and respiratory compliance . However to my last check most units were not equipped with esophageal pressure monitoring device. Combination of plateau pressure and PEEP can provide guidance for choosing optimal lung protective ventilation strategy.

    APRV modality has shown advantages in patients with ARDS but I am not sure how often it is used in this settings

    Even the use of neuromuscular blockers in the management of ventilated COVID19 patients is controversial

    These comments are only a partial list of the complexities facing those managing patients with ARDS on mechanical ventilation
    Mortality Among Patients Receiving Invasive Mechanical Mentilation: Know Your Denominator
    Jason Maley, M.D. | Massachusetts General Hospital and Beth Israel Deaconess Medical Center
    In this article, Dr. Richardson and colleagues report:"Mortality for those requiring mechanical ventilation was 88.1%." This is based on 282 deaths at the time of censoring out of 320 total "discharged alive and dead" patients receiving invasive mechanical ventilation. However, a closer examination of table 5, row 1 reveals that 1151 total patients received invasive mechanical ventilation in the cohort over the study period. 831 of these patients (72%) remain alive in the hospital. This is not openly discussed in the article, aside from a brief allusion to the problem at the end of the limitations section. Unfortunately, the 88.1% mortality has already gained widespread attention in the press and appears to have misled many to believe that this must represent the "true" mortality rate of ventilated patients. This conclusion cannot be drawn from these data.
    Mortality Outcomes by Inpatient ACEi/ARB treatment
    Antonio J Romero Puche, MD | Hospital General Universitario Reina Sofia, Murcia (Spain)
    Recently Zhang et al (1) reported a cohort of 1100 hospitalized COVID-19 patients who were hypertensive. Patients receiving inpatient ACEi or ARB treatment had far lower mortality in both unadjusted (3.7 vs 9.8%) or adjusted models (HR 0.42, CI 95% 0.19-0.92). These data seem to contradict that observation, but paying attention to eTable 2, it can be deducted that figures shown in the text refer to home medication.

    In this paper's patient cohort, there was an important switch between home and inpatient treatment (only half patients previously on ACEi/ARBs continued them during hospitalization and, according to data in
    the text and eTable 2, 107 out of 953 patients not taking ACEi or ARBs previously were switched to them during hospitalization). So, as home treatment was poorly related to inpatient treatment, it would be interesting to show supplementary data of mortality according to ACEi/ARBs usage during hospitalization and verify if they are consistent with a reduction in mortality.


    1. Association of Inpatient Use of Angiotensin Converting Enzyme Inhibitors and Angiotensin II Receptor Blockers with Mortality Among Patients With Hypertension Hospitalized With COVID-19 | Circulation Research. Accessed April 22, 2020.
    Biased Estimation of Mortality in Setting of Administrative Censoring
    Stephen Seliger, MD, MS | University of Maryland School of Medicine
    There is a substantial error in the estimation of mortality among patients requiring mechanical ventilation which I fear has led to a biased (overly high) estimate. This is the estimate (88%) that has been cited so often in the media.

    Based on the data presented in Table 5 of the manuscript, 1,151 patients hospitalized for COVID-19 required mechanical ventilation (top row of table). Among this group 282 died while hospitalized, 38 were discharged from hospital, and 831 remained alive and hospitalized at the time that data were administratively censored as of April 4th, 2020. The authors estimated
    the cumulative incidence of mortality as 282 deaths divided by a denominator of 320 (the number of persons who either died or were discharged), excluding the remaining 820 hospitalized patients.

    This approach to estimating cumulative mortality grossly distorts the actual death rate in mechanically ventilated patients. The Kaplan-Meier estimator, or other method for estimating censored survival, would provide a more accurate estimate of cumulative incidence of mortality, which is almost certainly much lower than 88%. As the authors’ estimate of 88% mortality among mechanically ventilated patients with COVID-19 has been widely reported in the lay press already, we are concerned that it will influence clinical decision making. Although we appreciate the enormous challenges in conducting large-scale epidemiologic research in the setting of an ongoing national health-care crisis and pandemic, it is important that clinical decision making be informed by accurate and non-biased estimates of outcomes.
    Methodologic flaws that lead to overestimates of mortality from COVID-19
    David Ost, MD | MD Anderson Cancer Center
    I read the report by Richardson and colleagues on the outcomes of COVID-19 patients in NewYork (1). The authors report that 88.1% of patients requiring mechanical ventilation died. This is potentially misleading and subject to misinterpretation.

    The study enrolled 5,700 patients hospitalized with COVID-19 during a 35-day period from March 1 to April 4, 2020. Outcome analysis on the 2,634 patients who died or were discharged was performed. The remaining 3,066 patients that were alive and remain in the hospitals were excluded from analysis. Mechanical ventilation was required in 320 (12.1%) of the 2,634 patients in the analysis, and
    death occurred in 282 (88.1%) of these patients. Among the 3,066 patients still alive, 831 (27.1%) required mechanical ventilation but, because they had not been discharged, they were excluded from the analysis.

    Mechanical ventilation is a marker of severity of illness and many of the patients on mechanical ventilation probably had acute respiratory distress syndrome (ARDS). ARDS carries a mortality of approximately 40%, with median time to death being 7 to 10 days (2, 3). Recovery is slow, with median hospital length of stay amongst survivors being 21 days for women and 25 days for men (4). Now, consider a patient with ARDS in this study admitted on March 14th who is destined to survive, and that he/she requires 21-25 days to recover. This patient will likely be discharged after April 4, excluding him/her from the analysis. Conversely, because death occurs earlier, a patient admitted at the same time who dies will be included in the analysis. This form of bias favoring inclusion of deaths while excluding survivors results in an overestimate of mortality.

    How can we arrive at a more accurate estimate? We cannot assume all remaining inpatients currently alive will survive. Survival analysis techniques, such as the Kaplan-Meier method and Cox models can solve these problems. Why is proper methodology important? Respected public figures and journalists will quote the 88% mortality, and patients and their families will be frightened. The governor of New York has repeatedly cited a mortality greater than 80% amongst ventilated patients. However, that number is probably wrong. COVID-19 reported mortality in critically ill patients in other studies has varied, ranging from 22%-62%.5,6 The public will reasonably ask why is mortality excessively high in New York? Is quality of care poor? The answer is not that quality of care is poor, but rather that the data analysis is flawed.

    David Ost, MD, MPH
    Professor of Medicine
    MD Anderson Cancer Center


    1. Richardson S, Hirsch J, Narasimhan M, Crawford J, McGinn T, Davidson K. Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area. JAMA. 2020;in press.
    2. Esteban A, Frutos-Vivar F, Muriel A, et al. Evolution of mortality over time in patients receiving mechanical ventilation. Am J Respir Crit Care Med. 2013;188(2):220-230.
    3. Stapleton RD, Wang BM, Hudson LD, Rubenfeld GD, Caldwell ES, Steinberg KP. Causes and timing of death in patients with ARDS. Chest. 2005;128(2):525-532.
    4. McNicholas BA, Madotto F, Pham T, et al. Demographics, management and outcome of females and males with acute respiratory distress syndrome in the LUNG SAFE prospective cohort study. Eur Respir J. 2019;54(4).
    5. Yang X, Yu Y, Xu J, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respi
    Editors' Note: Clarification and Article Correction
    Michael Berkwits, MD, MSCE | JAMA Network
    JAMA appreciates the above comments noting the potentially misleading nature of the report of 88% mortality in ventilated patients, and noting possible math errors in Table 2.

    On April 24 a clarification was published and the article was corrected (1). The clarification states:

    In the Abstract, Results paragraph, the sentence reporting mortality for patients receiving mechanical ventilation should read, “As of April 4, 2020, for patients requiring mechanical ventilation (n = 1151, 20.2%), 38 (3.3%) were discharged alive, 282 (24.5%) died, and 831 (72.2%) remained in hospital.” This same sentence was added to the second paragraph of the
    Results section in the text. In the first paragraph of the text Results, the sentence about test results should read, “The first test for COVID-19 was positive in 5517 patients (96.8%), while 183 patients (3.2%) had a negative first test and positive repeat test.” In the Discussion, a paragraph was added to clarify the calculation of mortality rates. In Table 2, the number (%) of patients with concurrent entero/rhinovirus infection should be “22 (52.4).”

    We hope this clarifies the findings.


    1. Clarification of Mortality Rate and Data in Abstract, Results, and Table 2. JAMA. Published online April 24, 2020. doi:10.1001/jama.2020.7681. Access at
    CONFLICT OF INTEREST: Digital Media Editor, JAMA Network
    On the Treatment of Right-Censored Outcome Data
    Matthew Pappas, MD, MPH | Cleveland Clinic, Cleveland, OH
    We are grateful for the contribution Richardson and colleagues have made to the literature in difficult times [1]. In it, they describe the characteristics and co-morbidities of 5700 patients admitted to New York hospitals with COVID19.

    Although they purport to describe outcomes for this same group of patients, only 2634 patients had been discharged or had died by the end of the study. The rest remained hospitalized, and their outcomes are yet to be determined. Nevertheless, the authors report the outcomes for the discharged patients as though they applied to the entire cohort. Particularly concerning was the conclusion that
    "Mortality for those requiring mechanical ventilation was 88.1%". This figure was widely reported in the mainstream press [2] and may be misinterpreted by some as evidence that mechanical ventilation in cases of COVID19 is generally futile. In fact, at the end of the study, of the 1151 ventilated patients, 38 patients had been discharged alive and 282 died. The majority of subjects (831) were still hospitalized.

    When research subjects do not have an event during a period of observation, they are generally right-censored. Calculating mortality using only those subjects who have had an outcome by the end of the observation period offers a biased estimate of mortality, which Richardson and colleagues acknowledge as a limitation. If a time-to-event analysis is not performed, we think it would be more accurate to communicate the current mortality as approximately 24.5% (282/1151). While more of these patients will undoubtedly die, there is no reason to assume the hospital mortality will approach 90%. In fact, mortality may be no worse than other forms of ARDS, which carries in-hospital mortality of 40% [3]. This is an important distinction, because decision-making may well be different for conditions whose expected mortality is 1 in 4, or even 1 in 2, compared to 9 in 10.

    We again thank Richardson and colleagues for sharing their data and experience, but we hope others will not be overly discouraged by their conclusions and avoid potentially life-saving ventilation based on these data.

    Matthew A. Pappas, MD, MPH*†
    Moises Auron, MD*
    Michael B. Rothberg, MD, MPH†‡

    1: Richardson S, Hirsch JS, Narasimhan M, et al. Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area. JAMA. 2020 Apr 22. doi: 10.1001/jama.2020.6775.
    2. Cha AE. Almost 90 percent of coronavirus patients on ventilators died in large U.S. study - The Washington Post [Internet]. 2020 [cited 2020 Apr 24]. Available from:
    3: Epidemiology, Patterns of Care, and Mortality for Patients With Acute Respiratory Distress Syndrome in Intensive Care Units in 50 Countries. Bellani G, Laffey JG, Pham T, Fan E, Brochard L, Esteban A, Gattinoni L, van Haren F, Larsson A, McAuley DF, Ranieri M, Rubenfeld G, Thompson BT, Wrigge H, Slutsky AS, Pesenti A, LUNG SAFE Investigators, ESICM Trials Group. JAMA. 2016 Feb;315(8):788-800.

    *: Department of Hospital Medicine, Cleveland Clinic
    †: Center for Value-based Care Research, Cleveland Clinic
    ‡: Department of Internal Medicine, Cleveland Clinic
    Arturo Tozzi, Pediatrician | University of North Texas
    This study, once again (Guan et al., 2020), points towards smokers as counterintuitively affected by COVID-19 in the same way (if not less) than non-smokers. It’s time to understand why the otherwise impaired lungs of smokers are not more sensitive to severe COVID-19 than non-smokers. The hypothesis of a decreased amount of ACE2 receptors is smokers is flebile, because SARS-Cov-2 enters pneumocytes also through other receptors (Milanetti et al., 2002; Iacobellis et al., 2020), and because old animals display a decrease in such receptors, compared with younger animals (Xie, 2006). We suggest to take bronchoalveolar lavage fluid from SARS-Cov-2-negative individuals and to test it with coronavirus-infected fluids, to understand whether smokers display a humoral protective factor that is able to decrease viral load.


    1) Guan W-j, Ni Z-y, Hu Y, Liang W-h, Ou C-q, et al. 2020. Clinical Characteristics of Coronavirus Disease 2019 in China. NEJM, February 28, 2020. DOI: 10.1056/NEJMoa2002032.
    2) Iacobellis G. 2020. COVID-19 and diabetes: Can DPP4 inhibition play a role? Diabetes Research and Clinical Practice. 162, 108125.
    3) Milanetti E, Miotto M, Di Rienzo L, Monti M, Gosti G. 2020. In-Silico evidence for two receptors based strategy of SARS-CoV-2. BioRxiv, doi:
    4) Xie X, Chen J, Wang X, Zhang F, Liu Y. 2006. Age- and gender-related difference of ACE2 expression in rat lung. Life Sci, 78(19):2166-71

    Arturo Tozzi
    Center for Nonlinear Science, Department of Physics, University of North Texas, Denton, Texas, USA
    Further Information Might Have Provided Better Contextual Analysis
    Basil Fadipe, MBBS | Consultant Surgeon . Justin Fadipe Centre/ All Saints College of Medicine
    Richly informative, but the study was silent on the virological and serological status of the patients at the endpoints chosen; death and discharge .

    It would have been even more instructive were this information obtained and / or supplied.

    a. The former for obvious reasons: infection status not just on admission or treatment initiation but also at the chosen end points

    b. The latter to generate a database on the immunologic response or inertia as the patients recover or succumb .

    c. The immunological status for the readmitted cases should also count for
    something in assessing disease evolution vis a vis clinicopathologic behaviors .

    The relative lymphopenia mentioned and its greater severity in older or more morbid patients might be brought into better context were the antibody status also known in the various cases.
    Male Sex and COVID
    Gary Wittert, MBBch | University
    There are clearly marked disparities between males and females. It would be useful to see data tabulated by sex across all fields for all reports such as this one.
    HIV and COVID-19
    George Siberry, MD, MPH | Public Health
    The summary by Richardson and colleagues of COVID-19 patients hospitalized in NYC is instructive and appreciated. I note that there were 43 cases of COVID-19 that occurred in people living with HIV. The authors are implored to provide a summary of the presentations, characteristics and outcomes of this important subpopulation, as there remains very little published information about COVID-19 in the context of HIV infection.
    Clinical observations appear highly consistent with genomics-guided mapping of COVID-19 targets
    Gennadi Glinsky, MD, Ph.D. | University of California San Doego
    Genomics-guided tracing of SARS-CoV-2 targets in human cells revealed very unusual, perhaps unique features of this virus. It highlighted discordant patterns of testosterone vs estradiol impacts on SARS-CoV-2 targets suggesting a plausible molecular explanation of the apparently higher male mortality during coronavirus pandemic (1). These findings are in agreement with several observations regarding discordant effects of androgens and estrogens described in the comments on this excellent clinical work. Of major concern is the ACE2 and FURIN expression in many human cells and tissues, including immune cells, suggesting that SARS-CoV-2 coronavirus may infect a broad range of cellular targets in the human body. Infection of immune cells may cause immunosuppression, long-term persistence of the virus, and spread of the virus to secondary targets. A similar path to the disease's broad impact is highlighted by the potential susceptibility to infection of endothelial cells denoted in comments. Clearly, testing must be expanded beyond individuals with classic symptoms of upper respiratory tract viral infection.


    1. hemRxiv. Preprint. 
    An Idea for A Data Driven Mobile App for Personalizing COVID-19 Risks
    Ken Kolkebeck, BSEE | Retired Software Entrepreneur
    As a former data driven software application person I have an idea for an app that I think could change the game; I know, this is a big claim. Doctors who are interested in this data and also the development of apps to help society cope are the folks I want to reach, in hopes you might pass this idea around. This is a big claim but I think it can make a meaningful impact on how we as people come to grips with COVID-19. But it needs to be built and deployed.

    I think laypeople have been
    troubled trying to understand and rationalize the fear we should or should not have related to COVID-19. What we hear and see is very confusing. Yet data are emerging, some in your study which I reference in the attachment, that with a bit of data science and software engineering will help us all.

    Very simply my idea is for a mobile app that allows anyone to enter data about themselves and get a personalized understanding of the severity risk should they get the virus. It also would allow them to share this with other members of their family and friends so that they can assess the impact of being around each other.

    A product brief is attached. I don't want anything for this idea although I would love to help in developing it. Feel free to share it far and wide if you know people who can help turn it into reality. this link will get you to my Product Brief:
    Covid19/HIV+ In NYC
    Pablo Pella, Chief Medical officer | Hope Across the Globe
    Do you know how many of the 43 patients with HIV comorbidity got admitted to the ICU and how many cases were fatal? Also, what was the average length of stay?.
    Positive Disease Feedback by Reinhalation of Viral Particles
    Richard Decker, PhD EE | Emeritus Professor, Lehigh University
    Is anyone currently considering the possibility of re-inhalation of (invisible) viral particles while patients are being mechanically ventilated? In advanced stages, the patient should be generating and exhaling large quantities of virus from lung cells that have reproduced the virus. Since these particles are prevented from exiting the ventilator (by filtration) to prevent contamination of the hospital environment, they have nowhere to go. If re-inhaled, they may increase the rate of progression of the disease. Is there any way to measure this effect, or is there a reason to discount the possibility of this mechanism of positive feedback?
    Risk Factors for COVID-19?
    Muriel Gillick, MD | Harvard Medical School
    Richardson et al report that among 5700 consecutive patients with severe COVID-19 admitted to any of twelve hospitals in the greater New York City area, the most common co-morbidities were hypertension, obesity, and diabetes. To assess the importance of this observation, comparisons with rates in the population as a whole and age-adjusted rates would be very useful.

    In the case of hypertension, the observed rate was 56.6 percent, very similar to the 60 percent rate reported among Americans over age 65 in the general population (1) and considerably higher than the rate of 32.2 percent found in the general population
    aged 40-59 (2).

    In the case of diabetes, the observed rate of 33.8 percent among COVID-19 patients is similar to the rate of 27 percent found among the general population aged 65 and older, and markedly higher than the 17.5 percent found in the general population of 45-64-year-olds (3). 

    Finally, the 47.7 percent rate of obesity in the COVID-19 sample is comparable to the rate among adults generally: 44.8 percent of 40-59-year-olds and 42.8 percent of those over age 60 are obese (4).

    Without knowing the age-specific rates of diabetes and hypertension in the COVID-19 patients, we cannot determine whether these diagnoses are risk factors and, if they are, to how great an extent. Consider three possibilities. Since the median age of the COVID-19 patients in the New York study is 63, roughly half are over age 65 and half under 65. This means that if the observed average rate of hypertension in the COVID-19 is the same for all age groups (one possibility), then the rate in the older age group is borderline lower than in the general elderly population (57 vs 60) and the rate in the younger patients is dramatically higher (57 vs 32). A second, even less plausible possibility is that the rate of hypertension in the older COVID-19 patients is lower than among their healthy counterparts, say 44 percent, making it a protective factor, and the rate in younger COVID-19 patients is very much higher than in their healthy counterparts, say 70 percent. A third and perhaps most likely possibility is that the observed average rate of hypertension in the COVID-19 patients reflects higher than typical rates in both young and old, say 44 percent in the young and 70 percent in the old. In only one of these scenarios is hypertension actually a risk factor for older patients and in that instance its contribution may be modest. The same argument can be made for diabetes. Obesity does not appear to be a risk factor at all since its prevalence in the COVID-19 population is the same as in the population at large, regardless of age.

    Cautioning older individuals with hypertension or diabetes that they are at high risk and conversely, reassuring those without these conditions that they are at low risk is unwarranted without more convincing analysis.


    The Cost of Treating COVID by Sheltering in Place
    George Niedt, MD, MBA | Columbia University, Valegos College of Physicians and Surgeons
    We are closing businesses and halting economic activity to “flatten the curve”. By cutting down on the number of infections we are lowering our need principally for respirators. According to the Harvard epidemiology website (1), in their worst case scenario (60% of Americans infected over a 6 month period), we are short 394,865 beds. If each of these beds is occupied at full capacity for the entire 6 month period, then 18 patients can be put in each bed over the 6 month period, or a total of 7,107,865 patients. However, the Harvard data does not account for how ineffective respirators have been in treating COVID19, as shown in this study. The survival of the patients on respirators is 11.8%, and only 2.7% for those over 65; thus in the best case scenario, we can save at most 838,728 lives. In this study the average age of death is approximately 74 years. The average number of years of life left at this age is 12 (US Gov. actuarial tables), therefore at best we can save 10,064,736 years of life by flattening the curve. As most of these folks have 2 or more comorbidities, we could estimate that the years of life saved are probably half of that, and quality years of life even less.

    What are the costs associated with this? Well there are direct costs of approximately $40k for ICU care for each patient, regardless of whether they survive. Because only 11.8% of patients survive, that means a direct cost of $336,000 per patient. By closing the economy, we have already lost $50 trillion in market capital in the stock market. It is also estimated (by the Wall Street Journal) that we will lose approximately $1.5 trillion in lost GDP, and we have already authorized $2 trillion in federal relief, for a total of $3.5 trillion. This amounts to approximately $4,172,759 in indirect costs per life saved, a total cost of $4,508,759 per life, or a maximum of $375,729 per year of life saved, using an average life span, not the reduced lifespan of patients with comorbidities. This is an extraordinarily high number, but it doesn’t include the $50 trillion dollars of stock market losses. If we add these, then the numbers are more than 14 times as high. Normally, we regard $30K or less per year of life saved as a reasonable medical cost. The cost of COVID is 10 to 100 times that.
    Things are worse for folks over 65. Only 2.7% of these patients survived mechanical ventilation: a direct cost of $1,480,000 per survivor. Seniors account for 56% of the ventilator use in this study. Using numbers analogous to those above, 3,980,404 beds would be used by seniors but only 107,471 senior lives would be saved by flattening the curve. If we apply 56% of GDP loss to just seniors, that amount to $18,273,478 per life saved (indirect) and 1,480,000 in direct costs, for a total of $19,717,478 per life or $2,075,524 per year of life saved, or likely twice that as these patients have comorbidities.

    In sum, given the data, the cost of flattening the curve is high, and not cost effective vis a vis other medical treatments. Clearly, measures such as mask wearing, hand washing and social distancing without sheltering in place, would be much more cost effective, and not have ruined the economy. Sadly, much of this information was available in February, from data in Wuhan (2). We could have used it to make more rational decisions.


    2. Lancet
    Male Sex as a Risk Factor for COVID-19
    Suhail Aamar, MD, MSc, MA | Hadassah Mount Scopus Medical Center- Hebrew University, Jerusalem, Israel
    Richardson et al report numbers from the American epicenter and important data regarding known male gender vulnerability, besides hypertension, cardiovascular disease, obesity, and diabetes mellitus as frequent comorbidities and risk factors in patients with COVID-19 (1).

    The male preponderance is alarming and needs further validation. According to their report, compared to females there is a prominent increased rates of COVID-19 and higher risk of severity and mortality in males in all adult age intervals; over 6 times more male fatalities in age range (40-49 years) and a general more male admissions.

    Male risk raises many presumed explanations
    for sex vulnerability related to biological, molecular, immunological, and behavioral differences. Androgen-related expression of different genes and molecules is an example, such as Transmembrane Protease, Serine 2 (TMPRSS2), the protease that primes the Spike protein of the virus for infectivity (2).

    Another explanation for male vulnerability for COVID-19 could be simply their tendency to grow facial hair; this sex-related feature of facial hair may interfere with masking adjustment and effectiveness. Neglected facial hair of admitted, and if sedated, COVID-19 patients might add to the risk of contamination of the main port-of-entry to the respiratory tract, the nose and mouth. Facial hair may become an auto-reservoir for repeated inoculation of contaminated droplets, adding to the viral load and its dose, resulting in further disease deterioration and worse outcome.

    In their article (1), Dr. Richardson and colleagues reported that around 6% of cases had no underlying comorbidities and a similar proportion of their cohort (5700 cases) had only one risk factor for COVID-19. It would be highly informative to elaborate on their gender and on the issue of "neglected" facial hair. Presumably, these patients with one or no risk factors of comorbidities, are mainly bearded men. This missing information in this important article (1) may assist to solve this debate; is male sex risk behavioral or inherent?

    My subtle clinical viewpoint from observations of young patients with severe COVID-19, lacking any underlying sickness and of those from Israeli communities, where facial hair and even braids are common due to religious and traditional reasons, could be supported by this missing information, and might shed light on a proposed assumption that "hairborne" transmission is an epidemiological essential issue in COVID-19 pandemic, and should be addressed.


    1. Richardson S, Hirsch JS, Narasimhan M, et al. Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area. JAMA.

    2. Wambier CG, Goren A. SARS-COV-2 infection is likely to be androgen mediated. J Am Acad Dermatol. April 2020. doi:10.1016/j.jaad.2020.04.032
    Stratify By Mechanical Ventilation
    Hans-Joachim Kremer, Dr. rer. nat. | Medical Writing Service, Freiburg, Germany
    I assume that all patients who received mechanical ventilation (MV) were in ICU. I also assume that all patients admitted to ICU were quite homogeneously ill, namely critically ill.

    Then, a reasonable and easily available subset analysis would be to split all ICU patients into those who received MV and did not receive MV. For these subsets I extracted the following outcome categories from Table 5 of the article:

    Received MV: 38 discharged alive (3.3%), 831 still hospitalized (72.2%), 282 died (24.5%)
    No MV: 44 discharged alive (33.8%), 77 still hospitalized (59.2%), 9 died (6.9%)

    These are
    huge differences. A chi-square test across these 6 categories yields a p-value of <0.00001.

    Although this p-value is on purely observational and selected data, it should be taken seriously and warrants further investigation.

    Could it be that mechanical ventilation occurred too early? Could the authors comment on this? Could they run a similar analysis with updated data?
    Treat Coagulopathy or ARDs?
    Camilo Colaco, PhD | ImmunoBiology ltd
    As the previous comment states, the d-dimer question is crucial as it may shed light on whether treating early for coagulopathy could help reduce or avoid mechanical ventilation (1). Pulmonary Intravascular Coagulopathy (PIC) has also been proposed as the pathophysiology of CoVID 19 (2). Both endothelial dysfunction and PIC could explain the coagulopathy seen in CoVID 19, but treating the clotting cascade early with anticoagulants like LMW Heparin may be beneficial as has been reported in a preprint retrospective study (3).


    1. Oudkerk M Diagnosis, Prevention, and Treatment of Thromboembolic Complications in COVID-19: Report of the
    National Institute for Public Health of the Netherlands. Radiology Published Online Apr 23 2020.

    2. McGonagle D, O’Donnell JS, Sharif K, Emery P, Bridgewood C. Immune mechanisms of pulmonary intravascular coagulopathy in COVID-19 pneumonia. Lancet Rheumatology Published online May 7, 2020.

    3. Chen S The potential of low molecular weight heparin to mitigate cytokine storm in severe COVID-19 patients: a retrospective clinical study. medRxiv 2020.03.28.20046144;
    Original Investigation
    April 22, 2020

    Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area

    Author Affiliations
    • 1Institute of Health Innovations and Outcomes Research, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York
    • 2Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Northwell Health, Hempstead, New York
    • 3Department of Information Services, Northwell Health, New Hyde Park, New York
    JAMA. 2020;323(20):2052-2059. doi:10.1001/jama.2020.6775
    Key Points

    Question  What are the characteristics, clinical presentation, and outcomes of patients hospitalized with coronavirus disease 2019 (COVID-19) in the US?

    Findings  In this case series that included 5700 patients hospitalized with COVID-19 in the New York City area, the most common comorbidities were hypertension, obesity, and diabetes. Among patients who were discharged or died (n = 2634), 14.2% were treated in the intensive care unit, 12.2% received invasive mechanical ventilation, 3.2% were treated with kidney replacement therapy, and 21% died.

    Meaning  This study provides characteristics and early outcomes of patients hospitalized with COVID-19 in the New York City area.


    Importance  There is limited information describing the presenting characteristics and outcomes of US patients requiring hospitalization for coronavirus disease 2019 (COVID-19).

    Objective  To describe the clinical characteristics and outcomes of patients with COVID-19 hospitalized in a US health care system.

    Design, Setting, and Participants  Case series of patients with COVID-19 admitted to 12 hospitals in New York City, Long Island, and Westchester County, New York, within the Northwell Health system. The study included all sequentially hospitalized patients between March 1, 2020, and April 4, 2020, inclusive of these dates.

    Exposures  Confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection by positive result on polymerase chain reaction testing of a nasopharyngeal sample among patients requiring admission.

    Main Outcomes and Measures  Clinical outcomes during hospitalization, such as invasive mechanical ventilation, kidney replacement therapy, and death. Demographics, baseline comorbidities, presenting vital signs, and test results were also collected.

    Results  A total of 5700 patients were included (median age, 63 years [interquartile range {IQR}, 52-75; range, 0-107 years]; 39.7% female). The most common comorbidities were hypertension (3026; 56.6%), obesity (1737; 41.7%), and diabetes (1808; 33.8%). At triage, 30.7% of patients were febrile, 17.3% had a respiratory rate greater than 24 breaths/min, and 27.8% received supplemental oxygen. The rate of respiratory virus co-infection was 2.1%. Outcomes were assessed for 2634 patients who were discharged or had died at the study end point. During hospitalization, 373 patients (14.2%) (median age, 68 years [IQR, 56-78]; 33.5% female) were treated in the intensive care unit care, 320 (12.2%) received invasive mechanical ventilation, 81 (3.2%) were treated with kidney replacement therapy, and 553 (21%) died. As of April 4, 2020, for patients requiring mechanical ventilation (n = 1151, 20.2%), 38 (3.3%) were discharged alive, 282 (24.5%) died, and 831 (72.2%) remained in hospital. The median postdischarge follow-up time was 4.4 days (IQR, 2.2-9.3). A total of 45 patients (2.2%) were readmitted during the study period. The median time to readmission was 3 days (IQR, 1.0-4.5) for readmitted patients. Among the 3066 patients who remained hospitalized at the final study follow-up date (median age, 65 years [IQR, 54-75]), the median follow-up at time of censoring was 4.5 days (IQR, 2.4-8.1).

    Conclusions and Relevance  This case series provides characteristics and early outcomes of sequentially hospitalized patients with confirmed COVID-19 in the New York City area.