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Non‐severe immunosuppression might be associated with a lower risk of moderate–severe acute respiratory distress syndrome in COVID‐19: A pilot study – Monreal – – Journal of Medical Virology

globalresearchsyndicate by globalresearchsyndicate
November 24, 2020
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Non‐severe immunosuppression might be associated with a lower risk of moderate–severe acute respiratory distress syndrome in COVID‐19: A pilot study – Monreal – – Journal of Medical Virology
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1 BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), known to cause Coronavirus disease 2019 (COVID‐19), was first reported in Wuhan, China,1 and has rapidly spread worldwide.

The first published data from China indicated that nearly one‐third of patients may subsequently develop acute respiratory distress syndrome (ARDS), which results in a higher likelihood of needing mechanical ventilation (MV) and of death.2 Older age and the presence of comorbidities have been associated with a higher risk of ARDS, and with progression from ARDS to death.3

Patients with immunosuppression were initially thought to be at an increased risk of severe COVID‐19. However, preliminary data suggest a three‐stage SARS‐CoV‐2 infection, with two distinct but overlapping subsets4: the first triggered by the virus itself and the second consisting of a deregulated and excessive host immune response, which appears to be the main driver of lung tissue damage.5 Therefore, we hypothesize that a weaker immune response to the virus might prevent immunosuppressed patients from developing severe disease.

We aimed to evaluate differences in the inflammatory response during COVID‐19 between immunosuppressed (IS) and non‐immunosuppressed (non‐IS) patients by assessing the risk of ARDS, the need for mechanical (MV) or noninvasive ventilation (NIV), death, and the length of hospitalization.

2 METHODS

2.1 Study design

This single‐center, retrospective, observational study was performed at Hospital Universitario Ramón y Cajal, Madrid, a tertiary hospital in the region with the highest incidence of cases of the pandemic of COVID‐19 in Spain.6 Due to the emergency outbreak, the hospital was completely restructured and nearly all the specialists of the Neurology Department were assigned to attend COVID‐19 patients. A multidisciplinary group of Internal Medicine, Infectious Diseases, and Neurology experts elaborated on clinical guidelines, which were strictly followed by all the physicians treating COVID‐19 patients. All adult inpatients with confirmed or highly suspected SARS‐CoV‐2 infection from March 18, 2020, to April 4, 2020, were consecutively enrolled (Figure 1). For the analysis, only those with a laboratory‐confirmed infection and a minimum of baseline and outcome variables available (detailed below) were included. According to WHO guidance,7 confirmation of SARS‐CoV‐2 was defined as a positive result of real‐time reverse transcriptase–polymerase chain reaction (RT‐PCR) assay of nasal and pharyngeal swabs. The RT‐PCR assay was performed by expert microbiologists from the same center. The patients were followed up until May 15, 2020.

image

Study selection. RT‐PCR, reverse transcriptase‐polymerase chain reaction

This study was approved by the institutional ethics board of Hospital Universitario Ramón y Cajal. Due to the nature of the retrospective chart review, the need for informed consent from individual patients was waived.

2.2 Data collection

The electronic medical records of the participants were reviewed by a trained team of physicians from Hospital Universitario Ramón y Cajal during the epidemic period, after selection based on the eligibility criteria. Baseline characteristics included were demographics, medical history, comorbidities, laboratory examinations, radiological findings, and clinical and respiratory variables. Additionally, we included such variables as bacterial co‐infection and treatments administered. Immunosuppressed patients were defined as those with an inherited or acquired immunodeficiency or taking any drug with an immunomodulatory or immunosuppressive effect (see Electronic Supplementary Material for a complete description of all IS patients). Corticosteroids were considered immunomodulators at prednisone‐equivalent dosages >10 to <40 mg/day, but immunosuppressants at ≥40 mg/day.

The primary endpoint was the development of moderate or severe acute respiratory distress syndrome (ARDS), defined according to the Berlin definition.8 Secondary endpoints were percentages of death among those with a final outcome, need for mechanical (MV) or noninvasive ventilation (NIV), a composite of need of MV/NIV or death, length of hospitalization to May 15, 2020, and time to moderate–severe ARDS between the cohorts.

2.3 Statistical analysis

Continuous variables were described using means and standard deviations or medians and quartiles depending on whether or not data were normally distributed. The Shapiro‐Wilk test was used to test the normality of data distributions. Categorical variables were described using absolute and relative frequencies. The Fisher test was used to analyze categorical variables and the Mann–Whitney U test was used for quantitative variables. Logistic regression models were conducted to study the association between primary and secondary endpoints and immunosuppression; in the case of the length of hospitalization, we used linear regression instead. We performed both unadjusted (crude) and multivariate (adjusted) models, taking into account potential confounding factors (sex, age, and time from onset of symptoms to event or end of follow‐up). As a secondary analysis, we performed Kaplan–Meier survival curves of time to moderate or severe ARDS with a log‐rank test adjusted by immunosuppression status. A bivariate adjusted Cox proportional‐hazards model was used to determine HR and 95% CIs on the development of the primary endpoint between both groups. All data analyses were conducted using R (R Core Team (2017), Version 3.6.3., R Foundation for Statistical Computing, Vienna, Austria). Statistical hypotheses were tested using p < .05 as the level of significance.

3 RESULTS

From March 18, 2020, to April 4, 2020, 157 patients with highly suspected or confirmed COVID‐19 were admitted and attended by the treating physicians and were therefore selected for this study. After excluding those who did not fulfill the eligibility criteria (17 patients due to a negative test result for SARS‐CoV‐2 and 2 patients due to insufficient data), 138 patients were included in the analysis. From the final cohort, 19.6% (n = 27) of patients were IS and 80.4% (n = 111) were non‐IS. Among IS patients, 63% (n = 17) were diagnosed with an autoimmune disease (IS‐AD) and 37% (n = 10) were diagnosed with other diseases (IS‐NAD) (Figure 1). Additional information about IS patients is provided in the Electronic Supporting Information. The table outlines the demographic, clinical, and laboratory baseline characteristics of all patients and both groups. Overall, 68.8% (95 of 138 patients) were male and the median (IQR) age was 68 (54–78) years, distributed similarly among both cohorts. No statistically significant differences were observed between IS and non‐IS in terms of comorbidities, excepting for subsidiary diseases of immunosuppression such as AD (59.3% vs. 2.7%, p < .001) and organ transplant (18.5% vs. 0%, p < .001). The median (IQR) time from onset of symptoms to admission was 7 (4 – 11) days and a similar respiratory situation was observed between both groups, with a median (IQR) SatO2 of 93% (88%–96%) on room air, PaO2 (available in 92 patients, done mainly to those with a low SatO2) of 57 (51–66) mmHg, and a PaO2/FiO2 of 267 (233–310) mmHg. Bilateral pneumonia was the most frequent radiological finding (70.4% vs. 84.7% in IS vs. non‐IS, respectively, p = .19), with a median (IQR) CURB‐65 score of 1 (1–2) and 2 (1–2) (p = .48), respectively. Laboratory examinations were practically identical, with a mild lymphopenia (median [IQR], 855 [620–1210] cells/µl). Nevertheless, there was a trend (p = .08) towards a higher C‐reactive protein among non‐IS (median [IQR], 119.1 [56.7–186.1]) compared to IS (74.5; 33.3–144.9 mg/L). Bacterial co‐infection was infrequent in the overall population (14.5%) and the most frequently used treatments were hydroxychloroquine (98.6%) and lopinavir/ritonavir (70.4% vs. 88.2% [p = .033] in IS and non‐IS, respectively). Corticosteroids (51.9 vs. 65.8%) and the monoclonal antibodies tocilizumab (3.7% vs. 16.2%) and anakinra (0 vs. 2.7%) were more widely used during hospitalization in non‐IS, although the differences were not statistically significant. Among treatment‐induced IS patients, the immunosuppressive drug was discontinued at admission in 6 of 25 patients (24%). No patient had severe immunosuppression, as chemotherapy was actively administered in a single female and only five subjects were organ recipients but none had a Grade 3–4 leukopenia or neutropenia according to the CTCAE classification.9 For this reason, the immunosuppression among the IS cohort was considered nonsevere (Table 1).

Table 1.
Baseline characteristics of all patients and stratified by immunosuppression state at admission, including several treatments administered during hospitalization for SARS‐CoV‐2 infection
Demographic, clinical, and laboratory characteristics at admission
Total (n = 138) Immunosuppressed (n = 27) Nonimmunosuppressed (n = 111) p value
Age (years), median (IQR) 68 (54–78) 66 (48–80) 68 (56–78) .58
Men, no. (%) 95 (68.8%) 18 (66.7%) 77 (69.4%) .48
Comorbidities, no. (%)
None 28 (20.3%) 0 28 (25.2%) .002
Hypertension 70 (50.7%) 16 (59.3%) 54 (48.7%) .22
Diabetes type 2 36 (26.1%) 4 (14.8%) 31 (27.9%) .12
Obesity (BMI ≥ 30) 39 (28.3%) 6 (22.2%) 33 (29.7%) .49
Cardiovascular diseasea 33 (23.9%) 8 (29.6%) 25 (22.5%) .47
Chronic renal disease 18 (13.0%) 7 (25.9%) 11 (9.91%) .050
Chronic liver disease 9 (6.5%) 3 (11.1%) 6 (5.4%) .38
Chronic respiratory diseaseb 32 (23.2%) 5 (18.5%) 27 (24.3%) .62
Autoimmune disease 19 (13.8%) 16 (59.3%) 3 (2.7%) <.001
Active malignancy 15 (10.9%) 5 (18.5%) 10 (9%) .17
Malignancy in remission 12 (8.7%) 4 (14.8%) 8 (7.2%) .25
Organ transplant 5 (3.6%) 5 (18.5%) 0 <.001
Time from symptoms onset to admission (days), median (IQR) 7 (4–11) 6 (4–11) 7 (4–11) .64
Respiratory parameters
SatO2 (%), median (IQR) 93 (88–96) 95 (92–98) 92 (87–96) .07
PaO2 (mm Hg), no. with data 92 13 79
Median (IQR) 57 (51–66) 62 (52–73) 57 (51–66) .55
PaO2/FiO2 (mm Hg), median (IQR) 267 (233–310) 271 (232–348) 267 (233–310) .75
Pneumonia .19
None 6 (4.3%) 2 (7.4%) 4 (3.6%)
Unilateral 19 (13.8%) 6 (22.2%) 13 (11.7%)
Bilateral 113 (81.9%) 19 (70.4%) 94 (84.7%)
CURB‐65 score, median (IQR) 1.5 (1–2) 1 (1–2) 2 (1–2) .48
qSOFA, median (IQR) 1 (0–1) 1 (0–1) 1 (0–1) .78
Blood analysis, median (IQR)
White blood cell, /µl 6515 (4850–9140) 6470 (4250–9730) 6560 (4860–9110) .74
Neutrophil, /µl 4935 (3420–7540) 4550 (2850–7950) 4980 (3500–7400) .39
Lymphocyte, /µl 855 (620–1210) 810 (560–1140) 870 (630–1250) .62
C‐reactive protein, mg/L 113 (51.3–173.4) 74.5 (33.3–144.9) 119.1 (56.7–186.1) .08
D‐dimer (µg/L), no. with data 110 20 90
Median (IQR) 794.5 (535–1447) 897.5 (606.5–1651) 784 (482–1399) .44
Ferritine (ng/ml), no. with data 57 5 52
Median (IQR) 961 (544–1836) 610.7 (228–1084) 972 (564.5–1863) .28
Bacterial co‐infection, no. (%) 20 (14.5%) 4 (14.8%) 16 (14.4%) >.99
Treatments administered, no. (%)
Lopinavir/ritonavir 117 (84.8%) 19 (70.4%) 98 (88.2%) .033
Hydroxychloroquine 136 (98.6%) 26 (96.3%) 110 (99.1%) .35
Antibiotics 94 (69.1%) 19 (70.3%) 75 (68.8%) >.99
Azithromycin 95 (68.8%) 16 (59.3%) 79 (71.2%) .25
Corticosteroids 87 (63.0%) 14 (51.9%) 73 (65.8%) .19
Tocilizumab 19 (13.8%) 1 (3.7%) 18 (16.2%) .12
Anakinra 3 (2.2%) 0 3 (2.7%) >.99
  • Note: CURB‐65, confusion; urea > 7 mmol/L; respiratory rate ≥ 30/min; systolic (≤90 mmHg) or diastolic (≤60 mmHg) blood pressure and age ≥ 65 years.
  • Abbreviations: BMI, body mass index; FiO2, fraction of inspired oxygen; IQR, interquartile range; NS, nonsignificant; PaO2, partial pressure of oxygen; qSOFA, quick Sepsis‐related organ failure assessment; SatO2, oxygen saturation.
  • a Heart failure, myocardiopathy, ischemic and moderate–severe valvular heart diseases.
  • b Chronic obstructive pulmonary disease, obstructive sleep apnea‐hypopnea syndrome and diffuse interstitial lung disease.

3.1 Comparison of complications during hospitalization

The primary endpoint (development of moderate or severe ARDS) was significantly lower for IS patients (25.9%; 95% CI, 12.2%–46.8%) compared to non‐IS patients (52.3%; 95% CI, 42.9%–61.5%), with a crude OR of 0.32 (95% CI, 0.13–0.83) (p = .017). After adjusting by sex, age, and time from onset of symptoms to event, the adjusted OR (aOR) showed a stronger protective effect for IS (aOR, 0.25; 95% CI, 0.08–0.80; p = .019) (Figure 2). After stratifying by AD, significant differences were observed in the proportion of moderate–severe ARDS for IS‐AD (23.5%) when compared to IS‐NAD (30%). The logistic regression model was therefore replicated, and a lower risk was detected only for IS‐AD (aOR, 0.25; 95% CI, 0.07–0.98; p = .046), but not for IS‐NAD (aOR, 0.39; 95% CI, 0.06–2.38; p = .31). An adjusted Cox regression was subsequently conducted, finding a nonsignificant trend towards a shorter time to moderate–severe ARDS in non‐IS (mean ± SD, 14 ± 8.37 days) compared to IS (mean ±  SD, 16.5 ± 8.64 days) (aHR 0.47; 95% CI, 0.21–1.02; p = .056), despite a significant difference in the log‐rank test (p = .029) (Figure 3).

image

Primary and secondary endpoints. The figure shows the crude (red line) and adjusted (blue line) OR of the primary (moderate or severe ARDS) and secondary (ARDS, MV/NIV, a composite of MV/NIV and death and death) endpoints. ARDS, acute respiratory distress syndrome; MV, mechanical ventilation; NIV, noninvasive ventilation; OR, odds ratio

image

Time to moderate or severe ARDS. ARDS, acute respiratory distress syndrome

Although lower proportions were observed for IS patients, no statistically significant differences were detected in risk of need for MV/NIV (7.4% vs. 12.6%; aOR, 0.38; 95% CI, 0.07–2.07; p = .26) or in risk of a composite of need for MV/NIV or death (14.8% vs. 18.9%; aOR, 0.54; 95% CI, 0.14–2.12; p = .38) in IS compared to non‐IS, respectively. A final outcome (death/discharge) was recorded in 137 patients (99.3%), with an overall mortality of 14.6% (95% CI, 9.6%–21.7%). A comparison of both groups detected no significant differences between IS (14.8%) and non‐IS (14.6%), with an adjusted OR of 0.78 (95% CI, 0.20–3.13; p = .73) (Figure 2). The median (IQR) stay was 12 (7–16) days for the overall population, with a nonsignificant lower stay (β = −1.32; 95% CI, −6.06 to 3.41 days; p = .58) for IS after adjusting by sex, age, and time from onset of symptoms to admission.

4 DISCUSSION

In this retrospective, single‐center, observational study with inpatients with COVID‐19 in Madrid, Spain, a better outcome, in terms of lower risk to moderate or severe ARDS, was observed among a cohort of patients with non‐severe immunosuppression as compared to non‐IS. A trend towards a shorter time to moderate–severe ARDS and a shorter hospitalization were also observed. After stratifying by the source of IS, the protective effect seemed to be mainly driven by AD. However, no differences in time to moderate–severe ARDS, need for MV/NIV, or a composite of MV/NIV and death were detected between IS and non‐IS despite lower proportions for the first cohort. A comparison of both groups showed no differences in the death ratio.

Immunosuppression has been widely considered a risk factor for infections, with a higher incidence and a worse outcome, including those caused by a respiratory virus.10 For example, influenza infection was observed to be associated with a higher risk of more hospitalizations, a longer length of virus shedding, a more severe disease, and complications requiring intensive care and MV.11 Additionally, several studies consider immunosuppression to be a risk factor of more severe disease in MERS‐CoV infection.12–15 Previous studies have already described risk factors predicting a worse outcome in COVID‐19 patients, such as older age,3, 16–18 comorbidities (hypertension, diabetes, or vascular diseases),3, 16, 18 and laboratory findings, with special attention paid to those indicating hyperinflammation or cytokine storm syndrome,19, 20 like elevated serum D‐dimer, ferritin, C‐reactive protein, or interleukin‐6 (Il‐6) levels.3, 16–18 Nevertheless, none of these studies has specifically assessed immunosuppression as a risk factor in COVID‐19 patients. A population‐based study in China evaluated cancer patients with recent surgery or chemotherapy and found a higher risk of severe events.21 In addition, recent data about patients with moderate or severe immunosuppression associated to hematologic malignancy22, 23 and solid organ transplant recipients24, 25 detected higher death ratios compared to the general population. In line with these results, a large population‐based study with over 17 million subjects developed in the UK found higher mortality among organ transplant, immunosuppression, hematological malignancies, and several autoimmune diseases.26 However, limitations in interpreting these results are that all national COVID‐19 inpatients are compared to about 40% of the general population (with a potential selection bias), and no description of treatments and baseline characteristics of these groups is reported.

In our study, a lower proportion of IS patients developing moderate–severe ARDS was observed. We decided to assess this variable as a primary endpoint due to its higher specificity in detecting more inflammatory patients. This contrasts with previous data22–26 about immunosuppression, but differences might reside in the grade of immunosuppression, this being less severe in our cohort. To delve into a possible condition explaining these results, we further differentiated IS patients between those with an AD and those with other diseases (such as cancer or an organ transplant). A lower proportion was only observed for IS‐AD patients but not for IS‐NAD. In line with this result, a trend towards a lower proportion of MV/NIV or a composite of the need for MV/NIV was also detected, probably due to the lower risk of ARDS.

This data might be explained by pathophysiological findings of COVID‐19, such as the three‐stage classification model of SARS‐CoV‐2 infection proposed by Siddiqi and Meehra,4 with two distinct but overlapping subsets. The first triggered by the virus itself and the second, occurring in a minority of patients, host‐mediated and based on an excessive immune response, leading to ARDS, the need for MV, and, potentially death.3, 17–19 Pathophysiology similar to that of SARS‐CoV has been hypothesized for SARS‐CoV‐2 infection,27 in which a marked elevation of cytokines of the Th1 cell‐mediated immunity (such as interferon‐γ [IFN‐γ], IL‐1, IL‐6, and IL‐12) and hyperinnate (neutrophil chemokine IL‐8, monocyte chemoattractant protein‐1 [MCP‐1], and Th1 chemokine IFN‐γ‐inducible protein‐10) inflammatory response28 have been observed. In COVID‐19, both innate immune hyperactivation and adaptive immune dysregulation have been hypothesized to be responsible of ARDS.29 For this reason, several immunomodulatory drugs, such as corticosteroids, intravenous immune globulin, and cytokine inhibitors with a mild effect on the immune system have been proposed depending on whether the hyperinflammation stage is suspected.18, 20, 23 Preliminary data suggest a potential benefit of methylprednisolone in terms of the risk of death after the development of ARDS,3 though clinical trials are required before recommending this therapy. All these results support the notion that immunosuppression, at least if non‐severe, might confer a protective effect in the most severe stages of the disease. We found that the lowest risk of moderate–severe ARDS was detected in IS‐AD patients. This contrasts with evidence of an increased risk of infections observed in AD, through the presence of neutralizing autoantibodies against pro‐inflammatory cytokines. These autoantibodies may have the ability to interfere with key cytokines such as IL‐6, IFN‐γ, granulocyte/macrophage–colony‐stimulating factor (GM‐CSF), IL‐17, and IL‐22 resulting in a lower Th1 and Th17 inflammatory response.30 We have not assessed the risk of infection by SARS‐CoV‐2 in IS patients. But, it could be hypothesized that a complex interaction between AD and non‐severe immunosuppression in COVID‐19 could exert a protective effect of severe outcomes related to an innate immune hyperactivation.

No differences in death rate were observed in our cohort. The reasons for these results might be explained by the smaller sample size of patients with a final outcome, the short follow‐up, or unknown confounding factors. For example, during cytokine storm syndrome, ARDS is not the single inflammatory complication observed, as evidence of multiorgan dysfunction, with acute cardiac injury31 and liver and renal impairment,3, 17, 18, 32 has been described. This might be attributable to the widespread distribution of angiotensin converting enzyme 2—the functional receptor for SARS‐CoV‐2—in multiple organs.33 In addition, the results may be biased by the fact that IS patients may never get to MV/NIV, being considered too disabled, so they are more likely to die than non‐IS patients. Also, several factors related to the development of ARDS that were not associated with death have been described,3 which indicates that different pathophysiological changes—from hospital admission to the development of ARDS and from the development of ARDS to death—may exist.

Thus, our results might have relevance in terms of establishing recommendations for IS patients. Discontinuation of immunosuppressive drugs can be considered or suggested by either asymptomatic patients or treating physicians concerned about a possible worse course if a SARS‐CoV‐2 infection develops. But, this may have implications with respect to diminishing the underlying disease control, with potential fatal outcomes in either cancer or organ transplant patients or the reactivation34 or even rebound35 of disease activity among autoimmune disorders. Taking this data into account, careful individual decision‐making about maintaining immunosuppressive drugs must be performed in noninfected or even mild COVID‐19 patients. Second, less aggressive anti‐inflammatory management among IS patients might be contemplated, lowering the risk of bacterial co‐infections. Third, social and preventive care recommendations might be reconsidered for these patients.

This study has several limitations. First, a potential selection bias might have occurred, as only a part of hospitalized patients (those attended by the treating physicians reported) were evaluated, and IS might be admitted more easily by its own condition than non‐IS. For this reason, patients directly admitted to ICU from the emergency room were not included. Second, this study was conducted at a single center with limited sample size. Third, the cohort of IS patients is heterogeneous regarding diseases and immunosuppressive drugs, which may limit external validity to all types of IS patients. In addition, small sample size limits subgroup analyses by the source of immunosuppression. Fourth, due to the lack of evidence‐based treatment protocols, the treating physicians took different management approaches (especially with antiviral drugs or corticosteroids), which could have altered the development of the outcomes. And finally, the retrospective character of the study and the short follow‐up time warrant caution in interpreting the data. Further studies with a prospective design and a larger sample size, including outpatients, might help gain a better understanding of the role that immunosuppression plays among COVID‐19 patients.

In conclusion, in our cohort nonsevere immunosuppression was associated with a lower risk of moderate–severe ARDS, a trend towards a reduced need for MV/NIV, a shorter hospitalization, and a longer time before moderate or severe ARDS occurs. We found the mortality rate was not increased in IC patients. This reinforces the fact that there is a potential protective effect of immunosuppression against a possible hyperinflammation host response observed in SARS‐CoV‐2 infection and warrants reconsideration of discontinuing systematically immunosuppressive drugs in patients with severe underlying diseases.

CONFLICT OF INTERESTS

The authors declare that there are no conflict of interests.

AUTHOR CONTRIBUTIONS

Drs Monreal and Sainz de la Maza had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Monreal, Sainz de la Maza, Masjuan. Acquisition, analysis or interpretation of data: Monreal, Sainz de la Maza, Gullón, Natera‐Villalba, Chico‐García, Beltrán‐Corbellini, Martínez‐Sanz, García‐Barragán, Buisán, Toledano, Alonso‐Canovas, Pérez‐Torre, Matute‐Lozano, López‐Sendón, García‐Ribas, Corral, Fortún, Montero‐Errasquín, Manzano, Máiz‐Carro, Lucienne Costa‐Frossard, Masjuan. Drafting of the manuscript: Monreal, Sainz de la Maza, Gullón, Natera‐Villalba, Masjuan. Critical revision of the manuscript for important intellectual content: Monreal, Sainz de la Maza, Gullón, Natera‐Villalba, Chico‐García, Beltrán‐Corbellini, Martínez‐Sanz, García‐Barragán, Buisán, Toledano, Alonso‐Canovas, Pérez‐Torre, Matute‐Lozano, López‐Sendón, García‐Ribas, Corral, Fortún, Montero‐Errasquín, Manzano, Máiz‐Carro, Lucienne Costa‐Frossard, Masjuan. Statistical analyses: Monreal, Gullón. Administrative, technical or material support: Monreal, Sainz de la Maza, Gullón, Natera‐Villalba, Chico‐García, Beltrán‐Corbellini, Martínez‐Sanz, García‐Barragán, Buisán, Toledano, Alonso‐Canovas, Pérez‐Torre, Matute‐Lozano, López‐Sendón, García‐Ribas, Corral, Fortún, Montero‐Errasquín, Manzano, Máiz‐Carro, Lucienne Costa‐Frossard, Masjuan. Study supervision: Masjuan.

APPENDICE: ALL TREATING PHYSICIANS COMPRISING THE COVID‐HRC GROUP, A MULTIDISCIPLINARY GROUP CREATED DURING PANDEMICS IN THE HOSPITAL UNIVERSITARIO RAMÓN Y CAJAL A

The COVID‐HRC (COronaVIrus Disease 2019—Hospital Ramón y Cajal) Group: Masjuan, J; Fortún, J; Montero‐Errasquín, B; Manzano, L; Máiz‐Carro, L; Sánchez‐García, EM; Hidalgo, F; Domínguez, AR; Pérez‐Molina, JA; Sánchez‐Sánchez, O; Comeche, B; Monge‐Maillo, B; Barbero, E; Barbolla‐Díaz, I; Aranzábal Orgaz, L; Cobo, J; Rayo, I; Fernández‐Golfín, C; González, E; Rincón‐Díaz, LM; Ron, R; Mateos‐Muñoz, B; Navas, E; Moreno, J; Norman, J; Serrano, S; Quereda Rodríguez‐Navarro, C; Vallés, A; Herrera, S; Mateos del Nozal, J; Moreno‐Cobo, MA; Gioia, F; Concejo‐Badorrey, MC; Ortiz Barraza, EY; Moreno, A; Chamorro, S; Casado, JL; Almonacid, C; Nieto, R; Diz, S; Moreno, E; Conde, M; Hermida, JM; López, M; Monreal, E; Sainz de la Maza, S; Costa‐Frossard, L; Natera‐Villalba, E; Chico‐García, JL; Beltrán‐Corbellini, Á; Rodríguez‐Jorge, F; Fernández‐Velasco, JI; Rodríguez de Santiago, E; Rita, CG; Iturrieta‐Zuazo, I; De Andrés, A; Espiño, M; Vázquez, M; Fernández Lucas, M; Martínez‐Sanz, J; García‐Barragán, N; Buisán, J; Toledano, R; Alonso‐Canovas, A; Pérez‐Torre, P; Matute‐Lozano, MC; López‐Sendón, JL; García‐Ribas, G; Corral, Í; Villar, LM.

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