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COVID-19 pneumonia in Galicia (Spain): Impact of prognostic factors and therapies on mortality and need for mechanical ventilation

  • Luis Pérez-de-Llano,

    Roles Conceptualization, Funding acquisition, Investigation, Methodology, Writing – original draft

    Affiliation Pneumology Service, Lucus Augusti University Hospital, EOXI Lugo, Monforte, Cervo, Lugo, Spain

  • Eva María Romay-Lema,

    Roles Investigation, Writing – review & editing

    Affiliation Infectious Diseases Unit, Lucus Augusti University Hospital, EOXI Lugo, Monforte, Cervo, Lugo, Spain

  • Adolfo Baloira-Villar,

    Roles Investigation, Writing – review & editing

    Affiliation Pneumology Service, Complexo Hospitalario Universitario, Pontevedra, Spain

  • Christian Anchorena,

    Roles Investigation, Writing – review & editing

    Affiliation Pneumology Service, Complexo Hospitalario Universitario, Pontevedra, Spain

  • María Luisa Torres-Durán,

    Roles Investigation, Writing – review & editing

    Affiliation Pneumology Service, Complexo Hospitalario Universitario de Vigo, Vigo, Spain

  • Adrián Sousa,

    Roles Investigation, Writing – review & editing

    Affiliation Internal Medicine Service, Complexo Hospitalario Universitario de Vigo, Vigo, Spain

  • Dolores Corbacho-Abelaira,

    Roles Investigation, Writing – review & editing

    Affiliation Pneumology Service, Hospital POVISA, Vigo, Spain

  • José Paz-Ferrin,

    Roles Investigation, Writing – review & editing

    Affiliation Internal Medicine Service, Hospital POVISA, Vigo, Spain

  • Carmen Diego-Roza,

    Roles Investigation, Writing – review & editing

    Affiliation Pneumology Service, Hospital Arquitecto Marcide, Ferrol, Spain

  • Laura Vilariño-Maneiro,

    Roles Investigation, Writing – review & editing

    Affiliation Internal Medicine Service, Hospital Arquitecto Marcide, Ferrol, Spain

  • Pedro J. Marcos,

    Roles Investigation, Writing – review & editing

    Affiliation Pneumology Service, Complexo Universitario de A Coruña, A Coruña, Spain

  • Carmen Montero-Martínez,

    Roles Investigation, Writing – review & editing

    Affiliation Pneumology Service, Complexo Universitario de A Coruña, A Coruña, Spain

  • Fernando de la Iglesia-Martínez,

    Roles Investigation, Writing – review & editing

    Affiliation Internal Medicine Service, Complexo Universitario de A Coruña, A Coruña, Spain

  • Vanessa Riveiro-Blanco,

    Roles Investigation, Writing – review & editing

    Affiliation Pneumology Service, Complexo Hospitalario Universitario de Santiago, Santiago de Compostela, Spain

  • Nuria Rodríguez-Núñez,

    Roles Investigation, Writing – review & editing

    Affiliation Pneumology Service, Complexo Hospitalario Universitario de Santiago, Santiago de Compostela, Spain

  • José Abal-Arca,

    Roles Investigation, Writing – review & editing

    Affiliation Pneumology Service, Complexo Hospitalario Universitario de Ourense, Ourense, Spain

  • María Bustillo-Casado,

    Roles Investigation, Writing – review & editing

    Affiliation Infectious Diseases Unit, Complexo Hospitalario Universitario de Ourense, Ourense, Spain

  •  [ ... ],
  • Rafael Golpe

    Roles Formal analysis, Investigation, Methodology, Writing – original draft

    rafael.golpe.gomez@sergas.es, rafagolpe@gmail.com

    Affiliation Pneumology Service, Lucus Augusti University Hospital, EOXI Lugo, Monforte, Cervo, Lugo, Spain

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COVID-19 pneumonia in Galicia (Spain): Impact of prognostic factors and therapies on mortality and need for mechanical ventilation

  • Luis Pérez-de-Llano, 
  • Eva María Romay-Lema, 
  • Adolfo Baloira-Villar, 
  • Christian Anchorena, 
  • María Luisa Torres-Durán, 
  • Adrián Sousa, 
  • Dolores Corbacho-Abelaira, 
  • José Paz-Ferrin, 
  • Carmen Diego-Roza, 
  • Laura Vilariño-Maneiro
PLOS
x

Abstract

Introduction

This study was aimed to identify risk factors associated with unfavorable outcomes (composite outcome variable: mortality and need for mechanical ventilation) in patients hospitalized in Galicia with COVID-19 pneumonia.

Methods

Retrospective, multicenter, observational study carried out in the 8 Galician tertiary hospitals. All Patients admitted with confirmed COVID-19 pneumonia from 1st of March to April 24th, 2020 were included. A multivariable logistic regression analysis was performed in order to identify the relationship between risk factors, therapeutic interventions and the composite outcome variable.

Results

A total of 1292 patients (56.1% male) were included. Two hundred and twenty-five (17.4%) died and 327 (25.3%) reached the main outcome variable. Age [odds ratio (OR) = 1.03 (95% confidence interval (CI): 1.01–1.04)], CRP quartiles 3 and 4 [OR = 2.24 (95% CI: 1.39–3.63)] and [OR = 3.04 (95% CI: 1.88–4.92)], respectively, Charlson index [OR = 1.16 (95%CI: 1.06–1.26)], SaO2 upon admission [OR = 0.93 (95% CI: 0.91–0.95)], hydroxychloroquine prescription [OR = 0.22 (95%CI: 0.12–0.37)], systemic corticosteroids prescription [OR = 1.99 (95%CI: 1.45–2.75)], and tocilizumab prescription [OR = 3.39 (95%CI: 2.15–5.36)], significantly impacted the outcome. Sensitivity analysis using different alternative logistic regression models identified consistently the ratio admissions/hospital beds as a predictor of the outcome [OR = 1.06 (95% CI: 1.02–1.11)].

Conclusion

These findings may help to identify patients at hospital admission with a higher risk of death and may urge healthcare authorities to implement policies aimed at reducing deaths by increasing the availability of hospital beds.

Introduction

In late 2019, a new coronavirus (now called severe acute respiratory syndrome coronavirus 2: SARS-CoV-2) was identified in a number of patients presenting with pneumonia in Wuhan, Hubei province, China, and since then, virtually all countries have been affected by the pandemic. The severity of coronavirus disease-2019 (COVID-19) ranges from mild symptoms of upper respiratory tract infection to severe pneumonia and, although most reported cases are at the mild end of the spectrum, 15% of infected patients develop viral pneumonia and 1–5% of them die [1]. The fatality rate differs considerably across countries and different regions of the same country, most likely reflecting overwhelming of healthcare systems [2].

Over the past months, we have learnt what risk factors are most likely to impact on the prognosis [36] but it remains to be clarified how the different therapeutic strategies (antivirals, systemic corticosteroids, hydroxychloroquine, tocilizumab, antibiotics) may influence the outcome of the patients [79].

The aim of this study was to identify clinical, demographic and therapeutic risk factors associated with worse outcomes (mortality and need for mechanical ventilation) in patients hospitalized in Galicia with COVID-19 pneumonia during the spring 2020 outbreak.

Material and methods

Design

Retrospective, multicenter, observational study carried out in the 8 Galician tertiary hospitals (Complexo Hospitalario Universitario de A Coruña, Hospital Universitario Lucus Augusti, Complexo Hospitalario Universitario de Ferrol, Complexo Hospitalario Universitario de Ourense, Complexo Hospitalario Universitario de Vigo, Hospital Policlínico de Vigo, Complexo Hospitalario Universitario de Pontevedra, Complexo Hospitalario Universitario de Santiago). These 8 hospitals cover about 85% of the Galician population. Galicia has a population of 2,699,449 inhabitants (1,298,964 male), with a mean age of 47.2 y (44 y in Spain). It is an ageing population (515,847 over 70), particularly vulnerable to severe COVID-19 infection.

All Patients admitted with confirmed COVID-19 pneumonia from 1st of March to April 24th, 2020 were included. Confirmed COVID-19 infection was defined as: “Clinical criteria (at least, 2 of the following symptoms: fever, cough, headache, myalgias, diarrhea, asthenia) plus detection of SARS-CoV-2 from a clinical specimen using a validated PCR or significant rise of IgG antibody level to SARS-CoV-2 between paired sera plus radiologic infiltrates”.

Compliance with ethical standards

The study was approved by the ethics committee of Galicia (Cod. 2020/239). Data were de-identified for analysis. Informed consent was waived due to the retrospective, non-interventional design of the study and the use of anonymous clinical data for the analysis.

Data collection

Galicia has a network of 8 tertiary hospitals interconnected with a shared operating system that provides a unified electronic medical record, giving the researchers the opportunity to collect good quality data. Data were processed internally and in pseudonymised form were collected by two independent data managers from the electronic medical records. Demographic data, risk factors for poor outcome (cardiovascular diseases, arterial hypertension, diabetes, chronic bronchial diseases, renal failure, cancer, hepatic failure, Kidney transplantation, other organ transplantation), laboratory data on admission (D dimers, lymphocyte and platelet counts, PaO2, VSG, PCR…) and COVID-19 treatments used during admission (antiretroviral drugs, anti-malarial drugs, monoclonal antibodies, systemic corticosteroids, interferon, antibiotics) were collected.

Statistical analysis

Main outcome variable was a composite of in-hospital death (every death in patients included in this study was allocated to COVID-19 pneumoniae irrespective of secondary complications), and need for mechanical ventilation. Secondary outcome variable was in-hospital death. Category variables are presented in terms of absolute and relative frequencies, median and interquartile range. Normality was evaluated using the Kolmogorov-Smirnov test with Lilliefords´ correction. Between-groups comparisons were made by means of Chi-squared test for categorical variables and either Student’s t-test or Mann-Whitney U test for continuous variables, as appropriate.

A multivariable logistic regression analysis was performed in order to identify the relationship between risk factors, therapeutic interventions and the composite results variable. Variables with biological plausibility were entered simultaneously in one single step, without checking. We used the following independent variables: age, sex, crude (non-age-adjusted) Charlson comorbidity index, C-reactive protein (CRP), arterial oxygen saturation (SaO2) and the different treatments used during admission. We also included a ratio ([number of admissions per hospital/number of hospital beds] x 100) as a measure of the hospitals’ bed stress. Age, Charlson index, SaO2 and the ratio of hospitals’ bed stress were coded continuously. Sex and treatments were coded dichotomously. CRP was selected as a marker of inflammatory status because it was available for most patients. Because not all hospitals used the same measuring method and reference values for CRP, this variable was coded in each hospital in quartiles.

We performed a sensitivity analysis, using several different models. In these alternative analyses we replaced CRP in the multivariable analysis by the lymphocyte and neutrophils cell count, and also added the platelet count and the procalcitonin values. We used both a method that entered all the variables in the model without checking, and a forward automatic conditional selection method that sequentially entered variables with a p-value < 0.05.

Statistical tests were two-sided and significance was taken at the level of p < 0.05. We used MedCalc Statistical Software version 13.3.3 (MedCalc Software bvba, Ostend, Belgium). Strobe checklists can be found in S1 Appendix.

Results

Demographic characteristics

A total of 1292 patients (56.0% male) were included in this study. Mean age was 68.8 ± 14.5 years [median: 70.7 (interquartile range [IQR]: 59.5–79.3)]. Table 1 shows demographic characteristics of the sample and the prevalence of the main pre-existing comorbidities. The most frequent ones were arterial hypertension (49.7%), diabetes mellitus (20.2%), ischemic heart disease (12.6%) and atrial fibrillation (12.5%).

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Table 1. Demographic characteristics and comorbidity data of study subjects.

https://doi.org/10.1371/journal.pone.0253465.t001

Clinical and laboratory features. Therapy prescribed on admission

Mean days from symptom onset to admission was 7.5 ± 5.1 (median 7.0, IQR: 4.0–10.0). The most common symptoms were (S1 Table): fever (77.6%), cough (74.5%) and dyspnea (53.3%). Laboratory findings at admission are shown in Table 2. Of note, mean PaO2 was 63.9 ± 15.6 mmHg [median: 64 (IQR: 55–74)] and mean SaO2 was 92.1 ± 8.1% [median: 94 (IQR: 92–96)]. Two hundred and sixteen (16.7%) patients presented with respiratory failure.

Lopinavir/ritonavir was administered to 62.5% of patients, whereas 37.1% received systemic corticosteroids and tocilizumab was prescribed in 9.4% patients. Hydroxychloroquine (400 mg twice daily the first day followed by 200 mg twice daily for five days) and azithromycin (500 mg daily for 5 days) were employed in 91.9% and 79.2% of the patients, respectively (Table 3). It deserves to be emphasized that the patients who received systemic corticosteroids and tocilizumab had a more severe clinical condition on admission, whilst the ones who received hydroxychloroquine presented with a milder clinical picture (S2 Table).

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Table 3. Medications administered during hospitalization and prior to mechanical ventilation (MV).

https://doi.org/10.1371/journal.pone.0253465.t003

Outcome results

Of the total 1292 patients, 225 (17.4%) died, 149 (11.5%) were transferred to the Intensive care Unit and received mechanical ventilation and 327 (25.3%) either died or needed mechanical ventilation (main composite outcome variable). Median time from admission to mechanical ventilation was 2.0 days (IQR, 1.0–4.0) and the median of the hospital stay was 10 days (IQR, 6.0–15.0).

Risk factors for mortality or need for mechanical ventilation

The predictors of mortality or need for mechanical ventilation in the multivariable analysis were as follows (Table 4): age [odds ratio (OR) = 1.03 (95% confidence interval (CI): 1.01–1.04)], CRP quartiles 3 and 4 [OR = 2.24 (95% CI: 1.39–3.63)] and [OR = 3.04 (95% CI: 1.88–4.92)], respectively, Charlson index [OR = 1.16 (95%CI: 1.06–1.26)], SaO2 upon admission [OR = 0.93 (95% CI: 0.91–0.95)], hydroxychloroquine prescription [OR = 0.22 (95%CI: 0.12–0.37)], systemic corticosteroids prescription [OR = 1.99 (95%CI: 1.45–2.75)], and tocilizumab prescription [OR = 3.39 (95%CI: 2.15–5.36)].

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Table 4. Results of the multivariable logistic regression analysis for death or need of mechanical ventilation.

https://doi.org/10.1371/journal.pone.0253465.t004

We carried out an additional analysis using in-hospital mortality as a secondary outcome variable. Results are shown in Table 5. The association between corticosteroids treatment and an increased risk of death did not reach statistical significance, while there were significant associations between this outcome and age, comorbidity burden, CRP, SaO2, hydroxychloroquine and tocilizumab, similar to those found for the main composite outcome variable.

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Table 5. Results of the multivariable logistic regression analysis for in-hospital death.

https://doi.org/10.1371/journal.pone.0253465.t005

The results of the sensitivity analysis for the main outcome variable are shown in S3 and S4 Tables. The results of the analysis did not significantly change in these additional analyses, except for the fact that the ratio admissions/hospital beds consistently and significantly correlated with the outcome [OR: 1.69 (95% CI: 1.02–1.18)]

Discussion

Mortality and comparison with other series

We found a 17.2% in-hospital mortality in this cohort, formed by patients admitted with COVID-19 pneumonia in 8 tertiary Galician hospitals during the peak of the outbreak in March and April 2020. Among 126,137 patients hospitalized for COVID-19 from March to July 2020 in the USA, 15% of patients (19,594) died during the index hospitalization [10]. Du et al reported a 11.7% fatality rate among 179 hospitalized COVID-19 patients [11]. These rates are lower than the one we observed, but it is worth to mention that not all patients included in those studies were diagnosed as having pneumonia. Mortality figures were also higher in our series than in the Chen´s one (11.1%), but although this cohort was entirely formed by pneumonia-diagnosed patients, it should be remarked that mean age was much lower (55 yrs vs 68 yrs) and PaO2 was higher (72.0 vs 63.9 mmHg), likely reflecting less severe condition at admission [12]. In Spain, Berenguer et al found a 28% mortality rate in 4,035 hospitalized patients with COVID-19 disease, of which 77% presented with infiltrates on chest radiograph [13]. Rubio-Rivas et al reported a mortality that exceeded 15% among 12,066 patients admitted with COIVD-19 infection (the rate of those diagnosed with pneumonia has not been specified) in 109 Spanish hospitals [14]. More recently published clinical trials reported mortality rates between 5.1 and 10.4%, but included patients were recruited as late as July 2020 and mean age was considerably lower (55 years) [15, 16].

Data on COVID-19 pneumonia mortality during the second wave are lacking and the scarce available information suggests that mortality rates have declined, at least in developed countries, but this observation could be explained by the fact that second-wave infections tended to affect younger people and it cannot be attributed with certainty to therapeutic advances [1719]. Another plausible explanation is provided by Asch and colleagues, who found that the risk-adjusted mortality decreased from 16.56% to 9.29% in the early period of their study (January through April 2020) compared with the later period (May through June 2020), reflecting a possible association between an increased in-hospital mortality and a high prevalence of COVID-19 in the community [20].

Risk factors for unfavorable outcome

We identified predictors for poor outcome (need for mechanical ventilation or in-hospital death) in patients admitted with Covid-19 pneumonia: old age, low SaO2, high CRP values, preexistence of comorbidities and the use of systemic corticosteroids and tocilizumab. Hydroxychloroquine prescription was associated with a favorable outcome.

Increased age has been repeatedly associated with adverse outcome [21, 22] and case fatality rate was reported to be higher in patients with comorbidities, in particular cardiovascular diseases and diabetes [2326]. On the other hand, low blood oxygen saturation has also been used to identify severe COVID-19 pneumonia in admitted patients [27] and admission CRP correlated with disease severity and tended to be a good predictor of adverse outcome [28, 29].

In this study we have found that anti-inflammatory drugs (systemic corticosteroids and tocilizumab) negatively impact on prognosis, even after adjusting for other potential risk factors. In the earlier period of the pandemic, some influential experts advised not to use systemic corticosteroids in patients with COVID-19 pneumonia, relying on the lack of evidence, the negative results observed in influenza pneumonia and impaired clearance of SARS-CoV [30]. Ever since, several studies with an observational design (either retrospective or prospective) yielded contradictory results, with some reporting a positive impact on survival [3137], while others concluding the opposite [38, 39]. The only prospective and randomized clinical trial (although not double-blinded), demonstrated that dexamethasone treatment reduced deaths by one-third in mechanically ventilated patients and by one-fifth in patients receiving oxygen only, whereas no difference in mortality was found in patients who did not need any breathing support [40]. The results of three meta-analysis further support the employ of systemic corticosteroids in COVID-19 pneumonia, but it is worth to mention that the weight of RECOVERY trial was more than 50 per cent in all of them and the magnitude of the effect was modest (OR ranging from 0.70 to 0.88) [4143]. On the other hand, several propensity score matching (PSM) studies found no impact of corticosteroids on COVID-19 pneumonia outcome [4449], while an increased mortality was observed in other report [50] and two additional PSM studies concluded that corticosteroid therapy was associated with lower mortality [51, 52]. Therefore, considering all the available evidence, the role of corticosteroids remains controversial in non-critically ill patients who need supplemental oxygen. The evidence for the use of tocilizumab is far less, since only non-randomized single-arm studies and case-series were published with promising results [36, 5355]. Recently published studies seem to indicate that tocilizumab has additional benefit to corticosteroids in patients with clinically progressive disease [56, 57], whereas this treatment did not result in significantly lower mortality than placebo when given as monotherapy in most of the included patients [58].

In contrast, we have found a protective effect of hydroxychloroquine on death or need for mechanical ventilation, whilst investigators of the Recovery Trial reported that results convincingly exclude any significant mortality advantage of hydroxychloroquine in hospitalized COVID-19 patients [59].

Therefore, our results seem to be counterintuitive and two explanations can be put forward to account for these differences. The first one is obvious: in our population, corticosteroids and tocilizumab worsen the prognosis of patients with COVID-19 pneumonia. In fact, we have performed an exhaustive regression analysis containing significant covariates in an attempt to simultaneously adjust for their effect with the hope of isolating the impact of the intervention. The second explanation has to do with the inherent drawback of retrospective studies: the existence of potential bias and/or confounders. It is important to note that the captured data reflect the patients´ clinical condition at the moment of admission, but this situation changes over time, with some patients improving and some deteriorating, and this surely influences the physician´s decision to prescribe or not a given drug. Since this study was not performed under a controlled condition and treatments were not randomly assigned, we acknowledge that confounding by indication may still persist. Indeed, anti-inflammatory treatment was prescribed in patients with a more severe clinical condition and statistical adjustment for known confounders may not suffice to arrive at 2 groups that have truly the same prognosis at baseline (or, maybe more importantly, in the precise moment that the drug was administered). With hydroxychloroquine it happened exactly the opposite: it was given to patients with less severe disease.

Interestingly, we found that hospital stress was associated with a higher risk of unfavorable outcomes in sensitive analysis, applying different regression schemes (S3 and S4 Tables). A total of 178 out of the 225 deceased patients did not receive mechanical ventilation, but the decision making was not influenced by a lack of ICU resources and clinical criteria based on the likelihood of survival were applied in every case. Although we are not aware of prior studies reporting the association between hospital burden and mortality in patients with COVID-19, this is plausible because hospitals perform worse when they are overwhelmed. Nonetheless, it has been published that the quality of public health systems might be decisive in determining health benefits against pandemics [60]. Moreover, death rate in the North of Italy was twice as high as in the Center-South (13.03% and 6.65%, respectively) during the earlier phase of the current COVID-19 pandemic, likely reflecting a lower hospital stress in the latter (0.81 and 0.20, respectively) [61].

Strengths and limitations

The study’s strengths include the large sample size and the homogeneity of the included population (all patients had microbiologically proven COVID-19 infection and were radiologically diagnosed with pneumonia). Besides, the fact that all Galician hospitals share the same model of electronic medical record enabled us to include every patient admitted to hospital during the study period. Baseline demographic, clinical and laboratory characteristics, alongside the presence of significant comorbidities were individually and exhaustively studied. We also evaluated the effectiveness of viral and host-targeted medications. The main limitation is its retrospective character leading to missing data. Moreover, as aforementioned, studies with retrospective design are not the most accurate to evaluate the impact of treatment on prognosis and survival, due to the possible presence of unnoticed and uncontrolled confounders. Another limitation lies in the unavailability of certain variables that would have been of interest for the aim of our study, such as body mass index.

Conclusion

In conclusion, we identified several predictors of mortality (age, comorbidities, CRP and SpO2 values, the hospitals’ burden, the use of corticosteroids and tociluzumab, and the non-use of hydroxychloroquine) among a large cohort of COVID-19 pneumonia patients consecutively admitted to hospitals in Galicia (Spain) during the first outbreak of the epidemic. These findings offer a valuable insight into the characteristics and outcome of patients hospitalized with COVID-19 pneumonia. Our results also suggest that countries have the opportunity to implement policies aimed at reducing deaths by increasing the availability of hospital beds. Results concerning the efficacy of treatments should be interpreted with caution and more well-designed prospective studies are needed to clarify the role of the different therapies in this clinical context.

Supporting information

S1 Appendix. STROBE statement—checklist of items that should be included in reports of observational studies.

https://doi.org/10.1371/journal.pone.0253465.s001

(DOCX)

S2 Table. Differences between patients who received or not corticosteroids, tocilizumab and hydroxychloroquine.

https://doi.org/10.1371/journal.pone.0253465.s003

(DOCX)

S3 Table. Results of the sensitivity analysis, replacing CRP values by lymphocyte and neutrophil count.

Model 1: enter variables method; Model 2: forward automatic selection method.

https://doi.org/10.1371/journal.pone.0253465.s004

(DOCX)

S4 Table. Results of the sensitivity analysis, replacing CRP values by lymphocyte and neutrophil count and including procalcitonin and platelet count.

Model 1: enter variables method; Model 2: forward automatic selection method.

https://doi.org/10.1371/journal.pone.0253465.s005

(DOCX)

Acknowledgments

The authors acknowledge co-investigators Alberto Fernández-Villar, from the Pneumology Service, Hospital Alvaro Cunqueiro (Vigo), Ana Cobas-Paz, from the Pneumology Service, Hospital POVISA (Vigo) and Fernando Iglesias-Río, from the Pneumology Service, Hospital POVISA (Vigo). The authors also acknowledge Javier Muñiz García and Teresa Pérez Castro for their support in the statistical analysis, and Carlos Fernández Lamela for his great effort in collecting the data from the medical records.

References

  1. 1. WHO Coronavirus Disease (COVID-19) Dashboard. Available online: https://covid19.who.int/ (accessed on August 26, 2020, n.d.).
  2. 2. Johns Hopkins University: https://coronavirus.jhu.edu/data/mortality. Accessed on August 26, 2020, n.d.
  3. 3. Chen T, Wu D, Chen H, Yan W, Yang D, Chen G, et al. Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study. BMJ. 2020 Mar 26;368:m1091. pmid:32217556
  4. 4. Guan WJ, Liang WH, Zhao Y, Liang HR, Chen ZS, Li YM, et al; China Medical Treatment Expert Group for Covid-19. Comorbidity and its impact on 1590 patients with Covid-19 in China: A Nationwide Analysis. Eur Respir J. 2020 Mar 26. pii: 2000547.
  5. 5. Jordan RE, Adab P, Cheng KK. Covid-19: risk factors for severe disease and death. BMJ. 2020 Mar 26;368:m1198. pmid:32217618
  6. 6. Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, et al. Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China. JAMA Intern Med. 2020 Mar 13. pmid:32167524
  7. 7. Cao B, Wang Y, Wen D, Liu W, Wang J, Fan G, et al. A Trial of Lopinavir-Ritonavir in Adults Hospitalized with Severe Covid-19. N Engl J Med. 2020 Mar 18. pmid:32187464
  8. 8. Wu J, Li W, Shi X, Chen Z, Jiang B, Liu J, et al. Early antiviral treatment contributes to alleviate the severity and improve the prognosis of patients with novel coronavirus disease (COVID-19). J Intern Med. 2020 Mar 27. pmid:32220033
  9. 9. Shen C, Wang Z, Zhao F, Yang Y, Li J, Yuan J, et al. Treatment of 5 Critically Ill Patients With COVID-19 With Convalescent Plasma. JAMA. 2020 Mar 27. pmid:32219428
  10. 10. Available on: https://www.cdc.gov/mmwr/volumes/69/wr/mm6945e2.htm?s_cid=mm6945e2_w. (Accessed on November 12, 2020, n-d.)
  11. 11. Du RH, Liang LR, Yang CQ, Wang W, Cao TZ, Li M, et al. Predictors of mortality for patients with COVID-19 pneumonia caused by SARSCoV-2: a prospective cohort study. Eur Respir J 2020; 2002439. pmid:32747392
  12. 12. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet 2020; 395: 507–513. pmid:32007143
  13. 13. Berenguer J, Ryan P, Rodríguez-Baño J, Jarrín I, Carratalà J, Pachón J, et al. Characteristics and predictors of death among 4035 consecutively hospitalized patients with COVID-19 in Spain. Clin Microbiol Infect. 2020: S1198-743X(20)30431-6. pmid:32758659
  14. 14. Rubio-Rivas M, Corbella X, Mora-Luján JM, Loureiro-Amigo J, López Sampalo A, Yera Bergua C, et al. Predicting Clinical Outcome with Phenotypic Clusters in COVID-19 Pneumonia: An Analysis of 12,066 Hospitalized Patients from the Spanish Registry SEMI-COVID-19. J Clin Med. 2020; 9(11): E3488. pmid:33137919
  15. 15. Kalil AC, Patterson TF, Mehta AK, Tomashek KM, Wolfe CR, Ghazaryan V, et al. Baricitinib plus Remdesivir for Hospitalized Adults with Covid-19. N Engl J Med. 2021; 384(9):795–807. pmid:33306283
  16. 16. Salama C, Han J, Yau L, Reiss WG, Kramer B, Neidhart JD, et al. Tocilizumab in Patients Hospitalized with Covid-19 Pneumonia. N Engl J Med. 2021; 384(1): 20–30. pmid:33332779
  17. 17. Borghesi A, Golemi S, Carapella N, Zigliani A, Farina D, Maroldi R. Lombardy, Northern Italy: COVID-19 second wave less severe and deadly than the first? A preliminary investigation. Infect Dis (Lond). 202; 53(5):370–375.
  18. 18. Iftimie S, López-Azcona AF, Vallverdú I, Hernández-Flix S, de Febrer G, Parra S, et al. First and second waves of coronavirus disease-19: A comparative study in hospitalized patients in Reus, Spain. PLoS One. 2021; 16(3): e0248029. pmid:33788866
  19. 19. James N, Menzies M, Radchenko P. COVID-19 second wave mortality in Europe and the United States. Chaos. 2021; 31(3):031105. pmid:33810707
  20. 20. Asch DA, Sheils NE, Islam MN, Chen Y, Werner RM, Buresh J, et al. Variation in US Hospital Mortality Rates for Patients Admitted With COVID-19 During the First 6 Months of the Pandemic. JAMA Intern Med. 2021; 181(4): 471–478. pmid:33351068
  21. 21. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395: 1054–62. pmid:32171076
  22. 22. Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, et al. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern Med. 2020; 180: 1–11. pmid:32167524
  23. 23. Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention. JAMA. 2020;323: 1239. pmid:32091533
  24. 24. Singh AK, Gillies CL, Singh R, Singh A, Chudasama Y, Coles B, et al. Prevalence of co-morbidities and their association with mortality in patients with COVID-19: A systematic review and meta-analysis. Diabetes Obes Metab. 2020 Jun 23:10.1111/dom.14124. pmid:32573903
  25. 25. Imam Z, Odish F, Gill I, O’Connor D, Armstrong J, Vanood A, et al. Older age and comorbidity are independent mortality predictors in a large cohort of 1305 COVID-19 patients in Michigan, United States. J Intern Med. 2020 Jun 4:10.1111/joim.13119. pmid:32498135
  26. 26. Zheng Z, Peng F, Xu B, Zhao J, Liu H, Peng J, et al. Risk factors of critical & mortal COVID-19 cases: A systematic literature review and meta-analysis. J Infect. 2020; 81(2): e16–e25. pmid:32335169
  27. 27. Liu Y, Yan LM, Wan L, Xiang TX, Le A, Liu JM, et al. Viral dynamics in mild and severe cases of COVID-19. Lancet Infect Dis. 2020; 20:656–7. pmid:32199493
  28. 28. Luo X, Zhou W, Yan X, Guo T, Wang B, Xia H, et al. Prognostic value of C-reactive protein in patients with COVID-19. Clin Infect Dis. 2020 May 23: ciaa641. pmid:32344321
  29. 29. Liu F, Li L, Xu M, Wu J, Luo D, Zhu Y, et al. Prognostic value of interleukin-6, C-reactive protein, and procalcitonin in patients with COVID-19. J Clin Virol. 2020 Jun; 127: 104370. pmid:32344321
  30. 30. Russell CD, Millar JE, Baillie JK. Clinical evidence does not support corticosteroid treatment for 2019-nCoV lung injury. Lancet. 2020; 395(10223): 473–475. pmid:32043983
  31. 31. Narain S, Stefanov DG, Chau AS, Weber AG, Marder G, Kaplan B, et al. Comparative Survival Analysis of Immunomodulatory Therapy for Coronavirus Disease 2019 Cytokine Storm. Chest. 2020: S0012-3692(20)34901-1. pmid:33075378
  32. 32. Fadel R, Morrison AR, Vahia A, Smith ZR, Chaudhry Z, Bhargava P, et al. Early Short Course Corticosteroids in Hospitalized Patients with COVID-19. Clin Infect Dis. 2020: ciaa601. pmid:32427279
  33. 33. Salton F, Confalonieri P, Meduri GU, Santus P, Harari S, Scala R, et al. Prolonged Low-Dose Methylprednisolone in Patients with Severe COVID-19 Pneumonia. Open Forum Infect Dis. 2020; 7(10): ofaa421. pmid:33072814
  34. 34. Majmundar M, Kansara T, Lenik JM, Park H, Ghosh K, Doshi R, et al. Efficacy of corticosteroids in non-intensive care unit patients with COVID-19 pneumonia from the New York Metropolitan region. PLoS One. 2020; 15(9): e0238827. pmid:32903258
  35. 35. Ruiz-Irastorza G, Pijoan JI, Bereciartua E, Dunder S, Dominguez J, Garcia-Escudero P, et al. Second week methyl-prednisolone pulses improve prognosis in patients with severe coronavirus disease 2019 pneumonia: An observational comparative study using routine care data. PLoS One. 2020; 15(9): e0239401. pmid:32960899
  36. 36. Mikulska M, Nicolini LA, Signori A, Di Biagio A, Sepulcri C, Russo C, et al. Tocilizumab and steroid treatment in patients with COVID-19 pneumonia. PLoS One. 2020; 15(8): e0237831. pmid:32817707
  37. 37. Ji J, Wu M, Zhong L, Liu Z, Wang C, Shao Z, et al. Early, low-dose, short-term methylprednisolone decreased the mortality in critical COVID-19 patients: a multicenter retrospective cohort study. J Infect. 2020: S0163-4453(20)30696-4. pmid:33176176
  38. 38. Li X, Xu S, Yu M, Wang K, Tao Y, Zhou Y, et al. Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan. J Allergy Clin Immunol. 2020; 146(1): 110–118. pmid:32294485
  39. 39. Li Q, Li W, Jin Y, Xu W, Huang C, Li L, et al. Efficacy Evaluation of Early, Low-Dose, Short-Term Corticosteroids in Adults Hospitalized with Non-Severe COVID-19 Pneumonia: A Retrospective Cohort Study. Infect Dis Ther. 2020: 1–14. pmid:32880102
  40. 40. Horby P, Lim WS, Emberson JR, Mafham M, Bell JL, Linsell L, et al. Dexamethasone in Hospitalized Patients with Covid-19—Preliminary Report. NEJM. 2020 pmid:32678530
  41. 41. Siemieniuk RA, Bartoszko JJ, Ge L, Zeraatkar D, Izcovich A, Kum E, et al. Drug treatments for covid-19: living systematic review and network meta-analysis. BMJ. 2020; 370: m2980. pmid:32732190
  42. 42. WHO Rapid Evidence Appraisal for COVID-19 Therapies (REACT) Working Group. Association Between Administration of Systemic Corticosteroids and Mortality Among Critically Ill Patients With COVID-19: A Meta-analysis. JAMA. 2020; 324(13): 1330–1341. pmid:32876694
  43. 43. van Paassen J, Vos JS, Hoekstra EM, Neumann KMI, Boot PC, Arbous SM. Corticosteroid use in COVID-19 patients: a systematic review and meta-analysis on clinical outcomes. Crit Care. 2020; 24(1):696. pmid:33317589
  44. 44. Liang MY, Chen P, He M, Tang J, Li H, He XL, et al. Corticosteroids Treatment of Patients with Coronavirus Disease 2019: A Propensity Score Matching Study. Curr Med Sci. 2021;41(1): 24–30. pmid:33582901
  45. 45. Albani F, Fusina F, Granato E, Capotosto C, Ceracchi C, Gargaruti R, et al. Corticosteroid treatment has no effect on hospital mortality in COVID-19 patients. Sci Rep. 2021; 11(1): 1015. pmid:33441909
  46. 46. You X, Wu CH, Fu YN, He Z, Huang PF, Chen GP, et al. The use of methylprednisolone in COVID-19 patients: A propensity score matched retrospective cohort study. PLoS One. 2020; 15(12): e0244128. eCollection 2020. pmid:33382734
  47. 47. Wu J, Huang J, Zhu G, Liu Y, Xiao H, Zhou Q, et al. Systemic Corticosteroids and Mortality in Severe and Critical COVID-19 Patients in Wuhan, China. J Clin Endocrinol Metab. 2020; 105(12): dgaa627. pmid:32880390
  48. 48. Yuan M, Xu X, Xia D, Tao Z, Yin W, Tan W, et al. Effects of Corticosteroid Treatment for Non-Severe COVID-19 Pneumonia: A Propensity Score-Based Analysis. Shock. 2020; 54(5): 638–643. pmid:32496422
  49. 49. Liu Z, Li X, Fan G, Zhou F, Wang Y, Huang L, et al. Low-to-moderate dose corticosteroids treatment in hospitalized adults with COVID-19. Clin Microbiol Infect. 2021; 27(1): 112–117. pmid:33007478
  50. 50. Liu J, Zhang S, Dong X, Li Z, Xu Q, Feng H, et al. Corticosteroid treatment in severe COVID-19 patients with acute respiratory distress syndrome. J Clin Invest. 2020; 130(12): 6417–6428. pmid:33141117
  51. 51. Chen Q, Song Y, Wang L, Zhang Y, Han L, Liu J, et al. Corticosteroids treatment in severe patients with COVID-19: a propensity score matching study. Expert Rev Respir Med. 2021; 15(4): 543–552. pmid:33249945
  52. 52. Wu C, Hou D, Du C, Cai Y, Zheng J, Xu J, et al. Corticosteroid therapy for coronavirus disease 2019-related acute respiratory distress syndrome: a cohort study with propensity score analysis. Crit Care. 2020; (1):643. pmid:33172477
  53. 53. Ramiro S, Mostard RLM, Magro-Checa C, van Dongen CMP, Dormans T, Buijs J, et al. Historically controlled comparison of glucocorticoids with or without tocilizumab versus supportive care only in patients with COVID-19-associated cytokine storm syndrome: results of the CHIC study. Ann Rheum Dis. 2020;79(9): 1143–1151. pmid:32719045
  54. 54. Fernández-Ruiz M, López-Medrano F, Pérez-Jacoiste Asín MA, Maestro de la Calle G, Bueno H, Caro-Teller JM, et al. Tocilizumab for the treatment of adult patients with severe COVID-19 pneumonia: A single-center cohort study. J Med Virol. 2020: 10.1002/jmv.26308. pmid:32672860
  55. 55. Perrone F, Piccirillo MC, Ascierto PA, Salvarani C, Parrella R, Marata AM, et al. Tocilizumab for patients with COVID-19 pneumonia. The single-arm TOCIVID-19 prospective trial. J Transl Med. 2020; 18(1):405. pmid:33087150
  56. 56. Investigators REMAP-CAP. Interleukin-6 Receptor Antagonists in Critically Ill Patients with Covid-19. N Engl J Med. 2021; 384(16): 1491–1502. pmid:33631065
  57. 57. RECOVERY Collaborative Group. Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): preliminary results of a randomised, controlled, open-label, platform trial. Medrxiv. Posted February 11, 2021.
  58. 58. Rosas IO, Bräu N, Waters M, Go RC, Hunter BD, Bhagani S, et al. Tocilizumab in Hospitalized Patients with Severe Covid-19 Pneumonia. N Engl J Med. 2021; 384(16): 1503–1516. pmid:33631066
  59. 59. Horby P, Mafham M, Linsell L, Bell JL, Staplin N, Emberson JR, et al. RECOVERY Collaborative Group. Effect of Hydroxychloroquine in Hospitalized Patients with Covid-19. N Engl J Med. 2020; 383(21): 2030–2040. pmid:33031652
  60. 60. Nuzzo JB, Meyer D, Snyder M, Ravi SJ, Lapascu A, Souleles J, et al. What makes health systems resilient against infectious disease outbreaks and natural hazards? Results from a scoping review. BMC Public Health. 2019;19:1310. pmid:31623594
  61. 61. Bigiani L, Bigiani S, Bigiani A. How to Minimize the Impact of Pandemic Events: Lessons From the COVID-19 Crisis. Int J Health Policy Manag. 2020. pmid:32654431