Clinical Microbiology and Infection 27 (2021) 1040.e7e1040.e10 Contents lists available at ScienceDirect Clinical Microbiology and Infection journal homepage: www.clinicalmicrobiologyandinfection.com Research note Not all COVID-19 pandemic waves are alike Pere Domingo 1, *, Virgina Pomar 1, Isabel Mur 1, Ivan Castellví 2, He ctor Corominas 2, 1 Natividad de Benito 1) Department of Infectious Diseases, Hospital de la Santa Creu i Sant Pau, Institut de Recerca del Hospital de la Santa Creu i Sant Pau, Barcelona, Spain 2) Department of Rheumatology, Hospital de la Santa Creu i Sant Pau, Institut de Recerca del Hospital de la Santa Creu i Sant Pau, Barcelona, Spain a r t i c l e i n f o a b s t r a c t Article history: Objective: We aimed to assess differences in patients' profiles in the first two surges of the severe acute Received 10 February 2021 respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in Barcelona, Spain. Received in revised form Methods: We prospectively collected data from all adult patients with SARS-CoV-2 infection diagnosed at 1 April 2021 the Hospital de la Santa Creu i Sant Pau, Barcelona, Spain. All the patients were diagnosed through Accepted 8 April 2021 nasopharyngeal swab PCR. The first surge spanned from 1st March to 13th August 2020, while surge two Available online 19 April 2021 spanned from 14th August to 8th December 2020. Editor: L. Leibovici Results: There were 2479 and 852 patients with microbiologically proven SARS-CoV-2 infection in surges one and two, respectively. Patients from surge two were significantly younger (median age 52 (IQR 35) Keywords: versus 59 (40) years, respectively, p < 0.001), had fewer comorbidities (379/852, 44.5% versus 1237/2479, COVID-19 49.9%, p 0.007), and there was a shorter interval between onset of symptoms and diagnosis (median 3 (5) ICU admission versus 4 (5) days, p < 0.001). All-cause in-hospital mortality significantly decreased for both the whole In-hospital mortality population (24/852, 2.8% versus 218/2479, 8.8%, p < 0.001) and hospitalized patients (20/302, 6.6% versus Independent predictors of mortality 206/1570, 13.1%, p 0.012). At adjusted logistic regression analysis, predictors of in-hospital mortality were Mechanical ventilation older age (per year, adjusted odds ratio (aOR) 1.079, 95%CI 1.063e1.094), male sex (aOR 1.476, 95%CI SARS-CoV-2 infection Surges 1.079e2.018), having comorbidities (aOR 1.414, 95%CI 0.934e2.141), ICU admission (aOR 3.812, 95%CI 1.875e7.751), mechanical ventilation (aOR 2.076, 95%CI 0.968e4.454), and coronavirus disease 2019 (COVID-19) during surge one (with respect to surge two) (aOR 2.176, 95%CI 1.286e3.680). Conclusions: First-wave SARS-CoV-2-infected patients had a more than two-fold higher in-hospital mortality than second-wave patients. The causes are likely multifactorial. Pere Domingo, Clin Micro- biol Infect 2021;27:1040.e7e1040.e10 © 2021 The Author(s). Published by Elsevier Ltd on behalf of European Society of Clinical Microbiology and Infectious Diseases. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/). Introduction patients admitted to the hospitals was not threatening the ability of institutions to receive new ones, attending physicians soon The first wave of the severe acute respiratory syndrome coro- realized that patient characteristics from the two pandemic waves navirus 2 (SARS-CoV-2) pandemic hit Spain strongly, almost were somewhat different. collapsing the public health system [1]. After lockdown measures, the number of patients steadily decreased [1,2]. However, scattered Methods patients continued to be diagnosed during the summer, despite restrictions on population movement. By the end of August 2020, Study design and sample the number of SARS-CoV-2-infected patients began to rise again. By mid-October 2020, the pandemic figures were high enough to We prospectively collected data from all consecutive laboratory- force a new, although partial, lockdown together with an extended confirmed SARS-CoV-2-infected patients diagnosed at the Hospital curfew throughout the country [1]. Although the number of de la Santa Creu I Sant Pau, Barcelona, Spain, a tertiary university * Corresponding author: Pere Domingo, Department of Infectious Diseases, Hospital de la Santa Creu i Sant Pau, Av. Sant Antoni Ma Claret 167, 08025 Barcelona, Spain. E-mail address: pdomingo@santpau.cat (P. Domingo). https://doi.org/10.1016/j.cmi.2021.04.005 1198-743X/© 2021 The Author(s). Published by Elsevier Ltd on behalf of European Society of Clinical Microbiology and Infectious Diseases. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). P. Domingo et al. / Clinical Microbiology and Infection 27 (2021) 1040.e7e1040.e10 1040.e8 urban hospital covering a metropolitan area of 500 000 inhabi- confidence intervals (CIs); p < 0.05 was considered significant for tants. We analysed characteristics of all diagnosed SARS-CoV-2 all statistical tests. Data were analysed using IBM® SPSS®, statistics, patients and those admitted at our Hospital between 1st March version 26.0 (Armonk, NY, USA). and 8th December 2020. We categorized patients into surge one if Results they were diagnosed and admitted between 1st March and 13th August 2020, and into surge two if they were diagnosed and There were 2479 and 852 patients with microbiologically admitted between 14th August and 8th December 2020. These proved SARS-CoV-2 infection in surges one and two respectively. dates were the lowest incidence rates during the two surges in our Patient demographics and clinical characteristics are summarized area. The study was approved by the Ethics Committee of the in Table 1. Patients from the second pandemic wave were signifi- Hospital de la Santa Creu i Sant Pau (Ref. Nr. HSCSP-20/117). cantly younger (median age: 59.0 (35) versus 51.5 (40) years, p < 0.001), while gender distribution was not different between the Laboratory methods two waves. Patients with comorbidities were overrepresented during surge one (Table 1). However, this ratio was reversed when Nasopharyngeal swabs were obtained according to a standard- patients admitted to the hospital were considered (Table 2). In ized hospital protocol. Detection of SARS-CoV-2 was done through surge two, a microbiological diagnosis was obtained fewer days RT-PCR (Xpert® Xpress SARS-CoV-2, Cepheid Iberia, Barcelona, after the onset of symptoms, and infiltrates in chest x-ray were less Spain). common (Table 1). Significantly more patients from the first wave were admitted to the hospital, although the length of hospital stay Statistical methods was not significantly different (Tables 1 and 2). Regarding all SARS-CoV-2-diagnosed patients, those admitted We summarized continuous variables as means (and standard to the hospital were older, although patients hospitalized in surge deviations) or medians (and interquartile ranges) depending on two were still younger than those hospitalized in surge one their distribution, and categorical variables as percentages of the (Table 2). We found that inpatients in surge two had more total sample for that variable. We used the Student t (or Wilcoxon comorbidities and more often required intensive care unit (ICU) rank-sum) and c2 tests (or Fisher's exact tests when appropriate) to admission and mechanical ventilation; despite this, the all-cause evaluate group differences (patients from surges 1 and 2) for mortality was substantially lower, particularly in patients older continuous and categorical variables, respectively. A multivariable than 65 years. After adjusting for relevant clinical variables logistic regression model was used to identify factors indepen- (Table 3), first-wave patients had a more than two-fold higher all- dently associated with a higher risk of mortality. Any variable cause in-hospital mortality than second-wave patients. tested in univariate analysis with p < 0.25 and all known clinical significance variables were selected as the first multivariate model Discussion candidates. We then followed the purposeful selection of covariates method described by Hosmer et al. [3]. Final parameter estimates We found striking differences between patients with SARS-CoV- are shown as odds ratios (ORs) with their corresponding 95% 2 infection presenting during the first two waves of the pandemic Table 1 Sociodemographic, comorbidity, clinical and outcome characteristics in patients diagnosed with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) surge 1 and surge 2 Surge 1 (n ¼ 2479) Surge 2 (n ¼ 852) p Age, yearsdmedian (IQR) 59.0 (35.0) 51.5 (40.0) <0.001 <18 years, n (%) 24 (0.9) 46 (5.4) <0.001 18e64 years, n (%) 1433 (57.8) 531 (62.3) 0.0230 65 years, n (%) 1022 (41.2) 275 (32.3) <0.001 Gender Male, n (%) 1136 (45.8) 417 (48.9) 0.1249 Female, n (%) 1343 (54.2) 435 (51.1) Onset symptoms (PCR), daysdmedian (IQR) 4.0 (5.0) 3.0 (5.0) <0.001 Comorbiditiesa, n (%) 1237 (49.9) 379 (44.5) 0.0071 Arterial hypertension, n (%) 862 (34.8) 241 (28.3) 0.0006 Diabetes mellitus, n (%) 327 (13.2) 93 (10.9) 0.0957 CKD, n (%) 169 (6.8) 74 (8.7) 0.0831 Dementia, n (%) 155 (6.3) 25 (2.9) <0.001 COPD, n (%) 136 (5.5) 38 (4.5) 0.2838 Heart disease, n (%) 133 (5.4) 52 (6.1) 0.4684 Cancer, n (%) 116 (4.7) 53 (6.2) 0.0933 Obesity, n (%) 115 (4.6) 33 (3.9) 0.4012 Pregnancy, n (%) 33 (2.4) 26 (6.0) <0.001 Hospital admission, n (%) 1534 (61.9) 302 (35.4) <0.001 Chest x-ray infiltrates, n (%) 1332 (53.7) 147/647 (22.7) <0.001 All-cause mortality, n (%) 218 (8.8) 24 (2.8) <0.001 <18 y, n (%) 0 (0) 1 (0.2) d 18e64, n (%) 32 (2.2) 5 (0.9) 0.0924 >65 y 186 (18.2) 18 (6.5) <0.001 Male, n (%) 120 (4.8) 13 (1.5) <0.001 Female, n (%) 98 (3.9) 11 (1.3) <0.001 Values are expressed as numbers and percentage or as median and interquartile ranges (IQR) unless otherwise specified. IQR, interquartile range; PCR, polymerase chain reaction; CKD, chronic kidney disease; COPD, chronic pulmonary obstructive disease. a A patient can have more than one comorbidity or therapeutic intervention. 1040.e9 P. Domingo et al. / Clinical Microbiology and Infection 27 (2021) 1040.e7e1040.e10 Table 2 Sociodemographic, comorbidity, clinical and outcome characteristics in surge 1 and surge 2 hospitalized patients with coronavirus 2019 disease (COVID-19) Surge 1 (n ¼ 1570) Surge 2 (n ¼ 302) p Age, yearsdmedian (IQR) 68.0 (27.0) 67.0 (24.0) 0.071 <18 y, n (%) 3 (0.2) 2 (0.7) 0.344 18e64 y, n (%) 713 (45.4) 138 (45.7) 65 y, n (%) 854 (54.4) 162 (53.6) Gender male, n (%) 824 (52.5) 185 (61.3) 0.005 Onset symptoms PCR, daysdmedian (IQR) 5.0 (5.0) 4.0 (5.0) 0.249 Comorbiditiesa, n (%) 998 (63.6) 223 (74.3) <0.001 Arterial hypertension, n (%) 719 (45.8) 149 (49.3) 0.258 Diabetes mellitus, n (%) 291 (18.5) 56 (18.5) 0.997 CKD, n (%) 146 (9.3) 25 (8.3) 0.573 COPD, n (%) 115 (7.3) 28 (9.3) 0.243 Heart disease, n (%) 114 (7.3) 34 (11.3) 0.018 Cancer, n (%) 88 (5.6) 26 (8.6) 0.046 Obesity, n (%) 101 (6.4) 28 (9.3) 0.075 Dementia, n (%) 113 (7.2) 5 (1.7) <0.001 Pregnancy, n (%) 10 (0.6) 6 (2.0) 0.032 Therapeutic interventions HCQ þ AZR, n (%) 1122 (71.5) 0 (0) d Antibiotics, n (%) 620 (39.5) 129 (42.7) 0.4973 DRV/c/TAF/FTC, n (%) 47 (2.9) 0 (0) d Corticosteroids, n (%) 0 (0) 44 (5.2) d Tocilizumab, n (%) 58 (3.7) 28 (9.3) <0.001 IFN, n (%) 2 (0.1) 0 (0) d LPV/r, n (%) 1 (0.06) 0 (0) d Remdesivir, n (%) 0 (0) 1 (0.3) d ICU admission, n (%) 172 (10.9) 53 (17.5) <0.001 Mechanical ventilation, n (%) 124 (7.9) 35 (11.6) 0.018 Hospital stay, daysdmedian (IQR) 5.0 (6.0) 5.0 (8.0) 0.751 All-cause in-hospital mortality, n (%) 206 (13.1) 20 (6.6) 0.012 <18 years, n (%) 0 (0) 0 (0) d 18e64 years, n (%) 31 (4.4) 4 (3.2) 0.749 >65 years, n (%) 175 (20.5) 16 (9.9) 0.012 Male, n (%) 114 (13.8) 13 (8.2) 0.069 Female, n (%) 92 (12.3) 7 (6.8) 0.139 Values are expressed as numbers and percentages or as medians and interquartile ranges (IQRs) unless otherwise specified. PCR, polymerase chain reaction; CKD, chronic kidney disease; COPD, chronic pulmonary obstructive disease; HCQ, hydroxychloroquine; AZR, azithromycin; DRV/c/TAF/FTC, darunavir/cobicistat/tenofovir/alafenamide/ emtricitabine; IFN, interferon; LPV/r, lopinavir/ritonavir; ICU, intensive care unit. a A patient can have more than one comorbidity or therapeutic intervention. in Barcelona, Spain. Similar changes have been described in multiple spike protein mutationsdhas been detected in the United different geographical settings [4,5]. Possible explanations are Kingdom [10]. It is significantly more transmissible than previously various, including the increased ability to perform an aetiological reported variants, although it is not clearly associated with more diagnosis thanks to the availability of diagnostic tests, the lack of severe disease [10]. Moreover, a new SARS-CoV-2 variantdknown which was a severe drawback during the first pandemic wave. This as 20H/501Y.V2 or B.1.351, carrying many mutations in the spike wider availability may have led to the diagnosis of an increased proteindis quickly spreading in South Africa, and the P.1 variant, number of asymptomatic patients or patients in earlier phases of which is predominant in the Amazon region (Brazil), has three the disease when careful surveillance can be performed early and mutations in the spike receptor-binding domain thought to affect adequate interventions started promptly. The shorter interval be- its transmissibility and antigenic profile [11]. Unfortunately, we do tween the onset of symptoms and the microbiological diagnosis not have viral sequencing available at our hospital to document among patients in the second pandemic wave exemplifies this these possible changes. point (Table 1). During the first pandemic wave, except for sup- Modification of population structure may have played a signif- portive care, there were no interventions to modify the patho- icant role in pandemic behaviour, explaining the differential patient physiology of SARS-CoV-2 infection. However, randomized clinical profile. It could be that the most fragile patients, especially those trials have since shown which pharmacological interventions are institutionalized and those living in nursing homes, had already useless and which have some clinical benefit, such as remdesivir succumbed during the first pandemic wave. Their excess death rate and dexamethasone [6,7]. Nonetheless, remdesivir was not used in could partially explain the age shift since older adults represented our patients, while corticosteroids (mostly dexamethasone) were 41.5% and 32.3% of patients in both pandemic waves, respectively used only marginally during the study period (Table 2). The (Table 1). Besides, the enormous efforts made to protect this preferred immunomodulating agent in our hospital was tocilizu- vulnerable population may have impacted its reduced representa- mab, and combination therapy was not often used. tion during the second wave. We cannot thoroughly exclude viral changes implying shifts in The decreased hospital admission rates and pulmonary in- SARS-CoV-2 pathogenicity. However, the evidence of significant filtrates during the second pandemic wave suggest milder disease viral variation is limited to patients described in Singapore [8] and (Table 1). Nevertheless, a diagnostic bias cannot be excluded since, the amino acid change documented in the viral spike when it in surge one, microbiological tests were reserved for more severe reached Europe some months ago, a change which increased its patients (usually those requiring hospitalization) or perhaps for replicative capacity and transmissibility [9]. Recently, a SARS-CoV-2 patients with higher survival chances. Measures for controlling the variantdreferred to as SARS-CoV-2 VUI 202012/01 or B.1.1.7, with pandemic, such as more cautious social interaction and wearing P. Domingo et al. / Clinical Microbiology and Infection 27 (2021) 1040.e7e1040.e10 1040.e10 Table 3 All authors coordinated and oversaw the development of the Multivariable risk factors for death in Covid-19 inpatients manuscript. All authors participated in data interpretation. The Risk factor Adjusted odds ratio (95%CI) p manuscript was drafted by PD. All authors provided input to the Surge 1 (versus surge 2) 2.176 (1.286e3.680) 0.004 report and approved the final version of the manuscript. Age 1.079 (1.063e1.094) <0.001 Male sex 1.476 (1.079e2.018) 0.015 Comorbidity 1.414 (0.934e2.141) 0.101 Transparency declaration ICU admission 3.812 (1.875e7.751) <0.001 Mechanical ventilation 2.076 (0.968e4.454) 0.061 All authors declare no conflicts of interest. This work was Intercept 0 <0.001 partially supported by grant COV20/00070 (to PD), Instituto de R2 of Nagerkelke ¼ 0.244. Salud Carlos III, Madrid, Spain and by grant COVID19-PoC (to IC), Departament de Salut and BIOCET, Generalitat de Catalunya. PD is supported by a grant from the Programa de Intensificacio  n de masks, could be associated with decreased viral inoculum, and viral Investigadores (INT19/00036)-ISCIII. The funding sources played no load on admission is related to mortality [12,13]. Asch et al. [4] part in this work. found that the most substantial risk factor for hospital mortality was community prevalence of COVID-19, consistent with such an assumption. References In-hospital all-cause mortality significantly decreased during [1] Red Nacional de Vigilancia Epidemiolo gica. Situacio  n de COVID-19 en Espan~a the second wave, despite the higher percentage of hospitalized n de COVID-19 en Espan ~ a. a 9 de diciembre de 2020. Informe nº 56. Situacio people with comorbidities and disease severity markers such as ICU Casos diagnosticados a partir 10 de mayo. https://www.isciii.es/QueHacemos/ admission and mechanical ventilation (Table 2). The causes of such Servicios/VigilanciaSaludPublicaRENAVE/EnfermedadesTransmisibles/ a decrease are not entirely understood, but they are probably Documents/INFORMES/Informes%20COVID-19/Informe%20COVID-19.%20N% C2%BA%2056_09%20de%20diciembre%20de%202020.pdf. multifactorial, including an earlier diagnosis with less severe lung [2] Sehra ST, Salciccioli JD, Wiebe DJ, Fundin S, Baker JF. Maximum daily tem- involvement, and earlier subsequent interventions. The shorter perature, precipitation, ultraviolet light, and rates of transmission of severe interval between the onset of symptoms and diagnosis suggests acute respiratory syndrome coronavirus 2 in the United States. Clin Infect Dis 2020;71:2482e7. that this was an operating mechanism in the pandemic change. 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