First and Second Waves of Coronavirus Disease 2019 in Madrid, Spain: Clinical Characteristics and Hematological Risk Factors Associated With Critical/Fatal Illness

Abstract

Objectives: This study aims to determine similarities and differences in clinical characteristics between the patients from two waves of severe acute respiratory syndrome coronavirus-2 infection at the time of hospital admission, as well as to identify risk biomarkers of coronavirus disease 2019 severity. Design: Retrospective observational study. Setting: A single tertiary-care center in Madrid. Patients: Coronavirus disease 2019 adult patients admitted to hospital from March 4, 2020, to March 25, 2020 (first infection wave), and during July 18, 2020, and August 20, 2020 (second infection wave). Interventions: Treatment with a hospital-approved drug cocktail during hospitalization. Measurements and Main Results: Demographic, clinical, and laboratory data were compared between the patients with moderate and critical/fatal illness across both infection waves. The median age of patients with critical/fatal coronavirus disease 2019 was 67.5 years (interquartile range, 56.75–78.25 yr; 64.5% male) in the first wave and 59.0 years (interquartile range, 48.25–80.50 yr; 70.8% male) in the second wave. Hypertension and dyslipidemia were major comorbidities in both waves. Body mass index over 25 and presence of bilateral pneumonia were common findings. Univariate logistic regression analyses revealed an association of a number of blood parameters with the subsequent illness progression and severity in both waves. However, some remarkable differences were detected between both waves that prevented an accurate extrapolation of prediction models from the first wave into the second wave. Interleukin-6 and d-dimer concentrations at the time of hospital admission were remarkably higher in patients who developed a critical/fatal condition only during the first wave (p < 0.001), although both parameters significantly increased with disease worsening in follow-up studies from both waves. Multivariate analyses from wave 1 rendered a predictive signature for critical/fatal illness upon hospital admission that comprised six blood biomarkers: neutrophil-to-lymphocyte ratio (≥ 5; odds ratio, 2.684 [95% CI, 1.143–6.308]), C-reactive protein (≥ 15.2 mg/dL; odds ratio, 2.412 [95% CI, 1.006–5.786]), lactate dehydrogenase (≥ 411.96 U/L; odds ratio, 2.875 [95% CI, 1.229–6.726]), interleukin-6 (≥ 78.8 pg/mL; odds ratio, 5.737 [95% CI, 2.432–13.535]), urea (≥ 40 mg/dL; odds ratio, 1.701 [95% CI, 0.737–3.928]), and d-dimer (≥ 713 ng/mL; odds ratio, 1.903 [95% CI, 0.832–4.356]). The predictive accuracy of the signature was 84% and the area under the receiver operating characteristic curve was 0.886. When the signature was validated with data from wave 2, the accuracy was 81% and the area under the receiver operating characteristic curve value was 0.874, albeit most biomarkers lost their independent significance. Follow-up studies reassured the importance of monitoring the biomarkers included in the signature, since dramatic increases in the levels of such biomarkers occurred in critical/fatal patients over disease progression. Conclusions: Most parameters analyzed behaved similarly in the two waves of coronavirus disease 2019. However, univariate logistic regression conducted in both waves revealed differences in some parameters associated with poor prognosis in wave 1 that were not found in wave 2, which may reflect a different disease stage of patients on arrival to hospital. The six-biomarker predictive signature reported here constitutes a helpful tool to classify patient’s prognosis on arrival to hospital.

COVID-19: A comparative study of severity of patients hospitalized during the first and the second wave in South Africa

“…In contrast with most reports of second waves outside of South Africa, our study found that patients hospitalised during the second wave in a single hospital in the ECP were significantly older than in the first [6][7][8]. Of note, the second wave coincided with the end of the school and university years and also the annual summer public holidays in which there was significant liberalisation of lockdown rules.…”

“…Until November 2020, there had been a shift towards patients that were younger, with fewer associated comorbidities and lower in-hospital mortality. The latter was probably multifactorial and linked to the younger age, the lower comorbidity burden, possibly better medical management and less severe disease [1,[6][7][8][9]. However, the B 1.1.7 variant that emerged in November 2020 in the south of England and spread to both Europe and the United States (US) has been associated with higher transmissibility and mortality [4-5-10].…”

Circulating MR-proADM levels, as an indicator of endothelial dysfunction, for early risk stratification of mid-term mortality in COVID-19 patients

“…Noteworthy, most of these studies focused on a short follow-up period to outcome (28/30 days) [ García de Guadiana-Romualdo et al, 2021 ; Gregoriano et al, 2021 ]. Finally, differences in the predictive accuracies of biomarkers as D-dimer or IL-6 between the first and second wave have been reported, reflecting a different disease stage of patients on arrival to hospital [Mollinedo-Gajate et al, 2021] and a lower severity during the second wave [Fan et al, 2020] , conditions both affecting to the accuracy of biomarkers.…”

International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort Study

“…To date, there have been reports of at least two waves in numerous countries, including an initial one in the Spring of 2020 and a resurgence of cases in the Summer and Fall of 2020 [1][2][3][4][5][6][7][8][9][10]. A limited number of single-center studies have reported differences in laboratory values, demographic composition, and disease management between patients with COVID-19 admitted in the first and second waves [6,8,11,12]. Thus, there is substantial interest in comparing the clinical trajectories of patients with SARS-CoV-2 who were hospitalized across different waves of the pandemic to better understand the rapidly evolving epidemiology, pathophysiology, and health care dynamics of the COVID-19 pandemic.…”