Long-term kidney function recovery and mortality after COVID-19-associated acute kidney injury: An international multi-centre observational cohort study.

Background: While acute kidney injury (AKI) is a common complication in COVID-19, data on post-AKI kidney function recovery and the clinical factors associated with poor kidney function recovery is lacking. Methods: A retrospective multi-centre observational cohort study comprising 12,891 hospitalized patients aged 18 years or older with a diagnosis of SARS-CoV-2 infection confirmed by polymerase chain reaction from 1 January 2020 to 10 September 2020, and with at least one serum creatinine value 1-365 days prior to admission. Mortality and serum creatinine values were obtained up to 10 September 2021. Findings: Advanced age (HR 2.77, 95%CI 2.53-3.04, p < 0.0001), severe COVID-19 (HR 2.91, 95%CI 2.03-4.17, p < 0.0001), severe AKI (KDIGO stage 3: HR 4.22, 95%CI 3.55-5.00, p < 0.0001), and ischemic heart disease (HR 1.26, 95%CI 1.14-1.39, p < 0.0001) were associated with worse mortality outcomes. AKI severity (KDIGO stage 3: HR 0.41, 95%CI 0.37-0.46, p < 0.0001) was associated with worse kidney function recovery, whereas remdesivir use (HR 1.34, 95%CI 1.17-1.54, p < 0.0001) was associated with better kidney function recovery. In a subset of patients without chronic kidney disease, advanced age (HR 1.38, 95%CI 1.20-1.58, p < 0.0001), male sex (HR 1.67, 95%CI 1.45-1.93, p < 0.0001), severe AKI (KDIGO stage 3: HR 11.68, 95%CI 9.80-13.91, p < 0.0001), and hypertension (HR 1.22, 95%CI 1.10-1.36, p = 0.0002) were associated with post-AKI kidney function impairment. Furthermore, patients with COVID-19-associated AKI had significant and persistent elevations of baseline serum creatinine 125% or more at 180 days (RR 1.49, 95%CI 1.32-1.67) and 365 days (RR 1.54, 95%CI 1.21-1.96) compared to COVID-19 patients with no AKI. Interpretation: COVID-19-associated AKI was associated with higher mortality, and severe COVID-19-associated AKI was associated with worse long-term post-AKI kidney function recovery. Funding: Authors are supported by various funders, with full details stated in the acknowledgement section.

A Process Mining Pipeline to Characterize COVID-19 Patients' Trajectories and Identify Relevant Temporal Phenotypes From EHR Data.

The impact of the COVID-19 pandemic involved the disruption of the processes of care and the need for immediately effective re-organizational procedures. In the context of digital health, it is of paramount importance to determine how a specific patients' population reflects into the healthcare dynamics of the hospital, to investigate how patients' sub-group/strata respond to the different care processes, in order to generate novel hypotheses regarding the most effective healthcare strategies. We present an analysis pipeline based on the heterogeneous collected data aimed at identifying the most frequent healthcare processes patterns, jointly analyzing them with demographic and physiological disease trajectories, and stratify the observed cohort on the basis of the mined patterns. This is a process-oriented pipeline which integrates process mining algorithms, and trajectory mining by topological data analyses and pseudo time approaches. Data was collected for 1,179 COVID-19 positive patients, hospitalized at the Italian Hospital "Istituti Clinici Salvatore Maugeri" in Lombardy, integrating different sources including text admission letters, EHR and hospital infrastructure data. We identified five temporal phenotypes, from laboratory values trajectories, which are characterized by statistically significant different death risk estimates. The process mining algorithms allowed splitting the data in sub-cohorts as function of the pandemic waves and of the temporal trajectories showing statistically significant differences in terms of events characteristics.

International electronic health record-derived post-acute sequelae profiles of COVID-19 patients.

The risk profiles of post-acute sequelae of COVID-19 (PASC) have not been well characterized in multi-national settings with appropriate controls. We leveraged electronic health record (EHR) data from 277 international hospitals representing 414,602 patients with COVID-19, 2.3 million control patients without COVID-19 in the inpatient and outpatient settings, and over 221 million diagnosis codes to systematically identify new-onset conditions enriched among patients with COVID-19 during the post-acute period. Compared to inpatient controls, inpatient COVID-19 cases were at significant risk for angina pectoris (RR 1.30, 95% CI 1.09-1.55), heart failure (RR 1.22, 95% CI 1.10-1.35), cognitive dysfunctions (RR 1.18, 95% CI 1.07-1.31), and fatigue (RR 1.18, 95% CI 1.07-1.30). Relative to outpatient controls, outpatient COVID-19 cases were at risk for pulmonary embolism (RR 2.10, 95% CI 1.58-2.76), venous embolism (RR 1.34, 95% CI 1.17-1.54), atrial fibrillation (RR 1.30, 95% CI 1.13-1.50), type 2 diabetes (RR 1.26, 95% CI 1.16-1.36) and vitamin D deficiency (RR 1.19, 95% CI 1.09-1.30). Outpatient COVID-19 cases were also at risk for loss of smell and taste (RR 2.42, 95% CI 1.90-3.06), inflammatory neuropathy (RR 1.66, 95% CI 1.21-2.27), and cognitive dysfunction (RR 1.18, 95% CI 1.04-1.33). The incidence of post-acute cardiovascular and pulmonary conditions decreased across time among inpatient cases while the incidence of cardiovascular, digestive, and metabolic conditions increased among outpatient cases. Our study, based on a federated international network, systematically identified robust conditions associated with PASC compared to control groups, underscoring the multifaceted cardiovascular and neurological phenotype profiles of PASC.

Changes in laboratory value improvement and mortality rates over the course of the pandemic: an international retrospective cohort study of hospitalised patients infected with SARS-CoV-2.

OBJECTIVE: To assess changes in international mortality rates and laboratory recovery rates during hospitalisation for patients hospitalised with SARS-CoV-2 between the first wave (1 March to 30 June 2020) and the second wave (1 July 2020 to 31 January 2021) of the COVID-19 pandemic. DESIGN, SETTING AND PARTICIPANTS: This is a retrospective cohort study of 83 178 hospitalised patients admitted between 7 days before or 14 days after PCR-confirmed SARS-CoV-2 infection within the Consortium for Clinical Characterization of COVID-19 by Electronic Health Record, an international multihealthcare system collaborative of 288 hospitals in the USA and Europe. The laboratory recovery rates and mortality rates over time were compared between the two waves of the pandemic. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was all-cause mortality rate within 28 days after hospitalisation stratified by predicted low, medium and high mortality risk at baseline. The secondary outcome was the average rate of change in laboratory values during the first week of hospitalisation. RESULTS: Baseline Charlson Comorbidity Index and laboratory values at admission were not significantly different between the first and second waves. The improvement in laboratory values over time was faster in the second wave compared with the first. The average C reactive protein rate of change was -4.72 mg/dL vs -4.14 mg/dL per day (p=0.05). The mortality rates within each risk category significantly decreased over time, with the most substantial decrease in the high-risk group (42.3% in March-April 2020 vs 30.8% in November 2020 to January 2021, p<0.001) and a moderate decrease in the intermediate-risk group (21.5% in March-April 2020 vs 14.3% in November 2020 to January 2021, p<0.001). CONCLUSIONS: Admission profiles of patients hospitalised with SARS-CoV-2 infection did not differ greatly between the first and second waves of the pandemic, but there were notable differences in laboratory improvement rates during hospitalisation. Mortality risks among patients with similar risk profiles decreased over the course of the pandemic. The improvement in laboratory values and mortality risk was consistent across multiple countries.

International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality.

Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory values and standard demographic and clinical covariates across healthcare systems, countries, and continents. Specifically, we trained a Cox regression model with nine measured laboratory test values, standard demographics at admission, and comorbidity burden pre-admission. These models were compared at site, country, and continent level. Of the 39,969 hospitalized patients with COVID-19 (68.6% male), 5717 (14.3%) died. In the Cox model, age, albumin, AST, creatine, CRP, and white blood cell count are most predictive of mortality. The baseline covariates are more predictive of mortality during the early days of COVID-19 hospitalization. Models trained at healthcare systems with larger cohort size largely retain good transportability performance when porting to different sites. The combination of routine laboratory test values at admission along with basic demographic features can predict mortality in patients hospitalized with COVID-19. Importantly, this potentially deployable model differs from prior work by demonstrating not only consistent performance but also reliable transportability across healthcare systems in the US and Europe, highlighting the generalizability of this model and the overall approach.

Renin Angiotensin System Blockers and Risk of Mortality in Hypertensive Patients Hospitalized for COVID-19: An Italian Registry.

BACKGROUND: It is uncertain whether exposure to renin-angiotensin system (RAS) modifiers affects the severity of the new coronavirus disease 2019 (COVID-19) because most of the available studies are retrospective. METHODS: We tested the prognostic value of exposure to RAS modifiers (either angiotensin-converting enzyme inhibitors [ACE-Is] or angiotensin receptor blockers [ARBs]) in a prospective study of hypertensive patients with COVID-19. We analyzed data from 566 patients (mean age 75 years, 54% males, 162 ACE-Is users, and 147 ARBs users) hospitalized in five Italian hospitals. The study used systematic prospective data collection according to a pre-specified protocol. All-cause mortality during hospitalization was the primary outcome. RESULTS: Sixty-six patients died during hospitalization. Exposure to RAS modifiers was associated with a significant reduction in the risk of in-hospital mortality when compared to other BP-lowering strategies (odds ratio [OR]: 0.54, 95% confidence interval [CI]: 0.32 to 0.90, p = 0.019). Exposure to ACE-Is was not significantly associated with a reduced risk of in-hospital mortality when compared with patients not treated with RAS modifiers (OR: 0.66, 95% CI: 0.36 to 1.20, p = 0.172). Conversely, ARBs users showed a 59% lower risk of death (OR: 0.41, 95% CI: 0.20 to 0.84, p = 0.016) even after allowance for several prognostic markers, including age, oxygen saturation, occurrence of severe hypotension during hospitalization, and lymphocyte count (adjusted OR: 0.37, 95% CI: 0.17 to 0.80, p = 0.012). The discontinuation of RAS modifiers during hospitalization did not exert a significant effect (p = 0.515). CONCLUSIONS: This prospective study indicates that exposure to ARBs reduces mortality in hospitalized patients with COVID-19.

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

[This corrects the article DOI: 10.2196/31400.].

COVID-19-Associated Subacute Thyroiditis: Evidence-Based Data From a Systematic Review.

Subacute thyroiditis (SAT) is a thyroid disease of viral or post-viral origin. Whether SAT represents a complication of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is still unclear. Our aim was to systematically review the literature to 1) explore the size of the literature about SAT in COVID-19 and 2) evaluate the clinical characteristics of SAT. PubMed/MEDLINE, Embase, and Scopus were searched until April 20, 2021. Original papers, case reports, and case series reporting SAT in COVID-19 patients were included. Authors and their country, journal, year of publication, COVID-19 and SAT clinical presentation, thyroid function, therapy, and follow-up data were extracted. Nineteen papers (17 case reports and 2 case series) were included, describing 27 patients, 74.1% females, aged 18 to 69 years. COVID-19 was diagnosed by nasopharyngeal swab in 66.7% cases and required hospitalization in 11.1%. In 83.3% cases, SAT occurred after COVID-19. Neck pain was present in 92.6% cases and fever in 74.1%. Median TSH, fT3, and fT4 were 0.01 mU/l, 10.79 pmol/l, and 27.2 pmol/l, respectively. C-reactive-protein and erythrocyte sedimentation rate were elevated in 96% of cases. Typical ultrasonographic characteristics of SAT were observed in 83.3% of cases. Steroids were the most frequent SAT therapy. Complete remission of SAT was recorded in most cases. In conclusion, the size and quality of published data of SAT in COVID-19 patients are poor, with only case reports and case series being available. SAT clinical presentation in COVID-19 patients seems to be similar to what is generally expected.

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

BACKGROUND: Many countries have experienced 2 predominant waves of COVID-19-related hospitalizations. Comparing the clinical trajectories of patients hospitalized in separate waves of the pandemic enables further understanding of the evolving epidemiology, pathophysiology, and health care dynamics of the COVID-19 pandemic. OBJECTIVE: In this retrospective cohort study, we analyzed electronic health record (EHR) data from patients with SARS-CoV-2 infections hospitalized in participating health care systems representing 315 hospitals across 6 countries. We compared hospitalization rates, severe COVID-19 risk, and mean laboratory values between patients hospitalized during the first and second waves of the pandemic. METHODS: Using a federated approach, each participating health care system extracted patient-level clinical data on their first and second wave cohorts and submitted aggregated data to the central site. Data quality control steps were adopted at the central site to correct for implausible values and harmonize units. Statistical analyses were performed by computing individual health care system effect sizes and synthesizing these using random effect meta-analyses to account for heterogeneity. We focused the laboratory analysis on C-reactive protein (CRP), ferritin, fibrinogen, procalcitonin, D-dimer, and creatinine based on their reported associations with severe COVID-19. RESULTS: Data were available for 79,613 patients, of which 32,467 were hospitalized in the first wave and 47,146 in the second wave. The prevalence of male patients and patients aged 50 to 69 years decreased significantly between the first and second waves. Patients hospitalized in the second wave had a 9.9% reduction in the risk of severe COVID-19 compared to patients hospitalized in the first wave (95% CI 8.5%-11.3%). Demographic subgroup analyses indicated that patients aged 26 to 49 years and 50 to 69 years; male and female patients; and black patients had significantly lower risk for severe disease in the second wave than in the first wave. At admission, the mean values of CRP were significantly lower in the second wave than in the first wave. On the seventh hospital day, the mean values of CRP, ferritin, fibrinogen, and procalcitonin were significantly lower in the second wave than in the first wave. In general, countries exhibited variable changes in laboratory testing rates from the first to the second wave. At admission, there was a significantly higher testing rate for D-dimer in France, Germany, and Spain. CONCLUSIONS: Patients hospitalized in the second wave were at significantly lower risk for severe COVID-19. This corresponded to mean laboratory values in the second wave that were more likely to be in typical physiological ranges on the seventh hospital day compared to the first wave. Our federated approach demonstrated the feasibility and power of harmonizing heterogeneous EHR data from multiple international health care systems to rapidly conduct large-scale studies to characterize how COVID-19 clinical trajectories evolve.

Modulation of ACE-2 mRNA by inflammatory cytokines in human thyroid cells: a pilot study.

INTRODUCTION: Angiotensin-converting-enzyme-2 (ACE-2) was demonstrated to be the receptor for cellular entry of SARS-CoV-2. ACE-2 mRNA was identified in several human tissues and recently also in thyroid cells in vitro. PURPOSE: Aim of the present study was to investigate the effect of pro-inflammatory cytokines on the ACE-2 mRNA levels in human thyroid cells in primary cultures. METHODS: Primary thyroid cell cultures were treated with IFN-γ and TNF-α alone or in combination for 24 h. ACE-2 mRNA levels were measured by RT-PCR. As a control, the levels of IFN-γ inducible chemokine (CXCL10) were measured in the respective cell culture supernatants. RESULTS: The mean levels of ACE-2 mRNA increased after treatment with IFN-γ and TNF-α in all the thyroid cell preparations, while the combination treatment did not consistently synergically increase ACE-2-mRNA. At difference, CXCL10 was consistently increased by IFN-γ and synergically further increased by the combination treatment with IFN-γ + TNF-α, with respect to IFN-γ alone. CONCLUSIONS: The results of the present study show that IFN-γ and, to a lesser extent TNF-α consistently increase ACE-2 mRNA levels in NHT primary cultures. More interestingly, the combined stimulation (proven to be effective according to the synergic effect registered for CXCL10) produces different responses in terms of ACE-2 mRNA modulation. These results would suggest that elevated levels of pro-inflammatory cytokines could facilitate the entering of the virus in cells by further increasing ACE-2 expression and/or account for the different degree of severity of SARS-COV-2 infection. This hypothesis deserves to be confirmed by further specific studies.

Incidence of De Quervain's thyroiditis during the COVID-19 pandemic in an area heavily affected by Sars-CoV-2 infection.

PURPOSE: To evaluate the possible association between Covid-19 infection and subacute thyroiditis. METHODS: We reviewed the medical and imaging records of patients referred to our Department's outpatient setting dedicated to 'thyroid emergency' (records with a 'bollino verde'-green sticker, classifed as urgent) from April 2020 to October 2020. This outpatient clinic is devoted to patients requiring evaluation for severe hypothyroidism, thyrotoxicosis and neck discomfort or pain. All patients with a newly-diagnosed subacute thyroiditis were selected. The data of all patients receiving a diagnosis of subacute thyroiditis was collected retrospectively, taking into account the same period of time (April-October) and starting from 2016. RESULTS: During the COVID-19 outbreak in our region (April 2020 to October 2020) 396 patients attended the outpatient emergency clinic. Among them, 10 (2.5%) patients received a diagnosis of subacute thyroiditis. In a single patient, a 44-year-old man, a COVID-19 pulmonary infection had been diagnosed 7 weeks before the diagnosis of subacute thyroiditis. All of the remaining patients were and remain COVID-19 free as confirmed by telephone interview. The percentage of patients who received a diagnosis of subacute thyroiditis in the same period starting from 2016 was very similar (2.9%, 2.9%, 2.6% and 3.0% in 2016, 2017, 2018 and 2019, respectively). CONCLUSIONS: Our data do not show an increase in the incidence of subacute thyroiditis in the Brescia area, a region with the highest prevalence of COVID-19 in Italy during the period of the pandemic outbreak.

Interleukin-6, CXCL10 and Infiltrating Macrophages in COVID-19-Related Cytokine Storm: Not One for All But All for One!

SARS-COV-2 virus is responsible for the ongoing devastating pandemic. Since the early phase of the pandemic, the "cytokine-storm" appeared a peculiar aspect of SARS-COV-2 infection which, at least in the severe cases, is responsible for respiratory treat damage and subsequent multi-organ failure. The efforts made in the last few months elucidated that the cytokine-storm results from a complex network involving cytokines/chemokines/infiltrating-immune-cells which orchestrate the aberrant immune response in COVID-19. Clinical and experimental studies aimed at depicting a potential "immune signature" of SARS-COV-2, identified three main "actors," namely the cytokine IL-6, the chemokine CXCL10 and the infiltrating immune cell type macrophages. Although other cytokines, chemokines and infiltrating immune cells are deeply involved and their role should not be neglected, based on currently available data, IL-6, CXCL10, and infiltrating macrophages could be considered prototype factors representing each component of the immune system. It rapidly became clear that a strong and continuous interplay among the three components of the immune response is mandatory in order to produce a severe clinical course of the disease. Indeed, while IL-6, CXCL10 and macrophages alone would not be able to fully drive the onset and maintenance of the cytokine-storm, the establishment of a IL-6/CXCL10/macrophages axis is crucial in driving the sequence of events characterizing this condition. The present review is specifically aimed at overviewing current evidences provided by both in vitro and in vivo studies addressing the issue of the interplay among IL-6, CXCL10 and macrophages in the onset and progression of cytokine storm. SARS-COV-2 infection and the "cytokine storm."

Joint effect of heart failure and coronary artery disease on the risk of death during hospitalization for COVID-19.

AIMS: heart failure (HF) and coronary artery disease (CAD) are independent predictors of death in patients with COVID-19. The adverse prognostic impact of the combination of HF and CAD in these patients is unclear. METHODS AND RESULTS: we analysed data from 954 consecutive patients hospitalized for SARS-CoV-2 in five Italian Hospitals from February 23 to May 22, 2020. The study was a systematic prospective data collection according to a pre-specified protocol. All-cause mortality during hospitalization was the outcome measure. Mean duration of hospitalization was 33 days. Mortality was 11% in the total population and 7.4% in the group without evidence of HF or CAD (reference group). Mortality was 11.6% in the group with CAD and without HF (odds ratio [OR]: 1.6, p = 0.120), 15.5% in the group with HF and without CAD (OR: 2.3, p = 0.032), and 35.6% in the group with CAD and HF (OR: 6.9, p<0.0001). The risk of mortality in patients with CAD and HF combined was consistently higher than the sum of risks related to either disorder, resulting in a significant synergistic effect (p<0.0001) of the two conditions. Age-adjusted attributable proportion due to interaction was 64%. Adjusting for the simultaneous effects of age, hypotension, and lymphocyte count did not significantly lower attributable proportion which persisted statistically significant (p = 0.0360). CONCLUSION: The combination of HF and CAD exerts a marked detrimental impact on the risk of mortality in hospitalized patients with COVID-19, which is independent on other adverse prognostic markers.

The cytokine storm in COVID-19: Further advances in our understanding the role of specific chemokines involved.

SARS-COV-2 infection represents the greatest pandemic of the world, counting daily increasing number of subjects positive to the virus and, sadly, increasing number of deaths. Current studies reported that the cytokine/chemokine network is crucial in the onset and maintenance of the "cytokine storm", the event occurring in those patients in whom the progression of COVID-19 will progress, in most cases, to a very severe and potentially threatening disease. Detecting a possible "immune signature" in patients, as assessed by chemokines status in patients with COVID-19, could be helpful for individual risk stratification for developing a more or less severe clinical course of the disease. The present review is specifically aimed at overviewing current evidences provided by in vitro and in vivo studies addressing the issue of which chemokines seems to be involved, at least at present, in COVID-19. Currently available experimental and clinical studies regarding those chemokines more deeply studied in COVID-19, with a specific focus on their role in the cytokine storm and ultimately with their ability to predict the clinical course of the disease, will be taken into account. Moreover, similarities and differences between chemokines and cytokines, which both contribute to the onset of the pro-inflammatory loop characterizing SARS-COV-2 infection, will be briefly discussed. Future studies will rapidly accumulate in the next months and their results will hopefully provide more insights as to the complex physiopathology of COVID-19-related cytokine storm. This will likely make the present review somehow "dated" in a short time, but still the present review provides an overview of the scenario of the current knowledge on this topic.

Validation of an internationally derived patient severity phenotype to support COVID-19 analytics from electronic health record data.

OBJECTIVE: The Consortium for Clinical Characterization of COVID-19 by EHR (4CE) is an international collaboration addressing coronavirus disease 2019 (COVID-19) with federated analyses of electronic health record (EHR) data. We sought to develop and validate a computable phenotype for COVID-19 severity. MATERIALS AND METHODS: Twelve 4CE sites participated. First, we developed an EHR-based severity phenotype consisting of 6 code classes, and we validated it on patient hospitalization data from the 12 4CE clinical sites against the outcomes of intensive care unit (ICU) admission and/or death. We also piloted an alternative machine learning approach and compared selected predictors of severity with the 4CE phenotype at 1 site. RESULTS: The full 4CE severity phenotype had pooled sensitivity of 0.73 and specificity 0.83 for the combined outcome of ICU admission and/or death. The sensitivity of individual code categories for acuity had high variability-up to 0.65 across sites. At one pilot site, the expert-derived phenotype had mean area under the curve of 0.903 (95% confidence interval, 0.886-0.921), compared with an area under the curve of 0.956 (95% confidence interval, 0.952-0.959) for the machine learning approach. Billing codes were poor proxies of ICU admission, with as low as 49% precision and recall compared with chart review. DISCUSSION: We developed a severity phenotype using 6 code classes that proved resilient to coding variability across international institutions. In contrast, machine learning approaches may overfit hospital-specific orders. Manual chart review revealed discrepancies even in the gold-standard outcomes, possibly owing to heterogeneous pandemic conditions. CONCLUSIONS: We developed an EHR-based severity phenotype for COVID-19 in hospitalized patients and validated it at 12 international sites.

International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium.

We leveraged the largely untapped resource of electronic health record data to address critical clinical and epidemiological questions about Coronavirus Disease 2019 (COVID-19). To do this, we formed an international consortium (4CE) of 96 hospitals across five countries (www.covidclinical.net). Contributors utilized the Informatics for Integrating Biology and the Bedside (i2b2) or Observational Medical Outcomes Partnership (OMOP) platforms to map to a common data model. The group focused on temporal changes in key laboratory test values. Harmonized data were analyzed locally and converted to a shared aggregate form for rapid analysis and visualization of regional differences and global commonalities. Data covered 27,584 COVID-19 cases with 187,802 laboratory tests. Case counts and laboratory trajectories were concordant with existing literature. Laboratory tests at the time of diagnosis showed hospital-level differences equivalent to country-level variation across the consortium partners. Despite the limitations of decentralized data generation, we established a framework to capture the trajectory of COVID-19 disease in patients and their response to interventions.

COVID-19 Pulmonary and Olfactory Dysfunctions: Is the Chemokine CXCL10 the Common Denominator?

COVID-19 is an ongoing viral pandemic that emerged from East Asia and quickly spread to the rest of the world. SARS-CoV-2 is the virus causing COVID-19. Acute respiratory distress syndrome (ARDS) is definitely one of the main clinically relevant consequences in patients with COVID-19. Starting from the earliest reports of the COVID-19 pandemic, two peculiar neurological manifestations (namely, hyposmia/anosmia and dysgeusia) were reported in a relevant proportion of patients infected by SARS-CoV-2. At present, the physiopathologic mechanisms accounting for the onset of these symptoms are not yet clarified. CXCL10 is a pro-inflammatory chemokine with a well-established role in the COVID-19-related cytokine storm and in subsequent development of ARDS. CXCL10 is also known to be involved in coronavirus-induced demyelination. On these bases, a role for CXCL10 as the common denominator between pulmonary and olfactory dysfunctions could be envisaged. The aim of the present report will be to hypothesize a role for CXCL10 in COVID-19 olfactory dysfunctions. Previous evidences supporting our hypothesis, with special emphasis to the role of CXCL10 in coronavirus-induced demyelination, the anatomical and physiological peculiarity of the olfactory system, and the available data supporting their link during COVID-19 infections, will be overviewed.

The cytokine storm in COVID-19: An overview of the involvement of the chemokine/chemokine-receptor system.

In 2019-2020 a new coronavirus named SARS-CoV-2 was identified as the causative agent of a several acute respiratory infection named COVID-19, which is causing a worldwide pandemic. There are still many unresolved questions regarding the pathogenesis of this disease and especially the reasons underlying the extremely different clinical course, ranging from asymptomatic forms to severe manifestations, including the Acute Respiratory Distress Syndrome (ARDS). SARS-CoV-2 showed phylogenetic similarities to both SARS-CoV and MERS-CoV viruses, and some of the clinical features are shared between COVID-19 and previously identified beta-coronavirus infections. Available evidence indicate that the so called "cytokine storm" an uncontrolled over-production of soluble markers of inflammation which, in turn, sustain an aberrant systemic inflammatory response, is a major responsible for the occurrence of ARDS. Chemokines are low molecular weight proteins with powerful chemoattractant activity which play a role in the immune cell recruitment during inflammation. This review will be aimed at providing an overview of the current knowledge on the involvement of the chemokine/chemokine-receptor system in the cytokine storm related to SARS-CoV-2 infection. Basic and clinical evidences obtained from previous SARS and MERS epidemics and available data from COVID-19 will be taken into account.