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Abstract Introduction The impact of remdesivir on mortality in patients with COVID-19 is still controversial. We aimed to identify clinical phenotype clusters of COVID-19 hospitalized patients with highest benefit from remdesivir use and validate these findings in an external cohort. Methods We included consecutive patients hospitalized between February 2020 and February 2021 for COVID-19. The derivation cohort comprised subjects admitted to Hospital Clinic of Barcelona. The validation cohort included patients from Hospital Universitari Mutua de Terrassa (Terrassa) and Hospital Universitari La Fe (Valencia), all tertiary centers in Spain. We employed K-means clustering to group patients according to reverse transcription polymerase chain reaction (rRT-PCR) cycle threshold (Ct) values and lymphocyte counts at diagnosis, and pre-test symptom duration. The impact of remdesivir on 60-day mortality in each cluster was assessed. Results A total of 1160 patients (median age 66, interquartile range (IQR) 55–78) were included. We identified five clusters, with mortality rates ranging from 0 to 36.7%. Highest mortality rate was observed in the cluster including patients with shorter pre-test symptom duration, lower lymphocyte counts, and lower Ct values at diagnosis. The absence of remdesivir administration was associated with worse outcome in the high-mortality cluster (10.5% vs. 36.7%; p

ABSTRACT: Objective: To analyse differences in clinical presentation and outcome between bacteraemic pneumococcal community-acquired pneumonia (B-PCAP) and sSvere Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) pneumonia. Methods: This observational multi-centre study was conducted on patients hospitalized with B-PCAP between 2000 and 2020 and SARS-CoV-2 pneumonia in 2020. Thirty-day survival, predictors of mortality, and intensive care unit (ICU) admission were compared. Results: In total, 663 patients with B-PCAP and 1561 patients with SARS-CoV-2 pneumonia were included in this study. Patients with B-PCAP had more severe disease, a higher ICU admission rate and more complications. Patients with SARS-CoV-2 pneumonia had higher in-hospital mortality (10.8% vs 6.8%; P=0.004). Among patients admitted to the ICU, the need for invasive mechanical ventilation (69.7% vs 36.2%; P

The role of neutrophil and lymphocyte counts in blood as prognosis predictors in Community Acquired Pneumonia (CAP) has not been adequately studied. This was a derivation-validation retrospective study in hospitalized patients with CAP and no prior immunosuppression. We evaluated by multivariate analysis the association between neutrophil and lymphocyte counts and mortality risk at 30-days post hospital admission in these patients. The derivation cohort (n = 1550 patients) was recruited in a multi-site study. The validation cohort (n = 2846 patients) was recruited in a single-site study. In the derivation cohort, a sub-group of lymphopenic patients, those with

Bronchiectasis (BE) is a chronic and heterogeneous respiratory disease that requires a multidimensional scoring system to properly assess severity. The aim of this study was to compare the severity stratification by 2 validated scores (BSI and FACED) in a BE cohort and to determine their predictive capacity for exacerbations and hospitalizations. Moreover, we proposed a modified version of FACED which was created to better predict the risk of exacerbations in clinical practice. We performed a prospective cohort study including BE patients >18 years old with a follow-up period of 1-year. One-hundred eighty-two patients (40% males; mean age 68) were studied. Patients were stratified according to the number of exacerbations during the follow-up, and according to BSI and FACED scores. BSI classified most of our patients as severe 99 (54.4%) or moderate 47 (25.8%), while FACED mainly classified as mild 108 (59.3%) or moderate 61 (33.5%). BSI and FACED showed an area under ROC curve (AUC) for exacerbations of 0.808 and 0.734; and for hospitalizations (due to BE exacerbations) of 0.893 and 0.809, respectively. Subsequently, we modified FACED by adding previous exacerbations (Exa-FACED) and this new score classified patients as mild 48.4%, moderate 34.6% and severe 17.0%, with an improved AUC for exacerbations (0.760) and hospitalizations (0.820). Despite previous validations of BSI and FACED, they classified our patients very differently. As expected, FACED showed poor prognostic capacity for exacerbations. We support the Exa-FACED score to predict the risk future exacerbations for been easy to use in clinical practice.

Systemic corticosteroids have anti-inflammatory effects, whereas macrolides also have immunomodulatory activity in addition to their primary antimicrobial actions. We aimed to evaluate the potential interaction effect between corticosteroids and macrolides on the systemic inflammatory response in patients with severe community-acquired pneumonia to determine if combining these two immunomodulating agents was harmful, or possibly beneficial.We performed a post-hoc exploratory analysis of a randomized clinical trial conducted in three tertiary hospitals in Spain. This trial included patients with severe community-acquired pneumonia with high inflammatory response (C-reactive protein [CRP] >15 mg/dL) who were randomized to receive methylprednisolone 0.5 mg/kg/tpd or placebo. The choice of antibiotic treatment was at the physician's discretion. One hundred and six patients were classified into four groups according to antimicrobial therapy combination (β-lactam plus macrolide or β-lactam plus fluoroquinolone) and corticosteroid arm (placebo or corticosteroids). The primary outcome was treatment failure (composite outcome of early treatment failure, or of late treatment failure, or of both early and late treatment failure).The methylprednisolone with β-lactam plus macrolide group had more elderly patients, with comorbidities, and higher pneumonia severity index (PSI) risk class V, but a lower proportion of intensive care unit admission, compared to the other groups. We found non differences in treatment failure between groups (overall p = 0.374); however, a significant difference in late treatment failure was observed (4 patients in the placebo with β-lactam plus macrolide group (31%) vs. 9 patients in the placebo with β-lactam plus fluoroquinolone group (24%) vs. 0 patients in the methylprednisolone with β-lactam plus macrolide group (0%) vs. 2 patients [5%] in the methylprednisolone with β-lactam plus fluoroquinolone group overall p = 0.009). We found a significant difference for In-hospital mortality in the per protocol population (overall p = 0.01). We did not find significant differences in treatment failure, early or late; or In-hospital mortality after adjusting for severity (PSI), year and centre of enrolment.In this exploratory analysis, we observed that the glucocorticosteroids and macrolides combination had no statistically significant association with main clinical outcomes compared with other combinations in patients with severe community acquired pneumonia and a high inflammatory response after taking account potential confounders.Clinicaltrials.gov NCT00908713.

Bronchiectasis is one of the most neglected diseases in respiratory medicine. There are no approved therapies and few large-scale, representative epidemiological studies. The EMBARC (European Multicentre Bronchiectasis Audit and Research Collaboration) registry is a prospective, pan-European observational study of patients with bronchiectasis. The inclusion criterion is a primary clinical diagnosis of bronchiectasis consisting of: 1) a clinical history consistent with bronchiectasis; and 2) computed tomography demonstrating bronchiectasis. Core exclusion criteria are: 1) bronchiectasis due to known cystic fibrosis; 2) age

Abstract Background There exists consistent empirical evidence in the literature pointing out ample heterogeneity in terms of the clinical evolution of patients with COVID-19. The identification of specific phenotypes underlying in the population might contribute towards a better understanding and characterization of the different courses of the disease. The aim of this study was to identify distinct clinical phenotypes among hospitalized patients with SARS-CoV-2 pneumonia using machine learning clustering, and to study their association with subsequent clinical outcomes as severity and mortality. Methods Multicentric observational, prospective, longitudinal, cohort study conducted in four hospitals in Spain. We included adult patients admitted for in-hospital stay due to SARS-CoV-2 pneumonia. We collected a broad spectrum of variables to describe exhaustively each case: patient demographics, comorbidities, symptoms, physiological status, baseline examinations (blood analytics, arterial gas test), etc. For the development and internal validation of the clustering/phenotype models, the dataset was split into training and test sets (50% each). We proposed a sequence of machine learning stages: feature scaling, missing data imputation, reduction of data dimensionality via Kernel Principal Component Analysis (KPCA), and clustering with the k-means algorithm. The optimal cluster model parameters –including k, the number of phenotypes– were chosen automatically, by maximizing the average Silhouette score across the training set. Results We enrolled 1548 patients, each of them characterized by 92 clinical attributes (d=109 features after variable encoding). Our clustering algorithm identified k=3 distinct phenotypes and 18 strongly informative variables: Phenotype A (788 cases [50.9% prevalence] – age $$\sim$$ ∼ 57, Charlson comorbidity $$\sim$$ ∼ 1, pneumonia CURB-65 score $$\sim$$ ∼ 0 to 1, respiratory rate at admission $$\sim$$ ∼ 18 min-1, FiO2 $$\sim$$ ∼ 21%, C-reactive protein CRP $$\sim$$ ∼ 49.5 mg/dL [median within cluster]); phenotype B (620 cases [40.0%] – age $$\sim$$ ∼ 75, Charlson $$\sim$$ ∼ 5, CURB-65 $$\sim$$ ∼ 1 to 2, respiration $$\sim$$ ∼ 20 min-1, FiO2 $$\sim$$ ∼ 21%, CRP $$\sim$$ ∼ 101.5 mg/dL); and phenotype C (140 cases [9.0%] – age $$\sim$$ ∼ 71, Charlson $$\sim$$ ∼ 4, CURB-65 $$\sim$$ ∼ 0 to 2, respiration $$\sim$$ ∼ 30 min-1, FiO2 $$\sim$$ ∼ 38%, CRP $$\sim$$ ∼ 152.3 mg/dL). Hypothesis testing provided solid statistical evidence supporting an interaction between phenotype and each clinical outcome: severity and mortality. By computing their corresponding odds ratios, a clear trend was found for higher frequencies of unfavourable evolution in phenotype C with respect to B, as well as more unfavourable in phenotype B than in A. Conclusion A compound unsupervised clustering technique (including a fully-automated optimization of its internal parameters) revealed the existence of three distinct groups of patients – phenotypes. In turn, these showed strong associations with the clinical severity in the progression of pneumonia, and with mortality.

Abstract Improved phenotyping in pneumonia is necessary to strengthen risk assessment. Via a feasible and multidimensional approach with basic parameters, we aimed to evaluate the effect of host response at admission on severity stratification in COVID-19 and community-acquired pneumonia (CAP). Three COVID-19 and one CAP multicenter cohorts including hospitalized patients were recruited. Three easily available variables reflecting different pathophysiologic mechanisms—immune, inflammation, and respiratory—were selected (absolute lymphocyte count [ALC], C-reactive protein [CRP] and, SpO2/FiO2). In-hospital mortality and intensive care unit (ICU) admission were analyzed as outcomes. A multivariable, penalized maximum likelihood logistic regression was performed with ALC ( 60 mg/L), and, SpO2/FiO2 (

Background: Complications in community-acquired pneumonia (CAP), including cardiovascular events (CVE), can occur during an acute episode and in the long term. We aimed to analyse the role of endothelial damage biomarkers (C-terminal endothelin-1 precursor fragment [CT-proET-1] and mid-regional pro-adrenomedullin [MR-proADM]), in contrast to classic inflammation markers (C Reactive Protein [CRP] and procalcitonin [PCT]) in patients admitted for CAP and their relationship with ICU admission, CVE and mortality in the short and long term; Methods: Biomarkers were analysed in 515 patients with CAP at day 1, 285 at day 5 and 280 at day 30. Traditional inflammatory biomarkers and endothelial damage biomarkers were measured. ICU admission, CVE and mortality (in-hospital and 1-year follow-up) were assessed using receiver operating characteristic (ROC) curve analysis and univariate logistic regression. Results: A statistically significant association was observed between initial, raised CT-proET-1 and MR-proADM levels, the need for ICU admission and the development of in-hospital CVE or in-hospital mortality. Both endothelial markers maintained a strong association at day 30 with 1-year follow-up CVE. At day 1, CRP and PCT were only associated with ICU admission. On day 30, there was no association between inflammatory markers and long-term CVE or death. The odds ratio (OR) and area under the curve (AUC) of endothelial biomarkers were superior to those of classic biomarkers for all outcomes considered. Conclusions: Endothelial biomarkers are better indicators than classic ones in predicting worse outcomes in both the short and long term, especially CVE. MR-proADM is the best biomarker for predicting complications in CAP.

Abstract Background The identification of critically ill COVID-19 patients at risk of fatal outcomes remains a challenge. Here, we first validated candidate microRNAs (miRNAs) as biomarkers for clinical decision-making in critically ill patients. Second, we constructed a blood miRNA classifier for the early prediction of adverse outcomes in the ICU. Methods This was a multicenter, observational and retrospective/prospective study including 503 critically ill patients admitted to the ICU from 19 hospitals. qPCR assays were performed in plasma samples collected within the first 48 h upon admission. A 16-miRNA panel was designed based on recently published data from our group. Results Nine miRNAs were validated as biomarkers of all-cause in-ICU mortality in the independent cohort of critically ill patients (FDR

IntroductionThere are no data on the association of type of pneumonia and long-term mortality by the type of pneumonia (COVID-19 or community-acquired pneumonia [CAP]) on long-term mortality after an adjustment for potential confounding variables. We aimed to assess the type of pneumonia and risk factors for long-term mortality in patients who were hospitalized in conventional ward and later discharged.MethodsRetrospective analysis of two prospective and multicentre cohorts of hospitalized patients with COVID-19 and CAP. The main outcome under study was 1-year mortality in hospitalized patients in conventional ward and later discharged. We adjusted a Bayesian logistic regression model to assess associations between the type of pneumonia and 1-year mortality controlling for confounders.ResultsThe study included a total of 1,693 and 2,374 discharged patients in the COVID-19 and CAP cohorts, respectively. Of these, 1,525 (90.1%) and 2,249 (95%) patients underwent analysis. Until 1-year follow-up, 69 (4.5%) and 148 (6.6%) patients from the COVID-19 and CAP cohorts, respectively, died (p = 0.008). However, the Bayesian model showed a low probability of effect (PE) of finding relevant differences in long-term mortality between CAP and COVID-19 (odds ratio 1.127, 95% credibility interval 0.862–1.591; PE = 0.774).ConclusionCOVID-19 and CAP have similar long-term mortality after adjusting for potential confounders.

There is a limited understanding of the pathophysiology of postacute pulmonary sequelae in severe COVID-19. The aim of current study was to define the circulating microRNA (miRNA) profiles associated with pulmonary function and radiologic features in survivors of SARS-CoV-2-induced ARDS. The study included patients who developed ARDS secondary to SARS-CoV-2 infection (n = 167) and a group of infected patients who did not develop ARDS (n = 33). Patients were evaluated 3 months after hospital discharge. The follow-up included a complete pulmonary evaluation and chest computed tomography. Plasma miRNA profiling was performed using RT-qPCR. Random forest was used to construct miRNA signatures associated with lung diffusing capacity for carbon monoxide (DLCO) and total severity score (TSS). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were conducted. DLCO

Newer higher valency pneumococcal conjugate vaccines (PCVs) have the potential to reduce the adult community-acquired pneumonia (CAP) burden. We describe the evolution and distribution of adult community-acquired pneumonia (CAP) serotypes in Spain, focusing on serotypes contained in the 20-valent PCV (PCV20). This was a prospective, observational study of chest X-ray (CXR)-confirmed CAP in immunocompetent adults hospitalized in one of four Spanish hospitals between November 2016 and November 2020. Pneumococci were isolated from cultures and detected in urine using BinaxNow® and Pfizer serotype-specific urinary antigen tests UAD1 and UAD2. We included 1948 adults hospitalized with CXR-CAP. The median age was 69.0 years (IQR: 24 years). At least one comorbidity was present in 84.8% (n = 1653) of patients. At admission, 76.1% of patients had complicated pneumonia. Pneumococcus was identified in 34.9% (n = 680) of study participants. The PCV20 vaccine-type CAP occurred in 23.9% (n = 465) of all patients, 68.4% (n = 465) of patients with pneumococcal CAP, and 82.2% (83/101) of patients who had pneumococcus identified by culture. Serotypes 8 (n = 153; 7.9% of all CAP) and 3 (n = 152; 7.8% of all CAP) were the most frequently identified. Pneumococcus is a common cause of hospitalized CAP among Spanish adults and serotypes contained in PCV20 caused the majority of pneumococcal CAP.

Abstract Question We evaluated whether the time between first respiratory support and intubation of patients receiving invasive mechanical ventilation (IMV) due to COVID-19 was associated with mortality or pulmonary sequelae. Materials and methods Prospective cohort of critical COVID-19 patients on IMV. Patients were classified as early intubation if they were intubated within the first 48 h from the first respiratory support or delayed intubation if they were intubated later. Surviving patients were evaluated after hospital discharge. Results We included 205 patients (140 with early IMV and 65 with delayed IMV). The median [p25;p75] age was 63 [56.0; 70.0] years, and 74.1% were male. The survival analysis showed a significant increase in the risk of mortality in the delayed group with an adjusted hazard ratio (HR) of 2.45 (95% CI 1.29–4.65). The continuous predictor time to IMV showed a nonlinear association with the risk of in-hospital mortality. A multivariate mortality model showed that delay of IMV was a factor associated with mortality (HR of 2.40; 95% CI 1.42–4.1). During follow-up, patients in the delayed group showed a worse DLCO (mean difference of − 10.77 (95% CI − 18.40 to − 3.15), with a greater number of affected lobes (+ 1.51 [95% CI 0.89–2.13]) and a greater TSS (+ 4.35 [95% CI 2.41–6.27]) in the chest CT scan. Conclusions Among critically ill patients with COVID-19 who required IMV, the delay in intubation from the first respiratory support was associated with an increase in hospital mortality and worse pulmonary sequelae during follow-up.

With the COVID-19 pandemic having caused unprecedented numbers of infections and deaths, large research efforts have been undertaken to increase our understanding of the disease and the factors which determine diverse clinical evolutions. Here we focused on a fully data-driven exploration regarding which factors (clinical or otherwise) were most informative for SARS-CoV-2 pneumonia severity prediction via machine learning (ML). In particular, feature selection techniques (FS), designed to reduce the dimensionality of data, allowed us to characterize which of our variables were the most useful for ML prognosis. We conducted a multi-centre clinical study, enrolling n = 1548 patients hospitalized due to SARS-CoV-2 pneumonia: where 792, 238, and 598 patients experienced low, medium and high-severity evolutions, respectively. Up to 106 patient-specific clinical variables were collected at admission, although 14 of them had to be discarded for containing ⩾60% missing values. Alongside 7 socioeconomic attributes and 32 exposures to air pollution (chronic and acute), these became d = 148 features after variable encoding. We addressed this ordinal classification problem both as a ML classification and regression task. Two imputation techniques for missing data were explored, along with a total of 166 unique FS algorithm configurations: 46 filters, 100 wrappers and 20 embeddeds. Of these, 21 setups achieved satisfactory bootstrap stability (⩾0.70) with reasonable computation times: 16 filters, 2 wrappers, and 3 embeddeds. The subsets of features selected by each technique showed modest Jaccard similarities across them. However, they consistently pointed out the importance of certain explanatory variables. Namely: patient's C-reactive protein (CRP), pneumonia severity index (PSI), respiratory rate (RR) and oxygen levels -saturation Sp O2, quotients Sp O2/RR and arterial Sat O2/Fi O2-, the neutrophil-to-lymphocyte ratio (NLR) -to certain extent, also neutrophil and lymphocyte counts separately-, lactate dehydrogenase (LDH), and procalcitonin (PCT) levels in blood. A remarkable agreement has been found a posteriori between our strategy and independent clinical research works investigating risk factors for COVID-19 severity. Hence, these findings stress the suitability of this type of fully data-driven approaches for knowledge extraction, as a complementary to clinical perspectives.

Abstract Background Mortality due to COVID-19 is high, especially in patients requiring mechanical ventilation. The purpose of the study is to investigate associations between mortality and variables measured during the first three days of mechanical ventilation in patients with COVID-19 intubated at ICU admission. Methods Multicenter, observational, cohort study includes consecutive patients with COVID-19 admitted to 44 Spanish ICUs between February 25 and July 31, 2020, who required intubation at ICU admission and mechanical ventilation for more than three days. We collected demographic and clinical data prior to admission; information about clinical evolution at days 1 and 3 of mechanical ventilation; and outcomes. Results Of the 2,095 patients with COVID-19 admitted to the ICU, 1,118 (53.3%) were intubated at day 1 and remained under mechanical ventilation at day three. From days 1 to 3, PaO2/FiO2 increased from 115.6 [80.0–171.2] to 180.0 [135.4–227.9] mmHg and the ventilatory ratio from 1.73 [1.33–2.25] to 1.96 [1.61–2.40]. In-hospital mortality was 38.7%. A higher increase between ICU admission and day 3 in the ventilatory ratio (OR 1.04 [CI 1.01–1.07], p = 0.030) and creatinine levels (OR 1.05 [CI 1.01–1.09], p = 0.005) and a lower increase in platelet counts (OR 0.96 [CI 0.93–1.00], p = 0.037) were independently associated with a higher risk of death. No association between mortality and the PaO2/FiO2 variation was observed (OR 0.99 [CI 0.95 to 1.02], p = 0.47). Conclusions Higher ventilatory ratio and its increase at day 3 is associated with mortality in patients with COVID-19 receiving mechanical ventilation at ICU admission. No association was found in the PaO2/FiO2 variation.

Background: Up to 80% of patients surviving acute respiratory distress syndrome (ARDS) secondary to SARS-CoV-2 infection present persistent anomalies in pulmonary function after hospital discharge. There is a limited understanding of the mechanistic pathways linked to post-acute pulmonary sequelae. Aim: To identify the molecular underpinnings associated with severe lung diffusion involvement in survivors of SARS-CoV-2-induced ARDS. Methods: Survivors attended to a complete pulmonary evaluation 3 months after hospital discharge. RNA sequencing (RNA-seq) was performed using Illumina technology in whole-blood samples from 50 patients with moderate to severe diffusion impairment (DLCO

COVID-19 has been a diagnostic and therapeutic challenge. It has marked a paradigm shift when considering other types of pneumonia etiology. We analyzed the biomarkers related to endothelial damage and immunothrombosis in COVID-19 in comparison to community-acquired pneumonia (CAP) through a case–control study of 358 patients with pneumonia (179 hospitalized with COVID-19 vs. 179 matched hospitalized with CAP). Endothelial damage markers (endothelin and proadrenomedullin), neutrophil extracellular traps (NETs) (citrullinated-3 histone, cell-free DNA), and platelet activation (soluble P-selectin) were measured. In-hospital and 1-year follow-up outcomes were evaluated. Endothelial damage, platelet activation, and NET biomarkers are significantly higher in CAP compared to COVID-19. In-hospital mortality in COVID-19 was higher compared to CAP whereas 1-year mortality and cardiovascular complications were higher in CAP. In the univariate analysis (OR 95% CIs), proADM and endothelin were associated with in-hospital mortality (proADM: CAP 3.210 [1.698–6.070], COVID-19 8.977 [3.413–23.609]; endothelin: CAP 1.014 [1.006–1.022], COVID-19 1.024 [1.014–1.034]), in-hospital CVE (proADM: CAP 1.623 [1.080–2.439], COVID-19 2.146 [1.186–3.882]; endothelin: CAP 1.005 [1.000–1.010], COVID-19 1.010 [1.003–1.018]), and 1-year mortality (proADM: CAP 2.590 [1.644–4.080], COVID-19 13.562 [4.872–37.751]; endothelin: CAP 1.008 [1.003–1.013], COVID-19 1.026 [1.016–1.037]). In conclusion, COVID-19 and CAP showed different expressions of endothelial damage and NETs. ProADM and endothelin are associated with short- and long-term mortality.

The clinical evolution of patients infected with the Severe Acute Respiratory Coronavirus type 2 (SARS-CoV-2) depends on the complex interplay between viral and host factors. The evolution to less aggressive but better-transmitted viral variants, and the presence of immune memory responses in a growing number of vaccinated and/or virus-exposed individuals, has caused the pandemic to slowly wane in virulence. However, there are still patients with risk factors or comorbidities that put them at risk of poor outcomes in the event of having the coronavirus infectious disease 2019 (COVID-19). Among the different treatment options for patients with COVID-19, virus-targeted measures include antiviral drugs or monoclonal antibodies that may be provided in the early days of infection. The present expert consensus is based on a review of all the literature published between 1 July 2021 and 15 February 2022 that was carried out to establish the characteristics of patients, in terms of presence of risk factors or comorbidities, that may make them candidates for receiving any of the virus-targeted measures available in order to prevent a fatal outcome, such as severe disease or death. A total of 119 studies were included from the review of the literature and 159 were from the additional independent review carried out by the panelists a posteriori. Conditions found related to strong recommendation of the use of virus-targeted measures in the first days of COVID-19 were age above 80 years, or above 65 years with another risk factor; antineoplastic chemotherapy or active malignancy; HIV infection with CD4+ cell counts < 200/mm3; and treatment with anti-CD20 immunosuppressive drugs. There is also a strong recommendation against using the studied interventions in HIV-infected patients with a CD4+ nadir 3 or treatment with other immunosuppressants. Indications of therapies against SARS-CoV-2, regardless of vaccination status or history of infection, may still exist for some populations, even after COVID-19 has been declared to no longer be a global health emergency by the WHO.

IntroductionBronchial aspirates (BAS) obtained during invasive mechanical ventilation (IMV) constitutes a useful tool for molecular phenotyping and decision making.AimTo identify the proteomic determinants associated with disease pathogenesis, all-cause mortality and respiratory sequelae in BAS samples from critically ill patients with SARS-CoV-2-induced ARDSMethodsMulticenter study including 74 critically ill patients with COVID-19 and non-COVID-19 ARDS. BAS were obtained by bronchoaspiration after IMV initiation. Three hundred sixty-four proteins were quantified using proximity extension assay (PEA) technology. Random forest models were used to assess predictor importance.ResultsAfter adjusting for confounding factors, CST5, NADK, SRPK2 and TGF-α were differentially detected in COVID-19 and non-COVID-19 patients. In random forest models for COVID-19, CST5, DPP7, NADK, KYAT1 and TYMP showed the highest variable importance. In COVID-19 patients, reduced levels of ENTPD2 and PTN were observed in nonsurvivors of ICU stay, even after adjustment. AGR2, NQO2, IL-1α, OSM and TRAIL showed the strongest associations with in-ICU mortality and were used to construct a protein-based prediction model. Kaplan-Meier curves revealed a clear separation in mortality risk between subgroups of PTN, ENTPD2 and the prediction model. Cox regression models supported these findings. In survivors, the levels of FCRL1, NTF4 and THOP1 in BAS samples obtained during the ICU stay correlated with lung function (i.e., DLCO levels) 3 months after hospital discharge. Similarly, Flt3L and THOP1 levels were correlated with radiological features (i.e., TSS). These proteins are expressed in immune and nonimmune lung cells. Poor host response to viral infectivity and an inappropriate reparative mechanism seem to be linked with the pathogenesis of the disease and fatal outcomes, respectively.ConclusionBAS proteomics identified novel factors associated with the pathology of SARS-CoV-2-induced ARDS and its adverse outcomes. BAS-based protein testing emerges as a novel tool for risk assessment in the ICU.

The long-term clinical management and evolution of a cohort of critical COVID-19 survivors have not been described in detail. We report a prospective observational study of COVID-19 patients admitted to the ICU between March and August 2020. The follow-up in a post-COVID consultation comprised symptoms, pulmonary function tests, the 6-minute walking test (6MWT), and chest computed tomography (CT). Additionally, questionnaires to evaluate the prevalence of post-COVID-19 syndrome were administered at 1 year. A total of 181 patients were admitted to the ICU during the study period. They were middle-aged (median [IQR] of 61 [52;67]) and male (66.9%), with a median ICU stay of 9 (5–24.2) days. 20% died in the hospital, and 39 were not able to be included. A cohort of 105 patients initiated the follow-up. At 1 year, 32.2% persisted with respiratory alterations and needed to continue the follow-up. Ten percent still had moderate/severe lung diffusion (DLCO) involvement (

Summary: Background: The clinical heterogeneity of COVID-19 suggests the existence of different phenotypes with prognostic implications. We aimed to analyze comorbidity patterns in critically ill COVID-19 patients and assess their impact on in-hospital outcomes, response to treatment and sequelae. Methods: Multicenter prospective/retrospective observational study in intensive care units of 55 Spanish hospitals. 5866 PCR-confirmed COVID-19 patients had comorbidities recorded at hospital admission; clinical and biological parameters, in-hospital procedures and complications throughout the stay; and, clinical complications, persistent symptoms and sequelae at 3 and 6 months. Findings: Latent class analysis identified 3 phenotypes using training and test subcohorts: low-morbidity (n=3385; 58%), younger and with few comorbidities; high-morbidity (n=2074; 35%), with high comorbid burden; and renal-morbidity (n=407; 7%), with chronic kidney disease (CKD), high comorbidity burden and the worst oxygenation profile. Renal-morbidity and high-morbidity had more in-hospital complications and higher mortality risk than low-morbidity (adjusted HR (95% CI): 1.57 (1.34-1.84) and 1.16 (1.05-1.28), respectively). Corticosteroids, but not tocilizumab, were associated with lower mortality risk (HR (95% CI) 0.76 (0.63-0.93)), especially in renal-morbidity and high-morbidity. Renal-morbidity and high-morbidity showed the worst lung function throughout the follow-up, with renal-morbidity having the highest risk of infectious complications (6%), emergency visits (29%) or hospital readmissions (14%) at 6 months (p

The role of NETs and platelet activation in COVID-19 is scarcely known. We aimed to evaluate the role of NETs (citrullinated histone H3 [CitH3], cell-free DNA [cfDNA]) and platelet activation markers (soluble CD40 ligand [CD40L] and P-selectin) in estimating the hazard of different clinical trajectories in patients with COVID-19. We performed a prospective study of 204 patients, categorized as outpatient, hospitalized and ICU-admitted. A multistate model was designed to estimate probabilities of clinical transitions across varying states, such as emergency department (ED) visit, discharge (outpatient), ward admission, ICU admission and death. Levels of cfDNA, CitH3 and P-selectin were associated with the severity of presentation and analytical parameters. The model showed an increased risk of higher levels of CitH3 and P-selectin for ED-to-ICU transitions (Hazard Ratio [HR]: 1.35 and 1.31, respectively), as well as an elevated risk of higher levels of P-selectin for ward-to-death transitions (HR: 1.09). Elevated levels of CitH3 (HR: 0.90), cfDNA (HR: 0.84) and P-selectin (HR: 0.91) decreased the probability of ward-to-discharge transitions. A similar trend existed for elevated levels of P-selectin and ICU-to-ward transitions (HR 0.40); In conclusion, increased NET and P-selectin levels are associated with more severe episodes and can prove useful in estimating different clinical trajectories.

Abstract Background COVID-19 can course with respiratory and extrapulmonary disease. SARS-CoV-2 RNA is detected in respiratory samples but also in blood, stool and urine. Severe COVID-19 is characterized by a dysregulated host response to this virus. We studied whether viral RNAemia or viral RNA load in plasma is associated with severe COVID-19 and also to this dysregulated response. Methods A total of 250 patients with COVID-19 were recruited (50 outpatients, 100 hospitalized ward patients and 100 critically ill). Viral RNA detection and quantification in plasma was performed using droplet digital PCR, targeting the N1 and N2 regions of the SARS-CoV-2 nucleoprotein gene. The association between SARS-CoV-2 RNAemia and viral RNA load in plasma with severity was evaluated by multivariate logistic regression. Correlations between viral RNA load and biomarkers evidencing dysregulation of host response were evaluated by calculating the Spearman correlation coefficients. Results The frequency of viral RNAemia was higher in the critically ill patients (78%) compared to ward patients (27%) and outpatients (2%) (p

BackgroundThe pathophysiology of COVID-19-related critical illness is not completely understood. Here, we analyzed the microRNA (miRNA) profile of bronchial aspirate (BAS) samples from COVID-19 and non-COVID-19 patients admitted to the ICU to identify prognostic biomarkers of fatal outcomes and to define molecular pathways involved in the disease and adverse events.MethodsTwo patient populations were included (n = 89): (i) a study population composed of critically ill COVID-19 and non-COVID-19 patients; (ii) a prospective study cohort composed of COVID-19 survivors and non-survivors among patients assisted by invasive mechanical ventilation (IMV). BAS samples were obtained by bronchoaspiration during the ICU stay. The miRNA profile was analyzed using RT-qPCR. Detailed biomarker and bioinformatics analyses were performed.ResultsThe deregulation in five miRNA ratios (miR-122-5p/miR-199a-5p, miR-125a-5p/miR-133a-3p, miR-155-5p/miR-486-5p, miR-214-3p/miR-222-3p, and miR-221-3p/miR-27a-3p) was observed when COVID-19 and non-COVID-19 patients were compared. In addition, five miRNA ratios segregated between ICU survivors and nonsurvivors (miR-1-3p/miR-124-3p, miR-125b-5p/miR-34a-5p, miR-126-3p/miR-16-5p, miR-199a-5p/miR-9-5p, and miR-221-3p/miR-491-5p). Through multivariable analysis, we constructed a miRNA ratio-based prediction model for ICU mortality that optimized the best combination of miRNA ratios (miR-125b-5p/miR-34a-5p, miR-199a-5p/miR-9-5p, and miR-221-3p/miR-491-5p). The model (AUC 0.85) and the miR-199a-5p/miR-9-5p ratio (AUC 0.80) showed an optimal discrimination value and outperformed the best clinical predictor for ICU mortality (days from first symptoms to IMV initiation, AUC 0.73). The survival analysis confirmed the usefulness of the miRNA ratio model and the individual ratio to identify patients at high risk of fatal outcomes following IMV initiation. Functional enrichment analyses identified pathological mechanisms implicated in fibrosis, coagulation, viral infections, immune responses and inflammation.ConclusionsCOVID-19 induces a specific miRNA signature in BAS from critically ill patients. In addition, specific miRNA ratios in BAS samples hold individual and collective potential to improve risk-based patient stratification following IMV initiation in COVID-19-related critical illness. The biological role of the host miRNA profiles may allow a better understanding of the different pathological axes of the disease.

Resumen: La Sociedad Española de Neumología y Cirugía Torácica (SEPAR) ha elaborado este documento de recomendaciones sobre la vacuna para la COVID-19 en las enfermedades respiratorias, con el objetivo de ayudar al personal sanitario en la toma de decisiones sobre cómo actuar en la vacunación de estos pacientes.Las recomendaciones han sido elaboradas por un grupo de expertos en la materia, tras la revisión de la literatura recopilada hasta el 7 de marzo del 2021, y de la información aportada por distintas sociedades científicas, agencias del medicamento y estrategias de organismos gubernamentales hasta esa fecha.Podemos concluir que las vacunas para la COVID-19 no solo son seguras y eficaces, sino que, en aquellos pacientes vulnerables con enfermedades respiratorias crónicas, son prioritarias. Además, la implicación activa de los profesionales sanitarios que manejan estas patologías en la estrategia de vacunación es clave para lograr una buena adherencia y coberturas vacunales elevadas. Abstract: The Spanish Society of Pneumonology and Thoracic Surgery (SEPAR) has elaborated this document of recommendations for COVID-19 vaccination in patients with respiratory diseases aimed to help healthcare personnel make decisions about how to act in case of COVID-19 vaccination in these patients.The recommendations have been developed by a group of experts in this field after reviewing the materials published up to March 7, 2021, the information provided by different scientific societies, drug agencies and the strategies of the governmental bodies up to this date.We can conclude that COVID-19 vaccines are not only safe and effective, but also prior in vulnerable patients with chronic respiratory diseases. In addition, an active involvement of healthcare professionals, who manage these diseases, in the vaccination strategy is the key to achieve good adherence and high vaccination coverage.

We sought to investigate differential phenotypic characteristics according to neutrophil counts, using a biostatistics approach in a large-cohort study from the Spanish Online Bronchiectasis Registry (RIBRON). The 1034 patients who met the inclusion criteria were clustered into two groups on the basis of their blood neutrophil levels. Using the Mann–Whitney U test to explore potential differences according to FACED and EFACED scores between the two groups, a neutrophil count of 4990 cells/µL yielded the most balanced cluster sizes: (1) above-threshold (n = 337) and (2) below-threshold (n = 697) groups. Patients above the threshold showed significantly worse lung function parameters and nutritional status, while systemic inflammation levels were higher than in the below-threshold patients. In the latter group, the proportions of patients with mild disease were greater, while a more severe disease was present in the above-threshold patients. According to the blood neutrophil counts using biostatistics analyses, two distinct clinical phenotypes of stable patients with non-CF bronchiectasis were defined. Patients falling into the above-threshold cluster were more severe. Severity was characterized by a significantly impaired lung function parameters and nutritional status, and greater systemic inflammation. Phenotypic profiles of bronchiectasis patients are well defined as a result of the cluster analysis of combined systemic and respiratory variables.

Neutrophil extracellular traps (NETs) induce a procoagulant response linking inflammation and thrombosis. Low levels of miR-146a, a brake of inflammatory response, are involved in higher risk for cardiovascular events, but the mechanisms explaining how miR-146a exerts its function remain largely undefined. The aim of this study was to explore the impact of miR-146a deficiency in NETosis both, in sterile and non-sterile models in vivo, and to inquire into the underlying mechanism. Two models of inflammation were performed: 1) Ldlr-/- mice transplanted with bone marrow from miR-146a-/- or wild type (WT) were fed high-fat diet, generating an atherosclerosis model; and 2) an acute inflammation model was generated by injecting lipopolysaccharide (LPS) (1 mg/Kg) into miR-146a-/- and WT mice. miR-146a deficiency increased NETosis in both models. Accordingly, miR-146a-/- mice showed significant reduced carotid occlusion time and elevated levels of NETs in thrombi following FeCl3-induced thrombosis. Infusion of DNAse I abolished arterial thrombosis in WT and miR-146a-/- mice. Interestingly, miR-146a deficient mice have aged, hyperreactive and pro-inflammatory neutrophils in circulation that are more prone to form NETs independently of the stimulus. Furthermore, we demonstrated that community acquired pneumonia (CAP) patients with reduced miR-146a levels associated with the T variant of the functional rs2431697, presented an increased risk for cardiovascular events due in part to an increased generation of NETs.

Differential phenotypic characteristics using data mining approaches were defined in a large cohort of patients from the Spanish Online Bronchiectasis Registry (RIBRON). Three differential phenotypic clusters (hierarchical clustering, scikit-learn library for Python, and agglomerative methods) according to systemic biomarkers: neutrophil, eosinophil, and lymphocyte counts, C reactive protein, and hemoglobin were obtained in a patient large-cohort (n = 1092). Clusters #1–3 were named as mild, moderate, and severe on the basis of disease severity scores. Patients in cluster #3 were significantly more severe (FEV1, age, colonization, extension, dyspnea (FACED), exacerbation (EFACED), and bronchiectasis severity index (BSI) scores) than patients in clusters #1 and #2. Exacerbation and hospitalization numbers, Charlson index, and blood inflammatory markers were significantly greater in cluster #3 than in clusters #1 and #2. Chronic colonization by Pseudomonas aeruginosa and COPD prevalence were higher in cluster # 3 than in cluster #1. Airflow limitation and diffusion capacity were reduced in cluster #3 compared to clusters #1 and #2. Multivariate ordinal logistic regression analysis further confirmed these results. Similar results were obtained after excluding COPD patients. Clustering analysis offers a powerful tool to better characterize patients with bronchiectasis. These results have clinical implications in the management of the complexity and heterogeneity of bronchiectasis patients.