Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort.

BACKGROUND: Acute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster. METHODS: Multicenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3. RESULTS: Of 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3. CONCLUSIONS: During the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis.

The efficacy of telavancin in comparison with linezolid on endotracheal tube biofilm in pigs with methicillin-resistant Staphylococcus aureus pneumonia.

BACKGROUND: The effect of systemic treatment of ventilator-associated pneumonia (VAP) with telavancin, a semisynthetic lipoglycopeptide with good penetration in vitro biofilms, has not been tested in vivo during mechanical ventilation. This study examined the efficacy of telavancin compared with linezolid against endotracheal tube (ETT) biofilms in a porcine model of methicillin-resistant Staphylococcus aureus (MRSA) VAP. METHODS: VAP was induced in 18 pigs by instilling 107 colony-forming units (CFU/mL) of an MRSA strain susceptible to telavancin and linezolid into each pulmonary lobe. Randomization into three groups was done at pneumonia diagnosis: control (IV glucose 0.5% solution q24); linezolid (10 mg/kg q12) and telavancin groups (22.5 mg/kg q24). After 72 h of MV, data regarding bronchoalveolar lavage (BAL), tracheal aspirate (TA), ETT MRSA biofilm load and thickness measured by scanning electron microscopy were obtained. RESULTS: All 18 pigs completed the study. MRSA was isolated in 100% of ETTs from the control and linezolid groups and in 67% from the telavancin group. Telavancin treatment presented a lower MRSA load compared to the control and linezolid treatments (telavancin median [interquartile range (IQR)] = 1.94 [0.00-5.45], linezolid 3.99 [3.22-4.68] and control 4.93 [4.41-5.15], P = 0.236). Telavancin treatment also resulted in the lowest biofilm thickness according to the SEM (4.04 [2.09-6.00], P < 0.001). We found a positive correlation between ETT and BAL load (rho = 0.511, P = 0.045). CONCLUSIONS: In our VAP model, systemic telavancin treatment reduced ETT MRSA occurrence, load, and biofilm thickness. Our findings may have a bearing on ICU patients' clinical outcomes.

Procalcitonin and C-reactive protein to rule out early bacterial coinfection in COVID-19 critically ill patients.

PURPOSE: Although the prevalence of community-acquired respiratory bacterial coinfection upon hospital admission in patients with coronavirus disease 2019 (COVID-19) has been reported to be < 5%, almost three-quarters of patients received antibiotics. We aim to investigate whether procalcitonin (PCT) or C-reactive protein (CRP) upon admission could be helpful biomarkers to identify bacterial coinfection among patients with COVID-19 pneumonia. METHODS: We carried out a multicentre, observational cohort study including consecutive COVID-19 patients admitted to 55 Spanish intensive care units (ICUs). The primary outcome was to explore whether PCT or CRP serum levels upon hospital admission could predict bacterial coinfection among patients with COVID-19 pneumonia. The secondary outcome was the evaluation of their association with mortality. We also conducted subgroups analyses in higher risk profile populations. RESULTS: Between 5 February 2020 and 21 December 2021, 4076 patients were included, 133 (3%) of whom presented bacterial coinfection. PCT and CRP had low area under curve (AUC) scores at the receiver operating characteristic (ROC) curve analysis [0.57 (95% confidence interval (CI) 0.51-0.61) and 0.6 (95% CI, 0.55-0.64), respectively], but high negative predictive values (NPV) [97.5% (95% CI 96.5-98.5) and 98.2% (95% CI 97.5-98.9) for PCT and CRP, respectively]. CRP alone was associated with bacterial coinfection (OR 2, 95% CI 1.25-3.19; p = 0.004). The overall 15, 30 and 90 days mortality had a higher trend in the bacterial coinfection group, but without significant difference. PCT ≥ 0.12 ng/mL was associated with higher 90 days mortality. CONCLUSION: Our study suggests that measurements of PCT and CRP, alone and at a single time point, are not useful for ruling in or out bacterial coinfection in viral pneumonia by COVID-19.

Effect of viral storm in patients admitted to intensive care units with severe COVID-19 in Spain: a multicentre, prospective, cohort study.

BACKGROUND: The contribution of the virus to the pathogenesis of severe COVID-19 is still unclear. We aimed to evaluate associations between viral RNA load in plasma and host response, complications, and deaths in critically ill patients with COVID-19. METHODS: We did a prospective cohort study across 23 hospitals in Spain. We included patients aged 18 years or older with laboratory-confirmed SARS-CoV-2 infection who were admitted to an intensive care unit between March 16, 2020, and Feb 27, 2021. RNA of the SARS-CoV-2 nucleocapsid region 1 (N1) was quantified in plasma samples collected from patients in the first 48 h following admission, using digital PCR. Patients were grouped on the basis of N1 quantity: VIR-N1-Zero (<1 N1 copies per mL), VIR-N1-Low (1-2747 N1 copies per mL), and VIR-N1-Storm (>2747 N1 copies per mL). The primary outcome was all-cause death within 90 days after admission. We evaluated odds ratios (ORs) for the primary outcome between groups using a logistic regression analysis. FINDINGS: 1068 patients met the inclusion criteria, of whom 117 had insufficient plasma samples and 115 had key information missing. 836 patients were included in the analysis, of whom 403 (48%) were in the VIR-N1-Low group, 283 (34%) were in the VIR-N1-Storm group, and 150 (18%) were in the VIR-N1-Zero group. Overall, patients in the VIR-N1-Storm group had the most severe disease: 266 (94%) of 283 patients received invasive mechanical ventilation (IMV), 116 (41%) developed acute kidney injury, 180 (65%) had secondary infections, and 148 (52%) died within 90 days. Patients in the VIR-N1-Zero group had the least severe disease: 81 (54%) of 150 received IMV, 34 (23%) developed acute kidney injury, 47 (32%) had secondary infections, and 26 (17%) died within 90 days (OR for death 0·30, 95% CI 0·16-0·55; p<0·0001, compared with the VIR-N1-Storm group). 106 (26%) of 403 patients in the VIR-N1-Low group died within 90 days (OR for death 0·39, 95% CI 0·26-0·57; p<0·0001, compared with the VIR-N1-Storm group). INTERPRETATION: The presence of a so-called viral storm is associated with increased all-cause death in patients admitted to the intensive care unit with severe COVID-19. Preventing this viral storm could help to reduce poor outcomes. Viral storm could be an enrichment marker for treatment with antivirals or purification devices to remove viral components from the blood. FUNDING: Instituto de Salud Carlos III, Canadian Institutes of Health Research, Li Ka-Shing Foundation, Research Nova Scotia, and European Society of Clinical Microbiology and Infectious Diseases. TRANSLATION: For the Spanish translation of the abstract see Supplementary Materials section.

Hemorrhage, Disseminated Intravascular Coagulopathy, and Thrombosis Complications Among Critically Ill Patients with COVID-19: An International COVID-19 Critical Care Consortium Study.

OBJECTIVES: To determine the prevalence and outcomes associated with hemorrhage, disseminated intravascular coagulopathy, and thrombosis (HECTOR) complications in ICU patients with COVID-19. DESIGN: Prospective, observational study. SETTING: Two hundred twenty-nine ICUs across 32 countries. PATIENTS: Adult patients (≥ 16 yr) admitted to participating ICUs for severe COVID-19 from January 1, 2020, to December 31, 2021. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: HECTOR complications occurred in 1,732 of 11,969 study eligible patients (14%). Acute thrombosis occurred in 1,249 patients (10%), including 712 (57%) with pulmonary embolism, 413 (33%) with myocardial ischemia, 93 (7.4%) with deep vein thrombosis, and 49 (3.9%) with ischemic strokes. Hemorrhagic complications were reported in 579 patients (4.8%), including 276 (48%) with gastrointestinal hemorrhage, 83 (14%) with hemorrhagic stroke, 77 (13%) with pulmonary hemorrhage, and 68 (12%) with hemorrhage associated with extracorporeal membrane oxygenation (ECMO) cannula site. Disseminated intravascular coagulation occurred in 11 patients (0.09%). Univariate analysis showed that diabetes, cardiac and kidney diseases, and ECMO use were risk factors for HECTOR. Among survivors, ICU stay was longer (median days 19 vs 12; p < 0.001) for patients with versus without HECTOR, but the hazard of ICU mortality was similar (hazard ratio [HR] 1.01; 95% CI 0.92-1.12; p = 0.784) overall, although this hazard was identified when non-ECMO patients were considered (HR 1.13; 95% CI 1.02-1.25; p = 0.015). Hemorrhagic complications were associated with an increased hazard of ICU mortality compared to patients without HECTOR complications (HR 1.26; 95% CI 1.09-1.45; p = 0.002), whereas thrombosis complications were associated with reduced hazard (HR 0.88; 95% CI 0.79-0.99, p = 0.03). CONCLUSIONS: HECTOR events are frequent complications of severe COVID-19 in ICU patients. Patients receiving ECMO are at particular risk of hemorrhagic complications. Hemorrhagic, but not thrombotic complications, are associated with increased ICU mortality.

Key Factors Associated With Pulmonary Sequelae in the Follow-Up of Critically Ill COVID-19 Patients.

INTRODUCTION: Critical COVID-19 survivors have a high risk of respiratory sequelae. Therefore, we aimed to identify key factors associated with altered lung function and CT scan abnormalities at a follow-up visit in a cohort of critical COVID-19 survivors. METHODS: Multicenter ambispective observational study in 52 Spanish intensive care units. Up to 1327 PCR-confirmed critical COVID-19 patients had sociodemographic, anthropometric, comorbidity and lifestyle characteristics collected at hospital admission; clinical and biological parameters throughout hospital stay; and, lung function and CT scan at a follow-up visit. RESULTS: The median [p25-p75] time from discharge to follow-up was 3.57 [2.77-4.92] months. Median age was 60 [53-67] years, 27.8% women. The mean (SD) percentage of predicted diffusing lung capacity for carbon monoxide (DLCO) at follow-up was 72.02 (18.33)% predicted, with 66% of patients having DLCO<80% and 24% having DLCO<60%. CT scan showed persistent pulmonary infiltrates, fibrotic lesions, and emphysema in 33%, 25% and 6% of patients, respectively. Key variables associated with DLCO<60% were chronic lung disease (CLD) (OR: 1.86 (1.18-2.92)), duration of invasive mechanical ventilation (IMV) (OR: 1.56 (1.37-1.77)), age (OR [per-1-SD] (95%CI): 1.39 (1.18-1.63)), urea (OR: 1.16 (0.97-1.39)) and estimated glomerular filtration rate at ICU admission (OR: 0.88 (0.73-1.06)). Bacterial pneumonia (1.62 (1.11-2.35)) and duration of ventilation (NIMV (1.23 (1.06-1.42), IMV (1.21 (1.01-1.45)) and prone positioning (1.17 (0.98-1.39)) were associated with fibrotic lesions. CONCLUSION: Age and CLD, reflecting patients' baseline vulnerability, and markers of COVID-19 severity, such as duration of IMV and renal failure, were key factors associated with impaired DLCO and CT abnormalities.

Engineered live bacteria suppress Pseudomonas aeruginosa infection in mouse lung and dissolve endotracheal-tube biofilms.

Engineered live bacteria could provide a new modality for treating lung infections, a major cause of mortality worldwide. In the present study, we engineered a genome-reduced human lung bacterium, Mycoplasma pneumoniae, to treat ventilator-associated pneumonia, a disease with high hospital mortality when associated with Pseudomonas aeruginosa biofilms. After validating the biosafety of an attenuated M. pneumoniae chassis in mice, we introduced four transgenes into the chromosome by transposition to implement bactericidal and biofilm degradation activities. We show that this engineered strain has high efficacy against an acute P. aeruginosa lung infection in a mouse model. In addition, we demonstrated that the engineered strain could dissolve biofilms formed in endotracheal tubes of patients with ventilator-associated pneumonia and be combined with antibiotics targeting the peptidoglycan layer to increase efficacy against Gram-positive and Gram-negative bacteria. We expect our M. pneumoniae-engineered strain to be able to treat biofilm-associated infections in the respiratory tract.

Effects of intubation timing in patients with COVID-19 throughout the four waves of the pandemic: a matched analysis.

BACKGROUND: The primary aim of our study was to investigate the association between intubation timing and hospital mortality in critically ill patients with coronavirus disease 2019 (COVID-19)-associated respiratory failure. We also analysed both the impact of such timing throughout the first four pandemic waves and the influence of prior noninvasive respiratory support on outcomes. METHODS: This is a secondary analysis of a multicentre, observational and prospective cohort study that included all consecutive patients undergoing invasive mechanical ventilation due to COVID-19 from across 58 Spanish intensive care units (ICUs) participating in the CIBERESUCICOVID project. The study period was between 29 February 2020 and 31 August 2021. Early intubation was defined as that occurring within the first 24 h of ICU admission. Propensity score matching was used to achieve a balance across baseline variables between the early intubation cohort and those patients who were intubated after the first 24 h of ICU admission. Differences in outcomes between early and delayed intubation were also assessed. We performed sensitivity analyses to consider a different time-point (48 h from ICU admission) for early and delayed intubation. RESULTS: Of the 2725 patients who received invasive mechanical ventilation, a total of 614 matched patients were included in the analysis (307 for each group). In the unmatched population, there were no differences in mortality between the early and delayed groups. After propensity score matching, patients with delayed intubation presented higher hospital mortality (27.3% versus 37.1%; p=0.01), ICU mortality (25.7% versus 36.1%; p=0.007) and 90-day mortality (30.9% versus 40.2%; p=0.02) compared with the early intubation group. Very similar findings were observed when we used a 48-h time-point for early or delayed intubation. The use of early intubation decreased after the first wave of the pandemic (72%, 49%, 46% and 45% in the first, second, third and fourth waves, respectively; first versus second, third and fourth waves p<0.001). In both the main and sensitivity analyses, hospital mortality was lower in patients receiving high-flow nasal cannula (HFNC) (n=294) who were intubated earlier. The subgroup of patients undergoing noninvasive ventilation (n=214) before intubation showed higher mortality when delayed intubation was set as that occurring after 48 h from ICU admission, but not when after 24 h. CONCLUSIONS: In patients with COVID-19 requiring invasive mechanical ventilation, delayed intubation was associated with a higher risk of hospital mortality. The use of early intubation significantly decreased throughout the course of the pandemic. Benefits of such an approach occurred more notably in patients who had received HFNC.

Prognostic implications of comorbidity patterns in critically ill COVID-19 patients: A multicenter, observational study.

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<0.01). Interpretation: Comorbidity-based phenotypes were identified and associated with different expression of in-hospital complications, mortality, treatment response, and sequelae, with CKD playing a major role. This could help clinicians in day-to-day decision making including the management of post-discharge COVID-19 sequelae. Funding: ISCIII, UNESPA, CIBERES, FEDER, ESF.

Methodology of a Large Multicenter Observational Study of Patients with COVID-19 in Spanish Intensive Care Units.

INTRODUCTION: The COVID-19 pandemic created tremendous challenges for health-care systems. Intensive care units (ICU) were hit with a large volume of patients requiring ICU admission, mechanical ventilation, and other organ support with very high mortality. The Centro de Investigación Biomédica en Red-Enfermedades Respiratorias (CIBERES), a network of Spanish researchers to investigate in respiratory disease, commissioned the current proposal in response to the Instituto de Salud Carlos III (ISCIII) call. METHODS: CIBERESUCICOVID is a multicenter, observational, prospective/retrospective cohort study of patients with COVID-19 admitted to Spanish ICUs. Several work packages were created, including study population and ICU data collection, follow-up, biomarkers and miRNAs, data management and quality. RESULTS: This study included 6102 consecutive patients admitted to 55 ICUs homogeneously distributed throughout Spain and the collection of blood samples from more than 1000 patients. We enrolled a large population of COVID-19 ICU-admitted patients including baseline characteristics, ICU and MV data, treatments complications, and outcomes. The in-hospital mortality was 31%, and 76% of patients required invasive mechanical ventilation. A 3-6 month and 1 year follow-up was performed. Few deaths after 1 year discharge were registered. Low anti-SARS-CoV-2 S antibody levels predict mortality in critical COVID-19. These antibodies contribute to prevent systemic dissemination of SARS-CoV-2. The severity of COVID-19 impacts the circulating miRNA profile. Plasma miRNA profiling emerges as a useful tool for risk-based patient stratification in critically ill COVID-19 patients. CONCLUSIONS: We present the methodology used in a large multicenter study sponsored by ISCIII to determine the short- and long-term outcomes in patients with COVID-19 admitted to more than 50 Spanish ICUs.

Risk Factors and Clinical Impact of Fibrotic-Like Changes and the Organizing Pneumonia Pattern in Patients With COVID-19- and Non-COVID-19-Induced Acute Respiratory Distress Syndrome / Factores de riesgo e impacto clínico de los cambios fibróticos y el patrón de neumonía organizada en los pacientes con síndrome de distrés respiratorio agudo producido o no por COVID-19

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Low anti-SARS-CoV-2 S antibody levels predict increased mortality and dissemination of viral components in the blood of critical COVID-19 patients.

BACKGROUND: Anti-SARS-CoV-2 S antibodies prevent viral replication. Critically ill COVID-19 patients show viral material in plasma, associated with a dysregulated host response. If these antibodies influence survival and viral dissemination in ICU-COVID patients is unknown. PATIENTS/METHODS: We studied the impact of anti-SARS-CoV-2 S antibodies levels on survival, viral RNA-load in plasma, and N-antigenaemia in 92 COVID-19 patients over ICU admission. RESULTS: Frequency of N-antigenaemia was >2.5-fold higher in absence of antibodies. Antibodies correlated inversely with viral RNA-load in plasma, representing a protective factor against mortality (adjusted HR [CI 95%], p): (S IgM [AUC ≥ 60]: 0.44 [0.22; 0.88], 0.020); (S IgG [AUC ≥ 237]: 0.31 [0.16; 0.61], <0.001). Viral RNA-load in plasma and N-antigenaemia predicted increased mortality: (N1-viral load [≥2.156 copies/ml]: 2.25 [1.16; 4.36], 0.016); (N-antigenaemia: 2.45 [1.27; 4.69], 0.007). CONCLUSIONS: Low anti-SARS-CoV-2 S antibody levels predict mortality in critical COVID-19. Our findings support that these antibodies contribute to prevent systemic dissemination of SARS-CoV-2.