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.

Effectiveness of prolonged versus standard-course of oseltamivir in critically ill patients with severe influenza infection: A multicentre cohort study.

The aim of this study is to investigate the effectiveness of prolonged versus standard course oseltamivir treatment among critically ill patients with severe influenza. A retrospective study of a prospectively collected database including adults with influenza infection admitted to 184 intensive care units (ICUs) in Spain from 2009 to 2018. Prolonged oseltamivir was defined if patients received the treatment beyond 5 days, whereas the standard-course group received oseltamivir for 5 days. The primary outcome was all-cause ICU mortality. Propensity score matching (PSM) was constructed, and the outcome was investigated through Cox regression and RCSs. Two thousand three hundred and ninety-seven subjects were included, of whom 1943 (81.1%) received prolonged oseltamivir and 454 (18.9%) received standard treatment. An optimal full matching algorithm was performed by matching 2171 patients, 1750 treated in the prolonged oseltamivir group and 421 controls in the standard oseltamivir group. After PSM, 387 (22.1%) patients in the prolonged oseltamivir and 119 (28.3%) patients in the standard group died (p = 0.009). After adjusting confounding factors, prolonged oseltamivir significantly reduced ICU mortality (odds ratio [OR]: 0.53, 95% confidence interval [CI]: 0.40-0.69). Prolonged oseltamivir may have protective effects on survival at Day 10 compared with a standard treatment course. Sensitivity analysis confirmed these findings. Compared with standard treatment, prolonged oseltamivir was associated with reduced ICU mortality in critically ill patients with severe influenza. Clinicians should consider extending the oseltamivir treatment duration to 10 days, particularly in higher-risk groups of prolonged viral shedding. Further randomized controlled trials are warranted to confirm these findings.

Timing of intubation and ICU mortality in COVID-19 patients: a retrospective analysis of 4198 critically ill patients during the first and second waves.

BACKGROUND: The optimal time to intubate patients with SARS-CoV-2 pneumonia has not been adequately determined. While the use of non-invasive respiratory support before invasive mechanical ventilation might cause patient-self-induced lung injury and worsen the prognosis, non-invasive ventilation (NIV) is frequently used to avoid intubation of patients with acute respiratory failure (ARF). We hypothesized that delayed intubation is associated with a high risk of mortality in COVID-19 patients. METHODS: This is a secondary analysis of prospectively collected data from adult patients with ARF due to COVID-19 admitted to 73 intensive care units (ICUs) between February 2020 and March 2021. Intubation was classified according to the timing of intubation. To assess the relationship between early versus late intubation and mortality, we excluded patients with ICU length of stay (LOS) < 7 days to avoid the immortal time bias and we did a propensity score and a cox regression analysis. RESULTS: We included 4,198 patients [median age, 63 (54‒71) years; 71% male; median SOFA (Sequential Organ Failure Assessment) score, 4 (3‒7); median APACHE (Acute Physiology and Chronic Health Evaluation) score, 13 (10‒18)], and median PaO2/FiO2 (arterial oxygen pressure/ inspired oxygen fraction), 131 (100‒190)]; intubation was considered very early in 2024 (48%) patients, early in 928 (22%), and late in 441 (10%). ICU mortality was 30% and median ICU stay was 14 (7‒28) days. Mortality was higher in the "late group" than in the "early group" (37 vs. 32%, p < 0.05). The implementation of an early intubation approach was found to be an independent protective risk factor for mortality (HR 0.6; 95%CI 0.5‒0.7). CONCLUSIONS: Early intubation within the first 24 h of ICU admission in patients with COVID-19 pneumonia was found to be an independent protective risk factor of mortality. TRIAL REGISTRATION: The study was registered at Clinical-Trials.gov (NCT04948242) (01/07/2021).

Relationship between corticosteroid use and incidence of ventilator-associated pneumonia in COVID-19 patients: a retrospective multicenter study.

BACKGROUND: Ventilator-associated pneumonia (VAP) is common in patients with severe SARS-CoV-2 pneumonia. The aim of this ancillary analysis of the coVAPid multicenter observational retrospective study is to assess the relationship between adjuvant corticosteroid use and the incidence of VAP. METHODS: Planned ancillary analysis of a multicenter retrospective European cohort in 36 ICUs. Adult patients receiving invasive mechanical ventilation for more than 48 h for SARS-CoV-2 pneumonia were consecutively included between February and May 2020. VAP diagnosis required strict definition with clinical, radiological and quantitative microbiological confirmation. We assessed the association of VAP with corticosteroid treatment using univariate and multivariate cause-specific Cox's proportional hazard models with adjustment on pre-specified confounders. RESULTS: Among the 545 included patients, 191 (35%) received corticosteroids. The proportional hazard assumption for the effect of corticosteroids on the incidence of VAP could not be accepted, indicating that this effect varied during ICU stay. We found a non-significant lower risk of VAP for corticosteroid-treated patients during the first days in the ICU and an increased risk for longer ICU stay. By modeling the effect of corticosteroids with time-dependent coefficients, the association between corticosteroids and the incidence of VAP was not significant (overall effect p = 0.082), with time-dependent hazard ratios (95% confidence interval) of 0.47 (0.17-1.31) at day 2, 0.95 (0.63-1.42) at day 7, 1.48 (1.01-2.16) at day 14 and 1.94 (1.09-3.46) at day 21. CONCLUSIONS: No significant association was found between adjuvant corticosteroid treatment and the incidence of VAP, although a time-varying effect of corticosteroids was identified along the 28-day follow-up.

Invasive pulmonary aspergillosis among intubated patients with SARS-CoV-2 or influenza pneumonia: a European multicenter comparative cohort study.

BACKGROUND: Recent multicenter studies identified COVID-19 as a risk factor for invasive pulmonary aspergillosis (IPA). However, no large multicenter study has compared the incidence of IPA between COVID-19 and influenza patients. OBJECTIVES: To determine the incidence of putative IPA in critically ill SARS-CoV-2 patients, compared with influenza patients. METHODS: This study was a planned ancillary analysis of the coVAPid multicenter retrospective European cohort. Consecutive adult patients requiring invasive mechanical ventilation for > 48 h for SARS-CoV-2 pneumonia or influenza pneumonia were included. The 28-day cumulative incidence of putative IPA, based on Blot definition, was the primary outcome. IPA incidence was estimated using the Kalbfleisch and Prentice method, considering extubation (dead or alive) within 28 days as competing event. RESULTS: A total of 1047 patients were included (566 in the SARS-CoV-2 group and 481 in the influenza group). The incidence of putative IPA was lower in SARS-CoV-2 pneumonia group (14, 2.5%) than in influenza pneumonia group (29, 6%), adjusted cause-specific hazard ratio (cHR) 3.29 (95% CI 1.53-7.02, p = 0.0006). When putative IPA and Aspergillus respiratory tract colonization were combined, the incidence was also significantly lower in the SARS-CoV-2 group, as compared to influenza group (4.1% vs. 10.2%), adjusted cHR 3.21 (95% CI 1.88-5.46, p < 0.0001). In the whole study population, putative IPA was associated with significant increase in 28-day mortality rate, and length of ICU stay, compared with colonized patients, or those with no IPA or Aspergillus colonization. CONCLUSIONS: Overall, the incidence of putative IPA was low. Its incidence was significantly lower in patients with SARS-CoV-2 pneumonia than in those with influenza pneumonia. Clinical trial registration The study was registered at ClinicalTrials.gov, number NCT04359693 .

Early Bacterial Identification among Intubated Patients with COVID-19 or Influenza Pneumonia: A European Multicenter Comparative Clinical Trial.

Rationale: Early empirical antimicrobial treatment is frequently prescribed to critically ill patients with coronavirus disease (COVID-19) based on Surviving Sepsis Campaign guidelines.Objectives: We aimed to determine the prevalence of early bacterial identification in intubated patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia, as compared with influenza pneumonia, and to characterize its microbiology and impact on outcomes.Methods: A multicenter retrospective European cohort was performed in 36 ICUs. All adult patients receiving invasive mechanical ventilation >48 hours were eligible if they had SARS-CoV-2 or influenza pneumonia at ICU admission. Bacterial identification was defined by a positive bacterial culture within 48 hours after intubation in endotracheal aspirates, BAL, blood cultures, or a positive pneumococcal or legionella urinary antigen test.Measurements and Main Results: A total of 1,050 patients were included (568 in SARS-CoV-2 and 482 in influenza groups). The prevalence of bacterial identification was significantly lower in patients with SARS-CoV-2 pneumonia compared with patients with influenza pneumonia (9.7 vs. 33.6%; unadjusted odds ratio, 0.21; 95% confidence interval [CI], 0.15-0.30; adjusted odds ratio, 0.23; 95% CI, 0.16-0.33; P < 0.0001). Gram-positive cocci were responsible for 58% and 72% of coinfection in patients with SARS-CoV-2 and influenza pneumonia, respectively. Bacterial identification was associated with increased adjusted hazard ratio for 28-day mortality in patients with SARS-CoV-2 pneumonia (1.57; 95% CI, 1.01-2.44; P = 0.043). However, no significant difference was found in the heterogeneity of outcomes related to bacterial identification between the two study groups, suggesting that the impact of coinfection on mortality was not different between patients with SARS-CoV-2 and influenza.Conclusions: Bacterial identification within 48 hours after intubation is significantly less frequent in patients with SARS-CoV-2 pneumonia than patients with influenza pneumonia.Clinical trial registered with www.clinicaltrials.gov (NCT04359693).

Deploying unsupervised clustering analysis to derive clinical phenotypes and risk factors associated with mortality risk in 2022 critically ill patients with COVID-19 in Spain.

BACKGROUND: The identification of factors associated with Intensive Care Unit (ICU) mortality and derived clinical phenotypes in COVID-19 patients could help for a more tailored approach to clinical decision-making that improves prognostic outcomes. METHODS: Prospective, multicenter, observational study of critically ill patients with confirmed COVID-19 disease and acute respiratory failure admitted from 63 ICUs in Spain. The objective was to utilize an unsupervised clustering analysis to derive clinical COVID-19 phenotypes and to analyze patient's factors associated with mortality risk. Patient features including demographics and clinical data at ICU admission were analyzed. Generalized linear models were used to determine ICU morality risk factors. The prognostic models were validated and their performance was measured using accuracy test, sensitivity, specificity and ROC curves. RESULTS: The database included a total of 2022 patients (mean age 64 [IQR 5-71] years, 1423 (70.4%) male, median APACHE II score (13 [IQR 10-17]) and SOFA score (5 [IQR 3-7]) points. The ICU mortality rate was 32.6%. Of the 3 derived phenotypes, the A (mild) phenotype (537; 26.7%) included older age (< 65 years), fewer abnormal laboratory values and less development of complications, B (moderate) phenotype (623, 30.8%) had similar characteristics of A phenotype but were more likely to present shock. The C (severe) phenotype was the most common (857; 42.5%) and was characterized by the interplay of older age (> 65 years), high severity of illness and a higher likelihood of development shock. Crude ICU mortality was 20.3%, 25% and 45.4% for A, B and C phenotype respectively. The ICU mortality risk factors and model performance differed between whole population and phenotype classifications. CONCLUSION: The presented machine learning model identified three clinical phenotypes that significantly correlated with host-response patterns and ICU mortality. Different risk factors across the whole population and clinical phenotypes were observed which may limit the application of a "one-size-fits-all" model in practice.

The evolution of the ventilatory ratio is a prognostic factor in mechanically ventilated COVID-19 ARDS patients.

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.

Ventilator-associated pneumonia diagnosis: a prioritization exercise based on multi-criteria decision analysis.

The aim was to provide global experts ranking on priorities in diagnostic tools for VAP in clinical practice. A multiple criteria decision analysis (MCDA) was performed to identify diagnosis tools for VAP diagnosis. Priority factors were identified after literature review. An international, multidisciplinary expert panel reviewed variables and ranked diagnostic tools. Experts from ten European hospitals participated. Regarding bedside clinical practices, seven required chest X-ray use in all patients, whereas six reported the use of blood cultures and endotracheal aspirate in all patients. Invasive techniques were routinely performed in seven sites. CRP, PCT, and Gram stains were performed in all patients by 5, 2, and 8, respectively. Impact on patient outcomes, safety, and impact on the decision to start antibiotic therapy were ranked as the top three relevant concerns (7.7/10, 7/10, and 6.9/10, respectively). Chest X-ray was ranked as the most important imaging technique to diagnose VAP (score 251.7). Apart from blood cultures, endotracheal aspirate culture was identified as the main collection method for the microbiological testing (scores of 274.8 and 246.8, respectively). Mini-BAL was the preferred invasive technique with a score of 208. Top three biomarkers were CRP (score 184.3), PCT (181.3), and WBC (166.4). Gram stain (192.5) was prioritized among laboratory diagnostic techniques. Using MCDA, it is recommended to perform a combination of diagnostic techniques including images (chest X-ray), culture of clinical specimens (blood cultures and endotracheal aspirate), and biomarkers (CRP or PCT) for VAP diagnosis at the bedside. Gram stain was ranked as the preferred laboratory technique.

Update of the treatment of nosocomial pneumonia in the ICU.

In accordance with the recommendations of, amongst others, the Surviving Sepsis Campaign and the recently published European treatment guidelines for hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP), in the event of a patient with such infections, empirical antibiotic treatment must be appropriate and administered as early as possible. The aim of this manuscript is to update treatment protocols by reviewing recently published studies on the treatment of nosocomial pneumonia in the critically ill patients that require invasive respiratory support and patients with HAP from hospital wards that require invasive mechanical ventilation. An interdisciplinary group of experts, comprising specialists in anaesthesia and resuscitation and in intensive care medicine, updated the epidemiology and antimicrobial resistance and established clinical management priorities based on patients' risk factors. Implementation of rapid diagnostic microbiological techniques available and the new antibiotics recently added to the therapeutic arsenal has been reviewed and updated. After analysis of the categories outlined, some recommendations were suggested, and an algorithm to update empirical and targeted treatment in critically ill patients has also been designed. These aspects are key to improve VAP outcomes because of the severity of patients and possible acquisition of multidrug-resistant organisms (MDROs).

Risks for multidrug-resistant pathogens in the ICU.

PURPOSE OF REVIEW: The impact of multidrug-resistant organisms (MDROs) is rising and often underestimated. The epidemiology of MDROs is extremely complex and multifactorial. There is increasing antibiotic resistance, mainly related to antibiotic pressure and patients' characteristics. RECENT FINDINGS: Emphasis on MDRO epidemiology is needed to better understand current strategies of prevention and management. Among them, antibiotic stewardship has been one of the most successful strategies. It is important to note that there is a controversial issue when considering community and healthcare-related infections. In addition, different strategies have been determined to find the impact and optimal use of recently launched antibiotics for MDRO treatment. SUMMARY: Infections with MDROs can prolong hospital stay, promote antibiotic use and prolong duration of mechanical ventilation. Some points should be further explored in clinical research such as the heterogeneity of healthcare-associated pneumonia and the need of new drug development. Resistance to non fermentative Gram-negative bacilli, rising minimum inhibitory concentration in methicillin-resistant Staphylococcus aureus and spread of MDROs in patients without known risk factors suggest a review of guideline validation, taking into account ecology and severity of patient illness to provide timely and appropriate empiric therapy.

A Machine Learning Approach to Determine Risk Factors for Respiratory Bacterial/Fungal Coinfection in Critically Ill Patients with Influenza and SARS-CoV-2 Infection: A Spanish Perspective.

Background: Bacterial/fungal coinfections (COIs) are associated with antibiotic overuse, poor outcomes such as prolonged ICU stay, and increased mortality. Our aim was to develop machine learning-based predictive models to identify respiratory bacterial or fungal coinfections upon ICU admission. Methods: We conducted a secondary analysis of two prospective multicenter cohort studies with confirmed influenza A (H1N1)pdm09 and COVID-19. Multiple logistic regression (MLR) and random forest (RF) were used to identify factors associated with BFC in the overall population and in each subgroup (influenza and COVID-19). The performance of these models was assessed by the area under the ROC curve (AUC) and out-of-bag (OOB) methods for MLR and RF, respectively. Results: Of the 8902 patients, 41.6% had influenza and 58.4% had SARS-CoV-2 infection. The median age was 60 years, 66% were male, and the crude ICU mortality was 25%. BFC was observed in 14.2% of patients. Overall, the predictive models showed modest performances, with an AUC of 0.68 (MLR) and OOB 36.9% (RF). Specific models did not show improved performance. However, age, procalcitonin, CRP, APACHE II, SOFA, and shock were factors associated with BFC in most models. Conclusions: Machine learning models do not adequately predict the presence of co-infection in critically ill patients with pandemic virus infection. However, the presence of factors such as advanced age, elevated procalcitonin or CPR, and high severity of illness should alert clinicians to the need to rule out this complication on admission to the ICU.

Association of obesity on the outcome of critically ill patients affected by COVID-19.

OBJECTIVE: To evaluate the impact of obesity on ICU mortality. DESIGN: Observational, retrospective, multicentre study. SETTING: Intensive Care Unit (ICU). PATIENTS: Adults patients admitted with COVID-19 and respiratory failure. INTERVENTIONS: None. PRIMARY VARIABLES OF INTEREST: Collected data included demographic and clinical characteristics, comorbidities, laboratory tests and ICU outcomes. Body mass index (BMI) impact on ICU mortality was studied as (1) a continuous variable, (2) a categorical variable obesity/non-obesity, and (3) as categories defined a priori: underweight, normal, overweight, obesity and Class III obesity. The impact of obesity on mortality was assessed by multiple logistic regression and Smooth Restricted cubic (SRC) splines for Cox hazard regression. RESULTS: 5,206 patients were included, 20 patients (0.4%) as underweight, 887(17.0%) as normal, 2390(46%) as overweight, 1672(32.1) as obese and 237(4.5%) as class III obesity. The obesity group patients (n = 1909) were younger (61 vs. 65 years, p < 0.001) and with lower severity scores APACHE II (13 [9-17] vs. 13[10-17, p < 0.01) than non-obese. Overall ICU mortality was 28.5% and not different for obese (28.9%) or non-obese (28.3%, p = 0.65). Only Class III obesity (OR = 2.19, 95%CI 1.44-3.34) was associated with ICU mortality in the multivariate and SRC analysis. CONCLUSIONS: COVID-19 patients with a BMI > 40 are at high risk of poor outcomes in the ICU. An effective vaccination schedule and prolonged social distancing should be recommended.

Applicability of an unsupervised cluster model developed on first wave COVID-19 patients in second/third wave critically ill patients.

OBJECTIVE: To validate the unsupervised cluster model (USCM) developed during the first pandemic wave in a cohort of critically ill patients from the second and third pandemic waves. DESIGN: Observational, retrospective, multicentre study. SETTING: Intensive Care Unit (ICU). PATIENTS: Adult patients admitted with COVID-19 and respiratory failure during the second and third pandemic waves. INTERVENTIONS: None. MAIN VARIABLES OF INTEREST: Collected data included demographic and clinical characteristics, comorbidities, laboratory tests and ICU outcomes. To validate our original USCM, we assigned a phenotype to each patient of the validation cohort. The performance of the classification was determined by Silhouette coefficient (SC) and general linear modelling. In a post-hoc analysis we developed and validated a USCM specific to the validation set. The model's performance was measured using accuracy test and area under curve (AUC) ROC. RESULTS: A total of 2330 patients (mean age 63 [53-82] years, 1643 (70.5%) male, median APACHE II score (12 [9-16]) and SOFA score (4 [3-6]) were included. The ICU mortality was 27.2%. The USCM classified patients into 3 clinical phenotypes: A (n = 1206 patients, 51.8%); B (n = 618 patients, 26.5%), and C (n = 506 patients, 21.7%). The characteristics of patients within each phenotype were significantly different from the original population. The SC was -0.007 and the inclusion of phenotype classification in a regression model did not improve the model performance (0.79 and 0.78 ROC for original and validation model). The post-hoc model performed better than the validation model (SC -0.08). CONCLUSION: Models developed using machine learning techniques during the first pandemic wave cannot be applied with adequate performance to patients admitted in subsequent waves without prior validation.

[Nosocomial pneumonia]. / Neumonía nosocomial.

The hospital acquired pneumonia (HAP) is one of the most common infections acquired among hospitalised patients. Within the HAP, the ventilator-associated pneumonia (VAP) is the most common nosocomial infection complication among patients with acute respiratory failure. The VAP and HAP are associated with increased mortality and increased hospital costs. The rise in HAP due to antibiotic-resistant bacteria also causes an increase in the incidence of inappropriate empirical antibiotic therapy, with an associated increased risk of hospital mortality. It is very important to know the most common organisms responsible for these infections in each hospital and each Intensive Care Unit, as well as their antimicrobial susceptibility patterns, in order to reduce the incidence of inappropriate antibiotic therapy and improve the prognosis of patients. Additionally, clinical strategies aimed at the prevention of HAP and VAP should be employed in hospital settings caring for patients at risk for these infections.

A Multicentric Observational Study to Determine Myocardial Injury in Severe Community-Acquired Pneumonia (sCAP).

Background: Severe community-acquired pneumonia (sCAP) is the most frequent admission for acute respiratory failure in intensive care medicine. Observational studies have found a correlation between patients who were admitted with CAP and the development of cardiovascular events. The risk of acute myocardial damage in patients with CAP is particularly high within the first 30 days of hospitalization. Research design and methods: Multicenter prospective cohort analysis conducted in consecutive patients admitted to an ICU with microbiologically confirmed diagnoses of sCAP. The aim was to determine any structural cardiac damage detected by advanced imagining techniques (cardiac MRI) and cardiac biomarkers in patients with sCAP. The patients were stratified, according to their etiology, into pneumococcal or not-pneumococcal sCAP. The primary outcome was cardiac damage at day 5 and 7 of clinical presentation. Results: A total of 23 patients were consecutively and prospectively enrolled for two winter periods. No significant differences were observed between the median troponin when comparing the pneumococcal vs. non-pneumococcal. The incidence of myocardial damage was numerically higher in the pneumococcal subgroup (70% vs. 50%, p = 0.61) on day 5 and on day 7 (53% vs. 40%, p = 0.81) but did not achieve significance. Confirming a correlation between the biomarkers of cell damage and the biomarkers of myocardial damage, only a positive and significant correlation was observed between h-FABP and DNA on day 1 (r = 0.74; p < 0.01) and day 3 (r = 0.83; p < 0.010). Twenty cardiac MRIs were performed on the 23 patients (87%). No presence of fibrosis was observed in any of the studies carried out within the first 15 days of admission. Conclusions: No significant myocardial damage was found in patients with sCAP independent of the bacterial etiology in accordance with biomarker alterations (Troponin and/or h-FABP) or cardiac MRI. Using cardiac MRI, we could not find any presence of myocardial fibrosis within the first 15 days of admission.

European Network for ICU-Related Respiratory Infections (ENIRRIs): a multinational, prospective, cohort study of nosocomial LRTI.

PURPOSE: Lower respiratory tract infections (LRTI) are the most frequent infectious complication in patients admitted to the intensive care unit (ICU). We aim to report the clinical characteristics of ICU-admitted patients due to nosocomial LRTI and to describe their microbiology and clinical outcomes. METHODS: A prospective observational study was conducted in 13 countries over two continents from 9th May 2016 until 16th August 2019. Characteristics and outcomes of ventilator-associated pneumonia (VAP), ventilator-associated tracheobronchitis (VAT), ICU hospital-acquired pneumonia (ICU-HAP), HAP that required invasive ventilation (VHAP), and HAP in patients transferred to the ICU without invasive mechanical ventilation were collected. The clinical diagnosis and treatments were per clinical practice and not per protocol. Descriptive statistics were used to compare the study groups. RESULTS: 1060 patients with LRTI (72.5% male sex, median age 64 [50-74] years) were included in the study; 160 (15.1%) developed VAT, 556 (52.5%) VAP, 98 (9.2%) ICU-HAP, 152 (14.3%) HAP, and 94 (8.9%) VHAP. Patients with VHAP had higher serum procalcitonin (PCT) and Sequential Organ Failure Assessment (SOFA) scores. Patients with VAP or VHAP developed acute kidney injury, acute respiratory distress syndrome, multiple organ failure, or septic shock more often. One thousand eight patients had microbiological samples, and 711 (70.5%) had etiological microbiology identified. The most common microorganisms were Pseudomonas aeruginosa (18.4%) and Klebsiella spp (14.4%). In 382 patients (36%), the causative pathogen shows some antimicrobial resistance pattern. ICU, hospital and 28-day mortality were 30.8%, 37.5% and 27.5%, respectively. Patients with VHAP had the highest ICU, in-hospital and 28-day mortality rates. CONCLUSION: VHAP patients presented the highest mortality among those admitted to the ICU. Multidrug-resistant pathogens frequently cause nosocomial LRTI in this multinational cohort study.

Risk factors for developing ventilator-associated lower respiratory tract infection in patients with severe COVID-19: a multinational, multicentre study, prospective, observational study.

Around one-third of patients diagnosed with COVID-19 develop a severe illness that requires admission to the Intensive Care Unit (ICU). In clinical practice, clinicians have learned that patients admitted to the ICU due to severe COVID-19 frequently develop ventilator-associated lower respiratory tract infections (VA-LRTI). This study aims to describe the clinical characteristics, the factors associated with VA-LRTI, and its impact on clinical outcomes in patients with severe COVID-19. This was a multicentre, observational cohort study conducted in ten countries in Latin America and Europe. We included patients with confirmed rtPCR for SARS-CoV-2 requiring ICU admission and endotracheal intubation. Only patients with a microbiological and clinical diagnosis of VA-LRTI were included. Multivariate Logistic regression analyses and Random Forest were conducted to determine the risk factors for VA-LRTI and its clinical impact in patients with severe COVID-19. In our study cohort of 3287 patients, VA-LRTI was diagnosed in 28.8% [948/3287]. The cumulative incidence of ventilator-associated pneumonia (VAP) was 18.6% [610/3287], followed by ventilator-associated tracheobronchitis (VAT) 10.3% [338/3287]. A total of 1252 bacteria species were isolated. The most frequently isolated pathogens were Pseudomonas aeruginosa (21.2% [266/1252]), followed by Klebsiella pneumoniae (19.1% [239/1252]) and Staphylococcus aureus (15.5% [194/1,252]). The factors independently associated with the development of VA-LRTI were prolonged stay under invasive mechanical ventilation, AKI during ICU stay, and the number of comorbidities. Regarding the clinical impact of VA-LRTI, patients with VAP had an increased risk of hospital mortality (OR [95% CI] of 1.81 [1.40-2.34]), while VAT was not associated with increased hospital mortality (OR [95% CI] of 1.34 [0.98-1.83]). VA-LRTI, often with difficult-to-treat bacteria, is frequent in patients admitted to the ICU due to severe COVID-19 and is associated with worse clinical outcomes, including higher mortality. Identifying risk factors for VA-LRTI might allow the early patient diagnosis to improve clinical outcomes.Trial registration: This is a prospective observational study; therefore, no health care interventions were applied to participants, and trial registration is not applicable.

Device-associated infection rates in Adult Intensive Care Units in Catalonia: VINCat Program findings.

Hospital-acquired infections are a leading cause of morbidity and mortality, especially in the intensive care unit (ICU). Surveillance of device-associated infections plays a major role in infection control programs. In 2006, the Surveillance Program of Nosocomial Infections in Catalonia (VINCat Program) was started, with the major aim of reducing infection rates through a process of active monitoring. The study period comprised calendar years 2008 (with 21 ICUs participating), 2009 (with 21 ICUs participating), and 2010 (with 28 ICUs participating). Each participating hospital was required to have an infection control team made up of at least one physician, an infection surveillance nurse, and a microbiology laboratory. Hospitals were classified into three groups according to their size. Central venous catheter-associated bloodstream infection (CVC-BSI) and ventilator-associated pneumonia (VAP) were chosen as the device-associated infections to analyze. Incidence rates of device-associated infections were calculated by dividing the total number of device-associated infection (VAP or CVC-BSI) days by the total number of days use for the relevant device. Mechanical ventilation use ranged from 0.10 to 0.85 days (overall, 0.35), and central venous catheter use ranged from 0.18 to 0.98 days (overall, 0.65). Incidence rates of VAP ranged from 7.2 ± 3.7 to 10.7 ± 9.6 episodes of VAP/1000 ventilator days. Incidence rates of CVC-BSl ranged from 1.9 ± 1.6 to 2.7 ± 2.0 episodes of CVC-associated bloodstream infection/1000 central venous catheter days. The implementation of the VINCat Program allowed monitoring of nosocomial device-associated infections in ICUs in Catalonia and enabled corrective measures in ICUs with increased incidences of device-associated infections.