Biomarkers in pulmonary infections: a clinical approach.

Severe acute respiratory infections, such as community-acquired pneumonia, hospital-acquired pneumonia, and ventilator-associated pneumonia, constitute frequent and lethal pulmonary infections in the intensive care unit (ICU). Despite optimal management with early appropriate empiric antimicrobial therapy and adequate supportive care, mortality remains high, in part attributable to the aging, growing number of comorbidities, and rising rates of multidrug resistance pathogens. Biomarkers have the potential to offer additional information that may further improve the management and outcome of pulmonary infections. Available pathogen-specific biomarkers, for example, Streptococcus pneumoniae urinary antigen test and galactomannan, can be helpful in the microbiologic diagnosis of pulmonary infection in ICU patients, improving the timing and appropriateness of empiric antimicrobial therapy since these tests have a short turnaround time in comparison to classic microbiology. On the other hand, host-response biomarkers, for example, C-reactive protein and procalcitonin, used in conjunction with the clinical data, may be useful in the diagnosis and prediction of pulmonary infections, monitoring the response to treatment, and guiding duration of antimicrobial therapy. The assessment of serial measurements overtime, kinetics of biomarkers, is more informative than a single value. The appropriate utilization of accurate pathogen-specific and host-response biomarkers may benefit clinical decision-making at the bedside and optimize antimicrobial stewardship.

Utilization of expert opinion in infectious diseases clinical guidelines-A meta-epidemiological study.

INTRODUCTION: Expert opinion is widely used in clinical guidelines. No research has ever been conducted investigating the use of expert opinion in international infectious disease guidelines. This study aimed to create an analytical map by describing the prevalence and utilization of expert opinion in infectious disease guidelines and analyzing the methodological aspects of these guidelines. METHODS: In this meta-epidemiological study, systematic searches in PubMed and Trip Medical Database were performed to identify clinical guidelines on infectious diseases, published between January 2018 and May 2023 in English, by international organizations. Data extracted included guideline characteristics, expert opinion utilization, and methodological details. Prevalence and rationale of expert opinion use were analyzed descriptively. Methodological differences between groups were analyzed with Chi-square and Mann-Whitney U Test. RESULTS: The analysis covered 66 guidelines with 2296 recommendations, published/endorsed by 136 organizations. Most guidelines (79%) used systematic literature searches, 42% provided search strategies, and 38% presented screening flow diagrams and conducted risk of bias assessments. 48.5% of the guidelines allowed expert opinion, most of which included expert opinion as part of the evidence hierarchy within the grading system. Guidelines allowing expert opinion, compared to those which do not, issued more recommendations per guideline (48.82 vs.19.13, p<0.001), and reported fewer screening flow diagrams (25% vs. 65%, p = 0.002), and less risk of bias assessments (19% vs.78%, p<0.001). CONCLUSIONS: Expert opinion is utilized in half of assessed guidelines, often integrated into the evidence hierarchy within the grading system. Its utilization varies considerably in methodology, form, and terminology between guidelines. These findings highlight a pressing need for additional research and guidance, to improve and advance the standardization of infectious disease guidelines.

Intra-abdominal infections survival guide: a position statement by the Global Alliance For Infections In Surgery.

Intra-abdominal infections (IAIs) are an important cause of morbidity and mortality in hospital settings worldwide. The cornerstones of IAI management include rapid, accurate diagnostics; timely, adequate source control; appropriate, short-duration antimicrobial therapy administered according to the principles of pharmacokinetics/pharmacodynamics and antimicrobial stewardship; and hemodynamic and organ functional support with intravenous fluid and adjunctive vasopressor agents for critical illness (sepsis/organ dysfunction or septic shock after correction of hypovolemia). In patients with IAIs, a personalized approach is crucial to optimize outcomes and should be based on multiple aspects that require careful clinical assessment. The anatomic extent of infection, the presumed pathogens involved and risk factors for antimicrobial resistance, the origin and extent of the infection, the patient's clinical condition, and the host's immune status should be assessed continuously to optimize the management of patients with complicated IAIs.

A targeted likelihood estimation comparing cefepime and piperacillin/tazobactam in critically ill patients with community-acquired pneumonia (CAP).

Cefepime and piperacillin/tazobactam are antimicrobials recommended by IDSA/ATS guidelines for the empirical management of patients admitted to the intensive care unit (ICU) with community-acquired pneumonia (CAP). Concerns have been raised about which should be used in clinical practice. This study aims to compare the effect of cefepime and piperacillin/tazobactam in critically ill CAP patients through a targeted maximum likelihood estimation (TMLE). A total of 2026 ICU-admitted patients with CAP were included. Among them, (47%) presented respiratory failure, and (27%) developed septic shock. A total of (68%) received cefepime and (32%) piperacillin/tazobactam-based treatment. After running the TMLE, we found that cefepime and piperacillin/tazobactam-based treatments have comparable 28-day, hospital, and ICU mortality. Additionally, age, PTT, serum potassium and temperature were associated with preferring cefepime over piperacillin/tazobactam (OR 1.14 95% CI [1.01-1.27], p = 0.03), (OR 1.14 95% CI [1.03-1.26], p = 0.009), (OR 1.1 95% CI [1.01-1.22], p = 0.039) and (OR 1.13 95% CI [1.03-1.24], p = 0.014)]. Our study found a similar mortality rate among ICU-admitted CAP patients treated with cefepime and piperacillin/tazobactam. Clinicians may consider factors such as availability and safety profiles when making treatment decisions.

Identification of Marker Genes in Infectious Diseases from ScRNA-seq Data Using Interpretable Machine Learning.

A common result of infection is an abnormal immune response, which may be detrimental to the host. To control the infection, the immune system might undergo regulation, therefore producing an excess of either pro-inflammatory or anti-inflammatory pathways that can lead to widespread inflammation, tissue damage, and organ failure. A dysregulated immune response can manifest as changes in differentiated immune cell populations and concentrations of circulating biomarkers. To propose an early diagnostic system that enables differentiation and identifies the severity of immune-dysregulated syndromes, we built an artificial intelligence tool that uses input data from single-cell RNA sequencing. In our results, single-cell transcriptomics successfully distinguished between mild and severe sepsis and COVID-19 infections. Moreover, by interpreting the decision patterns of our classification system, we identified that different immune cells upregulating or downregulating the expression of the genes CD3, CD14, CD16, FOSB, S100A12, and TCRɣδ can accurately differentiate between different degrees of infection. Our research has identified genes of significance that effectively distinguish between infections, offering promising prospects as diagnostic markers and providing potential targets for therapeutic intervention.

Hospital-acquired bacterial pneumonia in critically ill patients: from research to clinical practice.

INTRODUCTION: Hospital-acquired pneumonia (HAP) represents a significant cause of mortality among critically ill patients admitted to Intensive Care Units (ICUs). Timely and precise diagnosis is imperative to enhance therapeutic efficacy and patient outcomes. However, the diagnostic process is challenged by test limitations and a wide-ranging list of differential diagnoses, particularly in patients exhibiting escalating oxygen requirements, leukocytosis, and increased secretions. AREAS COVERED: This narrative review aims to update diagnostic modalities, facilitating the prompt identification of nosocomial pneumonia while guiding, developing, and assessing therapeutic interventions. A comprehensive literature review was conducted utilizing the MEDLINE/PubMed database from 2013 to April 2024. EXPERT OPINION: An integrated approach that integrates clinical, microbiological, and imaging tools is paramount. Progress in diagnostic techniques, including novel molecular methods, the expanding utilization and accuracy of bedside ultrasound, and the emergence of Artificial Intelligence, coupled with an improved comprehension of lung microbiota and host-pathogen interactions, continues to enhance our capability to accurately and swiftly identify HAP and its causative agents. This advancement enables the refinement of treatment strategies and facilitates the implementation of precision medicine approaches.

Characteristics and outcomes of COVID-19 patients admitted to hospital with and without respiratory symptoms.

Background: COVID-19 is primarily known as a respiratory illness; however, many patients present to hospital without respiratory symptoms. The association between non-respiratory presentations of COVID-19 and outcomes remains unclear. We investigated risk factors and clinical outcomes in patients with no respiratory symptoms (NRS) and respiratory symptoms (RS) at hospital admission. Methods: This study describes clinical features, physiological parameters, and outcomes of hospitalised COVID-19 patients, stratified by the presence or absence of respiratory symptoms at hospital admission. RS patients had one or more of: cough, shortness of breath, sore throat, runny nose or wheezing; while NRS patients did not. Results: Of 178,640 patients in the study, 86.4 % presented with RS, while 13.6 % had NRS. NRS patients were older (median age: NRS: 74 vs RS: 65) and less likely to be admitted to the ICU (NRS: 36.7 % vs RS: 37.5 %). NRS patients had a higher crude in-hospital case-fatality ratio (NRS 41.1 % vs. RS 32.0 %), but a lower risk of death after adjusting for confounders (HR 0.88 [0.83-0.93]). Conclusion: Approximately one in seven COVID-19 patients presented at hospital admission without respiratory symptoms. These patients were older, had lower ICU admission rates, and had a lower risk of in-hospital mortality after adjusting for confounders.

Epidemiology and Burden of Ventilator-Associated Pneumonia among Adult Intensive Care Unit Patients: A Portuguese, Multicenter, Retrospective Study (eVAP-PT Study).

Ventilator-associated pneumonia (VAP) is a prevailing nosocomial infection in critically ill patients requiring invasive mechanical ventilation (iMV). The impact of VAP is profound, adversely affecting patient outcomes and placing a significant burden on healthcare resources. This study assessed for the first time the contemporary VAP epidemiology in Portugal and its burden on the healthcare system and clinical outcomes. Additionally, resource consumption (duration of iMV, intensive care unit (ICU), hospital length of stay (LOS)) and empirical antimicrobial therapy were also evaluated. This multicenter, retrospective study included patients admitted to the hospital between July 2016 and December 2017 in a participating ICU, who underwent iMV for at least 48 h. Patients with a VAP diagnosis were segregated for further analysis (n = 197). Control patients, ventilated for >48 h but without a VAP diagnosis, were also included in a 1:1 ratio. Cumulative VAP incidence was computed. All-cause mortality was assessed at 28, 90, and 365 days after ICU admission. Cumulative VAP incidence was 9.2% (95% CI 8.0-10.5). The all-cause mortality rate in VAP patients was 24.9%, 34.0%, and 40.6%, respectively, and these values were similar to those observed in patients without VAP diagnosis. Further, patients with VAP had significantly longer ICU (27.5 vs. 11.0 days, p < 0.001) and hospital LOS (61 vs. 35.9 days, p < 0.001), more time under iMV (20.7 vs. 8.0 days, p < 0.001) and were more often subjected to tracheostomy (36.5 vs. 14.2%; p < 0.001). Patients with VAP who received inappropriate empirical antimicrobials had higher 28-day mortality, 34.3% vs. 19.5% (odds ratio 2.16, 95% CI 1.10-4.23), although the same was not independently associated with 1-year all-cause mortality (p = 0.107). This study described the VAP impact and burden on the Portuguese healthcare system, with approximately 9% of patients undergoing iMV for >48 h developing VAP, leading to increased resource consumption (longer ICU and hospital LOS). An unexpectedly high incidence of inappropriate, empirical antimicrobial therapy was also noted, being positively associated with a higher mortality risk of these patients. Knowledge of the Portuguese epidemiology characterization of VAP and its multidimensional impact is essential for efficient treatment and optimized long-term health outcomes of these patients.

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.

Association of obesity on the outcome of critically ill patients affected by COVID-19 / Asociación de la obesidad en la evolución de los pacientes críticos afectados por 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. (AU)

Objetivo Evaluar el impacto de la obesidad en la mortalidad de la UCI. Diseño Estudio observacional, retrospectivo y multicéntrico. Ámbito Unidad de Cuidados Intensivos (UCI). Pacientes Pacientes adultos con COVID-19 e insuficiencia respiratoria. Intervenciones Ninguna. Variables de interés principales Características demográficas y clínicas, comorbilidades, pruebas de laboratorio y evolución en la UCI. El impacto del índice de masa corporal (IMC) sobre la mortalidad se estudió como (1) una variable continua, (2) una variable categórica obesidad/no obesidad, y (3) como categorías definidas a priori: bajo peso, normal, sobrepeso, obesidad y obesidad clase III. El impacto de la obesidad se evaluó mediante regresión logística múltiple y splines cúbicos suaves restringidos (SRC) para la regresión de riesgos de Cox. Resultados Se incluyeron 5.206 pacientes, 20 (0,4%) con bajo peso, 887 (17,0%) con peso normal, 2.390 (46%) con sobrepeso, 1.672 (32,1%) con obesidad y 237 (4,5%) con obesidad clase III. Los pacientes obesos (n = 1909) eran más jóvenes (61 vs. 65 años, p < 0,001) y con un nivel más bajo de APACHE II (13 [9–17] frente a 13[10−17, p < 0,01) que los no obesos. La mortalidad global en la UCI fue del 28,5% y no fue diferente entre obesos (28,9%) y no obesos (28,3%,p = 0,65). Sólo la obesidad clase III (OR = 2,19; IC del 95%: 1,44−3,34) se asoció con la mortalidad en la UCI en el análisis multivariante y SRC. Conclusiones Los pacientes con COVID-19 con un IMC > 40 tienen un alto riesgo de mala evolución en la UCI. Debe recomendarse un calendario de vacunación eficaz y un distanciamiento social prolongado. (AU)

Comprehensive study of mechanical power in controlled mechanical ventilation: Prevalence of elevated mechanical power and component analysis / Estudio Integral de la Potencia Mecánica en la Ventilación Mecánica Controlada: Prevalencia de Potencia Mecánica Elevada y Análisis de Componentes

Objective To determine the prevalence of elevated mechanical power (MP) values (>17J/min) used in routine clinical practice. Design Observational, descriptive, cross-sectional, analytical, multicenter, international study conducted on November 21, 2019, from 8:00 AM to 3:00 PM. NCT03936231. Setting One hundred thirty-three Critical Care Units. Patients Patients receiving invasive mechanical ventilation for any cause. Interventions None. Main variables of interest Mechanical power. Results A population of 372 patients was analyzed. PM was significantly higher in patients under pressure-controlled ventilation (PC) compared to volume-controlled ventilation (VC) (19.20±8.44J/min vs. 16.01±6.88J/min; p<0.001), but the percentage of patients with PM>17J/min was not different (41% vs. 35%, respectively; p=0.382). The best models according to AICcw expressing PM for patients in VC are described as follows: Surrogate Strain (Driving Pressure) + PEEP+Surrogate Strain Rate (PEEP/Flow Ratio) + Respiratory Rate. For patients in PC, it is defined as: Surrogate Strain (Expiratory Tidal Volume/PEEP) + PEEP+Surrogate Strain Rate (Surrogate Strain/Ti) + Respiratory Rate+Expiratory Tidal Volume+Ti. Conclusions A substantial proportion of mechanically ventilated patients may be at risk of experiencing elevated levels of mechanical power. Despite observed differences in mechanical power values between VC and PC ventilation, they did not result in a significant disparity in the prevalence of high mechanical power values. (AU)

Objetivo Determinar la prevalencia de valores elevados de potencia mecánica (PM) (>17J/min) utilizados en la práctica clínica habitual. Diseño estudio observacional, descriptivo de corte transversal, analítico, multicéntrico e internacional, realizado el 21 de noviembre de 2019 en horario de 8 a 15 horas. NCT03936231. Ámbito Ciento treinta y tres Unidad de Cuidados Críticos. Pacientes pacientes que recibirán ventilación mecánica por cualquier causa. Intervenciones ninguna Variables de interés principales Potencia mecánica. Resultados se analizaron 372 enfermos. La PM fue significativamente mayor en pacientes en ventilación controlada por presión (PC) que en ventilación controlada por volumen (VC) (19,20+8,44J/min frente a 16,01+6,88J/min; p<0,001), pero el porcentaje de pacientes con PM>17J/min no fue diferente (41% frente a 35% respectivamente; p=0,382). Los mejores modelos según AICcw que expresan la PM para los enfermos en VC se decribe como: Strain subrogante (Presión de conducción) + PEEP+Strain Rate subrogante (PEEP/cociente de flujo) + Frecuencia respiratoria. Para los enfermos en PC se define como: Strain subrogante (Volumen tidal expiratorio/PEEP) + PEEP+Strain Rate subrogante (Strain subrogante/Ti) + Frecuencia respiratoria+Expiratory Tidal Volumen+Ti. Conclusiones Gran parte de los pacientes en ventilación mecánica en condiciones de práctica clínica habitual reciben niveles de potencia mecánica peligrosos. A pesar de las diferencias observadas en los valores de potencia mecánica entre la ventilación VC y PC, este porcentaje de riesgo fue similar en PC y VC. (AU)

Major alteration of Lung Microbiome and the Host Reaction in critically ill COVID-19 Patients with high viral load.

Background: Patients with COVID-19 under invasive mechanical ventilation are at higher risk of developing ventilator-associated pneumonia (VAP), associated with increased healthcare costs, and unfavorable prognosis. The underlying mechanisms of this phenomenon have not been thoroughly dissected. Therefore, this study attempted to bridge this gap by performing a lung microbiota analysis and evaluating the host immune responses that could drive the development of VAP. Materials and methods: In this prospective cohort study, mechanically ventilated patients with confirmed SARS-CoV-2 infection were enrolled. Nasal swabs (NS), endotracheal aspirates (ETA), and blood samples were collected initially within 12 hours of intubation and again at 72 hours post-intubation. Plasma samples underwent cytokine and metabolomic analyses, while NS and ETA samples were sequenced for lung microbiome examination. The cohort was categorized based on the development of VAP. Data analysis was conducted using RStudio version 4.3.1. Results: In a study of 36 COVID-19 patients on mechanical ventilation, significant differences were found in the nasal and pulmonary microbiome, notably in Staphylococcus and Enterobacteriaceae, linked to VAP. Patients with VAP showed a higher SARS-CoV-2 viral load, elevated neutralizing antibodies, and reduced inflammatory cytokines, including IFN-δ, IL-1ß, IL-12p70, IL-18, IL-6, TNF-α, and CCL4. Metabolomic analysis revealed changes in 22 metabolites in non-VAP patients and 27 in VAP patients, highlighting D-Maltose-Lactose, Histidinyl-Glycine, and various phosphatidylcholines, indicating a metabolic predisposition to VAP. Conclusions: This study reveals a critical link between respiratory microbiome alterations and ventilator-associated pneumonia in COVID-19 patients, with elevated SARS-CoV-2 levels and metabolic changes, providing novel insights into the underlying mechanisms of VAP with potential management and prevention implications.

Invasive Fungal Diseases in Adult Patients in Intensive Care Unit (FUNDICU): 2024 consensus definitions from ESGCIP, EFISG, ESICM, ECMM, MSGERC, ISAC, and ISHAM.

PURPOSE: The aim of this document was to develop standardized research definitions of invasive fungal diseases (IFD) in non-neutropenic, adult patients without classical host factors for IFD, admitted to intensive care units (ICUs). METHODS: After a systematic assessment of the diagnostic performance for IFD in the target population of already existing definitions and laboratory tests, consensus definitions were developed by a panel of experts using the RAND/UCLA appropriateness method. RESULTS: Standardized research definitions were developed for proven invasive candidiasis, probable deep-seated candidiasis, proven invasive aspergillosis, probable invasive pulmonary aspergillosis, and probable tracheobronchial aspergillosis. The limited evidence on the performance of existing definitions and laboratory tests for the diagnosis of IFD other than candidiasis and aspergillosis precluded the development of dedicated definitions, at least pending further data. The standardized definitions provided in the present document are aimed to speed-up the design, and increase the feasibility, of future comparative research studies.

Challenges for a broad international implementation of the current severe community-acquired pneumonia guidelines.

Severe community-acquired pneumonia (sCAP) remains one of the leading causes of admission to the intensive care unit, thus consuming a large share of resources and is associated with high mortality rates worldwide. The evidence generated by clinical studies in the last decade was translated into recommendations according to the first published guidelines focusing on severe community-acquired pneumonia. Despite the advances proposed by the present guidelines, several challenges preclude the prompt implementation of these diagnostic and therapeutic measures. The present article discusses the challenges for the broad implementation of the sCAP guidelines and proposes solutions when applicable.

New Guidelines for Severe Community-acquired Pneumonia.

In 2023, the new European guidelines on severe community-acquired pneumonia, providing clinical practice recommendations for the management of this life-threatening infection, characterized by a high burden of mortality, morbidity, and costs for the society. This review article aims to summarize the principal evidence related to eight different questions covered in the guidelines, by also highlighting the future perspectives for research activity.

ARDS Mortality Prediction Model Using Evolving Clinical Data and Chest Radiograph Analysis.

INTRODUCTION: Within primary ARDS, SARS-CoV-2-associated ARDS (C-ARDS) emerged in late 2019, reaching its peak during the subsequent two years. Recent efforts in ARDS research have concentrated on phenotyping this heterogeneous syndrome to enhance comprehension of its pathophysiology. METHODS AND RESULTS: A retrospective study was conducted on C-ARDS patients from April 2020 to February 2021, encompassing 110 participants with a mean age of 63.2 ± 11.92 (26-83 years). Of these, 61.2% (68) were male, and 25% (17) experienced severe ARDS, resulting in a mortality rate of 47.3% (52). Ventilation settings, arterial blood gases, and chest X-ray (CXR) were evaluated on the first day of invasive mechanical ventilation and between days two and three. CXR images were scrutinized using a convolutional neural network (CNN). A binary logistic regression model for predicting C-ARDS mortality was developed based on the most influential variables: age, PaO2/FiO2 ratio (P/F) on days one and three, CNN-extracted CXR features, and age. Initial performance assessment on test data (23 patients out of the 110) revealed an area under the receiver operating characteristic (ROC) curve of 0.862 with a 95% confidence interval (0.654-0.969). CONCLUSION: Integrating data available in all intensive care units enables the prediction of C-ARDS mortality by utilizing evolving P/F ratios and CXR. This approach can assist in tailoring treatment plans and initiating early discussions to escalate care and extracorporeal life support. Machine learning algorithms for imaging classification can uncover otherwise inaccessible patterns, potentially evolving into another form of ARDS phenotyping. The combined features of these algorithms and clinical variables demonstrate superior performance compared to either element alone.

Practical Lessons on Antimicrobial Therapy for Critically Ill Patients.

Sepsis stands as a formidable global health challenge, with persistently elevated mortality rates in recent decades. Each year, sepsis not only contributes to heightened morbidity but also imposes substantial healthcare costs on survivors. This narrative review aims to highlight the targeted measures that can be instituted to alleviate the incidence and impact of sepsis in intensive care. Here we discuss measures to reduce nosocomial infections and the prevention of equipment and patient colonisation by resilient pathogens. The overarching global crisis of bacterial resistance to newly developed antimicrobial agents intensifies the imperative for antimicrobial stewardship and de-escalation. This urgency has been accentuated in recent years, notably during the COVID-19 pandemic, as high-dose steroids and opportunistic infections presented escalating challenges. Ongoing research into airway colonisation's role in influencing disease outcomes among critically ill patients underscores the importance of tailoring treatments to disease endotypes within heterogeneous populations, which are important lessons for intensivists in training. Looking ahead, the significance of novel antimicrobial delivery systems and drug monitoring is poised to increase. This narrative review delves into the multifaceted barriers and facilitators inherent in effectively treating critically ill patients vulnerable to nosocomial infections. The future trajectory of intensive care medicine hinges on the meticulous implementation of vigilant stewardship programs, robust infection control measures, and the continued exploration of innovative and efficient technological solutions within this demanding healthcare landscape.

Blood-brain barrier disruption and sustained systemic inflammation in individuals with long COVID-associated cognitive impairment.

Vascular disruption has been implicated in coronavirus disease 2019 (COVID-19) pathogenesis and may predispose to the neurological sequelae associated with long COVID, yet it is unclear how blood-brain barrier (BBB) function is affected in these conditions. Here we show that BBB disruption is evident during acute infection and in patients with long COVID with cognitive impairment, commonly referred to as brain fog. Using dynamic contrast-enhanced magnetic resonance imaging, we show BBB disruption in patients with long COVID-associated brain fog. Transcriptomic analysis of peripheral blood mononuclear cells revealed dysregulation of the coagulation system and a dampened adaptive immune response in individuals with brain fog. Accordingly, peripheral blood mononuclear cells showed increased adhesion to human brain endothelial cells in vitro, while exposure of brain endothelial cells to serum from patients with long COVID induced expression of inflammatory markers. Together, our data suggest that sustained systemic inflammation and persistent localized BBB dysfunction is a key feature of long COVID-associated brain fog.