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

Rapid identification of the causative agent of hospital-acquired pneumonia (HAP) will allow an earlier administration of a more appropriate antibiotic and could improve the outcome of these patients. The aim of this study was to develop a rapid protocol to identify the main microorganisms involved in HAP by loop-mediated isothermal amplification (LAMP) directly from respiratory samples. First of all, a rapid procedure (Staphylococcus aureus, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Stenotrophomonas maltophilia and Acinetobacter baumannii was performed with the extracted solution at 65 °C for 30−40 min. Overall, 58 positive BAL and 83 EA/BAS samples were tested. The limits of detection varied according to the microorganism detected. Validation of the LAMP assay with BAL samples showed that the assay was 100% specific and 86.3% sensitive (positive predictive value of 100% and a negative predictive value of 50%) compared with culture. Meanwhile for BAS/EA samples, the assay rendered the following statistical parameters: 100% specificity, 94.6% sensitivity, 100% positive predictive value and 69.2% negative predictive value. The turnaround time including sample preparation and LAMP was circa 1 h. LAMP method may be used to detect the most frequent bacteria causing HAP. It is a simple, cheap, sensitive, specific and rapid assay.

Background: Nosocomial lower respiratory tract infections (nLRTIs) are associated with unfavorable clinical outcomes and significant healthcare costs. nLRTIs include hospital-acquired pneumonia (HAP), ventilator-associated pneumonia (VAP), and other ICU-acquired pneumonia phenotypes. While risk factors for mortality in these infections are critical to guide preventive strategies, it remains unclear whether they vary based on their requirement of invasive mechanical ventilation (IMV) at any point during the hospitalization. Objectives: This study aims to identify risk factors associated with short- and long-term mortality in patients with nLRTIs, considering differences between those requiring IMV and those who do not. Methods: This multinational prospective cohort study included ICU-admitted patients diagnosed with nLRTI from 28 hospitals across 13 countries in Europe and South America between May 2016 and August 2019. Patients were selected based on predefined inclusion and exclusion criteria, and clinical data were collected from medical records. A random forest classifier determined the most optimal clustering strategy when comparing pneumonia site acquisition [ward or intensive care unit (ICU)] versus intensive mechanical ventilation (IMV) necessity at any point during hospitalization to enhance the accuracy and generalizability of the regression models. Results: A total of 1060 patients were included. The random forest classifier identified that the most efficient clustering strategy was based on ventilation necessity. In total, 76.4% of patients [810/1060] received IMV at some point during the hospitalization. Diabetes mellitus was identified to be associated with 28-day mortality in the non-IMV group (OR [IQR]: 2.96 [1.28–6.80], p = 0.01). The 90-day mortality-associated factor was MDRP infection (1.98 [1.13–3.44], p = 0.01). For ventilated patients, chronic liver disease was associated with 28-day mortality (2.38 [1.06–5.31] p = 0.03), with no variable showing statistical and clinical significance at 90 days. Conclusions: The risk factors associated with 28-day mortality differ from those linked to 90-day mortality. Additionally, these factors vary between patients receiving invasive mechanical ventilation and those in the non-invasive ventilation group. This underscores the necessity of tailoring therapeutic objectives and preventive strategies with a personalized approach.