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.

The development and implementation of a low-cost mechanical ventilator in a low-middle-income country during the COVID-19 pandemic: The Unisabana-HERONS.

Background: The COVID-19 pandemic in Latin America generated the need to develop low-cost, fast-manufacturing mechanical ventilators. The Universidad de La Sabana and the Fundacion Neumologica Colombiana designed and manufactured the Unisabana-HERONS (USH) ventilator. Here, we present the preclinical and clinical study results to evaluate its effectiveness and safety characteristics in an animal model (Yorkshire Sow) and five patients with acute respiratory failure receiving mechanical ventilatory support for 24 h. Methods: The effectiveness and safety outcomes included maintaining arterial blood gases and pulse oximetry saturation (SpO2), respiratory pressures and volumes (during continuous monitoring) in the range of ARDS and lung-protective strategy goals, and the occurrence of barotrauma. A significance level of 0.05 was used for statistical tests. This clinical trial was registered on Clinicaltrials.gov (NCT04497623) and approved by the ethics committee. Results: Among patients treated with the Unisabana-HERONS, the most frequent causes of acute respiratory failure were pneumonia in 3/5 (60 %) and ARDS in 2/5 (40 %). During the treatment, the ventilatory parameters related to lung protection protocols were kept within the safety range, and vital signs and blood gas were stable. The percentage of time that the respiratory pressures or volumes were out of safety range were plateau pressure >30 cm H2O: 0.00 %; driving pressure >15 cm H2O: 0.06 %; mechanical power >15 J/min: 0.00 %; and Tidal volume >8 mL/kg: 0.00 %. There were no adverse events related to the ventilator. The usability questionnaire retrieved a median score for all items between 9 and 10 (best score: 10), indicating great ease of use. Conclusion: The Unisabana-HERONS ventilator effectively provided adequate gas exchange and maintained the ventilatory parameters in the range of lung protection strategies in humans and an animal model. Furthermore, it is straightforward to use and is a low-cost medical device.

The potential impact of PCV-13, PCV-15 and PCV-20 vaccines in Colombia.

PURPOSE: To provide information about which pneumococcal vaccine could have greater coverage in Colombia. METHODS: This is a retrospective analysis of patients diagnosed with invasive pneumococcal disease (IPD) between 2015 and 2019 in Bogotá, Colombia. We compared the theoretical serotype coverage of the available anti-pneumococcal vaccines (i.e., PCV-10, PCV-10 SII, PCV-13, PCV-15, PCV-20, PCV-21, PCV24, PPSV-23) and the non-vaccine-covered serotypes stratified by age. RESULTS: 690 IPD cases were included. In children ≤5 y/o, of the approved vaccines PCV-20 showed the most theoretical protection (71.3 % [149/209]), while in adults aged 18-64 y/o was PCV-20 (61.8 % [164/265]), and in those ≥65 y/o was PPSV-23 (58.1 % [100/172]) followed by PCV-20 (55.2 % [95/172]). The non-covered serotypes represented one-third of the cohort (33.9 % [234/690]), being 6C (20.5 % [48/234]), 15A (12.8 % [30/234]), and 23A (11.5 % [27/234]) the most prevalent. CONCLUSION: Introducing PCV-20 for children and PCV-20 along with a PPSV-23 booster in adults may reduce IPD frequency in all ages in Colombia. The inclusion of non-covered serotypes is required for future vaccines.

Major adverse cardiovascular events (MACE) in patients with severe COVID-19 registered in the ISARIC WHO clinical characterization protocol: A prospective, multinational, observational study.

PURPOSE: To determine its cumulative incidence, identify the risk factors associated with Major Adverse Cardiovascular Events (MACE) development, and its impact clinical outcomes. MATERIALS AND METHODS: This multinational, multicentre, prospective cohort study from the ISARIC database. We used bivariate and multivariate logistic regressions to explore the risk factors related to MACE development and determine its impact on 28-day and 90-day mortality. RESULTS: 49,479 patients were included. Most were male 63.5% (31,441/49,479) and from high-income countries (84.4% [42,774/49,479]); however, >6000 patients were registered in low-and-middle-income countries. MACE cumulative incidence during their hospital stay was 17.8% (8829/49,479). The main risk factors independently associated with the development of MACE were older age, chronic kidney disease or cardiovascular disease, smoking history, and requirement of vasopressors or invasive mechanical ventilation at admission. The overall 28-day and 90-day mortality were higher among patients who developed MACE than those who did not (63.1% [5573/8829] vs. 35.6% [14,487/40,650] p < 0.001; 69.9% [6169/8829] vs. 37.8% [15,372/40,650] p < 0.001, respectively). After adjusting for confounders, MACE remained independently associated with higher 28-day and 90-day mortality (Odds Ratio [95% CI], 1.36 [1.33-1.39];1.47 [1.43-1.50], respectively). CONCLUSIONS: Patients with severe COVID-19 frequently develop MACE, which is independently associated with worse clinical outcomes.

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.

Prevalence, incidence, and severity associated with viral respiratory tract infections in Colombian adults before the COVID-19 pandemic.

BACKGROUND: Acute respiratory illness (ARI) remains the leading cause of global morbidity. Its primary etiology is viral; nevertheless, viral pathogen identification is limited. Clinical information about Latin America's viral etiology, outcomes, and severity is unknown. This study aims to identify the clinical burden of respiratory viral infections, severity, and adult outcomes. METHODS: This multicentric, population-based study was conducted through the Health Institute of Bogotá, Colombia, including adult patients diagnosed with ARI between 2013 and 2019. Data collection followed ARI public health surveillance program. Incidence, etiological pathogens, and mortality were calculated. RESULTS: A total of 2304 patients were included in the study. ARI was most frequently reported in 2018 (23.3% [538/2304]). Incidence varies between years, maintaining a range between 3.5 and 8.4. The most frequent clinical diagnosis was pneumonia in 59.1%. Etiological viral detection was obtained in 21.5% of patients [495/2304], principally by Influenza A. Mortality was 21.8%, and ICU admission was 7.3%. The type of event did not predict the causative pathogen, disease severity, or mortality. CONCLUSIONS: ARI is a leading cause of morbidity and mortality in Colombia. ARI incidence varies per year and is caused mainly by Influenza A. The classification used in the surveillance program does not correlate with viral etiology, disease severity, and mortality.

Respiratory support in patients with severe COVID-19 in the International Severe Acute Respiratory and Emerging Infection (ISARIC) COVID-19 study: a prospective, multinational, observational study.

BACKGROUND: Up to 30% of hospitalised patients with COVID-19 require advanced respiratory support, including high-flow nasal cannulas (HFNC), non-invasive mechanical ventilation (NIV), or invasive mechanical ventilation (IMV). We aimed to describe the clinical characteristics, outcomes and risk factors for failing non-invasive respiratory support in patients treated with severe COVID-19 during the first two years of the pandemic in high-income countries (HICs) and low middle-income countries (LMICs). METHODS: This is a multinational, multicentre, prospective cohort study embedded in the ISARIC-WHO COVID-19 Clinical Characterisation Protocol. Patients with laboratory-confirmed SARS-CoV-2 infection who required hospital admission were recruited prospectively. Patients treated with HFNC, NIV, or IMV within the first 24 h of hospital admission were included in this study. Descriptive statistics, random forest, and logistic regression analyses were used to describe clinical characteristics and compare clinical outcomes among patients treated with the different types of advanced respiratory support. RESULTS: A total of 66,565 patients were included in this study. Overall, 82.6% of patients were treated in HIC, and 40.6% were admitted to the hospital during the first pandemic wave. During the first 24 h after hospital admission, patients in HICs were more frequently treated with HFNC (48.0%), followed by NIV (38.6%) and IMV (13.4%). In contrast, patients admitted in lower- and middle-income countries (LMICs) were less frequently treated with HFNC (16.1%) and the majority received IMV (59.1%). The failure rate of non-invasive respiratory support (i.e. HFNC or NIV) was 15.5%, of which 71.2% were from HIC and 28.8% from LMIC. The variables most strongly associated with non-invasive ventilation failure, defined as progression to IMV, were high leukocyte counts at hospital admission (OR [95%CI]; 5.86 [4.83-7.10]), treatment in an LMIC (OR [95%CI]; 2.04 [1.97-2.11]), and tachypnoea at hospital admission (OR [95%CI]; 1.16 [1.14-1.18]). Patients who failed HFNC/NIV had a higher 28-day fatality ratio (OR [95%CI]; 1.27 [1.25-1.30]). CONCLUSIONS: In the present international cohort, the most frequently used advanced respiratory support was the HFNC. However, IMV was used more often in LMIC. Higher leucocyte count, tachypnoea, and treatment in LMIC were risk factors for HFNC/NIV failure. HFNC/NIV failure was related to worse clinical outcomes, such as 28-day mortality. Trial registration This is a prospective observational study; therefore, no health care interventions were applied to participants, and trial registration is not applicable.

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19.

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use.

A novel model to predict severe COVID-19 and mortality using an artificial intelligence algorithm to interpret chest radiographs and clinical variables.

Background: Patients with coronavirus disease 2019 (COVID-19) could develop severe disease requiring admission to the intensive care unit (ICU). This article presents a novel method that predicts whether a patient will need admission to the ICU and assesses the risk of in-hospital mortality by training a deep-learning model that combines a set of clinical variables and features in chest radiographs. Methods: This was a prospective diagnostic test study. Patients with confirmed severe acute respiratory syndrome coronavirus 2 infection between March 2020 and January 2021 were included. This study was designed to build predictive models obtained by training convolutional neural networks for chest radiograph images using an artificial intelligence (AI) tool and a random forest analysis to identify critical clinical variables. Then, both architectures were connected and fine-tuned to provide combined models. Results: 2552 patients were included in the clinical cohort. The variables independently associated with ICU admission were age, fraction of inspired oxygen (F iO2 ) on admission, dyspnoea on admission and obesity. Moreover, the variables associated with hospital mortality were age, F iO2 on admission and dyspnoea. When implementing the AI model to interpret the chest radiographs and the clinical variables identified by random forest, we developed a model that accurately predicts ICU admission (area under the curve (AUC) 0.92±0.04) and hospital mortality (AUC 0.81±0.06) in patients with confirmed COVID-19. Conclusions: This automated chest radiograph interpretation algorithm, along with clinical variables, is a reliable alternative to identify patients at risk of developing severe COVID-19 who might require admission to the ICU.

Dexamethasone as risk-factor for ICU-acquired respiratory tract infections in severe COVID-19.

PURPOSE: Dexamethasone is the only drug that has consistently reduced mortality in patients with COVID-19, especially in patients needing oxygen or invasive mechanical ventilation. However, there is a growing concern about the relation of dexamethasone with the unprecedented rates of ICU-acquired respiratory tract infections (ICU-RTI) observed in patients with severe COVID-19. METHODS: This was a multicenter, prospective cohort study; conducted in ten countries in Latin America and Europe. We included patients older than 18 with confirmed SARS-CoV-2 requiring ICU admission. A multivariate logistic regression and propensity score matching (PSM) analysis was conducted to determine the relation between dexamethasone treatment and ICU-RTI. RESULTS: A total of 3777 patients were included. 2065 (54.7%) were treated with dexamethasone within the first 24 h of admission. After performing the PSM, patients treated with dexamethasone showed significantly higher proportions of VAP (282/1652 [17.1%] Vs. 218/1652 [13.2%], p = 0.014). Also, dexamethasone treatment was identified as an adjusted risk factor of ICU-RTI in the multivariate logistic regression model (OR 1.64; 95%CI: 1.37-1.97; p < 0.001). CONCLUSION: Patients treated with dexamethasone for severe COVID-19 had a higher risk of developing ICU-acquired respiratory tract infections after adjusting for days of invasive mechanical ventilation and ICU length of stay, suggesting a cautious use of this treatment.

Clinical characteristics, risk factors and outcomes in patients with severe COVID-19 registered in the International Severe Acute Respiratory and Emerging Infection Consortium WHO clinical characterisation protocol: a prospective, multinational, multicentre, observational study.

Due to the large number of patients with severe coronavirus disease 2019 (COVID-19), many were treated outside the traditional walls of the intensive care unit (ICU), and in many cases, by personnel who were not trained in critical care. The clinical characteristics and the relative impact of caring for severe COVID-19 patients outside the ICU is unknown. This was a multinational, multicentre, prospective cohort study embedded in the International Severe Acute Respiratory and Emerging Infection Consortium World Health Organization COVID-19 platform. Severe COVID-19 patients were identified as those admitted to an ICU and/or those treated with one of the following treatments: invasive or noninvasive mechanical ventilation, high-flow nasal cannula, inotropes or vasopressors. A logistic generalised additive model was used to compare clinical outcomes among patients admitted or not to the ICU. A total of 40 440 patients from 43 countries and six continents were included in this analysis. Severe COVID-19 patients were frequently male (62.9%), older adults (median (interquartile range (IQR), 67 (55-78) years), and with at least one comorbidity (63.2%). The overall median (IQR) length of hospital stay was 10 (5-19) days and was longer in patients admitted to an ICU than in those who were cared for outside the ICU (12 (6-23) days versus 8 (4-15) days, p<0.0001). The 28-day fatality ratio was lower in ICU-admitted patients (30.7% (5797 out of 18 831) versus 39.0% (7532 out of 19 295), p<0.0001). Patients admitted to an ICU had a significantly lower probability of death than those who were not (adjusted OR 0.70, 95% CI 0.65-0.75; p<0.0001). Patients with severe COVID-19 admitted to an ICU had significantly lower 28-day fatality ratio than those cared for outside an ICU.