Case Report: Severe Community-Acquired Pneumonia in Réunion Island due to Acinetobacter baumannii.

Acinetobacter baumannii (Ab) is a well-known nosocomial pathogen that has emerged as a cause of community-acquired pneumonia (CAP) in tropical regions. Few global epidemiological studies of CAP-Ab have been published to date, and no data are available on this disease in France. We conducted a retrospective chart review of severe cases of CAP-Ab admitted to intensive care units in Réunion University Hospital between October 2014 and October 2022. Eight severe CAP-Ab cases were reviewed. Median patient age was 56.5 years. Sex ratio (male-to-female) was 3:1. Six cases (75.0%) occurred during the rainy season. Chronic alcohol use and smoking were found in 75.0% and 87.5% of cases, respectively. All patients presented in septic shock and with severe acute respiratory distress syndrome. Seven patients (87.5%) presented in cardiogenic shock, and renal replacement therapy was required for six patients (75.0%). Five cases (62.5%) presented with bacteremic pneumonia. The mortality rate was 62.5%. The median time from hospital admission to death was 3 days. All patients received inappropriate initial antibiotic therapy. Acinetobacter baumannii isolates were all susceptible to ceftazidime, cefepime, piperacillin-tazobactam, ciprofloxacin, gentamicin, and imipenem. Six isolates (75%) were also susceptible to ticarcillin, piperacillin, and cotrimoxazole. Severe CAP-Ab has a fulminant course and high mortality. A typical case is a middle-aged man with smoking and chronic alcohol use living in a tropical region and developing severe CAP during the rainy season. This clinical presentation should prompt administration of antibiotic therapy targeting Ab.

Duration of Invasive Mechanical Ventilation before Veno-Venous ExtraCorporeal Membrane Oxygenation for Covid-19 related Acute Respiratory Distress Syndrome: The experience of a tertiary care center.

Background: Veno-Venous Extracorporeal Membrane Oxygenation (VV-ECMO) is an efficient ventilatory support in patients with refractory Covid-19-related Acute Respiratory Distress Syndrome (ARDS), however the duration of invasive mechanical ventilation (IMV) before ECMO initiation as a contraindication is still controversial. The aim of this study was to investigate the impact of prolonged IMV prior to VV-ECMO in patients suffering from refractory Covid-19-related ARDS. Methods: This single-center retrospective study included all patients treated with VV-ECMO for refractory Covid-19-related ARDS between January 1, 2020 and May 31, 2022. The impact of IMV duration was investigated by comparing patients on VV-ECMO during the 7 days (and 10 days) following IMV with those assisted after 7 days (and 10 days). The primary endpoint was in-hospital mortality. Results: Sixty-four patients were hospitalized in the ICU for Covid-19-related refractory ARDS requiring VV-ECMO. Global in-hospital mortality was 55 %. Median duration of IMV was 4 [2; 8] days before VV-ECMO initiation. There was no significant difference in in-hospital mortality between patients assisted with IMV pre-VV-ECMO for a duration of ≤7 days (≤10 days) and those assisted after 7 days (and 10 days) ((p = 0.59 and p = 0.45). Conclusion: This study suggests that patients assisted with VV-ECMO after prolonged IMV had the same prognosis than those assisted earlier in refractory Covid-19-related ARDS. Therefore, prolonged mechanical ventilation of more than 7-10 days should not contraindicate VV-ECMO support. An individual approach is necessary to balance the risks and benefits of ECMO in this population.

Adaptive resistance to cefiderocol in carbapenem-resistant Acinetobacter baumannii (CRAB): Microbiological and clinical issues.

Objectives: Determining the best available therapy for carbapenem-resistant Acinetobacter baumannii (CRAB) infections is a challenge. Cefiderocol is an attractive alternative drug effective against many resistance mechanisms in Gram-negative bacteria. However, its place in the treatment of Acinetobacter baumannii infections remains unclear and much debated, with contradictory results. Methods: We describe here the case of a 37-year-old man with ventilator-associated bacteraemic CRAB pneumonia in an intensive care unit. He was initially treated with a combination of colistin and tigecycline, and was then switched onto colistin and cefiderocol. We then used a new accessible protocol to test 30 CRAB isolates (OXA-23/OXA-24/OXA-58/NDM-1) for adaptive resistance to cefiderocol (ARC) after exposure to this drug. Results: After clinical failure with the initial combination, we noted a significant clinical improvement in the patient on the second combination, leading to clinical cure. No ARC was detected in the two OXA-23 case-CRAB isolates. All NDM-1 CRAB isolates were resistant to cefiderocol in standard tests; the OXA-23, OXA-24 and OXA-58 CRAB isolates presented 84.2 %, 50 % and 0 % ARC, respectively. Conclusions: ARC is not routinely assessed for CRAB isolates despite frequently being reported in susceptible isolates (69.2 %). Subpopulations displaying ARC may account for treatment failure, but this hypothesis should be treated with caution in the absence of robust clinical data. The two main findings of this work are that (i) cefiderocol monotherapy should probably not be recommended for OXA-23/24 CRAB infections and (ii) the characterisation of carbapenemases in CRAB strains may be informative for clinical decision-making.

A transformer model for cause-specific hazard prediction.

BACKGROUD: Modelling discrete-time cause-specific hazards in the presence of competing events and non-proportional hazards is a challenging task in many domains. Survival analysis in longitudinal cohorts often requires such models; notably when the data is gathered at discrete points in time and the predicted events display complex dynamics. Current models often rely on strong assumptions of proportional hazards, that is rarely verified in practice; or do not handle sequential data in a meaningful way. This study proposes a Transformer architecture for the prediction of cause-specific hazards in discrete-time competing risks. Contrary to Multilayer perceptrons that were already used for this task (DeepHit), the Transformer architecture is especially suited for handling complex relationships in sequential data, having displayed state-of-the-art performance in numerous tasks with few underlying assumptions on the task at hand. RESULTS: Using synthetic datasets of 2000-50,000 patients, we showed that our Transformer model surpassed the CoxPH, PyDTS, and DeepHit models for the prediction of cause-specific hazard, especially when the proportional assumption did not hold. The error along simulated time outlined the ability of our model to anticipate the evolution of cause-specific hazards at later time steps where few events are observed. It was also superior to current models for prediction of dementia and other psychiatric conditions in the English longitudinal study of ageing cohort using the integrated brier score and the time-dependent concordance index. We also displayed the explainability of our model's prediction using the integrated gradients method. CONCLUSIONS: Our model provided state-of-the-art prediction of cause-specific hazards, without adopting prior parametric assumptions on the hazard rates. It outperformed other models in non-proportional hazards settings for both the synthetic dataset and the longitudinal cohort study. We also observed that basic models such as CoxPH were more suited to extremely simple settings than deep learning models. Our model is therefore especially suited for survival analysis on longitudinal cohorts with complex dynamics of the covariate-to-outcome relationship, which are common in clinical practice. The integrated gradients provided the importance scores of input variables, which indicated variables guiding the model in its prediction. This model is ready to be utilized for time-to-event prediction in longitudinal cohorts.

Severe leptospirosis in tropical and non-tropical areas: A comparison of two french, multicentre, retrospective cohorts.

BACKGROUND: Leptospirosis is an anthropozoonosis that occurs worldwide but is more common in tropical regions. Severe forms may require intensive care unit (ICU) admission. Whether the clinical patterns and outcomes differ between tropical and non-tropical regions with similar healthcare systems is unclear. Our objective here was to address this issue by comparing two cohorts of ICU patients with leptospirosis managed in mainland France and in the overseas French department of Réunion, respectively. METHODOLOGY/PRINCIPAL FINDINGS: We compared two retrospective cohorts of patients admitted to intensive care for severe leptospirosis, one from Reunion Island in the Indian Ocean (tropical climate) and the other from metropolitan France (temperate climate). Chi-square and Student's t tests were used for comparisons. After grouping the two cohorts, we also performed multiple correspondence analysis and hierarchical clustering to search for distinct clinical phenotypes. The Réunion and Metropolitan France cohorts comprised 128 and 160 patients respectively. Compared with the Réunion cohort, the metropolitan cohort had a higher mean age (42.5±14.1 vs. 51.4±16.5 years, p<0.001). Severity scores, length of stay and mortality did not differ between the two cohorts. Three phenotypes were identified: hepato-renal leptospirosis (54.5%) characterized by significant hepatic, renal and coagulation failure, with a mortality of 8.3%; moderately severe leptospirosis (38.5%) with less severe organ failure and the lowest mortality rate (1.8%); and very severe leptospirosis (7%) manifested by neurological, respiratory and cardiovascular failure, with a mortality of 30%. CONCLUSIONS/SIGNIFICANCE: The outcomes of severe leptospirosis requiring ICU admission did not differ between tropical and temperate regions with similar healthcare access, practices, and resources, despite some differences in patient characteristics. The identification of three different clinical phenotypes may assist in the early diagnosis and management of severe leptospirosis.

The IMPACT Score: A New Score to Predict the Risk of Early Mortality in Cardiogenic Shock Patients Treated With Venoarterial Extracorporeal Membrane Oxygenation.

OBJECTIVES: Venoarterial extracorporeal membrane oxygenation (VA-ECMO) requires considerable human and financial resources. Few studies have focused on early mortality (ie, occurring within 72 hours after VA-ECMO implantation). The objective of this study was to establish a prognosis score-the IMPACT score (prediction of early mortality associated with VA-ECMO using preimplantation characteristics)-by determining the risk factors associated with early mortality. DESIGN: This was a retrospective and observational study. SETTING: The study was conducted at a University hospital. PARTICIPANTS: This single-center retrospective study included 147 patients treated with VA-ECMO for cardiogenic shock between 2014 and 2021. METHODS: The primary outcome was early mortality (ie, occurring within 72 hours after VA-ECMO implantation). Multivariate logistic regression was performed using a bootstrapping methodology to identify factors independently associated with early mortality. To construct the score, identified variables had points (pts) assigned corresponding to their odds ratio. RESULTS: A total of 147 patients were included in the study. Early mortality (<72 hours) was 26% (38 patients). Four variables were established: cardiac arrest (2 pts), lactate levels (3 pts), platelet count <100 g/L (4 pts), and renal-replacement therapy (5 pts). The IMPACT score had an area under the receiver operating characteristic curve of 0.78 (95% CI 0.86-0.70) to predict early mortality. CONCLUSIONS: In the authors' experience, 26% of patients treated with VA-ECMO presented early mortality. The IMPACT score is a reliable predictor of early mortality and may assist with VA-ECMO initiation decision-making.

Introducing the BlendedICU dataset, the first harmonized, international intensive care dataset.

OBJECTIVE: This study introduces the BlendedICU dataset, a massive dataset of international intensive care data. This dataset aims to facilitate generalizability studies of machine learning models, as well as statistical studies of clinical practices in the intensive care units. METHODS: Four publicly available and patient-level intensive care databases were used as source databases. A unique and customizable preprocessing pipeline extracted clinically relevant patient-related variables from each source database. The variables were then harmonized and standardized to the Observational Medical Outcomes Partnership (OMOP) Common Data Format. Finally, a brief comparison was carried out to explore differences in the source databases. RESULTS: The BlendedICU dataset features 41 timeseries variables as well as the exposure times to 113 active ingredients extracted from the AmsterdamUMCdb, eICU, HiRID, and MIMIC-IV databases. This resulted in a database of more than 309000 intensive care admissions, spanning over 13 years and three countries. We found that data collection, drug exposure, and patient outcomes varied strongly between source databases. CONCLUSION: The variability in data collection, drug exposure, and patient outcomes between the source databases indicated some dissimilarity in patient phenotypes and clinical practices between different intensive care units. This demonstrated the need for generalizability studies of machine learning models. This study provides the clinical data research community with essential data to build efficient and generalizable machine learning models, as well as to explore clinical practices in intensive care units around the world.

Impact of the COVID-19 pandemic on severe non-SARS-CoV-2 community-acquired pneumonia in Reunion Island: a multicenter retrospective observational study, 2016-2021.

The Coronavirus 2019 (COVID-19) pandemic has had a considerable impact on the incidence of severe community-acquired pneumonia (CAP) worldwide. The aim of this study was to assess the early impact of the COVID-19 pandemic in the Reunion Island. This multicenter retrospective observational study was conducted from 2016 to 2021 in the hospitals of Reunion Island. The incidence of severe non-SARS-CoV-2 CAP, microorganisms, characteristics and outcomes of patients hospitalized in intensive care unit were compared between the pre-COVID-19 period (January 1, 2016 to February 29, 2020) and the early COVID-19 period (March 1, 2020 to October 31, 2021). Over the study period, 389 patients developed severe non-SARS-CoV-2 CAP. The incidence of severe non-SARS-CoV-2 CAP significantly decreased between the two periods (9.16 vs. 4.13 cases per 100,000 person-years). The influenza virus was isolated in 43.5% patients with severe non-SARS-CoV-2 CAP in the pre-COVID-19 period and in none of the 60 patients in the early COVID-19 period (P < 0.0001). The only virus that did not decrease was rhinovirus. Streptococcus pneumoniae was the most frequently isolated bacterial microorganism, with no significant difference between the two periods. In Reunion Island, the COVID-19 pandemic led to a significant decrease in the incidence of influenza, which likely explains the observed decrease in the incidence of severe non-SARS-CoV-2 CAP. The pandemic had no impact on the incidence of other viral and bacterial severe non-SARS-CoV-2 CAP. Monitoring influenza incidence is crucial now that COVID-19 control measures have been removed.

Clinical utility of a deep-learning mortality prediction model for cardiac surgery decision making.

OBJECTIVES: The aim of this study using decision curve analysis (DCA) was to evaluate the clinical utility of a deep-learning mortality prediction model for cardiac surgery decision making compared with the European System for Cardiac Operative Risk Evaluation (EuroSCORE) II and to 2 machine-learning models. METHODS: Using data from a French prospective database, this retrospective study evaluated all patients who underwent cardiac surgery in 43 hospital centers between January 2012 and December 2020. A receiver operating characteristic analysis was performed to compare the accuracy of the EuroSCORE II, machine-learning models, and an adapted Tabular Bidirectional Encoder Representations from Transformers deep-learning model in predicting postoperative in-hospital mortality. The clinical utility of these models for cardiac surgery decision making was compared using DCA. RESULTS: Over the study period, 165,640 patients underwent cardiac surgery, with a mean EuroSCORE II of 3.99 ± 6.67%. In the receiver operating characteristic analysis, the area under the curve was significantly greater for the deep-learning model (0.834; 95% confidence interval, 0.831-0.838) than the EuroSCORE II (P < .001), the random forest model (P = .03), and the Extreme Gradient Boosting model (P = .03). In the DCA, the clinical utility of the 3 artificial intelligence models was superior to that of the EuroSCORE II, especially when the threshold probability of death was high (>45%). The deep-learning model showed the greatest advantage over the EuroSCORE II. CONCLUSIONS: The deep-learning model had better predictive accuracy and greater clinical utility than the EuroSCORE II and the 2 machine-learning models. These findings suggest that deep learning with Tabular Bidirectional Encoder Representations from Transformers prediction model could be used in the future as the gold standard for cardiac surgery decision making.

Image augmentation and automated measurement of endotracheal-tube-to-carina distance on chest radiographs in intensive care unit using a deep learning model with external validation.

BACKGROUND: Chest radiographs are routinely performed in intensive care unit (ICU) to confirm the correct position of an endotracheal tube (ETT) relative to the carina. However, their interpretation is often challenging and requires substantial time and expertise. The aim of this study was to propose an externally validated deep learning model with uncertainty quantification and image segmentation for the automated assessment of ETT placement on ICU chest radiographs. METHODS: The CarinaNet model was constructed by applying transfer learning to the RetinaNet model using an internal dataset of ICU chest radiographs. The accuracy of the model in predicting the position of the ETT tip and carina was externally validated using a dataset of 200 images extracted from the MIMIC-CXR database. Uncertainty quantification was performed using the level of confidence in the ETT-carina distance prediction. Segmentation of the ETT was carried out using edge detection and pixel clustering. RESULTS: The interrater agreement was 0.18 cm for the ETT tip position, 0.58 cm for the carina position, and 0.60 cm for the ETT-carina distance. The mean absolute error of the model on the external test set was 0.51 cm for the ETT tip position prediction, 0.61 cm for the carina position prediction, and 0.89 cm for the ETT-carina distance prediction. The assessment of ETT placement was improved by complementing the human interpretation of chest radiographs with the CarinaNet model. CONCLUSIONS: The CarinaNet model is an efficient and generalizable deep learning algorithm for the automated assessment of ETT placement on ICU chest radiographs. Uncertainty quantification can bring the attention of intensivists to chest radiographs that require an experienced human interpretation. Image segmentation provides intensivists with chest radiographs that are quickly interpretable and allows them to immediately assess the validity of model predictions. The CarinaNet model is ready to be evaluated in clinical studies.

A descriptive study of routine laboratory testing in intensive care unit in nearly 140,000 patient stays.

To describe the relationship between the use of laboratory tests and changes in laboratory parameters in ICU patients is necessary to help optimize routine laboratory testing. A retrospective, descriptive study was conducted on the large eICU-Collaborative Research Database. The relationship between the use of routine laboratory tests (chemistry and blood counts) and changes in ten common laboratory parameters was studied. Factors associated with laboratory tests were identified in a multivariate regression analysis using generalized estimating equation Poisson models. The study included 138,734 patient stays, with an ICU mortality of 8.97%. For all parameters, the proportion of patients with at least one test decreased from day 0 to day 1 and then gradually increased until the end of the ICU stay. Paradoxically, the results of almost all tests moved toward normal values, and the daily variation in the results of almost all tests decreased over time. The presence of an arterial catheter or teaching hospitals were independently associated with an increase in the number of laboratory tests performed. The paradox of routine laboratory testing should be further explored by assessing the factors that drive the decision to perform routine laboratory testing in ICU and the impact of such testing on patient.

SARS-CoV-2 with Panton-Valentine leukocidin-producing Staphylococcus aureus healthcare-associated pneumonia in the Indian Ocean.

At this time, the literature reports only one case of superinfection with Panton-Valentine leukocidin (PVL)-producing Staphylococcus aureus in a patient with severe acute respiratory distress syndrome secondary to coronavirus 2 (SARS-CoV-2) pneumonia. Here we report the first two cases of PVL-producing S. aureus healthcare-associated pneumonia in patients hospitalized for SARS-CoV-2 pneumonia in the Indian Ocean region. The two isolated strains of S. aureus were found to belong to the ST152/t355 clone, a known PVL-producing S. aureus clone that circulates in Africa and is responsible for infections imported into Europe. Our two cases reinforce the hypothesis that SARS-CoV-2 infection favors the occurrence of PVL-producing S. aureus pneumonia. Production of PVL should be searched in patients returning from the Indian Ocean region who present with severe SARS-CoV-2 pneumonia complicated by superinfection with S. aureus even in the case of late onset healthcare-associated pneumonia.

Prognosis of patients with acute respiratory failure due to the SARS-CoV-2 501Y.V2 variant: a multicenter retrospective matched cohort study.

The aim of this study was to compare the prognosis of patients with acute respiratory failure (ARF) due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant 501Y.V2 to that of patients with ARF due to the original strain. This retrospective matched cohort study included all consecutive patients who were hospitalized for ARF due to SARS-CoV-2 in Reunion Island University Hospital between March 2020 and March 2021. Twenty-eight in hospital mortality was evaluated before and after matching. A total of 218 patients with ARF due to SARS-CoV-2 were enrolled in the study. Of these, 83 (38.1%) were infected with the 501Y.V2 variant. During intensive care unit stay, 104 (47.7%) patients received invasive mechanical ventilation and 20 (9.2%) patients were supported by venovenous extracorporeal membrane oxygenation. Patients infected with the 501Y.V2 variant were younger (58 [51-68] vs. 67 [56-74] years old, P = 0.003), had less hypertension (54.2% vs 68.1%, P = 0.04), and had less chronic kidney disease (13.3% vs. 31.9%, P = 0.002) than patients infected with the original strain. After controlling for confounding variables (62 matched patients in each group), 28-day mortality was higher in the group of patients infected with the 501Y.V2 variant (30.6%) than in the group of patients infected with the original strain (19.4%, P = 0.04). In Reunion Island, where SARS-CoV-2 incidence remained low until February 2021 and the health care system was never saturated, mortality was higher in patients with ARF infected with the 501Y.V2 variant than in patients infected with the original strain.

Severe community-acquired pneumonia in Reunion Island: Epidemiological, clinical, and microbiological characteristics, 2016-2018.

PURPOSE: No data are available on severe community-acquired pneumonia (CAP) in the French overseas department of Reunion Island. This is unfortunate as the microorganisms responsible for the disease are likely to differ from those in temperate regions due to a tropical climate and proximity to other islands of the Indian Ocean region. The aim of this study was to assess the epidemiological, clinical, prognosis, and microbiological characteristics of patients with severe CAP in Reunion Island. MATERIALS AND METHODS: This retrospective study evaluated all patients with CAP aged >18 years and hospitalized in one of the two intensive care units of Reunion Island between 2016 and 2018. Microorganisms were identified by culture from blood and respiratory samples, multiplex polymerase chain reaction from respiratory samples, urinary antigen tests, and serology. RESULTS: Over the study period, 573 cases of severe CAP were recorded, with a mean incidence of 22 per 100,000 person-years. The most frequently isolated microorganism was influenza (21.9%) followed by Streptococcus pneumoniae (12%). The influenza virus was detected in affected patients all year round. Twenty-four patients with severe CAP came from another island of the Indian Ocean region (4.2%), mainly Madagascar (>50%). Two of these patients presented with melioidosis and 4 were infected with Acinetobacter spp. CONCLUSIONS: Our findings have major implications for the management of severe CAP in tropical regions. The most frequently isolated microorganism in patients with severe CAP in Reunion Island is influenza followed by S. pneumoniae. Physicians should be aware that influenza is the main cause of severe CAP in patients living in or returning from Reunion Island, where this virus circulates all year round.

Extracorporeal Membrane Oxygenation for Respiratory Failure Related to COVID-19: A Nationwide Cohort Study.

BACKGROUND: Despite expanding use, knowledge on extracorporeal membrane oxygenation support during the COVID-19 pandemic remains limited. The objective was to report characteristics, management, and outcomes of patients receiving extracorporeal membrane oxygenation with a diagnosis of COVID-19 in France and to identify pre-extracorporeal membrane oxygenation factors associated with in-hospital mortality. A hypothesis of similar mortality rates and risk factors for COVID-19 and non-COVID-19 patients on venovenous extracorporeal membrane oxygenation was made. METHODS: The Extracorporeal Membrane Oxygenation for Respiratory Failure and/or Heart failure related to Severe Acute Respiratory Syndrome-Coronavirus 2 (ECMOSARS) registry included COVID-19 patients supported by extracorporeal membrane oxygenation in France. This study analyzed patients included in this registry up to October 25, 2020, and supported by venovenous extracorporeal membrane oxygenation for respiratory failure with a minimum follow-up of 28 days after cannulation. The primary outcome was in-hospital mortality. Risk factors for in-hospital mortality were analyzed. RESULTS: Among 494 extracorporeal membrane oxygenation patients included in the registry, 429 were initially supported by venovenous extracorporeal membrane oxygenation and followed for at least 28 days. The median (interquartile range) age was 54 yr (46 to 60 yr), and 338 of 429 (79%) were men. Management before extracorporeal membrane oxygenation cannulation included prone positioning for 411 of 429 (96%), neuromuscular blockage for 419 of 427 (98%), and NO for 161 of 401 (40%). A total of 192 of 429 (45%) patients were cannulated by a mobile extracorporeal membrane oxygenation unit. In-hospital mortality was 219 of 429 (51%), with a median follow-up of 49 days (33 to 70 days). Among pre-extracorporeal membrane oxygenation modifiable exposure variables, neuromuscular blockage use (hazard ratio, 0.286; 95% CI, 0.101 to 0.81) and duration of ventilation (more than 7 days compared to less than 2 days; hazard ratio, 1.74; 95% CI, 1.07 to 2.83) were independently associated with in-hospital mortality. Both age (per 10-yr increase; hazard ratio, 1.27; 95% CI, 1.07 to 1.50) and total bilirubin at cannulation (6.0 mg/dl or more compared to less than 1.2 mg/dl; hazard ratio, 2.65; 95% CI, 1.09 to 6.5) were confounders significantly associated with in-hospital mortality. CONCLUSIONS: In-hospital mortality was higher than recently reported, but nearly half of the patients survived. A high proportion of patients were cannulated by a mobile extracorporeal membrane oxygenation unit. Several factors associated with mortality were identified. Venovenous extracorporeal membrane oxygenation support should be considered early within the first week of mechanical ventilation initiation.

COVID-19 cluster in vaccinated healthcare workers in Mayotte.

We report a significant cluster of SARS-CoV-2 (B.1.617.2 variant) among young healthcare workers (HCW) (median age of 27years) living in the Mamoudzou interns apartment complex, belonging to the Hospital Center in Mayotte. Among them, 18 developed SARS-CoV-2 infection (62.1%) and all were symptomatic. The infection rate was higher for people who had had a second dose more than 6 months before than for those who had had a second dose less than 6 months before (P=0.05). This epidemic had no individual consequence, but the hospital functioning in Mayotte was significant impacted. This report reinforces the need for a third dose of vaccine among HCWs, in addition to non-pharmaceutical measures.

Effect of Body Mass Index on the Clinical Outcomes of Adult Patients Treated With Venoarterial ECMO for Cardiogenic Shock.

OBJECTIVE: Current guidelines consider obesity to be a relative contraindication to venoarterial extracorporeal membrane oxygenation (VA-ECMO) for refractory cardiogenic shock. The authors investigated the effect of body mass index (BMI) on clinical outcomes in patients treated with VA-ECMO for cardiogenic shock. DESIGN: This was a retrospective and observational study. SETTING: University hospital. PARTICIPANTS: The study comprised 150 adult patients who underwent VA-ECMO for cardiogenic shock. MEASUREMENTS AND MAIN RESULTS: The primary outcome was intensive care unit (ICU) mortality. Of the 150 included patients, 10 were underweight (BMI < 18.5 kg/m²), 62 were normal weight (BMI = 18.5-24.9 kg/m²), 34 were overweight (BMI = 25.0-29.9 kg/m²), 34 were obese class I (BMI = 30.0-34.9 kg/m²), and 10 were obese class II (BMI = 35.0-39.9 kg/m²). All-cause ICU mortality was 62% (underweight, 70%; normal weight, 53%; overweight, 65%; class I obese, 71%; class II obese, 70%). After multivariate logistic regression, BMI was not associated with ICU mortality (adjusted odds ratio [aOR] 0.99 [0.92-1.07], p = 0.8). Analysis by BMI category showed unfavorable mortality trends in underweight patients (aOR 3.58 [0.82-19.6], p = 0.11) and class I obese patients (aOR 2.39 [0.95-6.38], p = 0.07). No statistically significant differences were found among BMI categories in the incidences of complications. CONCLUSION: The results suggested that BMI alone should not be considered an exclusion criterion for VA-ECMO. The unfavorable trend observed in underweight patients could be the result of malnutrition.

Effect of antibiotic therapy on the prognosis of ventilator-associated pneumonia caused by Stenotrophomonas maltophilia.

BACKGROUND: Ventilator-associated pneumonia (VAP) caused by Stenotrophomonas maltophilia is poorly described in the literature. However, it has been shown to be associated with increased morbidity and mortality. Probabilistic antibiotic therapy against S. maltophilia is often ineffective as this pathogen is resistant to many antibiotics. There is no consensus at present on the best therapeutic strategy to adopt (class of antibiotics, antibiotic combination, dosage, treatment duration). The aim of this study was to evaluate the effect of antibiotic therapy strategy on the prognosis of patients with VAP caused by S. maltophilia. RESULTS: This retrospective study evaluated all consecutive patients who developed VAP caused by S. maltophilia between 2010 and 2018 while hospitalized in the intensive care unit (ICU) of a French university hospital in Reunion Island, in the Indian Ocean region. A total of 130 patients with a median Simplified Acute Physiology Score II of 58 [43-73] had VAP caused by S. maltophilia after a median duration of mechanical ventilation of 12 [5-18] days. Ventilator-associated pneumonia was polymicrobial in 44.6% of cases, and ICU mortality was 50.0%. After multivariate Cox regression analysis, the factors associated with increased ICU mortality were older age (hazard ratio (HR): 1.03; 95% CI 1.01-1.04, p = 0.001) and high Sequential Organ Failure Assessment score on the day of VAP onset (HR: 1.08; 95% CI 1.03-1.14, p = 0.002). Appropriate antibiotic therapy, and in particular trimethoprim-sulfamethoxazole, was associated with decreased ICU mortality (HR: 0.42; 95% CI 0.24-0.74, p = 0.003) and decreased hospital mortality (HR: 0.47; 95% CI 0.28-0.79, p = 0.04). Time to start of appropriate antibiotic therapy, combination therapy, and duration of appropriate antibiotic therapy had no effect on ICU mortality (p > 0.5). CONCLUSION: In our study, appropriate antibiotic therapy, and in particular trimethoprim-sulfamethoxazole, was associated with decreased ICU and hospital mortality in patients with VAP caused by S. maltophilia.

Nosocomial cluster of carbapenemase-producing Enterobacter cloacae in an intensive care unit dedicated COVID-19.

Concomitant prevention of SARS-CoV-2 and extensively drug-resistant bacteria transmission is a difficult challenge in intensive care units dedicated to COVID-19 patients. We report a nosocomial cluster of four patients carrying NDM-1 plasmid-encoded carbapenemase-producing Enterobacter cloacae. Two main factors may have contributed to cross-transmission: misuse of gloves and absence of change of personal protective equipment, in the context of COVID-19-associated shortage. This work highlights the importance of maintaining infection control measures to prevent CPE cross-transmission despite the difficult context and that this type of outbreak can potentially involve several species of Enterobacterales.