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.

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.

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.

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.

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.

Differential diagnoses of severe COVID-19 in tropical areas: the experience of Reunion Island.

OBJECTIVE: To identify the differential diagnoses of severe COVID-19 and the distinguishing characteristics of critically ill COVID-19 patients in Reunion Island to help improve the triage and management of patients in this tropical setting. METHODS: This retrospective observational study was conducted from 11 March to 4 May 2020 in the only intensive care unit (ICU) authorised to manage COVID-19 patients in Reunion Island, a French overseas department located in the Indian Ocean region. All patients with unknown COVID-19 status were tested by polymerase chain reaction (PCR) on ICU admission; those who tested negative were transferred to the COVID-19-free area of the ICU. RESULTS: Over the study period, 99 patients were admitted to our ICU. A total of 33 patients were hospitalised in the COVID-19 isolation ward, of whom 11 were positive for COVID-19. The main differential diagnoses of severe COVID-19 were as follows: community-acquired pneumonia, dengue, leptospirosis causing intra-alveolar haemorrhage and cardiogenic pulmonary oedema. The median age of COVID-19-positive patients was higher than that of COVID-19-negative patients (71 [58-74] vs. 54 [46-63.5] years, P = 0.045). No distinguishing clinical, biological or radiological characteristics were found between the two groups of patients. All COVID-19-positive patients had recently travelled or been in contact with a recent traveller. CONCLUSIONS: In Reunion Island, dengue and leptospirosis are key differential diagnoses of severe COVID-19, and travel is the only distinguishing characteristic of COVID-19-positive patients. Our findings apply only to the particular context of Reunion Island at this time of the epidemic.

Severe bilateral pleuropneumonia caused by Legionella sainthelensi: a case report.

BACKGROUND: Legionella spp. are ubiquitous freshwater bacteria responsible for rare but potentially severe cases of Legionnaires' disease (LD). Legionella sainthelensi is a non-pneumophila Legionella species that was first isolated in 1980 from water near Mt. St-Helens (USA). Although rare cases of LD caused by L. sainthelensi have been reported, very little data is available on this pathogen. CASE PRESENTATION: We describe the first documented case of severe bilateral pleuropneumonia caused by L. sainthelensi. The patient was a 35-year-old woman with Sharp's syndrome treated with long-term hydroxychloroquine and corticosteroids who was hospitalized for an infectious illness in a university hospital in Reunion Island (France). The patient's clinical presentation was complicated at first (bilateral pneumonia, multiloculated pleural effusion, then bronchopleural fistula) but her clinical condition eventually improved with the reintroduction of macrolides (spiramycin) in intensive care unit. Etiological diagnosis was confirmed by PCR syndromic assay and culture on bronchoalveolar lavage. CONCLUSIONS: To date, only 14 documented cases of L. sainthelensi infection have been described worldwide. This pathogen is difficult to identify because it is not or poorly detected by urinary antigen and molecular methods (like PCR syndromic assays that primarily target L. pneumophila and that have only recently been deployed in microbiology laboratories). Pneumonia caused by L. sainthelensi is likely underdiagnosed as a result. Clinicians should consider the possibility of non-pneumophila Legionella infection in patients with a compatible clinical presentation when microbiological diagnostic tools targeted L. pneumophila tested negative.

Postpandemic Influenza Mortality of Venovenous Extracorporeal Membrane Oxygenation-Treated Patients in Reunion Island: A Retrospective Single Center Study.

OBJECTIVES: The aim of the present study was to assess the post-pandemic mortality of influenza in patients receiving venovenous extracorporeal membrane oxygenation (VV-ECMO) in Reunion Island, France, by comparing the incidence with other patients undergoing VV-ECMO. DESIGN: Retrospective, descriptive, and single-center cohort study. The primary outcome was the standardized mortality ratio for influenza based on the quartiles of the Respiratory Extracorporeal Membrane Oxygenation Survival Prediction score (RESP Score) in the reference population of patients undergoing VV-ECMO. SETTING: Intensive care unit (ICU), Felix Guyon Hospital, University Teaching Hospital of La Réunion, La Réunion, France. PARTICIPANTS: Consecutive patients on ECMO with positive polymerase chain reaction for influenza. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: One hundred twenty-seven consecutive patients were hospitalized in the ICU with a positive influenza polymerase chain reaction from January 2013 to December 2017. Twenty-four influenza patients underwent ECMO including 18 patients with VV-ECMO. During this period, 72 patients requiring VV-ECMO were hospitalized in the ICU. The overall mortality rate of influenza patients on VV-ECMO was 61% versus 46% for non-influenza patients. The standardized mortality ratio per quartile of RESP Score was 1.28 (95% confidence interval 0.61-2.35). CONCLUSIONS: In Reunion, the mortality of patients undergoing VV-ECMO for severe influenza is not lower than the expected mortality of all patients undergoing VV-ECMO.

Clinical, Radiological, and Microbiological Characteristics of Mycobacterium simiae Infection in 97 Patients.

Mycobacterium simiae is a rare species of slow-growing nontuberculous mycobacteria (NTM). From 2002 to 2017, we conducted a retrospective study that included all patients with NTM-positive respiratory samples detected in two university hospitals of the French overseas department of Reunion Island. We recorded the prevalence of M. simiae in this cohort, as well as the clinical, radiological, and microbiological features of patients with at least 1 sample positive for M. simiae In our cohort, 97 patients (15.1%) were positive for M. simiae Twenty-one patients (21.6%) met the American Thoracic Society (ATS) criteria for infection. M. simiae infection was associated with bronchiectasis, micronodular lesions, and weight loss. Antibiotic susceptibility testing was performed for 60 patients, and the isolates were found to have low susceptibility to antibiotics, except for amikacin, fluoroquinolones, and clarithromycin. Treatment failed for 4 of the 8 patients treated for M. simiae infection. Here, we describe a specific cluster corresponding to a large cohort of patients with M. simiae, a rare nontuberculous mycobacterium associated with low pathogenicity and poor susceptibility to antibiotics.

Leptospirosis in ICU: A Retrospective Study of 134 Consecutive Admissions.

OBJECTIVES: Leptospirosis causes reversible multiple organ failure, and its mortality remains high. The aim of this study was to determine the mortality rate of leptospirosis in an ICU offering all types of organ support available nowadays and to compare it with mortality in bacterial sepsis. DESIGN: Retrospective, descriptive, and single-center cohort study. SETTINGS: The largest ICU of Reunion Island (Indian Ocean) in a teaching hospital. PATIENTS: Consecutive patients hospitalized in ICU for leptospirosis from January 2004 to January 2015. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We report 134 cases of patients with leptospirosis hospitalized in ICU. The median age was 40 years (interquartile range, 30-52 yr), with a Simplified Acute Physiology Score II of 38 (27-50) and a Sequential Organ Failure Assessment score of 10 (8-12). Forty-one patients (31%) required mechanical ventilation and 76 (56%) required renal replacement therapy. The door-to-renal replacement therapy time was 0 (0-1) day after admission with a median urea of 25 mmol/L (17-32 mmol/L). Five patients required extracorporeal membrane oxygenation. The mortality rate was 6.0% (95% CI, 2.6-11.4). Among patients hospitalized for sepsis, the standardized mortality ratio of patients with leptospirosis with regards to Simplified Acute Physiology Score II was dramatically low: 0.40 (95% CI, 0.17 - 0.79). CONCLUSIONS: The mortality of severe leptospirosis is lower than for other bacterial infection, provided modern resuscitation techniques are available. Prompt organ support ensures very low mortality rates despite high severity scores.

First case of pleural empyema and pulmonary abscess caused by Eggerthia catenaformis.

Few data are available on the anaerobic bacterium Eggerthia catenaformis. Here we report the first clinical case of a patient with sepsis caused by pulmonary infection with E. catenaformis, and present the minimal inhibitory concentrations of different antimicrobial agents.

Postoperative pneumonia following cardiac surgery in non-ventilated patients versus mechanically ventilated patients: is there any difference?

INTRODUCTION: No studies have compared ventilator-associated pneumonia (VAP) and non-VAP following cardiac surgery (CS). The aim of this study was to assess the incidence, clinical and microbiologic features, treatment characteristics and prognosis of postoperative pneumonia following CS with a special focus on non-VAP. METHODS: This was a retrospective cohort study based on a prospectively collected database. We compared cases of non-VAP and VAP following CS observed between January 2005 and December 2012. Statistical analysis consisted of bivariate and multivariate analysis. RESULTS: A total of 257 (3.5%) of 7,439 consecutive CS patients developed postoperative pneumonia, including 120 (47%) cases of non-VAP. Patients with VAP had more frequent history of congestive heart failure (31% vs. 17%, P = 0.006) and longer duration of cardiopulmonary bypass (105 vs 76 min, P < 0.0001), than patients with non-VAP. No significant differences were observed between the 2 groups in terms of the types of microorganisms isolated with high proportions of Enterobacteriaceae (35%), Pseudomonas aeruginosa (20.2%) and Haemophilus spp (20.2%), except for a lower proportion of Methicillin-susceptible S. aureus in the non-VAP group (3.2% vs 7.9%, P = 0.03). In the intensive care unit, patients with non-VAP had lower sequential organ failure assessment scores than patients with VAP (8 ± 3 versus 9 ± 3, P = 0.004). On multivariate analysis, in-hospital mortality was similar in both groups (32% in the non-VAP group and 42% in the VAP group, adjusted Odds Ratio (aOR): 1.4; 95% confidence intervals (CI): 0.7-2.5; P = 0.34) and appropriate empiric antibiotic therapy was associated with a reduction of in-hospital mortality (aOR: 0.4; 95% CI: 0.2-1; P = 0.05). Piperacillin/tazobactam or imipenem monotherapy constituted appropriate empiric therapy in the two groups, with values reaching 93% and 95% with no differences between VAP and non-VAP cases. CONCLUSIONS: Intensive care patients with VAP are more severely ill than non-VAP patients following CS. Nevertheless, patients with non-VAP and VAP following CS have similar outcomes. This study suggests that the empiric antibiotic regimen in patients with pneumonia following CS should include at least a broad-spectrum antibiotic targeting non-fermenting Gram-negative bacilli, regardless of the type of pneumonia, and targeting S. aureus in VAP patients.

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.

Marfan's syndrome during pregnancy: anesthetic management of delivery in 16 consecutive patients.

BACKGROUND: Marfan's syndrome is characterized by progressive dilatation of the aortic root. This dilatation is accelerated by pregnancy, exposing patients to an increased risk of aortic dissection. Literature on the anesthetic management of delivery in patients with Marfan's syndrome consists only of case reports. We therefore conducted a retrospective review of medical records focusing on anesthetic management of delivery in patients with Marfan's syndrome in a national referral center. METHODS: We reviewed the medical records of all pregnant women with Marfan's syndrome who were followed at their institution over a 6-year period. RESULTS: Sixteen pregnancies in 15 patients were analyzed. The initial aortic root diameter was larger than 40 mm in 9 patients and larger than 45 mm in 1 patient. Two patients did not receive ß-blockers throughout pregnancy because of poor tolerance. One patient with an aortic root diameter of 47 mm did not receive ß-blocker before 33 weeks' gestation because of late referral. This woman developed acute type 1 aortic dissection at 37 weeks, requiring emergency cesarean delivery under general anesthesia followed by aortic repair. Thirteen other patients underwent cesarean delivery, 1 under spinal anesthesia and 12 under general anesthesia. General anesthesia management included close arterial blood pressure monitoring, avoidance of high blood pressure, administration of opioids before delivery, and titrated nicardipine administration. Two patients (including one with intrauterine fetal death) underwent vaginal delivery under epidural analgesia. There were no maternal deaths. CONCLUSIONS: Pregnant women with Marfan's syndrome who received care in a multidisciplinary tertiary care setting that included active peripartum involvement of anesthesiologists had good clinical outcomes.

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.

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.

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.