Predicting clinically significant events in children with ureteropelvic junction obstruction.

Introduction: Ureteropelvic junction obstruction (UPJO) syndrome is one of the most common causes of neonatal hydronephrosis. Management varies from simple monitoring to surgical intervention, with indications differing between institutions. A consensus of 8 societies recently described a new Urinary Tract Dilation (UTD) classification which aims to standardize ultrasound description of hydronephrosis, but which is also supposed to have predictive value in children with hydronephrosis. Our aim was to compare, in a monocentric prospective cohort of children with UPJO, the ability of UTD to predict the occurrence of a clinically significant event within the first year of life, as compared to anteroposterior diameter of the renal pelvis (APD). Study design: We used a preexisting cohort of children followed in a prospective study on UPJO. A pediatric radiologist, blinded to the children's outcome, classified the last antenatal ultrasound and postnatal ultrasound according to the UTD-A and UTD-P classification. He also confirmed the APD-A and APD-P measures. We defined a clinically significant event as being: increased pelvic dilation (>5 mm) and/or the presence of a febrile urinary tract infection (fUTI) and/or impaired renal function on initial nuclear scan (<40%). We performed a ROC-AUC curve and Random Forest (RF) analysis to compare the ability of the APD-A, APD-P, UTD-A and UTD-P scores to predict a clinically significant event. Results: The cohort included 28 children. Clinically significant events were noted in 20 out of 28 patients: 13 children presented an increase >5 mm in dilation, 6 presented an episode of fUTI and 9 had impaired function of the affected kidney. APD-A was the most effective individual criterion for predicting the occurrence of a significant clinical event (AUC = 0.867). Conclusion: In our series, for children with UPJO, the most significant marker was prenatal APD >15 mm to predict an increase in dilation >5 mm.

PRESOLRE: study protocol for a primary school-based, cluster randomised controlled trial of three sun exposure risk prevention strategies on Reunion Island.

INTRODUCTION: Reunion Island, a French overseas department, is located in the southern hemisphere, close to the Capricorn tropic. This island has a multicultural and multiethnic population of 860 000 inhabitants, a quarter of whom are at high risk of developing skin cancer due to intense ultraviolet radiation. Melanoma is responsible for the majority of skin cancer deaths. The early prevention of melanoma is based on sun protection in childhood, but French regulations are not adapted to the environmental conditions of this tropical region.The main objective of our study is to evaluate the effectiveness of three sun protection programs conducted in Reunionese primary schools through a pupil knowledge questionnaire. METHODS AND ANALYSIS: PRESOLRE is an interventional, open-label, cluster-randomised controlled trial, in four parallel arms, that is being conducted throughout 2022-2023 on Reunion Island. The trial design assumes an escalation interventional effect using: first, a control arm without proposed intervention (arm 1); second, an arm whose classes are encouraged to use the validated educational programme 'Living With the Sun' (LWS) (arm 2); third, an arm whose classes are encouraged to use both 'LWS' combined with 'Mission Soleil Réunion's sun protection awareness programme (arm 3); fourth, an arm benefiting from an intervention similar to arm 3, combined with the distribution of hats, sunglasses and sun creams (arm 4). In all, 1780 pupils from 18 classes of 20 pupils, on average, will be included. Randomisation applies to the classes of pupils (so defined as clusters). The primary outcome is based on the proportion of correct answers to the knowledge questions after the awareness programme, compared between the four arms using a linear mixed model with random intercept. ETHICS AND DISSEMINATION: The study obtained ethics approval in 2022 (ID: 2022-A00350-43). Results will be published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT05367180.

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.

Validation of the French version of the Caregivers' Priorities and Child Health Index of Life with Disabilities questionnaire.

INTRODUCTION: The Caregivers' Priorities and Child Health Index of Life with Disabilities (CPCHILD) is a questionnaire that measures the health-related quality of life (HRQL) of children with cerebral palsy (CP). Though measuring HRQL is challenging in these children, it is a valuable help for medical decision-making. There is no questionnaire to assess HRQL in French-speaking children with severe CP. OBJECTIVE: To translate and adapt transculturally the CPCHILD questionnaire into French (CPCHILD-FV). MATERIAL AND METHODS: The CPCHILD was translated from English into French by forward and backward translation by independents translators. The questionnaire was then tested on 32 caregivers of patients with CP classified as GMFCS IV or V, remarks of caregivers were analyzed by an expert committee and, if necessary, modifications were performed. Internal consistency of the CPCHILD-FV was assessed using a sample of 32 parents or caregivers and test-retest reliability was assessed on a random sample of 10 patients. RESULTS: The translation and transcultural process resulted in a French version of the CPCHILD. Some items of the CPCHILD required careful discussion to ensure that items had the same meaning as in the original. Internal consistencies were over 0.70 for each domain except for health, and 0.97 for the total scores. The ICC for the test-retest reliability of the CHILD-FV total score was 0.98 (95% CI: 0.93-0.99) and ranged from 0.59 to 0.99 for the domains. CONCLUSION: The translation and cross-cultural adaptation of the CPCHILD questionnaire provides a French version than can measure the HRQL of children with severe CP. LEVEL OF EVIDENCE: IV; prospective study without control group.

Psychometric properties of a Creole version of Medical Outcome Study - Short Form 36 among type II diabetes patients on Reunion Island.

Introduction: Health quality of life assessment is particularly important to measure the impact of chronic diseases. The aims of this study were to provide a cross-culturally adapted Creole-translation of the Medical Outcome Study Short-Form 36 (SF-36) and to assess psychometric performance of the Creole and French versions of the SF-36 among patients with type II diabetes in Reunion Island. Materials and methods: The Creole translation and cross-cultural adaptation processes were based on the International Quality Of Life Assessment (IQOLA) methods. Internal consistency, test-retest reliability, convergent and discriminant validity using Multi-Trait-Multi-Method analysis and structural validity using exploratory factor analysis of the SF-36 for both versions were performed. Results: In the Creole version of the SF-36, Cronbach's alpha exceeded 0.70 for all subscales except general health. In the French SF-36, Cronbach's alpha exceeded 0.70 on all subscales except general health and bodily pain. In the Creole SF-36, intraclass correlation coefficient (ICC) for reproducibility was suboptimal. Multi-trait multi-method analysis showed that item-scale correlation exceeded 0.4 for all items except two general health items of the Creole SF-36 and one of the French SF-36. Factor analysis of 2 versions showed that the physical functioning, vitality, and mental health were each divided into two subscales. Discussion: Overall, our findings provided evidence that the SF-36 is adapted to Reunion Island in both Creole and French versions. However, further research could be conducted to investigate French-Creole differences in perceived health status and a cultural adaptation of the French version will be considered.

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.

Financial and relational impact of having a boy with posterior urethral valves.

Introduction: Childhood chronic diseases affect family functioning and well-being. The aim of this study was to measure the impact of caring for a child with PUV, and the factors that most impact the burden of care. Patients and method: We gave a questionnaire on the familial impact of having a child with posterior urethral valves to all parents of a child included in the CIRCUP trial from 2015 onwards. The questionnaire included questions about the parents' demographics, health, professional, financial and marital status and how these evolved since the child's birth as well as the "impact on family scale" (IOFS), which gives a total score ranging from 15 (no impact) to 60 (maximum impact). We then analyzed both the results of the specific demographic questions as well as the factors which influenced the IOFS score. Results: We retrieved answers for 38/51 families (74.5% response rate). The average IOFS score was 23.7 (15-51). We observed that the child's creatinine level had an effect on the IOFS score (p = 0.02), as did the parent's gender (p = 0.008), health status (p = 0.015), being limited in activity since the birth of the child (p = 0.020), being penalized in one's job (p = 0.009), being supported in one's job (p = 0.002), and decreased income (p = 0.004). Out of 38 mother/father binomials, 8/33 (24.2%) declared that they were no longer in the same relationship afterwards. Conclusion: In conclusion, having a boy with PUV significantly impacts families. The risk of parental separation and decrease in revenue is significant. Strategies aiming to decrease these factors should be put in place as soon as possible.

Quality of life assessment in diabetic patients: validity of the creole version of the EQ-5D-5L in Reunion Island.

Introduction: Due to the high prevalence of diabetes and its complications, evaluating the patient's quality of life is critical. EQ-5D-5L is a valid tool for assessing health-related quality of life (HRQOL) in chronic diseases, including diabetes. However, no psychometric measures have been validated in a Creole-speaking population. Therefore, this study aimed for the first time to validate and cross-culturally adapt Creole and French versions of EQ-5D-5L on Type II diabetes patients in Reunion Island. Materials and methods: The Creole translation and cross-cultural adaptation process were based on the EUROQOL methods. Internal consistency and construct validity were determined using confirmatory factor analysis (CFA) of EQ-5D-5L for both versions. CFA model for HRQOL and global fit measures were calculated based on the EQ-5D-5L items using the maximum likelihood (ML) method. Results: From November 2016 to October 2017, 148 patients were included in the Creole group and 152 in the French group. EQ-5D-5L measures were unidimensional for both versions. Cronbach's coefficient alpha was 0.76 for the Creole version and 0.81 for the French version in CFA models. The root mean square error of approximation (RMSEA) was 0.06 for the Creole version and 0.02 for the French version. The Comparative Fit Index (CFI) was closer to 1 for both versions. CFA models for both the Creole and French versions fit the data adequately. Discussion: Overall, our findings provided evidence that both the Creole and French versions of EQ-5D-5L are suitable for assessing HRQOL in diabetes patients in Reunion Island. However, further research could be done to investigate French-Creole differences concerning the perception of health status, and a cultural adaptation of the French version will be considered.

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.

Effectiveness of intraoperative use of dexmedetomidine in reducing the incidence of tachyarrhythmia after congenital cardiac surgery in neonates and infants: a doubly robust method estimation analysis.

OBJECTIVES: The antiarrhythmic effects of dexmedetomidine (DEX) have been suggested, but there are controversial reports on the effectiveness of intraoperative use of DEX to reduce the incidence of postoperative tachyarrhythmia (POT). METHODS: From a local European Congenital Heart Surgery Association database, we included patients operated for congenital heart diseases under cardiopulmonary bypass within a 5-year period (2017-2021), during which intraoperative use of high dose of DEX (1-1.4 µg/kg/h) was implemented. A doubly robust matching estimation of the causal effect of DEX on the incidence of POT was conducted. We combined a multimodal estimation model in patients not exposed to DEX (disease risk score) as well as a regression analysis in a matched cohort for patients exposured to DEX. RESULTS: From a cohort of 593 surgeries (514 patients) occurring during the study period, doubly matched analysis consisted of the analysis of 426 surgeries conducted under DEX or not (213 per group). The probability of developing POT in patients exposed to DEX was 6.6% (95% confidence interval 0.032-0.099) vs 14.5% (95% confidence interval 0.098-0.193) in the group of patients not exposed to DEX. The doubly robust matched estimation method showed a mean reduction of 8.8% (95% confidence interval -0.137 to -0.023) of POT when DEX is used for intraoperative anaesthesia. CONCLUSIONS: The use of high doses of DEX during anaesthesia for congenital heart surgery in neonates and infants is associated with a moderate but significant reduction of POT.

Running Endurance in Women Compared to Men: Retrospective Analysis of Matched Real-World Big Data.

BACKGROUND AND OBJECTIVE: To determine whether the gap in endurance performance between men and women is reduced as distances increase, i.e. if there is a sex difference in endurance, one can analyse the performance of elite runners, all participants, or one can pair women and men during short-distance events and examine the difference over longer distances. The first two methods have caveats, and the last method has never been performed with a large dataset. This was the goal of the present study. METHODS: A dataset including 38,860 trail running races from 1989 to 2021 in 221 countries was used. It provided information on 1,881,070 unique runners, allowing 7251 pairs of men and women with the same relative level of performance to be obtained, i.e. the same percentage of the winner time of the considered race on short races (25-45 km-effort) that were compared during longer races (45-260 km-effort). The effect of distance on sex differences in average speed was determined using a gamma mixed model. RESULTS: The gap between sexes decreased as distance increases, i.e. men's speed decreased by 4.02% (confidence interval 3.80-4.25) for every 10 km-effort increase, whereas it decreased by 3.25% (confidence interval 3.02-3.46) for women. The men-women ratio decreases from 1.237 (confidence interval 1.232-1.242) for a 25 km-effort to 1.031 (confidence interval 1.011-1.052) for a 260 km-effort. This interaction was modulated by the level of performance, i.e. the greater the performance level of the runner, the lower the difference in endurance between sexes. CONCLUSIONS: This study shows for the first time that the gap between men and women shrinks when trail running distance increases, which demonstrates that endurance is greater in women. Although women narrow the performance gap with men as race distance increases, top male performers still outperform the top women.

Machine learning for predicting neurodegenerative diseases in the general older population: a cohort study.

BACKGROUND: In the older general population, neurodegenerative diseases (NDs) are associated with increased disability, decreased physical and cognitive function. Detecting risk factors can help implement prevention measures. Using deep neural networks (DNNs), a machine-learning algorithm could be an alternative to Cox regression in tabular datasets with many predictive features. We aimed to compare the performance of different types of DNNs with regularized Cox proportional hazards models to predict NDs in the older general population. METHODS: We performed a longitudinal analysis with participants of the English Longitudinal Study of Ageing. We included men and women with no NDs at baseline, aged 60 years and older, assessed every 2 years from 2004 to 2005 (wave2) to 2016-2017 (wave 8). The features were a set of 91 epidemiological and clinical baseline variables. The outcome was new events of Parkinson's, Alzheimer or dementia. After applying multiple imputations, we trained three DNN algorithms: Feedforward, TabTransformer, and Dense Convolutional (Densenet). In addition, we trained two algorithms based on Cox models: Elastic Net regularization (CoxEn) and selected features (CoxSf). RESULTS: 5433 participants were included in wave 2. During follow-up, 12.7% participants developed NDs. Although the five models predicted NDs events, the discriminative ability was superior using TabTransformer (Uno's C-statistic (coefficient (95% confidence intervals)) 0.757 (0.702, 0.805). TabTransformer showed superior time-dependent balanced accuracy (0.834 (0.779, 0.889)) and specificity (0.855 (0.0.773, 0.909)) than the other models. With the CoxSf (hazard ratio (95% confidence intervals)), age (10.0 (6.9, 14.7)), poor hearing (1.3 (1.1, 1.5)) and weight loss 1.3 (1.1, 1.6)) were associated with a higher DNN risk. In contrast, executive function (0.3 (0.2, 0.6)), memory (0, 0, 0.1)), increased gait speed (0.2, (0.1, 0.4)), vigorous physical activity (0.7, 0.6, 0.9)) and higher BMI (0.4 (0.2, 0.8)) were associated with a lower DNN risk. CONCLUSION: TabTransformer is promising for prediction of NDs with heterogeneous tabular datasets with numerous features. Moreover, it can handle censored data. However, Cox models perform well and are easier to interpret than DNNs. Therefore, they are still a good choice for NDs.

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.

Risk factors for febrile urinary tract infection in boys with posterior urethral valves.

Objective: Boys with posterior urethral valves (PUV) present an increased risk of febrile urinary tract infection (fUTI). Identifying specific risk factors could allow for tailoring UTI prevention. The aim of this study was to use the data from the CIRCUP randomized controlled trial data to identify patient characteristics associated with a higher risk of fUTI. Patients and methods: We performed a secondary analysis of the data from the CIRCUP randomized trial which included boys with PUV, randomized to circumcision and antibiotic prophylaxis vs. antibiotic prophylaxis alone and followed for 2 years. There was only 1 episode of fUTI in the circumcision group vs. 17 in the uncircumcised group. We therefore only studied the antibiotic prophylaxis alone group and compared age at prenatal diagnosis, size and weight at birth, presence of dilating VUR at diagnosis, abnormal DMSA scan at 2 months, and nadir creatinine between children who presented a fUTI and those who did not, as well as age at first episode of fUTI. Results: The study group consisted of 42 patients of which 17 presented at least on fUTI. Presence of dilating VUR was significantly associated with risk of fUTI (p = 0.03), OR: 6 [CI 95% = (1.13-27.52)]. None of the other parameters were associated with increased risk of fUTI. We observed three distinct time periods for presenting a fUTI with a decrease in infection rate after the first 40 days of life, then at 240 days of life. Conclusion: In boys with PUV, presence of high-grade VUR is associated with a higher risk of presenting a fUTI. The rate of febrile UTIs seems to decrease after 9 months.

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.

Incidence and factors associated with out-of-hospital peri-intubation cardiac arrest: a secondary analysis of the CURASMUR trial.

The Incidence of peri-intubation cardiac arrest (PICA) has been rarely assessed in the out-of-hospital setting. The objectives of this study were to assess the incidence and factors associated with PICA (cardiac arrest occurring within 15 min of intubation) in an out-of-hospital emergency setting, wherein emergency physicians perform standardized airway management using a rapid sequence intubation technique in adult patients. This was a secondary analysis of the "Succinylcholine versus Rocuronium for out-of-hospital emergency intubation" (CURASMUR) trial, which compared the first attempt intubation success rate between succinylcholine and rocuronium in adult patients requiring emergency tracheal intubation for any vital distress except cardiac arrest. Enrollment occurred from January 2014 to August 2016 in 17 French out-of-hospital emergency medical units. All operators were emergency physicians. The PICA incidence was recorded and multivariable logistic regression analysis was used to identify the factors associated with its occurrence. A total of 1226 patients were included with a mean age of 55.9 ± 19 years. PICA was recorded in 35 (2.8%) patients. Multivariable analysis indicated that the occurrence of PICA was independently associated with a body mass index (BMI) > 30 kg m2 [adjusted odds ratio (aOR) 4.85; 95% confidence interval (CI) 1.82-12.90, p = 0.02], oxygen saturation (SpO2) before intubation < 90% (aOR 3.4; 95% CI 1.50-7.60, p = 0.003), difficult intubation (defined by an Intubation Difficulty Score [IDS] > 5, [aOR 3.59; 95% CI 1.82-8.08, p = 0.02], the use of rocuronium instead of succinylcholine (aOR 2.47; 95% CI 1.08-5.64, p = 0.03), post intubation hypoxaemia (aOR 2.70; 95% CI 1.05-6.95, p = 0.04), post-intubation hypotension (aOR 4.07; 95% CI 1.62-10.22, p = 0.003), and pulmonary aspiration(aOR 4.78; 95% CI 1.48-15.36, p = 0.009). Early PICA occurred in approximately 3% of cases in the out-of-hospital setting. We identified several independent risk factors for PICA, including obesity, hypoxaemia before intubation and difficult intubation.

Incidence, Complications, and Factors Associated with Out-of-Hospital First Attempt Intubation Failure in Adult Patients: A Secondary Analysis of the CURASMUR Trial Data.

Objectives: The objectives of this study were to evaluate first attempt intubation failure rate, its associated factors, and its related complications in out-of-hospital emergency setting, when emergency physicians perform standardized airway management using rapid sequence intubation in adult patients. Material and methods: The present study was a substudy of the Succinylcholine versus Rocuronium for out-of-hospital Emergency Intubation (CURASMUR) Trial, which compared Succinylcholine and Rocuronium used for Rapid sequence intubation. First attempt Intubation failure rate and early intubation related complications were recorded. We used multivariable logistic regression analysis to determine first intubation failure associated factors. Results: A total of 1230 patients were included with mean age of 55.9 +/- 19 years. First attempt intubation failure was recorded in 285 (23.2%) patients. The occurrence of a first attempt intubation failure was independently associated with history of ear, nose, and throat neoplasia (OR 2.20, CI 95% 1.06-4.60). Early intubation related complications were more frequent in case of first attempt intubation failure: 80 of 285 (28.4%) in patients with first attempt intubation failure and 185 of 945 (19.6%) in patients with successful first attempt intubation [OR 1.44; CI 95%, 1.11-1.87]. Conclusion: Based on a large multicenter study on out-of-hospital tracheal intubation of adult patients, we found that first attempt intubation failure rate was high and that history of ear, nose, and throat (ENT) neoplasia was an independent associated factor. Failure in first intubation attempt was associated with significantly more intubation related complications.