Explore the vast range of titles available.

This study aimed to describe the prevalence and determinants of financial precarity and examine its associations with mental health, healthcare avoidance and academic outcomes among French health students. Nationwide cross-sectional study based on an online self-administered questionnaire. Multivariate logistic regression models were used to identify factors associated with financial precarity. All 34 French health universities. A total of 12 565 health students participated, including medical (56%), paramedical (21%), midwifery, odontology, pharmacy or physiotherapy students (12%) and first-year health students (11%). Financial precarity was defined as an indicator combining financial insecurity, frequent overdrafts and foregoing essential purchases. Primary outcomes included depressive symptoms, anxiety and emotional exhaustion. Secondary outcomes included healthcare avoidance and academic outcomes. Among 12,565 respondents, 56% were medical students, 21% were paramedical, 12% midwifery, odontology, pharmacy or physiotherapy and 11% first-year health students. Financial precarity varies by academic fields of health, ranging from 4.6% in first-year health students to 12% in paramedical students. Adjusted analyses showed lower odds of precarity among medical (aOR=0.69; 95% CI 0.52 to 0.83), midwifery, odontology, pharmacy or physiotherapy (aOR=0.55; 95% CI 0.43 to 0.72) and first-year health students (aOR=0.54; 95% CI 0.38 to 0.77) than paramedical students. Risk factors included very low parental socio-economic status (aOR=2.96; 95% CI 2.33 to 3.89) and student loans (aOR=2.78; 95% CI 2.33 to 3.32). Financial precarity was strongly associated with depressive symptoms (aOR=4.90; 95% CI 4.13 to 5.80), anxiety (aOR=3.84; 95% CI 3.13 to 4.52), emotional exhaustion (aOR=8.49; 95% CI 5.98 to 12.06), renouncing healthcare (aOR=6.21; 95% CI 5.01 to 7.70) and repeating a year (aOR=1.80; 95% CI 1.54 to 2.10). Financial precarity among health students is shaped by economic and academic factors, with family support protective of and low socio-economic background increasing vulnerability, and is associated with poorer mental health, reduced healthcare access and academic difficulties.

Abstract Rationale Fever control may improve vascular tone and decrease oxygen consumption, but fever may contribute to combat infection. Objectives To determine whether fever control by external cooling diminishes vasopressor requirements in septic shock. Methods In a multicenter randomized controlled trial, febrile patients with septic shock requiring vasopressors, mechanical ventilation, and sedation were allocated to external cooling (n = 101) to achieve normothermia (36.5–37°C) for 48 hours or no external cooling (n = 99). Vasopressors were tapered to maintain the same blood pressure target in the two groups. The primary endpoint was the number of patients with a 50% decrease in baseline vasopressor dose after 48 hours. Measurements and Main Results Body temperature was significantly lower in the cooling group after 2 hours of treatment (36.8 ± 0.7 vs. 38.4 ± 1.1°C; P < 0.01). A 50% vasopressor dose decrease was significantly more common with external cooling from 12 hours of treatment (54 vs. 20%; absolute difference, 34%; 95% confidence interval [95% CI], −46 to −21; P < 0.001) but not at 48 hours (72 vs. 61%; absolute difference, 11%; 95% CI, −23 to 2). Shock reversal during the intensive care unit stay was significantly more common with cooling (86 vs. 73%; absolute difference, 13%; 95% CI, 2 to 25; P = 0.021). Day-14 mortality was significantly lower in the cooling group (19 vs. 34%; absolute difference, –16%; 95% CI, −28 to −4; P = 0.013). Conclusions In this study, fever control using external cooling was safe and decreased vasopressor requirements and early mortality in septic shock.

The variant 20I/501Y.V1, associated to a higher risk of transmissibility, emerged in Nice city (Southeast of France, French Riviera) during January 2021. The pandemic has resumed late December 2020 in this area. A high incidence rate together with a fast turn-over of the main circulating variants, provided us the opportunity to analyze modifications in clinical profile and outcome traits. We performed an observational study in the University hospital of Nice from December 2020 to February 2021. We analyzed data of sequencing of SARS-CoV-2 from the sewage collector and PCR screening from all positive samples at the hospital. Then, we described the characteristics of all COVID-19 patients admitted in the emergency department (ED) (n = 1247) and those hospitalized in the infectious diseases ward or ICU (n = 232). The UK-variant was absent in this area in December, then increasingly spread in January representing 59% of the PCR screening performed mid-February. The rate of patients over 65 years admitted to the ED decreased from 63 to 50% (p = 0.001). The mean age of hospitalized patients in the infectious diseases ward decreased from 70.7 to 59.2 (p < 0.001) while the proportion of patients without comorbidity increased from 16 to 42% (p = 0.007). Spread of the UK-variant in the Southeast of France affects younger and healthier patients.

Background Weaning from mechanical ventilation (MV) is a key phase in the management of intensive care unit (ICU) patient. According to the WEAN SAFE study, weaning from MV initiation is defined as the first attempt to separate a patient from the ventilator and the success is the absence of reintubation (or death) within 7 days of extubation. Mortality rates increase with the difficulty of weaning, reaching 38% for the most challenging cases. Predicting the success of weaning is difficult, due to the complexity of factors involved. The many biosignals that are measured in patients during ventilation may be considered “weak signals”, a concept rarely used in medicine. The aim of this research is to investigate the performance of machine learning (ML) models based on biosignals to predict spontaneous breathing trial success (SBT) using biosignals and to identify the most important variables. Methods This retrospective study used data from two centers (Nice University Hospital, Archet and Pasteur) collected from 232 intensive care patients who underwent MV (149 successfully and 83 unsuccessfully) between January, 2020 and April, 2023. The study focuses on the development of ML algorithms to predict the success of the spontaneous breathing trial based on a combination of discrete variables and biosignals (time series) recorded during the 24 h prior to the SBT. Results For the models tested, the best results were obtained with Support Vector Classifier model: AUC-PR 0.963 (0.936–0.970, p  = 0.001), AUROC 0.922 (0.871–0.940, p  < 0.001). Conclusions We found that ML models are effective in predicting the success of SBT based on biosignals. Predicting weaning from mechanical ventilation thus appears to be a promising area for the application of AI, through the development of multidimensional models to analyze weak signals.

Background COVID-19 infections are associated with accrued inflammatory responses which may result in cardiac injury. Immune response to infection appears different between men and women, suggesting that COVID-19 patients’ outcomes may differ according to biological sex. However, the impact of biological sex on the occurrence of cardiac injury during intensive care unit (ICU) stay in COVID-19 patients remain unclear. Methods In this multicenter and prospective study, we included consecutive patients admitted to ICU for severe COVID-19 pneumonia, during the first two pandemic waves. Biological, electrocardiogram (ECG) and echocardiographic variables were collected on ICU admission. Cardiac injury was defined by increased troponin above 99th percentile of upper norm value and newly diagnosed ECG and/or echocardiographic abnormalities. The primary endpoint was the proportion of patients with cardiac injury during ICU stay according to biological sex. The impact of biological sex on other subsequent clinical outcomes was also evaluated. Results We included 198 patients with a median age of 66 (56–73) years, 147 (74%) patients were men and 51 (26%) were women. Overall, 119 (60%) patients had cardiac injury during ICU stay and the proportion of patients with cardiac injury during ICU stay was not different between men and women (60% vs. 61%, p = 1.00). Patients with cardiac injury during ICU stay showed more cardiovascular risk factors and chronic cardiac disease and had a higher ICU mortality rate. On ICU admission, they had a more marked lymphopenia (0.70 (0.40–0.80) vs. 0.80 (0.50–1.10) × 10 9 /L, p < 0.01) and inflammation (C-Reactive Protein (155 (88–246) vs. 111 (62–192) mg/L, p = 0.03); D-Dimers (1293 (709–2523) vs. 900 (560–1813) µg/L, p = 0.03)). Plasmatic levels of inflammatory biomarkers on ICU admission correlated with SAPS-2 and SOFA scores but not with the different echocardiographic variables. Multivariate analysis confirmed cardiovascular risk factors (OR = 2.31; 95%CI (1.06–5.02), p = 0.03) and chronic cardiac disease (OR = 8.58; 95%CI (1.01–73.17), p = 0.04) were independently associated with the occurrence of cardiac injury during ICU stay, whereas biological sex (OR = 0.88; 95%CI (0.42–1.84), p = 0.73) was not. Biological sex had no impact on the occurrence during ICU stay of other clinical outcomes. Conclusions Most critically ill patients with COVID-19 were men and experienced cardiac injury during ICU stay. Nevertheless, biological sex had no impact on the occurrence of cardiac injury during ICU stay or on other clinical outcomes. Clinical trial registration NCT04335162

The SARS-CoV-2 infection has spread rapidly around the world causing millions of deaths. Several treatments can reduce mortality and hospitalization. However, their efficacy depends on the choice of the molecule and the precise timing of its administration to ensure viral clearance and avoid a deleterious inflammatory response. Here, we investigated IFN-γ, assessed by a functional immunoassay, as a predictive biomarker for the risk of hospitalization at an early stage of infection or within one month prior to infection. Individuals with IFN-γ levels below 15 IU/mL were 6.57-times more likely to be hospitalized than those with higher values (p<0.001). As confirmed by multivariable analysis, low IFN-γ levels, age >65 years, and no vaccination were independently associated with hospitalization. In addition, we found a significant inverse correlation between low IFN-γ response and high level of IL-6 in plasma (Spearman’s rho=-0.38, p=0.003). Early analysis of the IFN-γ response in a contact or recently infected subject with SARS-CoV-2 could predict hospitalization and thus help the clinician to choose the appropriate treatment avoiding severe forms of infection and hospitalization.

Large language models (LLMs) have emerged as promising tools in medical education due to their ability to understand, generate, and reason with natural language. Their ability to simulate expert reasoning suggests a potential for supporting quality control in assessment design. In this study, the use of LLMs in identifying ambiguous or poorly constructed exam items in critical care academic assessments was evaluated. The study aimed to develop automated ambiguity and quality scores to objectively assess individual questions and entire exam components. We analyzed 264 questions from academic exams conducted over 3 academic years (2023-2025) at the Medical School of Université Côte d'Azur. Questions were drawn from 4 docimological formats: progressive clinical cases (PCC), mini-PCC, key feature problems, and isolated question sequences (IQS). Each element was submitted to 4 LLMs (ChatGPT, Gemini Pro, Le Chat, and DeepSeek) without prompt engineering. Performance was evaluated using the official correction key. We applied 4 binary diagnostic tags based on model agreement and self-reported ambiguity: ambiguity, low performance, incoherence, and subjective ambiguity. These tags generated a composite ambiguity score and contributed to a weighted quality score for each exam component. LLMs achieved mean scores in the same range as students, with no significant differences across academic years and significantly higher performance on the mini-PCC and IQS formats (P=.049 and P=.04, respectively). IQS items had the highest ambiguity scores (54 items received a score of 2 in both 2023 and 2024, and 53 items retained the same score). Tag patterns revealed frequent issues with ambiguity and inconsistency. Quality scores varied across academic years. IQS predominantly showed moderate ambiguity (score 2), with occasional instances of strong signals. There was no significant difference in quality based on author specialty or seniority (P=.08 and P=.44, respectively). In this pilot study, LLMs may offer a preliminary framework to proactively detect ambiguous exam questions and estimate the overall quality of an exam. Integrating these tools into the assessment design process could potentially reduce the need for postexam corrections and may help improve fairness and clarity in medical evaluations.

Background Almitrine, a selective pulmonary vasoconstrictor in hypoxic area, improves oxygenation in mechanically ventilated patients with COVID-19 but its effects in spontaneously breathing patients with COVID-19 remain to be determined. Methods We prospectively studied the effects of almitrine (16 µg/kg/min over 30 min followed by continuous administration in responders only) in 62 patients (66% of male, 63 [53–69] years old) with COVID-19 treated with high-flow nasal cannula oxygen therapy (HFNO) and with persistent hypoxemia, defined as a PaO 2 /FiO 2 ratio < 100 with FiO 2  > 80% after a single awake prone positioning session. Patients with an increase in PaO 2 /FiO 2 ratio > 20% were considered as responders. Results Overall, almitrine increased the PaO 2 /FiO 2 ratio by 50% (p < 0.01), decreased the partial arterial pressure of carbon dioxide by 7% (p = 0.01) whereas the respiratory rate remained unchanged and 46 (74%) patients were responders. No patient experienced right ventricular dysfunction or acute cor pulmonale. The proportion of responders was similar regardless of the CT-Scan radiological pattern: 71% for the pattern with predominant ground-glass opacities and 76% for the pattern with predominant consolidations (p = 0.65). Responders had lower intubation rate (33 vs. 88%, p < 0.01), higher ventilator-free days at 28-day (28 [20–28 ]  vs.  19 [2–24] days, p < 0.01) and shorter ICU length of stay (5 [3–10]  vs. 12 [7–30] days, p < 0.01) than non-responders. Conclusions Almitrine could be an interesting therapy in spontaneously breathing patients with COVID-19 treated with HFNO and with persistent hypoxemia, given its effects on oxygenation without serious adverse effects regardless of the CT-Scan pattern, and potentially on intubation rate. These preliminary results need to be confirmed by further randomized studies.

Background There is wide variability between intensivists in the decisions to forgo life-sustaining treatment (DFLST). Advance directives (ADs) allow patients to communicate their end-of-life wishes to physicians. We assessed whether ADs reduced variability in DFLSTs between intensivists. Methods We conducted a multicenter, prospective, simulation study. Eight patients expressed their wishes in ADs after being informed about DFLSTs by an intensivist-investigator. The participating intensivists answered ten questions about the DFLSTs of each patient in two scenarios, referring to patients’ characteristics without ADs (round 1) and then with (round 2). DFLST score ranged from 0 (no-DFLST) to 10 (DFLST for all questions). The main outcome was variability in DFLSTs between intensivists, expressed as relative standard deviation (RSD). Results A total of 19,680 decisions made by 123 intensivists from 27 ICUs were analyzed. The DFLST score was higher with ADs than without (6.02 95% CI [5.85; 6.19] vs 4.92 95% CI [4.75; 5.10], p  < 0.001). High inter-intensivist variability did not change with ADs (RSD: 0.56 (round 1) vs 0.46 (round 2), p  = 0.84). Inter-intensivist agreement on DFLSTs was weak with ADs (intra-class correlation coefficient: 0.28). No factor associated with DFLSTs was identified. A qualitative analysis of ADs showed focus on end-of-life wills, unwanted things and fear of pain. Conclusions ADs increased the DFLST rate but did not reduce variability between the intensivists. In the decision-making process using ADs, the intensivist’s decision took priority. Further research is needed to improve the matching of the physicians’ decision with the patient’s wishes. Trial registration ClinicalTrials.gov Identifier: NCT03013530. Registered 6 January 2017; https://clinicaltrials.gov/ct2/show/NCT03013530 .