Hôpital Maisonneuve-Rosemont

Stem cell transplantation is a highly stressful treatment for hematological cancer patients, negatively impacting their quality of life. Hypnosis has proven effective in managing symptoms like pain, fatigue, and anxiety, and improving quality of life. Virtual reality (VR) is used in cancer treatments to distract from pain, and combining VR with hypnosis (VRH) could enhance the hypnotic experience. However, methodological limitations in current studies prevent clear evaluation of its effectiveness, particularly for individualized care and psychosocial interventions. 1) To evaluate the preliminary effects of VRH in reducing anxiety, pain, and fatigue during stem cell transplant, improving quality of life post-intervention. 2) To assess intervention feasibility, including patients' experiences, satisfaction levels, and recommendations for improving the VRH tool. This study will involve 60 hematology patients divided into two groups: VRH and waiting list. Anxiodepressive symptoms, pain, quality of life, fatigue, absorption, dissociation, and amusement will be assessed before, immediately after the intervention, and at one- and three-month follow-ups using validated psychological scales and numeric rating scales (0-10). Semi-structured interviews will capture patient expectations, satisfaction, and feedback. Data will be analyzed using MANOVA (or non-parametric alternatives) and thematic analysis. The study's primary goal is to assess VRH's effectiveness compared to standard care in a feasibility randomized controlled trial (RCT). It will also provide data for improving the VRH tool (version 2.0) and assess its usability. In the long term, findings will help integrate VRH into oncology clinics, offering an innovative intervention to support patients throughout treatment. ClinicalTrials.gov NCT06817759.

Our objective was to develop a Core Outcome Set for Research on Critically Ill Obstetric Patients (COSCO) through international consensus, with the aim of improving consistency, comparability, and clinical relevance across studies involving this population. This international, multi-method study was conducted between February 16, 2023, and January 18, 2024. The process included a two-round online Delphi survey, three small group discussions, and a final consensus meeting. Participants comprised health service users (HSUs) with lived experience of critical illness during pregnancy and healthcare professionals from diverse specialties and geographic regions. Sixty-eight participants (11 HSUs and 57 healthcare professionals) from 16 countries scored 23 candidate items identified through a systematic review and qualitative interviews. Through consensus, 10 core outcomes and 7 reporting checklist items were selected for inclusion in all research on critical illness in obstetrics. Core outcomes included maternal all-cause mortality; cardiac arrest and the need for cardiopulmonary resuscitation (not resulting in death); severe (maternal) organ dysfunction; length of stay in the intensive care unit (ICU) and total hospital stay; readmission to hospital or ICU or repeated hospital/emergency department visits following discharge from ICU; presence of a new medical condition at the time of discharge from hospital, which was not present at the time of admission to the hospital; permanent infertility as a consequence of critical illness or intervention; perinatal loss; severe neonatal morbidity requiring prolonged neonatal ICU admission; and gestational age/preterm birth. Four additional noncore outcomes were identified as important but may be challenging to measure consistently; these should be reported when relevant and feasible. COSCO provides a standardized, consensus-based framework for outcome reporting in research on critically ill obstetric patients. Its adoption will strengthen methodological rigor, reduce reporting heterogeneity, enhance comparability across studies, and support evidence-based, patient-centered guideline development.

Artificial intelligence (AI) embedded in point-of-care ultrasound (POCUS) could reduce operator dependence in left ventricular ejection fraction (LVEF) assessment and accelerate bedside decision making by non-cardiologists and non-radiologists. Prospective comparative studies evaluating real-time AI-assisted POCUS for LVEF across point-of-care settings were systematically reviewed. The PubMed/MEDLINE, Embase, and Cochrane databases were searched from inception to June 11, 2025. The authors included prospective analytical observational studies in intensive care unit (ICU), emergency department, perioperative, ward, or home settings that used AI during image acquisition and/or interpretation to estimate LVEF in real time against a reference standard. Risk of bias was appraised using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Because of heterogeneity, the findings were narratively synthesized. Twelve studies met the inclusion criteria across ICU, emergency department, perioperative, ward, and community settings. For continuous outcomes, agreement (r) between AI-derived and reference LVEF ranged from 0.56 to 0.92 and intraclass correlation coefficients ranged from 0.84 to 0.94. Bland-Altman analyses demonstrated broad limits of agreement, from approximately -31.8% to +20.0%, often indicating a tendency for AI to underestimate LVEF compared with reference measures. For categorical classification at a 50% threshold, sensitivities ranged from 70% to 93%; specificities, from 89% to 100%; and areas under the receiver operating characteristic curves, from 0.85 to 0.98. Weighted κ values ranged from 0.49 to 0.83. No study achieved a low risk of bias across all QUADAS-2 domains. AI-assisted POCUS can approximate reference LVEF and reasonably classify reduced LVEF at the bedside, supporting its use as a screening and triage tool in settings in which comprehensive echocardiography is not immediately available. Future studies should adopt intention-to-diagnose designs, standardize the Simpson biplane reference, minimize test delay, report calibration and failure rates, and incorporate image quality feedback.

Hypertensive disorders during pregnancy increase the risk of long-term cardiovascular disease in postpartum women. Exercise-based rehabilitation may help manage blood pressure (BP) and improve physical activity levels in this population, but supporting evidence remains limited. This pre-post single-arm proof-of-concept study aimed to assess the feasibility of a 4-week cardio-obstetrics rehabilitation program for women following hypertensive pregnancy. Women 3-6 months postpartum with a history of gestational hypertension or pre-eclampsia were recruited. The intervention combined exercise and educational components delivered through in-person, live virtual, and independent sessions. Feasibility was evaluated through recruitment, retention, adherence, acceptability, and safety. Outcomes included BP, six-minute walk distance, body weight and BMI, physical activity levels, health-related quality of life, and depressive symptoms. Six of 20 screened participants (30% recruitment) completed the intervention (100% retention). Overall adherence to scheduled sessions was 71%. All participants expressed high satisfaction, and no adverse events were reported. Descriptive analysis indicated improvements across all measured outcomes after the intervention. A cardio-obstetrics rehabilitation program for postpartum women after hypertensive pregnancy is feasible. Improvements in cardiovascular, anthropometric, behavioral, and psychosocial outcomes suggest potential efficacy and support further investigation.

BackgroundThe digital health research field is growing rapidly, and a summary of the available digital tools for triaging musculoskeletal conditions is needed. Effective and safe digital triage tools for musculoskeletal conditions could support patients and clinicians in making informed care decisions and may contribute to reducing emergency department overcrowding and health care costs.ObjectiveThe aim of the study is to identify and describe digital health tools for use by adults to triage musculoskeletal conditions across primary, urgent, or emergency care settings.MethodsOur scoping review was conducted following the Johanna Briggs Institute recommendations for scoping reviews and Arksey and O’Malley’s framework. Systematic searches in MEDLINE (OVID), Embase (OVID), CENTRAL (OVID), CINAHL (EBSCO), Compendex, Web of Science, OpenGrey, Google Scholar, arXiv, medRxiv, and an extensive gray literature search were conducted with a librarian scientist from inception to September 18, 2025. Studies had to recruit adults (aged 18 years and older) with musculoskeletal conditions that identified a digital health tool designed to triage or diagnose in primary, urgent, or emergency care settings and report primary data to be included. In total, 2 reviewer pairs independently screened abstracts and full-text papers. Relevant data were extracted in duplicate, and results were summarized descriptively.ResultsThe search yielded 5695 records, and we screened 189 full-text papers. In total, 34 studies (n=37,509 patients) met the inclusion criteria. The most common musculoskeletal conditions reported were rheumatoid or inflammatory arthritis (13/34, 38%). In total, 19 (19/34, 56%) studies reported on symptom checkers, 13 (13/34, 38%) studies on triage or diagnosis tools, and 2 (2/34, 6%) were studies of diagnostic predictor tools. There were 16 unique digital health tools. A total of 2 tools were built for triaging musculoskeletal conditions and were not publicly available outside the UK National Health Service. Most tools were generic tools designed to screen for general health problems, including musculoskeletal conditions. The most common approach to evaluating performance (eg, accuracy) of the tools was to compare the concordance of the tool to a clinician diagnosis or triage recommendation. Sensitivity and specificity ranged from 39% to 91% and 23% to 80%, respectively. The reported accuracy of the included tools ranged from 33% to 98%.ConclusionsMusculoskeletal conditions remain a blind spot for people designing, implementing, and evaluating digital health for triage: few tools were specifically designed for musculoskeletal conditions, and most existing tools performed poorly when applied to musculoskeletal populations. We recommend health systems and clinicians use a multimodal approach, integrating both digital health tools and clinical decision-making to safely triage and diagnose until a more robust tool for musculoskeletal conditions is available. Future tool developers need to use transparent, standardized processes that prioritize tool safety, clinical value, and trustworthiness when designing for clinicians and patients.

Different memory CD8+ T-cell subsets are generated following acute responses: central, effector and resident (Trm). CD8+ Trm cells established residency at the sites of infection and provide an efficient and rapid frontline defense against reinfection. The NR4A family members (NR4A1, NR4A2, and NR4A3) of orphan nuclear receptor are transiently expressed following TCR signaling and NR4As were shown to influence CD8+ T-cell response. Interestingly, Nr4a1, Nr4a2, and Nr4a3 have been reported to be transcribed by CD8+ Trm cells. NR4A1 and NR4A2 were shown to influence the generation of CD8+ Trm cells. However, evidence is still lacking for the contribution of NR4A3 during CD8+ Trm cell differentiation. In this study, we evaluated the role of NR4A3 in the differentiation and maintenance of CD8+ Trm cells. Our data demonstrate that in contrast to the other family members NR4A1 and NR4A2, NR4A3 is dispensable for the generation of CD8+ Trm cells at both epithelial and nonepithelial sites.

Individuals with atrial fibrillation (AF) are at increased risk of stroke, cognitive impairment and dementia. Observational studies suggest that anticoagulation may reduce the risk of cognitive decline in patients with AF and elevated thromboembolic risk, implicating subclinical cerebral emboli as a potential mechanistic link. Whether anticoagulation prevents cognitive deterioration in patients with AF at low risk of stroke remains uncertain. Here we conducted a multicenter, double-blind, placebo-controlled trial in which participants with AF and low thromboembolic risk (CHA2DS2-VASc scores of 0 or 1, excluding female sex) were randomized 1:1 to receive rivaroxaban 15 mg daily or placebo. The primary outcome was a composite of cognitive decline (≥2-point drop in Montreal Cognitive Assessment), stroke or transient ischemic attack with a motor deficit or aphasia. The trial was halted after meeting the predetermined futility criterion following a planned interim analysis, with 1,235 of the intended 1,424 participants (919 men; 316 women) enrolled. Over a median follow-up of 3.7 years, the primary outcome occurred in 256 (20.7%) participants, at an annual rate of 7.0% with rivaroxaban versus 6.4% with placebo, yielding a hazard ratio of 1.10 (95% confidence interval (0.86–1.40); P = 0.46). Conditional power analysis indicated a 1.2% probability of achieving a statistically significant treatment effect if the trial had been continued to its planned total of 410 events. Major bleeding occurred in two patients treated with rivaroxaban (0.09% per year) and five patients treated with placebo (0.21% per year). In conclusion, despite the high incidence of cognitive decline observed among patients with AF and low stroke risk, the BRAIN-AF trial, which tested a low dose of rivaroxaban to prevent stroke, transient ischemic attack and cognitive decline in patients with prior AF, was stopped early due to futility. ClinicalTrials.gov registration: NCT02387229.