Explore the vast range of titles available.

Adenosine boasts promising preclinical and clinical data supporting a vital role in modulating vascular homeostasis. Its widespread use as a diagnostic and therapeutic agent have been limited by its short half‐life and complex biology, though adenosine‐modulators have shown promise in improving vascular healing. Moreover, circulating adenosine has shown promise in predicting cardiovascular (CV) events. We sought to delineate whether circulating plasma adenosine levels predict CV events in patients undergoing invasive assessment for coronary artery disease. Patients undergoing invasive angiography had clinical data prospectively recorded in the Cardiovascular and Percutaneous ClInical TriALs (CAPITAL) revascularization registry and blood samples collected in the CAPITAL Biobank from which adenosine levels were quantified. Tertile‐based analysis was used to assess prediction of major adverse cardiovascular events (MACE; composite of death, myocardial infarction, unplanned revascularization, and cerebrovascular accident). Secondary analyses included MACE subgroups, clinical subgroups and adenosine levels. There were 1,815 patients undergoing angiography who had blood collected with adenosine quantified in 1,323. Of those quantified, 51.0% were revascularized and 7.3% experienced MACE in 12 months of follow‐up. Tertile‐based analysis failed to demonstrate any stratification of MACE rates (log rank, P = 0.83), when comparing low‐to‐middle (hazard ratio (HR) 1.10, 95% confidence interval (CI) 0.68–1.78, P = 0.70) or low‐to‐high adenosine tertiles (HR 0.95, 95% CI 0.56–1.57, P = 0.84). In adjusted analysis, adenosine similarly failed to predict MACE. Finally, adenosine did not predict outcomes in patients with acute coronary syndrome nor in those revascularized or treated medically. Plasma adenosine levels do not predict subsequent CV outcomes or aid in patient risk stratification.

Bleeding complications are a major contributor to adverse drug events among older inpatients, particularly in those treated with antithrombotic agents. Timely and accurate detection of bleeding events is essential for improving drug safety surveillance and clinical risk management. The study aimed to develop and validate automated algorithms for detecting major bleeding (MB) and clinically relevant nonmajor bleeding (CRNMB) events from electronic medical records (EMRs) by combining structured data-based rule models and a natural language processing (NLP) approach, and to evaluate their performance and generalizability against a manually reviewed gold standard and an external dataset. We conducted a multicenter retrospective study using routinely collected EMR data from 3 Swiss university hospitals. Patients 65 years or older who received at least one antithrombotic agent and were hospitalized between January 2015 and December 2016 were included. To detect MB and CRNMB events, rule-based algorithms were developed using structured data (International Statistical Classification of Diseases, 10th Revision, German Modification [ICD-10-GM] codes, laboratory values, transfusion records, and antihemorrhagic prescriptions), with variables and cutoff values defined according to adapted International Society on Thrombosis and Haemostasis definitions and expert consensus. In parallel, a supervised NLP model was applied to discharge summaries from one hospital. A manual review of 754 EMRs served as the reference standard for internal validation, and the algorithm performance of the structured data algorithms (SDA), NLP, and their combination (SDA+NLP) was evaluated against this manually reviewed gold standard using standard performance metrics. External validation was performed on an independent dataset from the Lausanne University Hospital to assess model robustness and generalizability. Among 36,039 inpatient stays, SDA identified 8.26% (n=2979) as MB and 15.04% (n=5419) as CRNMB cases. ICD-10-GM codes alone detected 28.5% (n=849) of MB and 31.48% (n=1706) of CRNMB cases, while laboratory data contributed most to event detection (n=1994, 66.94% for MB and n=3663, 67.60% for CRNMB). Integrating SDA with NLP improved detection, identifying 12.2% (920/7513) of MB and 27.4% (2062/7513) of CRNMB cases at 1 hospital. The combined model achieved the best performance (sensitivity 0.84, positive predictive value 0.51, F1-score 0.64). External validation on Lausanne University Hospital 2021-2022 data (n=24,054 stays) confirmed the algorithms' reproducibility; the prevalence of MB decreased while CRNMB increased, reflecting evolving clinical practices and antithrombotic use patterns. Our integrated approach, combining SDA with NLP, enhances the detection of hemorrhagic events in older hospitalized patients treated with antithrombotic agents, suggesting its potential usefulness for drug safety monitoring and clinical risk management.

Background: Awake craniotomy (AC) is recommended for the resection of tumors in eloquent areas. It is traditionally performed under monitored anesthesia care (MAC), which relies on hypnotics and opioids. Hypnosis-assisted AC (HAAC) is an emerging technique that aims to provide psychological support while reducing the need for pharmacological sedation and analgesia. We aimed to compare the characteristics and outcomes of patients who underwent AC under HAAC or MAC. Methods: We retrospectively analyzed the clinical, anesthetic, surgical, and neuropsychological data of patients who underwent awake surgical resection of eloquent brain tumors under HAAC or MAC. We used Mann–Whitney U tests, Wilcoxon signed-rank tests, and repeated-measures analyses of variance to identify statistically significant differences at the 0.05 level. Results: A total of 22 patients were analyzed, 14 in the HAAC group and 8 in the MAC group. Demographic, radiological, and surgical characteristics as well as postoperative outcomes were similar. Patients in the HAAC group received less remifentanil (p = 0.047) and propofol (p = 0.002), but more dexmedetomidine (p = 0.025). None of them received ketamine as a rescue analgesic. Although patients in the HAAC group experienced higher levels of perioperative pain (p < 0.05), they reported decreasing stress levels (p = 0.04) and greater levels of satisfaction (p = 0.02). Conclusion: HAAC is a safe alternative to MAC as it reduces perioperative stress and increases overall satisfaction. Further research is necessary to assess whether hypnosis is clinically beneficial.

Child protection intervention is already complex, and it is further complicated when it concerns families from cultural diversity. Information on the cases of 48 visible minority children receiving protective services underwent qualitative content analysis. The caseworkers' interviews brought to light 2 issues central to the relationship between parents and caseworkers: their degree of collaboration and the cultural distance between their respective concepts of parental and spousal roles. Based on these issues, 4 types of family caseworker dynamics were identified, as well as suitable strategies for dealing with each of them. This study underscores the fact that visible minority families receiving child protective services are a far from homogeneous group and that there are a number of effective methods that can be used with them.

Background Ventricular assist devices (VAD) are valuable options for patients with heart failure awaiting cardiac transplantation. We assessed the impact of pre-transplant VAD implantation on the incidence of post-transplant infections in a nationwide cohort of heart transplant recipients. Methods Heart transplant recipients included in the Swiss Transplant Cohort Study between May 2008 and December 2012 were analyzed. Cumulative incidence curves were used to calculate the incidence of bacterial or Candida infections (primary endpoint) and of other infections (secondary endpoint) after transplant. Cox regression models treating death as a competing risk were used to identify risk factors for the development of infection after transplant. Results Overall, 119 patients were included in the study, 35 with a VAD and 84 without VAD. Cumulative incidences of post-transplant bacterial or Candida infections were 37.7 % in VAD patients and 40.4 % in non-VAD patients. In multivariate analysis, the use of cotrimoxazole prophylaxis was the only variable associated with bacterial/ Candida infections after transplant (HR 0.29 [95 % CI 0.15-0.57], p < 0.001), but presence of a VAD was not (HR 0.94, [95 % CI 0.38-2.32], p = 0.89, for continuous-flow devices, and HR 0.45 [0.15 – 1.34], p  = 0.15, for other devices). Risk for post-transplant viral and all fungal infections was not increased in patients with VAD. One-year survival was 82.9 % (29/35) in the VAD group and 82.1 % (69/84) in the non-VAD group. All 6 patients in the VAD group that died after transplant had a history of pre-transplant VAD infection. Conclusion In this nationwide cohort of heart transplant recipients, the presence of VAD at the time of transplant had no influence on the development of post-transplant infections.