Predicting chronic post-traumatic head and neck pain: the role of bedside parameters.

Traumatic brain injury (TBI) annually impacts 69 million individuals worldwide. Mild TBI constitutes approximately 90% of all TBIs. Chronic pain post-mTBI occurs in 29% to 58% of patients.

Enhancing Coronary Revascularization Decisions: The Promising Role of Large Language Models as a Decision-Support Tool for Multidisciplinary Heart Team.

Background: While clinical practice guidelines advocate for multidisciplinary heart team (MDHT) discussions in coronary revascularization, variability in implementation across health care settings remains a challenge. This variability could potentially be addressed by language learning models like ChatGPT, offering decision-making support in diverse health care environments. Our study aims to critically evaluate the concordance between recommendations made by MDHT and those generated by language learning models in coronary revascularization decision-making.

Evaluating the effectiveness of a sliding window technique in machine learning models for mortality prediction in ICU cardiac arrest patients.

Extensive research has been devoted to predicting ICU mortality, to assist clinical teams managing critical patients. Electronic health records (EHR) contain both static and dynamic medical data, with the latter accumulating during ICU stays. Existing models often rely on a fixed time window (e.

Towards a practical use of text mining approaches in electrodiagnostic data.

Healthcare professionals produce abounding textual data in their daily clinical practice. Text mining can yield valuable insights from unstructured data. Extracting insights from multiple information sources is a major challenge in computational medicine.

Incidence and Outcome of Neurologic Immune-Related Adverse Events Associated With Immune Checkpoint Inhibitors in Patients With Melanoma.

Background And Objectives: Neurologic immune-related adverse events (n-irAEs) reportedly occur in up to 8% of patients treated with immune checkpoint inhibitors (ICIs) of all age groups. We investigated the association between age and n-irAEs in patients treated with ICIs and examined the effect of n-irAEs on survival outcomes in a large cohort of patients with melanoma.

Methods: We conducted a retrospective analysis of patients with advanced melanoma treated with ICIs at Ella Institute for Immuno-oncology and Melanoma between January 1, 2015, and April 20, 2022.

Nerve Conduction Differences in a Large Clinical Population: The Role of Age and Sex.

Background: The normal limits of nerve conduction studies are commonly determined by testing healthy subjects. However, in comprehensive real-life nerve conduction electrodiagnostic (EDX) evaluations, multiple nerves are tested, including normal nerves, for purposes of comparison with abnormal ones.

Objective: This study aims to evaluate the average values of normal nerve conduction studies in a large population and examined the influence of age and sex.

Utilizing shared frailty with the Cox proportional hazards regression: Post discharge survival analysis of CHF patients.

Understanding patients' survival probability as well as the factors affecting it constitute a significant concern for researchers and practitioners, in particular for patients with severe chronic illnesses such as congestive heart failure (CHF). CHF is a clinical syndrome characterized by comorbidities and adverse medical events. Risk stratification to identify patients most likely to die shortly after hospital discharge can improve the quality of care by better allocating organizational resources and personalized interventions.

Disease evolution and risk-based disease trajectories in congestive heart failure patients.

Congestive Heart Failure (CHF) is among the most prevalent chronic diseases worldwide, and is commonly associated with comorbidities and complex health conditions. Consequently, CHF patients are typically hospitalized frequently, and are at a high risk of premature death. Early detection of an envisaged patient disease trajectory is crucial for precision medicine.