Predicting lack of clinical improvement following varicose vein ablation using machine learning.

Objective: Varicose vein ablation is generally indicated in patients with active/healed venous ulcers. However, patient selection for intervention in individuals without venous ulcers is less clear. Tools that predict lack of clinical improvement (LCI) following vein ablation may help guide clinical decision-making but remain limited.

Prospective Preference Assessment for the Psilocybin for Enhanced Analgesia in Chronic nEuropathic PAIN (PEACE-PAIN) Trial.

Background: Negative perceptions of psilocybin and challenges of participant enrollment may represent barriers to conducting a randomized controlled trial examining psilocybin for chronic neuropathic pain.

Aim: Prior to trial initiation, we aimed to examine patient attitudes toward the trial via a prospective preference assessment.

Methods: Twenty-six patients with chronic neuropathic pain participated in a prospective preference assessment comprising quantitative (survey) and qualitative (interview) components.

Clinical Tools to Assess Functional Capacity During Risk Assessment Before Elective Noncardiac Surgery : A Scoping Review.

Background: Functional capacity is critical to preoperative risk assessment, yet guidance on its measurement in clinical practice remains lacking.

Purpose: To identify functional capacity assessment tools studied before surgery and characterize the extent of evidence regarding performance, including in populations where assessment is confounded by noncardiopulmonary reasons.

Data Sources: MEDLINE, EMBASE, and EBM Reviews (until July 2024).

STRIVE pilot trial: a protocol for a multicentre pragmatic internal pilot randomised controlled trial of Structured TRaining to Improve fitness in a Virtual Environment (STRIVE) before surgery.

Introduction: Home-based, virtually-supported care models may represent the most efficient and scalable approach to delivering prehabilitation services. However, virtual approaches to prehabilitation are understudied. This manuscript describes the protocol for an internal pilot randomised controlled trial of a virtually-delivered, multimodal prehabilitation intervention.

Transfusion in Anemic Patients With Acute Coronary Syndromes: A Population-Based Cohort Study.

Background: There is controversy surrounding the effectiveness of red blood cell (RBC) transfusion for treating anemia in patients hospitalized for acute coronary syndromes (ACS), particularly as hemoglobin (Hb) levels approach and drop below the range of moderate anemia.

Methods: This population-based cohort study followed all adults hospitalized for ACS who experienced an in-hospital nadir Hb between 6.0 and 8.

Joint models inform the longitudinal assessment of patient-reported outcomes in clinical trials: a simulation study and secondary analysis of the restrictive Vs. liberal fluid therapy for major abdominal surgery (RELIEF) randomized controlled trial.

Objectives: Evaluate the utility of a joint model when analysing a patient-reported endpoint as part of a randomized controlled trial (RCT) in which censoring occurs when patients die during follow-up.

Study Design And Setting: The present study comprises two parts as follows: first we reanalyzed data from a previously published RCT comparing two fluid regimens in the first 24 hours of major abdomino-pelvic surgery ('Restrictive versus Liberal Fluid Therapy for Major Abdominal Surgery [RELIEF]' trial). In this trial, patient-reported disability was measured at multiple timepoints before and after surgery.

Comprehensive review of virtual assistants in vascular surgery.

Virtual assistants, broadly defined as digital services designed to simulate human conversation and provide personalized responses based on user input, have the potential to improve health care by supporting clinicians and patients in terms of diagnosing and managing disease, performing administrative tasks, and supporting medical research and education. These tasks are particularly helpful in vascular surgery, where the clinical and administrative burden is high due to the rising incidence of vascular disease, the medical complexity of the patients, and the potential for innovation and care advancement. The rapid development of artificial intelligence, machine learning, and natural language processing techniques have facilitated the training of large language models, such as GPT-4 (OpenAI), which can support the development of increasingly powerful virtual assistants.

Incidence and relative risk of delirium after major surgery for patients with pre-operative depression: a systematic review and meta-analysis.

Background: Delirium is a common and potentially serious complication after major surgery. A previous history of depression is a known risk factor for experiencing delirium in patients admitted to the hospital, but the generalised risk has not been estimated in surgical patients.

Methods: We conducted a systematic review and meta-analysis of studies reporting the incidence or relative risk (or relative odds) of delirium in the immediate postoperative period for adults with pre-operative depression.

Using Machine Learning to Predict Outcomes Following Transfemoral Carotid Artery Stenting.

Background: Transfemoral carotid artery stenting (TFCAS) carries important perioperative risks. Outcome prediction tools may help guide clinical decision-making but remain limited. We developed machine learning algorithms that predict 1-year stroke or death following TFCAS.

Insurance-Related Disparities in Withdrawal of Life Support and Mortality After Spinal Cord Injury.

Importance: Identifying disparities in health outcomes related to modifiable patient factors can improve patient care.

Objective: To compare likelihood of withdrawal of life-supporting treatment (WLST) and mortality in patients with complete cervical spinal cord injury (SCI) with different types of insurance.

Design, Setting, And Participants: This retrospective cohort study collected data between 2013 and 2020 from 498 trauma centers participating in the Trauma Quality Improvement Program.

Predicting inferior vena cava filter complications using machine learning.

Objective: Inferior vena cava (IVC) filter placement is associated with important long-term complications. Predictive models for filter-related complications may help guide clinical decision-making but remain limited. We developed machine learning (ML) algorithms that predict 1-year IVC filter complications using preoperative data.

Insurance Type and Withdrawal of Life-Sustaining Therapy in Critically Injured Trauma Patients.

Importance: Withdrawal of life-sustaining therapy (WLST) decisions for critically injured trauma patients are complicated and multifactorial, with potential for patients' insurance status to affect decision-making.

Objectives: To determine if patient insurance type (private insurance, Medicaid, and uninsured) is associated with time to WLST in critically injured adults cared for at US trauma centers.

Design, Setting, And Participants: This retrospective registry-based cohort study included reported data from level I and level II trauma centers in the US that participated in the American College of Surgeons Trauma Quality Improvement Program (TQIP) registry.

Intraoperative Hypotension in Patients Having Major Noncardiac Surgery Under General Anesthesia: A Systematic Review of Blood Pressure Optimization Strategies.

Introduction: Intraoperative hypotension is associated with increased risks of postoperative complications. Consequently, a variety of blood pressure optimization strategies have been tested to prevent or promptly treat intraoperative hypotension. We performed a systematic review to summarize randomized controlled trials that evaluated the efficacy of blood pressure optimization interventions in either mitigating exposure to intraoperative hypotension or reducing risks of postoperative complications.

Recent Cannabis Use and Accelerometer-Measured Physical Activity and Sedentary Behavior Among Young-to-Midlife Adults: An Analysis of the National Health and Nutrition Examination Survey from 2011 to 2014.

Cannabis use has been associated with reduced physical activity and increased sedentary behavior in adolescents. In adults, however, there is no conclusive evidence of such an association, and existing studies have primarily relied on self-reported activity measures. As cannabis use increases globally, a deeper understanding of its relationship with activity levels may inform clinical counseling and guidelines.

Ambulatory Cardiology or General Internal Medicine Assessment Prior to Scheduled Major Vascular Surgery is Associated with Improved Outcomes.

Objective: To characterize the association between ambulatory cardiology or general internal medicine (GIM) assessment prior to surgery and outcomes following scheduled major vascular surgery.

Background: Cardiovascular risk assessment and management prior to high-risk surgery remains an evolving area of care.

Methods: This is population-based retrospective cohort study of all adults who underwent scheduled major vascular surgery in Ontario, Canada, April 1, 2004-March 31, 2019.

Incidence and Risk Factors of Chronic Postoperative Pain in Same-day Surgery: A Prospective Cohort Study.

Background: The amount of same-day surgery has increased markedly worldwide in recent decades, but there remains limited evidence on chronic postsurgical pain in this setting.

Methods: This study assessed pain 90 days after ambulatory surgery in an international, multicenter prospective cohort study of patients at least 45 yr old with comorbidities or at least 65 yr old. Pain was assessed using the Brief Pain Inventory.

Days alive and out of hospital for adult female and male cardiac surgery patients: a population-based cohort study.

Background: Research shows women experience higher mortality than men after cardiac surgery but information on sex-differences during postoperative recovery is limited. Days alive and out of hospital (DAH) combines death, readmission and length of stay, and may better quantify sex-differences during recovery. This main objective is to evaluate (i) how DAH at 30-days varies between sex and surgical procedure, (ii) DAH responsiveness to patient and surgical complexity, and (iii) longer-term prognostic value of DAH.

Predicting Outcomes Following Lower Extremity Endovascular Revascularization Using Machine Learning.

Background: Lower extremity endovascular revascularization for peripheral artery disease carries nonnegligible perioperative risks; however, outcome prediction tools remain limited. Using machine learning, we developed automated algorithms that predict 30-day outcomes following lower extremity endovascular revascularization.

Methods And Results: The National Surgical Quality Improvement Program targeted vascular database was used to identify patients who underwent lower extremity endovascular revascularization (angioplasty, stent, or atherectomy) for peripheral artery disease between 2011 and 2021.