Snuffbox distal transradial access (dTRA) for arteriovenous fistuloplasty in Singapore: Going distal is safe.

AIM: Arteriovenous fistula (AVF) dysfunction resulting from stenosis or occlusion, is a prevalent issue in end-stage renal failure patients reliant on autogenous AVFs for dialysis. Recently, a distal transradial approach (dTRA) has emerged, offering advantages such as diminished access site complications, better patient comfort and reduced risk of radial artery occlusion. Our study seeks to assess the effectiveness, outcomes and complication rates of employing dTRA for arteriovenous fistuloplasty in Singaporean patients. METHODS: A retrospective review of all dTRA fistuloplasties performed on dysfunctional or slow to mature AVFs from 2017 to 2023 in our institution was performed. Patients with a distal radial artery measuring 2 mm or more with no evidence of occlusion or thrombosis were included. Patients who required central venoplasty or cutting balloon angioplasty were excluded. Outcome measures included technical success, mean procedure duration, complications and post-intervention primary patency at 1, 3 and 6 months. Patients were followed up for 12 months post-intervention. RESULTS: A total of 37 patients were included. 97.3% of patients undergoing dTRA fistuloplasty had radiocephalic fistulas while 2.7% had brachiobasilic fistulas. There was 100% technical success (defined as success in radial artery cannulation, sheath insertion and crossing of stenotic lesions) in our study as all patients successfully underwent fistuloplasty via dTRA approach. One-month patency rate was 97.4%, 3-month patency rate was 92.1% and 6-month patency rate was 86.8%. There were no immediate complications (haematoma, infection, bleeding, pseudoaneurysm, occlusion) of the radial artery post-intervention. CONCLUSION: Our paper illustrates the safety and efficacy of utilising dTRA for arteriovenous fistuloplasty. This approach offers distinct benefits in addressing non-mature or dysfunctional distal forearm arteriovenous fistulas and should be taken into account in anatomically suitable cases.

Risk Prediction of Diabetic Foot Amputation Using Machine Learning and Explainable Artificial Intelligence.

BACKGROUND: Diabetic foot ulcers (DFUs) are serious complications of diabetes which can lead to lower extremity amputations (LEAs). Risk prediction models can identify high-risk patients who can benefit from early intervention. Machine learning (ML) methods have shown promising utility in medical applications. Explainable modeling can help its integration and acceptance. This study aims to develop a risk prediction model using ML algorithms with explainability for LEA in DFU patients. METHODS: This study is a retrospective review of 2559 inpatient DFU episodes in a tertiary institution from 2012 to 2017. Fifty-one features including patient demographics, comorbidities, medication, wound characteristics, and laboratory results were reviewed. Outcome measures were the risk of major LEA, minor LEA and any LEA. Machine learning models were developed for each outcome, with model performance evaluated using receiver operating characteristic (ROC) curves, balanced-accuracy and F1-score. SHapley Additive exPlanations (SHAP) was applied to interpret the model for explainability. RESULTS: Model performance for prediction of major, minor, and any LEA event achieved ROC of 0.820, 0.637, and 0.756, respectively, with XGBoost, XGBoost, and Gradient Boosted Trees algorithms demonstrating best results for each model, respectively. Using SHAP, key features that contributed to the predictions were identified for explainability. Total white cell (TWC) count, comorbidity score and red blood cell count contributed highest weightage to major LEA event. Total white cell, eosinophils, and necrotic eschar in the wound contributed most to any LEA event. CONCLUSIONS: Machine learning algorithms performed well in predicting the risk of LEA in a patient with DFU. Explainability can help provide clinical insights and identify at-risk patients for early intervention.

Managing elderly with colorectal cancer.

The aging population is an increasing healthcare concern in developing countries. In Singapore, 25% of the local population are expected to be older than 65 years old by 2030. Colorectal cancer (CRC) is ranked third most diagnosed cancers worldwide with up to 1.8 million new cases diagnosed in 2018. 60% of newly diagnosed CRC are among patients who are 70 years or older and hence majority of these patients will invariably face challenges with frailty and multiple comorbidities that require appropriate assessment and stratification. The standard of care in patients with stage I or II CRC is surgery with curative intent. For patients with stage III CRC, upfront surgical resection of tumor along with adjuvant chemotherapy is the internationally recommended treatment approach. As for those patients with metastatic disease, they are usually managed within a multidisciplinary team and considered for surgical resection if deemed feasible. Elderly patients are mostly burdened with frailty, functional dependency and existing co-morbidities, all of which are predictors of early postoperative mortality and morbidity in patients with CRC. This article thus aims to review existing evidence to discuss the intricate decision-making process for the surgical management of elderly patient with CRC.