"I am not pain, I have pain": A pilot study examining iRest yoga nidra as a mind-body intervention for persistent pain.

Purpose: This pilot study was the first of its kind to examine the experiences of people with persistent pain engaging in a six-week iRest for Pain group program as part of multidisciplinary pain care.

Method: The present study used a qualitative, phenomenological design and reflexive thematic analysis to gain an understanding of the firsthand experience of patients who participated in the iRest for Pain group program. This program was offered in a specialist outpatient pain management service within a regional public hospital in Victoria, Australia.

Machine-learning versus traditional methods for prediction of all-cause mortality after transcatheter aortic valve implantation: a systematic review and meta-analysis.

Background: Accurate mortality prediction following transcatheter aortic valve implantation (TAVI) is essential for mitigating risk, shared decision-making and periprocedural planning. Surgical risk models have demonstrated modest discriminative value for patients undergoing TAVI and are typically poorly calibrated, with incremental improvements seen in TAVI-specific models. Machine learning (ML) models offer an alternative risk stratification that may offer improved predictive accuracy.

Developing, Piloting and Evaluating a Patient Support Portal for Men With Prostate Cancer in Victoria: An Action Research Study.

Introduction: Men with prostate cancer (PCa) and their support providers face challenges in accessing high-quality, impartial information tailored to their specific needs to enhance their overall care and decision-making. We describe the development, piloting and evaluation of the co-designed web portal 'BroSupPORT'.

Methods: IT teams developed and integrated BroSupPORT into the Victorian Prostate Cancer Outcomes Registry (PCOR-Vic) electronic patient-reported outcome follow-up process.