Publications by authors named "B M J Martens"

Background: Anterior column realignment (ACR), using a lateral lumbar or thoracic interbody fusion (LLIF) approach to release the anterior longitudinal ligament (ALL), is a powerful technique to increase segmental lordosis. We here report our experience with the use of expandible LLIF cages for ACR.

Methods: Retrospective, single-center observational cohort study including consecutive patients treated by LLIF using an expandible interbody implant.

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Understanding variables that influence antibody responses to COVID-19 vaccination within a population can provide valuable information on future vaccination strategies. In this population-based study, we examined the antibody responses to COVID-19 vaccination in Manitoba using residual serum specimens collected between January 2021 and March 2022 (n = 20,365). Samples were tested for spike and nucleocapsid IgG against SARS-CoV-2 using clinically validated assays.

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Purpose: To report on the failure rates of an expandable interbody spacer, used for spinal instrumented transforaminal lumbar interbody fusion (TLIF) or posterior thoracolumbar interbody fusion (PLIF).

Methods: In this retrospective, single-center observational cohort study we reviewed consecutive PLIF/TLIF patients using the Catalyft™ PL and PL40 expandable titanium interbody implant (Medtronic, Minneapolis (USA)) between 07/2022 and 11/2023. We recorded patient demographics, surgical parameters, adverse events, radiological parameters and clinical outcomes according to the MacNab criteria.

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Article Synopsis
  • - Atrial fibrillation is the most common heart arrhythmia in adults, significantly contributing to heart-related health issues and deaths.
  • - The EAST-AFNET 4 trial shows that early rhythm control, particularly through catheter ablation, improves cardiovascular outcomes more than standard care, especially in patients with multiple health issues.
  • - Research from studies like STOP-AF First and Cryo-FIRST indicates that catheter ablation is more effective than drugs in maintaining normal heart rhythm, prompting a shift towards prioritizing this approach in treatment.
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Objectives: Body composition assessment using CT images at the L3-level is increasingly applied in cancer research and has been shown to be strongly associated with long-term survival. Robust high-throughput automated segmentation is key to assess large patient cohorts and to support implementation of body composition analysis into routine clinical practice. We trained and externally validated a deep learning neural network (DLNN) to automatically segment L3-CT images.

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