Publications by authors named "M W Hatton"
Spinal Injuries and Spine Care in the U.S. Military Health System (2001-Present).
Spine (Phila Pa 1976)
February 2025
Article Synopsis
- This study reviews literature on spinal injuries among military personnel, focusing on both traumatic and repetitive stress injuries that can arise during service.
- It highlights the unique physical requirements and risks military members face, which can lead to different spinal care needs compared to civilians.
- The findings emphasize the importance of updated, long-term research to better understand spinal injuries in light of modern advancements in military technology and medical care.
Article Synopsis
- - The study investigates if expandable transforaminal lumbar interbody fusion (TLIF) cages can effectively increase disc height and segmental lordosis after surgery compared to static cages, while also assessing complication rates associated with both types of cages.
- - A retrospective cohort study was conducted with 417 adult patients who underwent single-level TLIF from 2021 to 2023, with outcomes measured at 2 weeks, 6 months, and 1 year post-surgery.
- - Results indicated that patients with expandable cages showed a significant increase in disc height at both 2 weeks and 6 months compared to those with static cages, suggesting potential benefits of using expandable cages in spinal surgeries.
Palliative Radiotherapy Practice in Lung Cancer: Time to Advance?
Clin Oncol (R Coll Radiol)
December 2024
Background And Purpose: Survival is frequently assessed using Cox proportional hazards (CPH) regression; however, CPH may be too simplistic as it assumes a linear relationship between covariables and the outcome. Alternative, non-linear machine learning (ML)-based approaches, such as random survival forests (RSFs) and, more recently, deep learning (DL) have been proposed; however, these techniques are largely black-box in nature, limiting explainability. We compared CPH, RSF and DL to predict overall survival (OS) of non-small cell lung cancer (NSCLC) patients receiving radiotherapy using pre-treatment covariables.
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- Retroperitoneal sarcomas have a poor prognosis, and it's challenging to accurately characterize them before treatment, which leads to frequent under-grading of the tumours.
- Researchers aimed to create a CT-based radiomics model to predict the histological type and grade of retroperitoneal leiomyosarcoma and liposarcoma, validating their model using patient data from both discovery and independent validation cohorts.
- A total of 170 patients were part of the discovery cohort and 89 in the validation cohort, with median ages of 63 and 59 years, respectively, leading up to promising results in predicting the types and grades of sarcomas.