Spinal cord injury (SCI) is a devastating condition that affects millions of people worldwide. While significant strides have been made in the field of SCI research over the past few decades, regaining lost neurologic function remains a major challenge. However, recent advances in neuroprotective and regenerative therapies, as well as neuromodulation strategies, hold great promise in revolutionizing the way we manage and treat SCI. In addition, the development of biomarkers and advanced measurement tools, as well as the use of machine learning algorithms, are changing the landscape of SCI prognostication and treatment. These advances have the potential to improve the lives of individuals with SCI and their caregivers. A brief overview of some of these advances include:
Changing Demographics: SCI used to affect younger people due to high-velocity accidents such as car crashes, but now it increasingly affects older people due to low-velocity falls. As a result, the public health system needs to adapt to address the needs of the aging population, which may have different comorbidities and require different types of care.
Hemodynamic Management: Maintaining spinal cord perfusion, or blood flow to the spinal cord, is important after an SCI. This can be achieved by supporting mean arterial pressure (MAP), which is the average pressure in the arteries during one cardiac cycle. New invasive technologies are being investigated to guide blood pressure management, which could optimize hemodynamic management and improve patient outcomes.
Timing of Surgical Intervention: Early surgery within 24 hours of injury enhances neurologic recovery, but further research is needed to identify which patients benefit from surgery and the optimal timing of intervention. Some patients may not be suitable for surgery due to other health conditions, and there is a risk of complications from surgery.
Biomarkers: Despite progress in SCI treatment, patients with similar SCIs show variable recovery outcomes. Biomarkers, which are measurable indicators of biological processes or disease, can help stratify patients who are most likely to benefit from neuroprotective or neuroregenerative therapies. For example, serological and genetic biomarkers may influence clinical outcomes. Inflammatory and structural protein biomarkers may predict AIS grade recovery and motor score improvement in acute traumatic SCI patients. Advanced imaging techniques, such as microstructural MRI, can also predict outcomes in patients with traumatic SCIs. a spinal cord lesion evolves and enlarges over time, and biomarkers can help stratify injury severity, improve prognostication of neurologic recovery, and guide personalized SCI care.
Neuroprotective Therapeutics: Neuroprotective therapies aim to prevent further damage after an SCI. However, patients with severe SCI may not benefit as much from neuroprotective therapies as those with less severe SCI. Combining different neuroprotective therapies can optimize the effectiveness of these therapies.
Advances in Neuroregenerative Therapeutics: There are barriers to regenerating the spinal cord after an SCI, but clinical trials have developed neuroregenerative strategies that target different aspects of the injury, such as loss of cells and inhibitory microenvironments. Personalized stem cell treatments are on the horizon, including cells designed to address specific neurologic deficits. Biomarkers can be used to identify which patients will benefit most from these therapies.
Advances in Neuromodulation: Neuromodulation therapies aim to restore communication between the brain and spinal cord after an SCI. Spinal cord stimulation combined with intense rehabilitation has shown promise in promoting ambulation and stepping in patients with chronic SCI. Brain machine or brain spine interfaces bypass the disrupted communication between brain and spinal circuits, providing patients with the ability to move. These advances in neuromodulation could revolutionize SCI treatment and improve patient outcomes.
Detection of Treatment Effects and Prognostication: Assessment and prediction tools can help guide patient management and assess the effectiveness of novel therapies. Capturing positive treatment effects of investigative therapies is a challenge in clinical trial design, but machine learning algorithms can help predict outcomes for SCI patients and guide clinical decision-making. These advanced tools could improve the efficiency and efficacy of SCI treatment, ultimately leading to better outcomes for patients.
In conclusion, while SCI remains a challenging and devastating condition, advances in research have given rise to promising new treatments and management strategies. With ongoing progress in identifying biomarkers, developing neuroprotective and regenerative therapies, and advancing neuromodulation techniques, there is hope for improved outcomes and quality of life for individuals with SCI and a future in which SCI is no longer a life-altering injury but a manageable condition.
Reference:
Fehlings MG, Pedro K, Hejrati N. Management of Acute Spinal Cord Injury: Where Have We Been? Where Are We Now? Where Are We Going? Journal of Neurotrauma. (2022).