Correlations Between Family History of Psychiatric Illnesses and Outcomes of Spinal Cord Stimulation

The Predicted Outcome of Spinal Cord Stimulation in Patients With a Psychopathological Disorder and Persistent Spinal Pain Syndrome Type 2: A Systematic Review From 2009 to 2021

OBJECTIVES

Psychologic screening is often included as a mandatory component of evaluation of the impact of psychopathology disorders on the predicted outcome of spinal cord stimulation (SCS) for patients with chronic pain due to persistent spinal pain syndrome type 2 (PSPS type 2). The conclusion of such screenings can influence the decision to offer SCS therapy to a patient. However, evidence on the impact of psychopathology on SCS outcomes is still scarce.

MATERIALS AND METHODS

To address this knowledge gap, we systematically reviewed the literature from 2009 to 2021 to explore the correlation between the presence of a psychopathological disorder and the predicted outcome of SCS in patients with PSPS type 2. The literature search was conducted using various online data bases with "failed back surgery syndrome," "psychopathology," and "spinal cord stimulation" used as essential keywords. The identified studies were organized in a Rayyan AI data base, and the quality was analyzed with the Critical Appraisal Skills Program tool.

RESULTS

Our search generated the identification of 468 original articles, of which two prospective and four retrospective studies met our inclusion criteria. These studies reported pain relief, a reduction of symptoms of anxiety and depression, and an improvement in rumination on the Pain Catastrophizing Scale in patients with PSPS type 2 after SCS therapy. The studies also found contradictory outcomes measured using the Oswestry Disability Index, and in terms of the impact of psychopathological disorder on the clinical outcome and revision rate of the SCS system.

CONCLUSION

In this systematic review, we found no convincing evidence that the presence of a psychopathological disorder affects the predicted outcome of SCS therapy in patients with PSPS type 2.

Review of the Treatments for Central Neuropathic Pain

Central neuropathic pain (CNP) affects millions worldwide, with an estimated prevalence of around 10% globally. Although there are a wide variety of treatment options available, due to the complex and multidimensional nature in which CNP arises and presents symptomatically, many patients still experience painful symptoms. Pharmaceutical, surgical, non-invasive, cognitive and combination treatment options offer a generalized starting point for alleviating symptoms; however, a more customized approach may provide greater benefit. Here, we comment on the current treatment options that exist for CNP and further suggest the need for additional research regarding the use of biomarkers to help individualize treatment options for patients.

Development of Machine Learning-Based Models to Predict Treatment Response to Spinal Cord Stimulation

BACKGROUND

Despite spinal cord stimulation's (SCS) proven efficacy, failure rates are high with no clear understanding of which patients benefit long term. Currently, patient selection for SCS is based on the subjective experience of the implanting physician.

OBJECTIVE

To develop machine learning (ML)-based predictive models of long-term SCS response.

METHODS

A combined unsupervised (clustering) and supervised (classification) ML technique was applied on a prospectively collected cohort of 151 patients, which included 31 features. Clusters identified using unsupervised K-means clustering were fitted with individualized predictive models of logistic regression, random forest, and XGBoost.

RESULTS

Two distinct clusters were found, and patients in the cohorts significantly differed in age, duration of chronic pain, preoperative numeric rating scale, and preoperative pain catastrophizing scale scores. Using the 10 most influential features, logistic regression predictive models with a nested cross-validation demonstrated the highest overall performance with the area under the curve of 0.757 and 0.708 for each respective cluster.

CONCLUSION

This combined unsupervised-supervised learning approach yielded high predictive performance, suggesting that advanced ML-derived approaches have potential to be used as a functional clinical tool to improve long-term SCS outcomes. Further studies are needed for optimization and external validation of these models.

Can dogs and cats really help our spinal cord stimulation patients?

OBJECTIVES

Pet ownership has been shown to decrease morbidity and mortality in several aspects of health but has not been studied in chronic pain patients. We evaluate whether subjects who underwent spinal cord stimulation (SCS) and own a pet have improved outcomes compared to non-pet owners.

METHODS

After obtaining IRB approval, we re-contacted 38 subjects who underwent SCS surgery with preoperative and 1-year postoperative data on Numerical Rating Scale (NRS), McGill Pain Questionnaire (MPQ), Oswestry Disability Index (ODI), Beck Depression Inventory (BDI), and Pain Catastrophizing scale (PCS). We examined influence of pets and pet ownership-specific behaviors on improvement in SCS outcomes.

RESULTS

Patients included 24 males/14 females with a mean age of 59.9 ± 11.5 years. At mean follow-up of 12.2 months (range 10-14), there were improvements in NRS, ODI, BDI, PCS and MPQ. Twenty subjects owned pets and 18 did not; all believed pet ownership could improve health. Pet owners improved more on NRS-right now (p = 0.05) and BDI (p = 0.05), and were more satisfied with SCS (p = 0.04). No significant improvement was seen in ODI, MPQ, or PCS. However, PCS did improve in pet owners who exercised their pet (PCS-total, p < 0.01; PCS-helplessness, p < 0.01; PCS-rumination, p = 0.05; PCS-magnification, p = 0.02).

CONCLUSIONS

We provide preliminary evidence that pet ownership is associated with improved pain, depression and SCS satisfaction. Exercising with a pet also appears to be beneficial in limiting pain catastrophizing. Pets show promise as a novel means to improve patient SCS outcomes.