Post-mastectomy pain syndrome (PMPS) is a common and often debilitating condition. The syndrome is defined by chest wall pain unresponsive to standard pain medications and the presence of exquisite point tenderness along the inframammary fold at the site of the T4 and T5 cutaneous intercostal nerve branches as they exit from the chest wall. Pressure at the site triggers and reproduces the patient's spontaneous or motion-evoked pain. The likely pathogenesis is neuroma formation after injury to the T4 and T5 intercostal nerves during breast surgery. We assessed the rate of long-term resolution of post-mastectomy pain after trigger point injections (2 mL of 1:1 mixture of 0.5% bupivacaine and 4 mg/mL dexamethasone) to relieve neuropathic pain in a prospective single-arm cohort study. Fifty-two women (aged 31-92) who underwent partial mastectomy with reduction mammoplasty or mastectomy with or without reconstruction, and who presented with PMPS were enrolled at the University of California San Francisco Breast Care Center from August 2010 through April 2018. The primary outcome was a long-term resolution of pain, defined as significant or complete relief of pain for greater than 3 months. A total of 91 trigger points were treated with mean follow-up 43.9 months with a 91.2% (83/91) success rate. Among those with a long-term resolution of pain, 60 trigger points (72.3%) required a single injection to achieve long-lasting relief. Perineural infiltration with bupivacaine and dexamethasone is a safe, simple, and effective treatment for PMPS presenting as trigger point pain along the inframammary fold.

Object

Ependymomas are a common type of CNS tumor in children, although only 13% originate from the spinal cord. Aside from location and extent of resection, the factors that affect outcome are not well understood.

Methods

The authors performed a search of an institutional neuropathology database to identify all patients with spinal cord ependymomas treated over the past 20 years. Data on patient age, sex, clinical presentation, symptom duration, tumor location, extent of resection, use of radiation therapy, surgical complications, presence of tumor recurrence, duration of follow-up, and residual symptoms were collected. Pediatric patients were defined as those 21 years of age or younger at diagnosis. The extent of resection was defined by the findings of the postoperative MR images.

Results

A total of 24 pediatric patients with spinal cord ependymomas were identified with the following pathological subtypes: 14 classic (Grade II), 8 myxopapillary (Grade I), and 2 anaplastic (Grade III) ependymomas. Both anaplastic ependymomas originated in the intracranial compartment and spread to the spinal cord at recurrence. The mean follow-up duration for patients with classic and myxopapillary ependymomas was 63 and 45 months, respectively. Seven patients with classic ependymomas underwent gross-total resection (GTR), while 4 received subtotal resection (STR), 2 received STR as well as radiation therapy, and 1 received radiation therapy alone. All but 1 patient with myxopapillary ependymomas underwent GTR. Three recurrences were identified in the Grade II group at 45, 48, and 228 months. A single recurrence was identified in the Grade I group at 71 months. The mean progression-free survival (PFS) was 58 months in the Grade II group and 45 months in the Grade I group.

Conclusions

Extent of resection is an important prognostic factor in all pediatric spinal cord ependymomas, particularly Grade II ependymomas. These data suggest that achieving GTR is more difficult in the upper spinal cord, making tumor location another important factor. Although classified as Grade I lesions, myxopapillary ependymomas had similar outcomes when compared with classic (Grade II) ependymomas, particularly with respect to PFS. Long-term complications or new neurological deficits were rare. Among patients with long-term follow-up, those who underwent GTR had a recurrence rate of 20% compared with 40% among those with STR or biopsy only, suggesting that extent of resection is perhaps a more important prognostic factor than histological grade in predicting PFS, which has been suggested by other data in the literature. Given the relative paucity of these lesions, collaborative multiinstitutional studies are needed, and such efforts should also focus on molecular and genetic analysis to refine the current classification system.

Objective

The use of telemedicine has dramatically increased due to the coronavirus disease 2019 pandemic. Many neurosurgeons are now using telemedicine technologies for preoperative evaluations and routine outpatient visits. Our goal was to standardize the telemedicine motor neurologic examination, summarize the evidence surrounding clinical use of telehealth technologies, and discuss financial and legal considerations.

Methods

We identified a 12-member panel composed of spine surgeons, fellows, and senior residents at a single institution. We created an initial telehealth strength examination protocol based on published data and developed 10 agree/disagree statements summarizing the protocol. A blinded Delphi method was utilized to build consensus for each statement, defined as > 80% agreement and no significant disagreement using a 2-way binomial test (significance threshold of p < 0.05). Any statement that did not meet consensus was edited and iteratively resubmitted to the panel until consensus was achieved. In the final round, the panel was unblinded and the protocol was finalized.

Results

After the first round, 4/10 statements failed to meet consensus ( < 80% agreement, and p = 0.031, p = 0.031, p = 0.003, and p = 0.031 statistical disagreement, respectively). The disagreement pertained to grading of strength of the upper (3/10 statements) and lower extremities (1/10 statement). The amended statements clarified strength grading, achieved consensus ( > 80% agreement, p > 0.05 disagreement), and were used to create the final telehealth strength examination protocol.

Conclusion

The resulting protocol was used in our clinic to standardize the telehealth strength examination. This protocol, as well as our summary of telehealth clinical practice, should aid neurosurgical clinics in integrating telemedicine modalities into their practice.

Artificial intelligence and machine learning (AI/ML) is becoming increasingly more accessible to biomedical researchers with significant potential to transform biomedicine through optimization of highly-accurate predictive models and enabling better understanding of disease biology. Automated machine learning (AutoML) in particular is positioned to democratize artificial intelligence (AI) by reducing the amount of human input and ML expertise needed. However, successful translation of AI/ML in biomedicine requires moving beyond optimizing only for prediction accuracy and towards establishing reproducible clinical and biological inferences. This is especially challenging for clinical studies on rare disorders where the smaller patient cohorts and corresponding sample size is an obstacle for reproducible modeling results. Here, we present a model-agnostic framework to reinforce AutoML using strategies and tools of explainable and reproducible AI, including novel metrics to assess model reproducibility. The framework enables clinicians to interpret AutoML-generated models for clinical and biological verifiability and consequently integrate domain expertise during model development. We applied the framework towards spinal cord injury prognostication to optimize the intraoperative hemodynamic range during injury-related surgery and additionally identified a strong detrimental relationship between intraoperative hypertension and patient outcome. Furthermore, our analysis captured how evolving clinical practices such as faster time-to-surgery and blood pressure management affect clinical model development. Altogether, we illustrate how expert-augmented AutoML improves inferential reproducibility for biomedical discovery and can ultimately build trust in AI processes towards effective clinical integration.

Diagnosis of spinal cord injury (SCI) severity at the ultra-acute stage is of great importance for emergency clinical care of patients as well as for potential enrollment into clinical trials. The lack of a diagnostic biomarker for SCI has played a major role in the poor results of clinical trials. We analyzed global gene expression in peripheral white blood cells during the acute injury phase and identified 197 genes whose expression changed after SCI compared with healthy and trauma controls and in direct relation to SCI severity. Unsupervised coexpression network analysis identified several gene modules that predicted injury severity (AIS grades) with an overall accuracy of 72.7% and included signatures of immune cell subtypes. Specifically, for complete SCIs (AIS A), ROC analysis showed impressive specificity and sensitivity (AUC: 0.865). Similar precision was also shown for AIS D SCIs (AUC: 0.938). Our findings indicate that global transcriptomic changes in peripheral blood cells have diagnostic and potentially prognostic value for SCI severity.