Subarachnoid hemorrhage (SAH) is a devastating subtype of stroke that represents a significant global health burden and causes permanent disability in approximately 30% of survivors (D’Souza, 2015; Weir, 2002; Zhang et al., 2023). Early brain injury can occur within the first 24–48 hr after ictus, which involves a cascade of elevated intracranial pressure (ICP) and a subsequent drop of cerebral perfusion (Schneider et al., 2018). Systemic and local inflammation, cerebral edema, blood–brain barrier disruption, sympathetic nervous system activation, autoregulatory failure, microthrombosis, spreading depolarizations, and inflammation have all been observed during this period (Macdonald et al., 2012; Budohoski et al., 2013). These biological processes result in the inability of cerebral perfusion to match metabolic demands, leading to secondary brain injury and delayed cerebral ischemia that typically occurs between 5 and 14 days after the SAH (Provencio, 2013; van Gijn et al., 2007; Tracey, 2002; Lv et al., 2018). Delayed cerebral ischemia and deleterious inflammation are major predictors of poor outcomes and morbidity. The autonomic nervous system (ANS), comprising the sympathetic and the parasympathetic nervous system, plays a critical role in maintaining physiological homeostasis. SAH is believed to cause sympathetic predominance, which plays a key role in the development of cerebral vasospasm, renders patients more susceptible to non-neurological complications, and exacerbates deleterious inflammatory processes (Naredi et al., 2000).

Numerous interventions have been explored to address the complex pathologies of SAH that contribute to secondary brain injury, aiming to improve patient outcomes (Provencio and Vora, 2005). Transcutaneous auricular vagus nerve stimulation (taVNS) is one of the most promising therapeutic options, as recent studies have demonstrated its efficacy in reducing inflammation, improving autonomic balance, and enhancing brain plasticity (Wu et al., 2023; Bonaz et al., 2016; Meyers et al., 2018; Provencio and Vora, 2005; Huguenard et al., 2023). The auricular branch of the vagus nerve is a sensory nerve that innervates the external ear, including the cymba concha. Stimulating the auricular branch of the vagus nerve has been shown to activate the same brain regions as cervical vagus nerve stimulation (Frangos et al., 2015). Specifically, taVNS mediates cholinergic signaling and regulates pro-inflammatory responses via the inflammatory reflex (Figure 1A; Sahn et al., 2023; Pavlov and Tracey, 2012) In this reflex, inflammatory mediators such as cytokines trigger afferent vagus nerve signaling. This afferent signal then prompts an efferent response from the vagus nerve that acts to reduce the production of pro-inflammatory cytokines (Tynan et al., 2022).

Figure 1

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The vagus nerve also mediates cardiovascular function by regulating the autonomic system and metabolic homeostasis (Figure 1A; Keute et al., 2021). Theoretically, taVNS increases parasympathetic activity, which can be measured as increased heart rate variability (HRV). While some animal studies have reported a potential risk of bradycardia and decreased blood pressure associated with vagus nerve stimulation, two reviews of human studies have considered the cardiovascular effects of taVNS generally safe, with adverse effects reported only in patients with pre-existing heart diseases (Naggar et al., 2014; Hua et al., 2023; Kim et al., 2022). However, its cardiovascular effect in SAH patients is largely unknown. Given that critically ill patients, such as those with SAH, are extremely vulnerable to cardiovascular complications, it is essential to thoroughly examine the cardiovascular implications of taVNS to ensure its safety in this fragile population. This is particularly notable as cardiovascular abnormalities following SAH, such as prolonged elevated heart rate and QT prolongation, are associated with an increased risk of poor outcomes (Norberg et al., 2018; Schmidt et al., 2014; Zhang and Qi, 2016; van der Bilt et al., 2009). However, our limited understanding of these effects constitutes a significant barrier, preventing the advancement of taVNS from a promising therapeutic approach to an established clinical treatment for SAH. To address this gap, we assessed the effects of acute and repetitive taVNS on cardiovascular function based on electrocardiogram (ECG) and other monitored vital signs from SAH patients in the intensive care unit (ICU). The current study is part of the NAVSaH trial (NCT04557618) and focuses on the trial’s secondary outcomes, including heart rate, QT interval, HRV, and blood pressure (Huguenard et al., 2024a). This interim analysis aims to evaluate the cardiovascular safety of the taVNS protocol and to provide insights that will inform the application of taVNS in SAH patients. The primary outcomes of this trial, including change in the inflammatory cytokine tumor necrosis factor-alpha (TNF-α) and rate of radiographic vasospasm, are available as a pre-print and currently under review (Huguenard et al., 2024b). Based on a meta-analysis, most aversive effects were seen in repeated sessions lasting 60 min or more; therefore, we hypothesized that repetitive taVNS increased HRV but did not cause bradycardia and QT prolongation (Kim et al., 2022). To test this hypothesis, we compared changes in cardiovascular metrics at the phase of early brain injury (within 72 hr) and at the phase when delayed cerebral ischemia develops (after Day 4) between patients receiving taVNS and sham treatments. Root mean square of successive differences (RMSSD) and the standard deviation of normal RR intervals (SDNN) are two commonly used HRV metrics. RMSSD indicates parasympathetic activity, while lower SDNN is associated with increased cardiac risk (Kleiger et al., 2005; Shaffer and Ginsberg, 2017). Providing effective taVNS treatment modulates the autonomic system, we propose that heart rate or HRV following acute taVNS could inform which SAH patients may experience the most clinical benefit from taVNS treatment. To explore this possibility, we correlated the changes in heart rate and HRV following acute taVNS treatment and changes in the modified Rankin Score (mRS), which measures the degree of disability or dependence in the daily activities of people suffering from neurological disability.

Twenty-four participants were randomized to receive the taVNS (N = 11) or Sham (N = 13) treatment (Table 1, Figure 2—figure supplement 2). Appendix 3—table 1 shows the clinical characteristics of the two treatment groups. The participants, the medical team who dictated all management decisions for the patient’s SAH, and the outcomes assessors who assigned mRS at admission and discharge were blinded to the treatment. The structure of this study is shown in Figure 1B. Following randomization, enrolled patients underwent 20 min of either taVNS or sham stimulation twice daily during their stay in the ICU. This treatment schedule was informed by findings from Addorisio et al., where a 5-min taVNS protocol was administered twice daily to patients with rheumatoid arthritis for 2 days (Addorisio et al., 2019). Their study found that circulating C-reactive protein levels significantly reduced after 2 days of treatment but returned to baseline at the second clinical assessment by Day 7. Given the high inflammatory state associated with SAH and our intention to maintain a steady reduction in inflammation, we decided to extend the treatment duration to 20 min per session. During treatment periods, a portable transcutaneous electrical nerve stimulation (TENS) device (TENS 7000 Digital TENS Unit, Compass Health Brands, OH, USA) was connected to the patient’s left ear using two ear clips (Figure 1C, D). For taVNS treatments, these ear clips were placed along the concha of the ear, while for sham treatments, the clips were placed along the earlobe to avoid stimulation of the auricular vagus nerve from tactile pressure (Figure 1C). For the taVNS group, stimulation parameters were selected based on values reported in prior studies that sought to maximize vagus somatosensory evoked potentials while avoiding the perception of pain: 20 Hz frequency, 250 µs pulse width, and 0.4 mA intensity (de Gurtubay et al., 2021). The stimulation parameters were designed to be imperceptible to the patients, and there were no reports of detection of taVNS, suggesting the success of the blinding. No electrical current was delivered during sham treatments. Please see Huguenard et al., 2024a for a detailed protocol of this study.

Effects of repetitive taVNS on cardiac function

A study has shown that 15 min of taVNS reduced sympathetic activity in healthy individuals, with effects that persist during the recovery period (Clancy et al., 2014). This finding suggests that taVNS may exert long-term effects on cardiovascular function. Therefore, we investigated whether repetitive taVNS treatment affects heart rate and QT interval, key indicators of bradycardia or QT prolongation, using 24-hr ECG recording. We found no significant differences in heart rate between groups (Figure 2D, Mann–Whitney U test, N(taVNS) = 94, N(Sham) = 95, p-value = 0.69, Cohen’s d = −0.01, W-statistics = 4317, power = 0.93). Changes in heart rate from Day 1 were equivalent between groups (two-tailed equivalence tests, p[lower threshold] = 0.006, test statistics[lower threshold] = 2.53; p[lower threshold] = 0.004, test statistics[lower threshold] = −2.72, N(VNS) = 94, N(VNS) = 95). We further confirmed that changes in heart rate were similar between treatment groups following SAH (Figure 2D, |Cohen’s d|<0.2 for Days 2–4, 5–8, 8–10, and 11–13). Moreover, changes in corrected QT interval from Day 1 were significantly higher in the Sham group compared to the taVNS group (Figure 2E, Mann–Whitney U test, N(taVNS) = 94, N(Sham) = 95, p-value <0.001, Cohen’s d = −0.57). Similarly, uncorrected QT intervals from Day 1 were higher in the Sham group (Figure 2—figure supplement 1, Cohen’s d = −0.42). After the phase of early brain injury, the mean and median corrected QT interval were lower in the taVNS group with large effect sizes (Figure 2E, |Cohen’s d| >0.5). To ensure that repetitive taVNS did not lead to QT prolongation outside the stimulation period, we calculated the percentage of prolonged QT intervals. Prolonged QT intervals were defined as corrected QT interval ≥500 ms. We found that changes in prolonged QT intervals percentage from Day 1 were higher in the Sham group (Figure 2F, Mann–Whitney U test, N(taVNS) = 94, N(Sham) = 95, p-value <0.001, Cohen’s d = −0.72).

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Subsequently, we investigated the effect of taVNS treatment on RMSSD and SDNN. We found that changes in SDNN using Day 1 as baseline were not significantly different between the treatment groups (T-test, N(taVNS) = 94, N(Sham) = 95, p = 0.479, Cohen’s d = 0.10, t statistics = 0.71, Figure 3A). Changes in RMSSD using Day 1 as baseline were significantly higher in the taVNS treatment group (T-test, N(taVNS) = 94, N(Sham) = 95, Bonferroni-corrected p = 0.025, Cohen’s d = 0.42, t statistics = 2.91, Figure 3B). We further studied the effects of taVNS in different phases following SAH. Figure 3A-B show the changes in SDNN and RMSSD in bins of 3 days for the two treatment groups. The taVNS treatment increased RMSSD over the course of the treatment, with a smaller effect size (Cohen’s d = 0.29) observed between Days 2 and 4, corresponding to the early brain injury phase, and large effect sizes at the later phases (Cohen’s d = 0.41 for Days 5–7, Cohen’s d = 0.54 for Days 8–10, Cohen’s d = 0.66 for Days 11–13). We further tested if the RMSSD reduction rate was greater in the Sham treatment group with a linear regression model: RMSSD change ~Day * Treatment. The results show that the RMSSD reduced slower in the taVNS treatment group when compared to the sham treatment, but this trend did not reach significance (coefficient of taVNS * Day interaction effect = 2.00, p = 0.21, Figure 3—figure supplement 1).

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RMSSD and SDNN are two of the most commonly used methods for quantifying HRV. Bartlett’s test indicated that there are significant correlations among these measures (p < 0.01, Figure 3C). To analyze the effect of taVNS treatment on the autonomic system, we used factor analysis to identify the underlying factors. We focused on the two factors with the greatest eigenvalue. Figure 3D shows the factor loading, that is, the variance explained by HRV metrics on the two factors. The first factor correlates positively with metrics representing variability, including RMSSD, SDNN, pNNI_50, and total power, and therefore has been termed overall HRV. The second factor correlated positively with RMSSD and normalized high-frequency power, representing parasympathetic activity, and negatively correlated with the cardiac sympathetic index (CSI). Hence, it is termed parasympathetic activity. Overall HRV change from Day 1 was significantly higher in the VNS group (Figure 3E, Mann–Whitney U test, N(taVNS) = 94, N(Sham) = 95, p-value = 0.04, Cohen’s d = 0.37). The effect size was trivial between Days 2 and 4 and increased over the course of treatment. The parasympathetic activity was also significantly higher in the VNS treatment group, and we observed the largest effect size between Days 2 and 4 (Cohen’s d = 0.50, Figure 3F).

We also investigated the potential association between clinical outcomes, as measured by changes in the mRS from admission to discharge, and HRV metrics. We found that heart rate was lower in patients with improved mRS (i.e., <0) (Mann–Whitney U test, N(mRS < 0) = 122, N(mRS > 0) = 98, p-value <0.01, Cohen’s d = −0.54). Parasympathetic activity, overall HRV, and corrected QT interval did not differ significantly between patients with improved mRS and patients with worsened mRS (Figure 3—figure supplement 4).

Effects of repetitive taVNS on vascular function

Elevated blood pressure is a common occurrence in SAH and is linked with a higher risk of re-rupture of cerebral aneurysms and vasospasm (Minhas et al., 2022; Hosmann et al., 2020). In this study, patients in both treatment groups received medical treatment determined by the medical team, including vasopressors and medication for blood pressure management. We investigated whether taVNS induced any additional blood pressure changes beyond those managed by the medical team. We found that the median and mean blood pressure change from the first hospitalized day were greater than 0 for both treatment groups (Figure 4B). No significant differences were detected in changes in blood pressure and ICP between the treatment groups (Figure 4B, C). Equivalence testing confirmed that the ICP changes from the first hospitalization day were not significantly different between treatment groups, with a 2-mmHg equivalence margin (two one-sided t-tests, p[lower threshold] = 3.66 × 10⁻¹³, t[lower threshold] = 8.07; p[upper threshold] = 3.33 × 10⁻¹⁰, t[upper threshold] = −6.73). Equivalence testing also indicated that there were no significant different changes in blood pressure between treatment groups (two one-sided t-tests, p[lower threshold] = 0.07, t[lower threshold] = 1.51; p[upper threshold] = 0.002, t[upper threshold] = −3.00). We further verified that there were no significant changes in arterial line blood pressure obtained via continuous invasive monitoring between treatment groups (Figure 4—figure supplement 1). We subsequently compared the plethysmography peripheral perfusion index (PPI) between the treatment groups as it is a proxy metric for cardiac stroke volume and vascular tone (Elshal et al., 2021; Coutrot et al., 2021). We found that PPI change was significantly lower (Mann–Whitney U test, N(taVNS) = 83, N(Sham) = 95, Bonferroni corrected p < 0.01, Cohen’s d = −0.49). In addition, respiration rate change was significantly higher (Mann–Whitney U test, N(taVNS) = 94, N(Sham) = 95, Bonferroni corrected p = 0.02, Cohen’s d = 0.37) in the taVNS group, as compared to the Sham group (Figure 4D, E). We hypothesized that the increase in respiratory rate was a compensatory mechanism to ensure similar oxygen delivery. We found a significant negative correlation between changes in PPI and changes in respiration rate only for the taVNS treatment group (Pearson correlation coefficient = −0.37, p < 0.001, t-test, Figure 4—figure supplement 1D). The Pearson correlation coefficient for the sham treatment group is −0.08 (p = 0.36).

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Acute effects of taVNS on cardiovascular function

Assessing the acute effect of taVNS on cardiovascular is crucial for its safe translation into clinical practice. We compared the acute change of heart rate, corrected QT interval, and HRV between treatment groups, as abrupt changes in the pacing cycle may increase the risk of arrhythmias (Zaniboni, 2024). The change in heart rate from treatment onset is shown in Figure 5B. We subsequently tested whether taVNS affects changes in heart rate between post- and pre-treatment. We found that the changes in heart rate were not significantly different between treatment groups although heart rate increased in the taVNS group (Wilcoxon rank-sum test, N = 188, Bonferroni corrected p = 0.03, Cohen’s d = 0.11) but not in the Sham group (Wilcoxon signed-rank test, N = 199, Bonferroni corrected p = 0.72, Cohen’s d = 0.00) (Figure 5C). However, the increase in heart rate after taVNS was within 0.5 standard deviations of daily heart rate. There were no significant differences in changes in corrected QT interval or HRV, as measured by RMSSD, SDNN, and relative power of high-frequency band between treatment groups (Figure 5D, E, Figure 5—figure supplements 1 and 3). Figure 2—figure supplement 1C shows the acute changes in uncorrected QT interval. Appendix 3—table 1 summarizes the absolute changes in cardiovascular metrics for the treatment groups. We further asked whether heart rate can serve as a biomarker that indicates which SAH patients would receive the greatest benefit from continuing taVNS treatment. We investigated the relationship between changes in heart rate from pre- to post-taVNS treatment and changes in mRS between admission and discharge using a linear mixed-effects model. In this model, the treatment group, mRS change, and their interaction were included as fixed effects, while subject was included as a random effect. Our analysis revealed that the slope between changes in heart rate and changes in mRS is significantly more negative for the taVNS treatment group (Table 2). This finding suggests that an increase in heart rate following acute taVNS treatment is associated with improved clinical outcomes (Figure 5F). Post hoc analysis showed that patients in the taVNS treatment group who had an improvement in mRS of –2 or greater compared to other patients had significantly greater increases in heart rate (Mann–Whitney U test, p = 0.02, N(mRS change < −1) = 53, N(mRS change ≥ −1) = 135, Cohen’s d = 0.34, Figure 5—figure supplement 1C). Conversely, HRV change, represented by RMSSD, was not significantly different based on mRS in SAH patients (Figure 5—figure supplement 1D).

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Table 2

Model	${\displaystyle H{R}_{subject,treatment}\left(mRS\right)={\beta }_0+{\beta }_{taVNS}\times 1_{treatment=taVNS}+}$${\displaystyle \left({\beta }_{mRS}+{\beta }_{taVNS,slope}\times 1_{treatment=taVNS}\right)\times mRS+u_{subject}}$
	Coefficient	p-value	95% confidence interval
${\beta }_0$	0.73	0.211	−0.41 to 1.87
${\beta }_{taVNS}$	−0.29	0.737	−1.95 to 1.38
${\beta }_{mRS}$	1.47	0.006	0.43 to 2.51
${\beta }_{taVNS,slope}$	−1.85	0.005	−3.12 to 0.57

1. Bold values denote statistical significance at the p < 0.05 level.

Subsequently, we compared changes in blood pressure, PPI, ICP, and respiration rate from pre- to post-treatment periods between treatment groups. We found that changes in PPI and blood pressure were significantly higher in the taVNS group, as compared to the Sham group (Mann–Whitney U test, blood pressure: p = 0.03, Cohen’s d = 0.22, N = 180 for Sham and 159 for taVNS; PPI: p < 0.01, Cohen’s d = 0.19, N = 227 for Sham and 186 for taVNS, Figure 5—figure supplement 2). Only PPI remained significantly different between treatment groups after Bonferroni correction. The acute changes in PPI and blood pressure remained within the daily standard deviation. No significant differences in post-treatment changes in ICP or respiration rate were observed between treatment groups.

This study examined the effects of taVNS on cardiovascular function in patients with SAH. We investigated both the cumulative and acute impacts of taVNS. The findings in our study indicate that repetitive taVNS is not associated with previously suggested risks, such as bradycardia and QT prolongation. Furthermore, repetitive taVNS treatment increased overall HRV and parasympathetic activity, which are indicators of a healthy cardiovascular system. When looking at the acute effects, taVNS only significantly increased the PPI but not heart rate, HRV, corrected QT interval, blood pressure, or ICP. The findings are summarized in Table 3. Interestingly, we found that heart rate can serve as a biomarker for identifying SAH patients who are most likely to benefit from taVNS treatment. Collectively, this study substantiates the safety of treating SAH patients with taVNS and provides foundational data for future efforts to optimize and translate taVNS therapy toward clinical use.

All relevant data has been made publicly available on Dryad at https://doi.org/10.5061/dryad.rfj6q57kw. Codes for generating the figures are available at https://github.com/GanshengT/taVNS_SAH (copy archived at Tan, 2024).

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Author details

1. Gansheng Tan

   1. Department of Neurosurgery, Washington University School of Medicine, Springfield, United States
   2. Department of Biomedical Engineering, Washington University in St. Louis, St Louis, United States

   Contribution

   Conceptualization, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   Contributed equally with

   Anna L Huguenard

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-8785-9499

2. Anna L Huguenard

   Department of Neurosurgery, Washington University School of Medicine, Springfield, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Project administration, Writing – review and editing

   Contributed equally with

   Gansheng Tan

   Competing interests

   Has stock ownership in Aurenar

3. Kara M Donovan

   1. Department of Neurosurgery, Washington University School of Medicine, Springfield, United States
   2. Department of Biomedical Engineering, Washington University in St. Louis, St Louis, United States

   Contribution

   Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

4. Phillip Demarest

   1. Department of Neurosurgery, Washington University School of Medicine, Springfield, United States
   2. Department of Biomedical Engineering, Washington University in St. Louis, St Louis, United States

   Contribution

   Visualization, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

5. Xiaoxuan Liu

   1. Department of Neurosurgery, Washington University School of Medicine, Springfield, United States
   2. Department of Biomedical Engineering, Washington University in St. Louis, St Louis, United States

   Contribution

   Validation, Writing – review and editing

   Competing interests

   No competing interests declared

6. Ziwei Li

   1. Department of Neurosurgery, Washington University School of Medicine, Springfield, United States
   2. Department of Biomedical Engineering, Washington University in St. Louis, St Louis, United States

   Contribution

   Validation, Writing – review and editing

   Competing interests

   No competing interests declared

7. Markus Adamek

   Department of Neuroscience, Washington University in St. Louis, St Louis, United States

   Contribution

   Data curation, Software

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-8519-9212

8. Kory Lavine

   Department of Neurosurgery, Washington University School of Medicine, Springfield, United States

   Contribution

   Validation

   Competing interests

   No competing interests declared

9. Ananthv K Vellimana

   1. Department of Neurosurgery, Washington University School of Medicine, Springfield, United States
   2. Department of Neurology, Washington University in St. Louis, St Louis, United States

   Contribution

   Data curation, Validation, Project administration

   Competing interests

   No competing interests declared

10. Terrance T Kummer

    Department of Neurology, Washington University in St. Louis, St Louis, United States

    Contribution

    Data curation, Validation, Project administration

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-8938-8280

11. Joshua W Osbun

    1. Department of Neurosurgery, Washington University School of Medicine, Springfield, United States
    2. Department of Neurology, Washington University in St. Louis, St Louis, United States

    Contribution

    Data curation, Validation, Project administration

    Competing interests

    No competing interests declared

12. Gregory J Zipfel

    Department of Neurosurgery, Washington University School of Medicine, Springfield, United States

    Contribution

    Funding acquisition, Validation, Project administration

    Competing interests

    No competing interests declared

13. Peter Brunner

    1. Department of Neurosurgery, Washington University School of Medicine, Springfield, United States
    2. Department of Biomedical Engineering, Washington University in St. Louis, St Louis, United States

    Contribution

    Resources, Software, Supervision, Funding acquisition, Validation, Project administration

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-2588-2754

14. Eric C Leuthardt

    1. Department of Neurosurgery, Washington University School of Medicine, Springfield, United States
    2. Department of Biomedical Engineering, Washington University in St. Louis, St Louis, United States

    Contribution

    Conceptualization, Resources, Supervision, Funding acquisition, Validation, Investigation, Methodology, Project administration, Writing – review and editing

    For correspondence

    leuthardte@wustl.edu

    Competing interests

    Has stock ownership in Neurolutions, Face to Face Biometrics, Caeli Vascular, Acera, Sora Neuroscience, Inner Cosmos, Kinetrix, NeuroDev, Inflexion Vascular, Aurenar, Cordance Medical, Silent Surgical, and Petal Surgical; consultant for E15, Neurolutions, Inc, Petal Surgical; Washington University owns equity in Neurolutions

    "This ORCID iD identifies the author of this article:" 0000-0003-4154-3135

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