A Comparison of Normalization Techniques for Individual Baseline-Free Estimation of Absolute Hypovolemic Status Using a Porcine Model

Hypovolemic shock is one of the leading causes of death in the military. The current methods of assessing hypovolemia in field settings rely on a clinician assessment of vital signs, which is an unreliable assessment of hypovolemia severity. These methods often detect hypovolemia when interventional methods are ineffective. Therefore, there is a need to develop real-time sensing methods for the early detection of hypovolemia. Previously, our group developed a random-forest model that successfully estimated absolute blood-volume status (ABVS) from noninvasive wearable sensor data for a porcine model (n = 6). However, this model required normalizing ABVS data using individual baseline data, which may not be present in crisis situations where a wearable sensor might be placed on a patient by the attending clinician. We address this barrier by examining seven individual baseline-free normalization techniques. Using a feature-specific global mean from the ABVS and an external dataset for normalization demonstrated similar performance metrics compared to no normalization (normalization: R2 = 0.82 ± 0.025|0.80 ± 0.032, AUC = 0.86 ± 5.5 × 10-3|0.86 ± 0.013, RMSE = 28.30 ± 0.63%|27.68 ± 0.80%; no normalization: R2 = 0.81 ± 0.045, AUC = 0.86 ± 8.9 × 10-3, RMSE = 28.89 ± 0.84%). This demonstrates that normalization may not be required and develops a foundation for individual baseline-free ABVS prediction.

Noninvasive Vagal Nerve Stimulation for Opioid Use Disorder

Background

Opioid Use Disorder (OUD) is an escalating public health problem with over 100,000 drug overdose-related deaths last year most of them related to opioid overdose, yet treatment options remain limited. Non-invasive Vagal Nerve Stimulation (nVNS) can be delivered via the ear or the neck and is a non-medication alternative to treatment of opioid withdrawal and OUD with potentially widespread applications.

Methods

This paper reviews the neurobiology of opioid withdrawal and OUD and the emerging literature of nVNS for the application of OUD. Literature databases for Pubmed, Psychinfo, and Medline were queried for these topics for 1982-present.

Results

Opioid withdrawal in the context of OUD is associated with activation of peripheral sympathetic and inflammatory systems as well as alterations in central brain regions including anterior cingulate, basal ganglia, and amygdala. NVNS has the potential to reduce sympathetic and inflammatory activation and counter the effects of opioid withdrawal in initial pilot studies. Preliminary studies show that it is potentially effective at acting through sympathetic pathways to reduce the effects of opioid withdrawal, in addition to reducing pain and distress.

Conclusions

NVNS shows promise as a non-medication approach to OUD, both in terms of its known effect on neurobiology as well as pilot data showing a reduction in withdrawal symptoms as well as physiological manifestations of opioid withdrawal.

Pain is reduced by transcutaneous cervical vagus nerve stimulation and correlated with cardiorespiratory variability measures in the context of opioid withdrawal

Over 100,000 individuals in the United States lost their lives secondary to drug overdose in 2021, with opioid use disorder (OUD) being a leading cause. Pain is an important component of opioid withdrawal, which can complicate recovery from OUD. This study's objectives were to assess the effects of transcutaneous cervical vagus nerve stimulation (tcVNS), a technique shown to reduce sympathetic arousal in other populations, on pain during acute opioid withdrawal and to study pain's relationships with objective cardiorespiratory markers. Twenty patients with OUD underwent opioid withdrawal while participating in a two-hour protocol. The protocol involved opioid cues to induce opioid craving and neutral conditions for control purposes. Adhering to a double-blind design, patients were randomly assigned to receive active tcVNS (n = 9) or sham stimulation (n = 11) throughout the protocol. At the beginning and end of the protocol, patients' pain levels were assessed using the numerical rating scale (0–10 scale) for pain (NRS Pain). During the protocol, electrocardiogram and respiratory effort signals were measured, from which heart rate variability (HRV) and respiration pattern variability (RPV) were extracted. Pre- to post- changes (denoted with a Δ) were computed for all measures. Δ NRS Pain scores were lower (P = 0.045) for the active group (mean ± standard deviation: −0.8 ± 2.4) compared to the sham group (0.9 ± 1.0). A positive correlation existed between Δ NRS pain scores and Δ RPV (Spearman's ρ = 0.46; P = 0.04). Following adjustment for device group, a negative correlation existed between Δ HRV and Δ NRS Pain (Spearman's ρ = −0.43; P = 0.04). This randomized, double-blind, sham-controlled pilot study provides the first evidence of tcVNS-induced reductions in pain in patients with OUD experiencing opioid withdrawal. This study also provides the first quantitative evidence of an association between breathing irregularity and pain. The correlations between changes in pain and changes in objective physiological markers add validity to the data. Given the clinical importance of reducing pain non-pharmacologically, the findings support the need for further investigation of tcVNS and wearable cardiorespiratory sensing for pain monitoring and management in patients with OUD.

Leveraging Accelerometry as a Prognostic Indicator for Increase in Opioid Withdrawal Symptoms

Treating opioid use disorder (OUD) is a significant healthcare challenge in the United States. Remaining abstinent from opioids is challenging for individuals with OUD due to withdrawal symptoms that include restlessness. However, to our knowledge, studies of acute withdrawal have not quantified restlessness using involuntary movements. We hypothesized that wearable accelerometry placed mid-sternum could be used to detect withdrawal-related restlessness in patients with OUD. To study this, 23 patients with OUD undergoing active withdrawal participated in a protocol involving wearable accelerometry, opioid cues to elicit craving, and non-invasive Vagal Nerve Stimulation (nVNS) to dampen withdrawal symptoms. Using accelerometry signals, we analyzed how movements correlated with changes in acute withdrawal severity, measured by the Clinical Opioid Withdrawal Scale (COWS). Our results revealed that patients demonstrating sinusoidal-i.e., predominantly single-frequency oscillation patterns in their motion almost exclusively demonstrated an increase in the COWS, and a strong relationship between the maximum power spectral density and increased withdrawal over time, measured by the COWS (R = 0.92, p = 0.029). Accelerometry may be used in an ambulatory setting to indicate the increased intensity of a patient's withdrawal symptoms, providing an objective, readily-measurable marker that may be captured ubiquitously.

Transcutaneous Cervical Vagus Nerve Stimulation Reduces Respiratory Variability in the Context of Opioid Withdrawal

Opioid withdrawal's physiological effects are a major impediment to recovery from opioid use disorder (OUD). Prior work has demonstrated that transcutaneous cervical vagus nerve stimulation (tcVNS) can counteract some of opioid withdrawal's physiological effects by reducing heart rate and perceived symptoms. The purpose of this study was to assess the effects of tcVNS on respiratory manifestations of opioid withdrawal - specifically, respiratory timings and their variability. Patients with OUD (N = 21) underwent acute opioid withdrawal over the course of a two-hour protocol. The protocol involved opioid cues to induce opioid craving and neutral conditions for control purposes. Patients were randomly assigned to receive double-blind active tcVNS (n = 10) or sham stimulation (n = 11) throughout the protocol. Respiratory effort and electrocardiogram-derived respiration signals were used to estimate inspiration time (T_i), expiration time (T_e), and respiration rate (RR), along with each measure's variability quantified via interquartile range (IQR). Comparing the active and sham groups, active tcVNS significantly reduced IQR(T_i) - a variability measure - compared to sham stimulation (p = .02). Relative to baseline, the active group's median change in IQR(T_i) was 500 ms less than the sham group's median change in IQR(T_i). Notably, IQR(T_i) was found to be positively associated with post-traumatic stress disorder symptoms in prior work. Therefore, a reduction in IQR(T_i) suggests that tcVNS downregulates the respiratory stress response associated with opioid withdrawal. Although further investigations are necessary, these results promisingly suggest that tcVNS - a non-pharmacologic, non-invasive, readily implemented neuromodulation approach - can serve as a novel therapy to mitigate opioid withdrawal symptoms.

Platelet heterogeneity enhances blood clot volumetric contraction: An example of asynchrono-mechanical amplification

Physiological processes such as blood clotting and wound healing as well as pathologies such as fibroses and musculoskeletal contractures, all involve biological materials composed of a contracting cellular population within a fibrous matrix, yet how the microscale interactions among the cells and the matrix lead to the resultant emergent behavior at the macroscale tissue level remains poorly understood. Platelets, the anucleate cell fragments that do not divide nor synthesize extracellular matrix, represent an ideal model to study such systems. During blood clot contraction, microscopic platelets actively pull fibers to shrink the macroscale clot to less than 10% of its initial volume. We discovered that platelets utilize a new emergent behavior, asynchrono-mechanical amplification, to enhanced volumetric material contraction and to magnify contractile forces. This behavior is triggered by the heterogeneity in the timing of a population of actuators. This result indicates that cell heterogeneity, often attributed to stochastic cell-to-cell variability, can carry an essential biophysical function, thereby highlighting the importance of considering 4 dimensions (space + time) in cell-matrix biomaterials. This concept of amplification via heterogeneity can be harnessed to increase mechanical efficiency in diverse systems including implantable biomaterials, swarm robotics, and active polymer composites.