Electrochemical Skin Conductance as a Marker of Painful Oxaliplatin-Induced Peripheral Neuropathy

Artificial Intelligence for Automatic Pain Assessment: Research Methods and Perspectives

Although proper pain evaluation is mandatory for establishing the appropriate therapy, self-reported pain level assessment has several limitations. Data-driven artificial intelligence (AI) methods can be employed for research on automatic pain assessment (APA). The goal is the development of objective, standardized, and generalizable instruments useful for pain assessment in different clinical contexts. The purpose of this article is to discuss the state of the art of research and perspectives on APA applications in both research and clinical scenarios. Principles of AI functioning will be addressed. For narrative purposes, AI-based methods are grouped into behavioral-based approaches and neurophysiology-based pain detection methods. Since pain is generally accompanied by spontaneous facial behaviors, several approaches for APA are based on image classification and feature extraction. Language features through natural language strategies, body postures, and respiratory-derived elements are other investigated behavioral-based approaches. Neurophysiology-based pain detection is obtained through electroencephalography, electromyography, electrodermal activity, and other biosignals. Recent approaches involve multimode strategies by combining behaviors with neurophysiological findings. Concerning methods, early studies were conducted by machine learning algorithms such as support vector machine, decision tree, and random forest classifiers. More recently, artificial neural networks such as convolutional and recurrent neural network algorithms are implemented, even in combination. Collaboration programs involving clinicians and computer scientists must be aimed at structuring and processing robust datasets that can be used in various settings, from acute to different chronic pain conditions. Finally, it is crucial to apply the concepts of explainability and ethics when examining AI applications for pain research and management.

The value of electrochemical skin conductance measurement by Sudoscan® for assessing autonomic dysfunction in peripheral neuropathies beyond diabetes

The diagnosis and follow-up of peripheral neuropathies involving small-diameter nerve fibers require specific examinations beyond conventional nerve conduction studies which only concern large-diameter nerve fibers. Among these tests, some are dedicated to the investigation of cutaneous innervation by the autonomic nervous system, mainly by unmyelinated sympathetic C fibers. To this end, various laboratory tests have been proposed, but the measurement of electrochemical skin conductance (ESC) by Sudoscan® is increasingly becoming the most widely used technique, because it allows a quick and simple assessment of the sudomotor function of the limb extremities. This technique is based on the principles of reverse iontophoresis and chronoamperometry and since its introduction in 2010, has been the source of nearly 200 publications. In the clinical field, most of these publications concern the evaluation of diabetic polyneuropathy, for which the value of Sudoscan® no longer needs to be demonstrated. However, there is also evidence for a role for Sudoscan® in the testing of the autonomic nervous system in various peripheral neuropathies of other origins or diseases primarily affecting the central nervous system. In this article, a comprehensive review of the literature on the clinical value of Sudoscan® outside of diabetes is presented, detailing ESC changes in neuropathies associated with various clinical conditions, such as hereditary amyloidosis or other genetic pathologies, chemotherapy neurotoxicity, dysimmune or infectious disorders, fibromyalgia, parkinsonism or other neurodegenerative diseases.

Physiological responses to pain in cancer patients: A systematic review

BACKGROUND AND OBJECTIVE

Pain is one of the most debilitating symptoms in persons with cancer. Still, its assessment is often neglected both by patients and healthcare professionals. There is increasing interest in conducting pain assessment and monitoring via physiological signals that promise to overcome the limitations of state-of-the-art pain assessment tools. This systematic review aims to evaluate existing experimental studies to identify the most promising methods and results for objectively quantifying cancer patients' pain experience.

METHODS

Four electronic databases (Pubmed, Compendex, Scopus, Web of Science) were systematically searched for articles published up to October 2020.

RESULTS

Fourteen studies (528 participants) were included in the review. The selected studies analyzed seven physiological signals. Blood pressure and ECG were the most used signals. Sixteen physiological parameters showed significant changes in association with pain. The studies were fairly consistent in stating that heart rate, the low-frequency to high-frequency component ratio (LF/HF), and systolic blood pressure positively correlate with the pain.

CONCLUSIONS

Current evidence supports the hypothesis that physiological signals can help objectively quantify, at least in part, cancer patients' pain experience. While there is much more to be done to obtain a reliable pain assessment method, this review takes an essential first step by highlighting issues that should be taken into account in future research: use of a wearable device for pervasive recording in a real-world context, implementation of a big-data approach possibly supported by AI, including multiple stratification factors (e.g., cancer site and stage, source of pain, demographic and psychosocial data), and better-defined recording procedures. Improved methods and algorithms could then become valuable add-ons in taking charge of cancer patients.

Association of electrochemical skin conductance with neuropathy in chemotherapy-treated patients

PURPOSE

Chemotherapy-induced peripheral neuropathy (CIPN) is an adverse event of cancer treatment that can affect sensory, motor, or autonomic nerves. Assessment of autonomic neuropathy is challenging, with limited available tools. Accordingly, it is not routinely assessed in chemotherapy-treated patients. In this study, we aimed to examine whether electrochemical skin conductance (ESC) via Sudoscan, a potential measure of autonomic function, associates with subjective and objective measures of CIPN severity and autonomic neuropathy.

METHODS

A cross-sectional assessment of patients who completed neurotoxic chemotherapy 3-24 months prior was undertaken using CIPN patient-reported outcomes (EORTC-QLQ-CIPN20), clinically graded scale (NCI-CTCAE), neurological examination score (TNSc), autonomic outcome measure (SAS), and Sudoscan. Differences in CIPN severity between participants with or without ESC dysfunction were investigated. Linear regression analyses were used to identify whether ESC values could predict CIPN severity.

RESULTS

A total of 130 participants were assessed, with 93 participants classified with CIPN according to the clinically graded scale (NCI-CTCAE/grade ≥ 1), while 49% demonstrated hands or feet ESC dysfunction (n = 46). Participants with ESC dysfunction did not significantly differ from those with no dysfunction on multiple CIPN severity measures (clinical-grade, patient-report, neurological examination), and no differences on the autonomic outcome measure (SAS) (all p > 0.0063). Linear regression analyses showed that CIPN could not be predicted by ESC values.

CONCLUSIONS

The inability of ESC values via Sudoscan to predict clinically-graded and patient-reported CIPN or autonomic dysfunction questions its clinical utility for chemotherapy-treated patients. The understanding of autonomic neuropathy with chemotherapy treatment remains limited and must be addressed to improve quality of life in cancer survivors.

Virtual Reality in Home Palliative Care: Brief Report on the Effect on Cancer-Related Symptomatology

Virtual reality (VR) has been used as a complementary therapy for managing psychological and physical symptoms in cancer patients. In palliative care, the evidence about the use of VR is still inadequate. This study aims to assess the effect of an immersive VR-based intervention conducted at home on anxiety, depression, and pain over 4days and to evaluate the short-term effect of VR sessions on cancer-related symptomatology. Participants were advanced cancer patients assisted at home who were provided with a VR headset for 4days. On days one and four, anxiety and depression were measured by the Hospital Anxiety and Depression Scale (HADS) and pain by the Brief Pain Inventory (BPI). Before and after each VR session, symptoms were collected by the Edmonton Symptom Assessment Scale (ESAS). Participants wore a smart wristband measuring physiological signals associated with pain, anxiety, and depression. Fourteen patients (mean age 47.2±14.2years) were recruited. Anxiety, depression (HADS), and pain (BPI) did not change significantly between days one and four. However, the ESAS items related to pain, depression, anxiety, well-being, and shortness of breath collected immediately after the VR sessions showed a significant improvement (p<0.01). A progressive reduction in electrodermal activity has been observed comparing the recordings before, during, and after the VR sessions, although these changes were not statistically significant. This brief research report supports the idea that VR could represent a suitable complementary tool for psychological treatment in advanced cancer patients assisted at home.

Prevalence and prognostic value of autonomic neuropathy assessed by Sudoscan® in transthyretin wild-type cardiac amyloidosis

Aims

The prevalence of autonomic neuropathy (AN) is high in patients with hereditary transthyretin amyloidosis but remains unknown in transthyretin wild‐type cardiac amyloidosis (ATTRwt‐CA). This study aimed to determine the prevalence of AN in patients with ATTRwt‐CA using Sudoscan®, a non‐invasive method used to provide evidence of AN in clinical practice and based on measurement of electrochemical skin conductance at the hands and feet (fESC).

Methods and results

A series of 62 non‐diabetic patients with ATTRwt‐CA was prospectively included over 2 years and compared with healthy elderly subjects, matched by age, gender, and body mass index. The presence of AN was defined as electrochemical skin conductance at the hands <60 μS and/or fESC <70 μS, and conductances were analysed according to clinical, biological, and echocardiographic data. Mean fESC was significantly lower in patients with ATTRwt‐CA compared with elderly controls: 68.3 (64.1–72.5) vs. 76.9 (75.6–78.1) μS (P < 0.0001), respectively. Prevalence of fESC <70 μS was higher in ATTRwt‐CA patients than in controls: 48.4% vs. 19.9%, P < 0.05. Univariate analysis showed that fESC, N‐terminal pro‐B‐type natriuretic peptide, creatinine plasma levels, and echocardiographic global longitudinal strain were associated with decompensated cardiac failure and death. Multivariate analysis revealed that fESC was an independent prognostic factor, and Kaplan–Meier estimator evidenced a greater occurrence of cardiac decompensation and death in patients with fESC <70 μS, P = 0.046.

Conclusions

Reduced fESC was observed in almost 50% of patients with ATTRwt‐CA and was associated with a worse prognosis. Sudoscan® could easily be used to screen ATTRwt‐CA patients for the presence of AN and identify patients at higher risk for a poor outcome.

Quantification of Small Fiber Neuropathy in Chemotherapy-Treated Patients

Chemotherapy-induced peripheral neuropathy (CIPN) is a major, dose-limiting side effect of treatment with neurotoxic cancer treatments which can result in long-term impairment. Deficits often reflect a large fiber polyneuropathy, however small fiber involvement resulting in neuropathic pain and autonomic dysfunction can occur. Quantification of both CIPN and small fiber neuropathy (SFN) remains a challenge. Accordingly, the prevalence and pathophysiology of small fiber neuropathy amongst cancer survivors remains poorly understood. This review will provide an overview of the clinical features of SFN associated with neurotoxic cancer treatments as well as a summary of current assessment tools for evaluating small fiber function, and their use in patients treated with neurotoxic chemotherapies. The continued development and utilization of novel measures quantifying small fiber involvement will help elucidate the pathophysiology underlying symptoms of CIPN and assist in informing treatment approaches. Accurately identifying subgroups of patients with neuropathic symptoms which may respond to existing pain medication may reduce the impact of CIPN and improve long-term quality of life as well as provide better categorization of patients for future clinical trials of neuroprotective and treatment strategies for CIPN. PERSPECTIVE: This review provides a critical analysis of SFN associated with neurotoxic cancer treatments and the assessment tools for evaluating small fiber dysfunction in cancer patients. Quantification of small fiber involvement in CIPN will assist in identifying subgroups of patients with neuropathic symptoms which may respond to existing pain medications.