AAPT Diagnostic Criteria for Peripheral Neuropathic Pain: Focal and Segmental Disorders

Vertebrobasilar dolichoectasia to trigeminal neuralgia: case report

Vertebrobasilar dolichoectasia (VBD) is a dilated arterial disease with a diameter ˃4.5 mm. Trigeminal neuralgia (TN) is chronic neuropathic pain. Through the diagnosis and treatment of this case we believe that there is a significant risk associated with the endovascular treatment of VBD. The development of post-operative complications caused some functional impairment to the patient, but the improvement in TN symptoms with this endovascular treatment was unexpected. This treatment procedure was considered to be possibly related to the alteration of the tortuous path of the vessels, changing their course, allowing the displacement of vascular compression in the trigeminal root entry zone, and possibly also altering the hemodynamics of the posterior circulation, improving the progression of ischemia and hypoxia-induced demyelination of the trigeminal nerve. Due to the low incidence of this disease, there are not enough large sample studies for systematic statistical analysis.

Single OnabotulinumtoxinA Session Add-On to Carbamazepine or Oxcarbazepine in Treatment-Refractory Trigeminal Neuralgia: A Case Series with 24-Week Follow Up

We sought to assess the efficacy of combining onabotulinumtoxinA (BoNTA) as add-on therapy to carbamazepine or oxcarbazepine in treatment-refractory patients with trigeminal neuralgia (TGN) who failed to respond (less than 30% response rate) to adequate monotherapy. We conducted a retrospective study on 15 patients with a definite diagnosis of TGN, according to the established criteria, and underwent BoNTA as part of their treatment plan. A single BoNTA session was administered subcutaneously, according to patients' perceived zone of pain, at different dosages ranging from 30 to 200 units (mean ± standard deviation: 87.3 ± 39.2). All patients (15/15; 100%) reported large reductions in the severity of their TGN-related neuropathic pain. The mean pain score on the VAS scale significantly decreased from 9.3 ± 1.1 to 3.7 ± 1.2 at 2 weeks after injecting BoNTA (p < 0.001) and remained stable at 4 and 24 weeks post-injection. Regarding the impact of BoNTA on patients' health-related quality of life, there were significant improvements in both the physical and mental health domains (p < 0.05) of SF-36 tool. BoNTA may be a safe and effective treatment option for patients with refractory TGN when added on to carbamazepine or oxcarbazepine. The use of a single BoNTA session for TGN treatment may be an alternative to surgical interventions and as add-on treatment to oral medications, providing patients with a minimally invasive, effective, safe and well-tolerated option.

BmK DKK13, A Scorpion Toxin, Alleviates Pain Behavior in a Rat Model of Trigeminal Neuralgia by Modulating Voltage-Gated Sodium Channels and MAPKs/CREB Pathway

BmK DKK13 (DKK13) is a mutated recombinant peptide, which has a significant antinociception in a rat model of the inflammatory pain. The purpose of this study was to evaluate the antinociceptive effect of DKK13 on trigeminal neuralgia (TN) in rats. Male Sprague-Dawley (SD) rats were treated with the chronic constriction injury of the infraorbital nerve (IoN-CCI) model to induce stable symptoms of TN. DKK13 (1.0 mg/kg, 2.0 mg/kg and 4.0 mg/kg, i.v.) or morphine (4.0 mg/kg, i.v.) was administered by tail vein once on day 14 after IoN-CCI injury. Behavioral tests, electrophysiology and western blotting were performed to investigate the role and underlying mechanisms of DKK13 on IoN-CCI model. Behavioral test results showed that DKK13 could significantly increase the mechanical pain and thermal radiation pain thresholds of IoN-CCI rats and inhibit the asymmetric spontaneous pain scratching behavior. Electrophysiological results showed that DKK13 could significantly reduce the current density of Nav1.8 in the ipsilateral side of trigeminal ganglion (TG) neurons in IoN-CCI rats, and the steady-state activation and inactivation curves of Nav1.8 shifted, respectively, to the direction of hyperpolarization and depolarization. Western blotting results showed that DKK13 significantly reduced the expression of Nav1.8 and the phosphorylation levels of key proteins of MAPKs/CREB pathway in TG tissues of IoN-CCI rats. In brief, DKK13 has a significant antinociceptive effect on IoN-CCI rats, which may be achieved by changing the dynamic characteristics of Nav1.8 channel and regulating the protein phosphorylation in MAPKs/CREB pathway.

Nrf2 Activation Mediates Antiallodynic Effect of Electroacupuncture on a Rat Model of Complex Regional Pain Syndrome Type-I through Reducing Local Oxidative Stress and Inflammation

Complex regional pain syndrome type-I (CRPS-I) represents a type of neurovascular condition featured by severe pain in affected extremities. Few treatments have proven effective for CRPS-I. Electroacupuncture (EA) is an effective therapy for pain relief. We explored the mechanism through which EA ameliorates pain in a rat CRPS-I model. The chronic postischemic pain (CPIP) model was established using Sprague-Dawley rats to mimic CRPS-I. We found that oxidative stress-related biological process was among the predominant biological processes in affected hindpaw of CPIP rats. Oxidative stress occurred primarily in local hindpaw but not in the spinal cord or serum of model rats. Antioxidant N-acetyl cysteine (NAC) attenuated mechanical allodynia and spinal glia overactivation in CPIP model rats, whereas locally increasing oxidative stress is sufficient to induce chronic pain and spinal glia overactivation in naive rats. EA exerted remarkable antiallodynia on CPIP rats by reducing local oxidative stress via enhancing nuclear factor erythroid 2-related factor 2 (Nrf2) expression. Pharmacological blocking Nrf2 abolished antioxidative and antiallodynic effects of EA. EA reduced spinal glia overactivation, attenuated the upregulation of inflammatory cytokines, reduced the enhanced TRPA1 channel activity in dorsal root ganglion neurons innervating the hindpaws, and improved blood flow dysfunction in hindpaws of CPIP rats, all of which were mimicked by NAC treatment. Thus, we identified local oxidative injury as an important contributor to pathogenesis of animal CRPS-I model. EA targets local oxidative injury by enhancing endogenous Nrf2-mediated antioxidative mechanism to relieve pain and inflammation. Our study indicates EA can be an alternative option for CRPS-I management.

Inhibitory Effects of Palmatine on P2X7 Receptor Expression in Trigeminal Ganglion and Facial Pain in Trigeminal Neuralgia Rats

Trigeminal Neuralgia (TN) refers to recurrent severe paroxysmal pain in the distribution area of the trigeminal nerve, which seriously affects the quality of life of patients. This research applied the chronic constriction injury of the infraorbital nerve (CCI—ION) approach to induce an animal model of TN in rats. The mechanical pain threshold of each group of rats was determined postoperatively; the expression of P2X7 receptor in trigeminal ganglion (TG) was assessed by qRT-PCR, immunofluorescence and Western blot; and the changes of the proinflammatory cytokines IL-1β and TNF-α in serum of rats were detected by ELISA. The results showed that the administration of palmatine in the TN rats could reduce the mechanical pain threshold, significantly decrease the expression of P2X7 receptor in TG, and lower the serum concentrations of IL-1β and TNF-α, compared to the sham group. In addition, the phosphorylation level of p38 in TG of TN rats was significantly decreased after treatment with palmatine. Likewise, inhibition of P2X7 expression by shRNA treatment could effectively counteract the adversary changes of pain sensitivity, IL-1β and TNF-α production, and p38 phosphorylation in TN rats. Our data suggest that palmatine may alleviate mechanical facial pain in TN rats possibly by reducing the expression of P2X7 receptor in TG of TN rats, which may be attributable to inhibiting p38 phosphorylation and reducing the release of IL-1β and TNF-α.

Medical Management of Trigeminal Neuralgia

Background

Trigeminal neuralgia (TN) is a painful condition, often leading to poor quality of life.

Objective

The aim of this review was to discuss the various treatment modalities for the medical management of TN.

Materials and Methods

We reviewed the available literature on TN in clinical databases including PubMed, Google Scholar, and the Cochrane Database of Systematic Reviews, with a specific focus on the pharmacological treatment and newer drugs under development for the treatment of TN.

Results

Carbamazepine (CBZ) is the gold standard of treatment for TN. The first-line drugs for the treatment of TN are CBZ and oxcarbazepine (OXC). A proportion of cases (30%) are initially resistant to the first-line drugs. Alternative drugs need to be considered if the first-line drugs are not well tolerated or become ineffective with prolonged therapy. The second-line drugs comprise lamotrigine, baclofen, gabapentin, and pregabalin used as monotherapy or in combination with CBZ/OXC. Botulinum toxin A may be a promising presurgical option. Newer drug like vixotrigine has shown good results in phase two randomized control trials. About 50% of cases develop treatment resistance to oral drugs over the subsequent years of therapy and require surgical options.

Conclusion

The first-line drugs for the treatment of TN (irrespective of the age group or type) are CBZ and OXC. Combination therapy with second-line or other drugs may become necessary with poor response to CBZ/OXC, or if adverse events occur. Patients should be offered surgical options if there is poor response or tolerance to the medical therapy.

AAAPT Diagnostic Criteria for Acute Neuropathic Pain

OBJECTIVE

Acute neuropathic pain is a significant diagnostic challenge, and it is closely related to our understanding of both acute pain and neuropathic pain. Diagnostic criteria for acute neuropathic pain should reflect our mechanistic understanding and provide a framework for research on and treatment of these complex pain conditions.

METHODS

The Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks (ACTTION) public-private partnership with the U.S. Food and Drug Administration (FDA), the American Pain Society (APS), and the American Academy of Pain Medicine (AAPM) collaborated to develop the ACTTION-APS-AAPM Pain Taxonomy (AAAPT) for acute pain. A working group of experts in research and clinical management of neuropathic pain was convened. Group members used literature review and expert opinion to develop diagnostic criteria for acute neuropathic pain, as well as three specific examples of acute neuropathic pain conditions, using the five dimensions of the AAAPT classification of acute pain.

RESULTS

AAAPT diagnostic criteria for acute neuropathic pain are presented. Application of these criteria to three specific conditions (pain related to herpes zoster, chemotherapy, and limb amputation) illustrates the spectrum of acute neuropathic pain and highlights unique features of each condition.

CONCLUSIONS

The proposed AAAPT diagnostic criteria for acute neuropathic pain can be applied to various acute neuropathic pain conditions. Both the general and condition-specific criteria may guide future research, assessment, and management of acute neuropathic pain.

Chronic Pain Diagnosis Using Machine Learning, Questionnaires, and QST: A Sensitivity Experiment

In the last decade, machine learning has been widely used in different fields, especially because of its capacity to work with complex data. With the support of machine learning techniques, different studies have been using data-driven approaches to better understand some syndromes like mild cognitive impairment, Alzheimer’s disease, schizophrenia, and chronic pain. Chronic pain is a complex disease that can recurrently be misdiagnosed due to its comorbidities with other syndromes with which it shares symptoms. Within that context, several studies have been suggesting different machine learning algorithms to classify or predict chronic pain conditions. Those algorithms were fed with a diversity of data types, from self-report data based on questionnaires to the most advanced brain imaging techniques. In this study, we assessed the sensitivity of different algorithms and datasets classifying chronic pain syndromes. Together with this assessment, we highlighted important methodological steps that should be taken into account when an experiment using machine learning is conducted. The best results were obtained by ensemble-based algorithms and the dataset containing the greatest diversity of information, resulting in area under the receiver operating curve (AUC) values of around 0.85. In addition, the performance of the algorithms is strongly related to the hyper-parameters. Thus, a good strategy for hyper-parameter optimization should be used to extract the most from the algorithm. These findings support the notion that machine learning can be a powerful tool to better understand chronic pain conditions.

Electroacupuncture Alleviates Mechanical Allodynia of a Rat Model of CRPS-I and Modulates Gene Expression Profiles in Dorsal Root Ganglia

Complex regional pain syndrome type-I (CRPS-I) is chronic neurological disorder accompanied with devastating pain. Most conventional medical treatments lack effectiveness, making CRPS-I a challenging clinical condition. Electroacupuncture (EA) showed effectiveness in alleviating the pain symptoms of CRPS-I patients. However, the molecular mechanisms underlying EA's therapeutic effect are still not well-understood. Here, we established the rat chronic post-ischemic pain (CPIP) model to mimic CRPS-I and performed repetitive EA on bilateral hind limbs of the CPIP model rats. We then performed RNA-sequencing (RNA-Seq) to study the differences in gene expression, gene networks, and molecular pathways in ipsilateral DRGs innervating the hind limb of the CPIP model rats with and without repetitive EA treatment. Our results found that repetitive EA treatment significantly alleviated mechanical allodynia in bilateral hind limbs of CPIP model rats. RNA-Seq analysis indicated that EA modulated the expression of multiple genes and gene networks in the DRGs of CPIP model rats. Further bioinformatics analysis identified the up-regulation of an array of genes involved in biological process such as neutrophil chemotaxis and immune response in the DRGs of CPIP model rats after EA treatment. Thus, these results suggest that EA may alleviate pain response in CPIP model rats via regulating multiple genes. Our work may help to further advance the understandings of the molecular mechanisms underlying EA's therapeutic effects on CRPS-I and help to identify novel targets for CRPS-I treatment.

Capturing Novel Non-opioid Pain Targets

The relatively high efficacy of opioids, which have associated risks of addiction, tolerance, and dependence, for the management of acute and terminal pain has been a major driver of the opioid crisis, together with the availability, overprescription, and diversion of these drugs. Eliminating opioids without an effective replacement is, however, no solution, as it substitutes one major problem with another. To deal successfully with the opioid crisis, we need to discover novel analgesics whose mechanisms do not involve the mu opioid receptor but that have high analgesic potency and low risk of adverse effects, particularly no abuse liability. The question is how to achieve this. There are several necessary elements; first, we need to understand the nature of pain and the mechanisms responsible for it, and second, we need to adopt novel and unbiased approaches to the identification and validation of pain targets.

Using Deep Learning and Resting-State fMRI to Classify Chronic Pain Conditions

Chronic pain is known as a complex disease due to its comorbidities with other symptoms and the lack of effective treatments. As a consequence, chronic pain seems to be under-diagnosed in more than 75% of patients. At the same time, the advance in brain imaging, the popularization of machine learning techniques and the development of new diagnostic tools based on these technologies have shown that these tools could be an option in supporting decision-making of healthcare professionals. In this study, we computed functional brain connectivity using resting-state fMRI data from one hundred and fifty participants to assess the performance of different machine learning models, including deep learning (DL) neural networks in classifying chronic pain patients and pain-free controls. The best result was obtained by training a convolutional neural network fed with data preprocessed using the MSDL probabilistic atlas and using the dynamic time warping (DTW) as connectivity measure. DL models had a better performance compared to other less costly models such as support vector machine (SVM) and RFC, with balanced accuracy ranged from 69 to 86%, while the area under the curve (ROC) ranged from 0.84 to 0.93. Also, DTW overperformed correlation as connectivity measure. These findings support the notion that resting-state fMRI data could be used as a potential biomarker of chronic pain conditions.