Accepted

Numerous medications are used for the preventive treatment of chronic migraine (CM), including oral treatments, onabotulinumtoxinA (onabotA; BOTOX), and calcitonin gene-related peptide (CGRP) monoclonal antibodies (mAbs). Despite substantial clinical trial evidence, less is published about the real-world experience of these treatments based on data routinely collected from a variety of sources. This systematic review assessed real-world evidence on the effectiveness and safety of preventive treatments for CM in adults.

The objectives of this study were to (1) report long-term health-related quality of life (HRQoL) outcomes among patients using rimegepant preventatively in BHV3000-305 (NCT03732638) open-label extension (OLE) and (2) map Migraine-Specific Quality of Life questionnaire version 2.1 (MSQv2) to EQ-5D-3L utility values over the double-blind treatment (DBT; 0-12 weeks) and the OLE (13-64 weeks) to assess the influence of treatment on these values.

Complex regional pain syndrome (CRPS) is associated with a range of sensory disturbances on the symptomatic side of the body but whether this includes olfaction is uncertain. To clarify this, the aims of this study were to compare ratings of intensity and hedonic appeal of household odorants in CRPS patients and controls, and to determine whether ratings differed between the symptomatic and contralateral sides within the sample of patients.

Central post-stroke pain (CPSP) refers to neuropathic pain in areas of the body corresponding to stroke lesions. Duloxetine, a serotonin-norepinephrine reuptake inhibitor, is safe and effective against neuropathic pain. In this randomized double-blind placebo-controlled study, we studied the effect of duloxetine in CPSP patients.

BACKGROUND: DRAGON was a phase 3, randomised, double-blind, placebo-controlled study which evaluated the efficacy and safety of erenumab in patients with chronic migraine (CM) from Asia not adequately represented in the global pivotal CM study.

Cluster headache is a highly debilitating neurological disorder with considerable inter-ethnic differences. Genome-wide association studies (GWAS) recently identified replicable genomic loci for cluster headache in Europeans, but the genetic underpinnings for cluster headache in Asians remain unclear. The objective of this study is to investigate the genetic architecture and susceptibility loci of cluster headache in Han Chinese resided in Taiwan.

Reliable and objective biomarkers promise to improve the assessment and treatment of chronic pain. Resting-state electroencephalography (EEG) is broadly available, easy-to-use, cost-efficient and, therefore, appealing as a potential biomarker of chronic pain. However, results of EEG studies are heterogeneous. We therefore conducted a systematic review (PROSPERO CRD42021272622) of quantitative resting state EEG and magnetoencephalography (MEG) studies in adult patients suffering from different types of chronic pain. We excluded populations with severe psychiatric or neurologic comorbidity. Risk of bias was assessed using a modified Newcastle-Ottawa Scale. Semi-quantitative data synthesis was conducted using modified albatross plots. We included 76 studies after searching MEDLINE, Web of Science Core Collection, Cochrane Central Register of Controlled Trials and EMBASE. For cross-sectional studies which can serve to develop diagnostic biomarkers, we found higher theta and beta power in chronic pain patients than in healthy participants. For longitudinal studies, which can yield monitoring and/or predictive biomarkers, we found no clear associations of pain relief with M/EEG measures. Likewise, descriptive studies which can yield diagnostic or monitoring biomarkers showed no clear correlations of pain intensity with M/EEG measures. Risk of bias was high in many studies and domains. Together, the present systematic review synthesizes evidence how resting-state M/EEG might serve as a diagnostic biomarker of chronic pain. Beyond, the review might help to guide future M/EEG studies on the development of pain biomarkers.

In this op-ed, we discuss the advantages of leveraging natural language processing (NLP) in the assessment of clinical reasoning. Clinical reasoning is a complex competency that cannot be easily assessed using multiple-choice questions. Constructed-response assessments can more directly measure important aspects of a learner's clinical reasoning ability, but substantial resources are necessary for their use. We provide an overview of INCITE, the Intelligent Clinical Text Evaluator, a scalable NLP-based computer-assisted scoring system that was developed to measure clinical reasoning ability as assessed in the written documentation portion of the now-discontinued USMLE Step 2 Clinical Skills examination. We provide the rationale for building a computer-assisted scoring system that is aligned with the intended use of an assessment. We show how INCITE's NLP pipeline was designed with transparency and interpretability in mind, so that every score produced by the computer-assisted system could be traced back to the text segment it evaluated. We next suggest that, as a consequence of INCITE's transparency and interpretability features, the system may easily be repurposed for formative assessment of clinical reasoning. Finally, we provide the reader with the resources to consider in building their own NLP-based assessment tools.

Seventy years ago, Hodgkin and Huxley published the first mathematical model that described action potential generation, laying the foundation for modern computational neuroscience. Since then, the field has evolved enormously with studies spanning from basic neuroscience to clinical neuromodulation applications. Computer models for neuromodulation have evolved in complexity and personalization, advancing clinical practice and novel neurostimulation therapies, such as spinal cord stimulation (SCS). SCS is a widely used therapy to treat chronic pain with rapidly expanding indications, such as restoring motor function. In general, simulations dramatically contributed to improved lead designs, stimulation configurations, waveform parameters, and programming procedures, as well as provided insight into potential mechanisms of action of electrical stimulation. However, while practical applications of neural models are relentlessly increasing in number and complexity, it is reasonable to ask whether this observed increase in complexity is necessary for improved accuracy and ultimately clinical efficacy. To this aim, we performed a systematic literature review with a qualitative meta-synthesis of the evolution of computational models, with a focus on complexity, personalization, and the use of medical imaging to capture realistic anatomy. Our review showed that increased model complexity improved both mechanistic as well as translational studies. More specifically, it enabled the development of patient-specific models that can help transform clinical practice in SCS. Finally, we combined our results to provide clear guidelines for standardization and expansion of computational models for SCS. Abstract figure legend Evolution of computational models of spinal cord stimulation. The use of computational models of spinal cord stimulation is rapidly expanding in the field of neuromodulation. Here, we evaluated the evolution of such models from the 1980s to 2022. Thanks to the advancement of medical images and computational tools, models evolved from 2D models (left) to 3D models with limited realism and tissue compartments (middle), then, to MRI-based patient specific models with high realism and complex tissue compartments (right). Model figures from left to right were adapted from Coburn 13, Capogrosso et al. 9, and Rowald et al. 62, respectively, with permission. Abbreviation key: gm-gray matter, wm-white matter, csf-cerebrospinal fluid, edf-epidural fat, root-roots and rootlets. This article is protected by copyright. All rights reserved.

Current clinical staging/grading schemes of endometriosis show poor correlation with clinical symptoms and histopathological confirmation is only in half of the clinically suspected endometriosis. In this study, done over an 8-year period, several histological features were analysed including an attempt to grade the severity of endometriosis histologically based on the number of per low power field. The components in each focus, the phasing of the glands and , the type of glands (endometrial type or undifferentiated type), and features were all analysed. This study attempts to histologically grade endometriosis while relating it to the clinical manifestations and anatomical location. Eighty cases of endometriosis were included. Most common clinical presentation was cyclical pain ( = 62) and the most common anatomical location was ( = 50). Histologically, severe endometriosis (>3 ) was seen in 37 cases. The components were mixed in 68 cases. Well-differentiated glandular pattern was typical ( = 54), while 6 cases had undifferentiated. Proliferative phase was seen in 38 cases. Fibrosis and inflammation were present in 29 and 42 cases, respectively. Significant vascular proliferation and plasma cell infiltrate was noted ( = 35). The severe grade was significantly associated with fibrosis ( = 0.03) and inflammation ( = 0.014). Endometriotic foci, unlike eutopic endometrium, shows significant plasma cell infiltrate and vascular proliferation.IMPACT STATEMENT Endometriosis, a chronic inflammatory condition in reproductive age group women. The currently used clinical staging and grading systems show poor correlation with patient symptoms and treatment outcomes. Endometriosis with classical histopathological features pose no diagnostic difficulty, however, there is poor concordance with histopathology. Atypical endometriosis is proposed as potential precursor for endometriosis related neoplasms, however, it remains as a controversial entity. The study identifies the uncommon histological patterns which may be encountered in biopsy samples from clinically identified endometriotic lesions. The recognition of these patterns will reduce clinico-pathological discrepancies. In keeping with the other grading systems, attempts at histological grading did not show any correlation with location or patient symptoms. Atypical features were seen only in two cases and was likely to be reactive in nature. Undifferentiated glandular pattern is often a under-recognized histological pattern. Histological grading of severity was a novel attempt to correlate with clinical parameters. Significant plasma cell infiltrate and vascular proliferation in endometriotic foci, underscores the quest for novel therapeutic targets. This study suggests that the use of non-invasive diagnostic methods like fibroscan/inflammatory markers to clinically identify severe disease should be investigated further.