Temporomandibular disorders (TMD) are a significant public health problem affecting approximately 5% to 12% of the population.1 TMD is the second most common musculoskeletal condition (after chronic low back pain) resulting in pain and disability.1 Pain-related TMD can impact the individual's daily activities, psychosocial functioning, and quality of life. Overall, the annual TMD management cost in the USA, not including imaging, has doubled in the last decade to $4 billion.1

Patients often seek consultation with dentists for their TMD, especially for pain-related TMD. Diagnostic criteria for TMD with simple, clear, reliable, and valid operational definitions for the history, examination, and imaging procedures are needed to render physical diagnoses in both clinical and research settings. In addition, biobehavioral assessment of pain-related behavior and psychosocial functioning—an essential part of the diagnostic process—is required and provides the minimal information whereby one can determine whether the patient's pain disorder, especially when chronic, warrants further multidisciplinary assessment. Taken together, a new dual-axis Diagnostic Criteria for TMD (DC/TMD) will provide evidence-based criteria for the clinician to use when assessing patients, and will facilitate communication regarding consultations, referrals, and prognosis.2

The research community benefits from the ability to use well-defined and clinically relevant characteristics associated with the phenotype in order to facilitate more generalizable research. When clinicians and researchers use the same criteria, taxonomy, and nomenclature, then clinical questions and experience can be more easily transferred into relevant research questions, and research findings are more accessible to clinicians to better diagnose and manage their patients. The Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD) have been the most widely employed diagnostic protocol for TMD research since its publication in 1992.3 This classification system was based on the biopsychosocial model of pain4 that included an Axis I physical assessment, using reliable and well-operationalized diagnostic criteria, and an Axis II assessment of psychosocial status and pain-related disability. The intent was to simultaneously provide a physical diagnosis and identify other relevant characteristics of the patient that could influence the expression and thus management of their TMD. Indeed, the longer the pain persists, the greater the potential for emergence and amplification of cognitive, psychosocial, and behavioral risk factors, with resultant enhanced pain sensitivity, greater likelihood of additional pain persistence, and reduced probability of success from standard treatments.5

The RDC/TMD (1992) was intended to be only a first step toward improved TMD classification, and the authors stated the need for future investigation of the accuracy of the Axis I diagnostic algorithms in terms of reliability and criterion validity—the latter involving the use of credible reference standard diagnoses. Also recommended was further assessment of the clinical utility of the Axis II instruments. The original RDC/TMD Axis I physical diagnoses have content validity based on the critical review by experts of the published diagnostic approach in use at that time and were tested using population-based epidemiologic data.6 Subsequently, a multicenter study showed that, for the most common TMD, the original RDC/TMD diagnoses exhibited sufficient reliability for clinical use.7 While the validity of the individual RDC/TMD diagnoses has been extensively investigated, assessment of the criterion validity for the complete spectrum of RDC/TMD diagnoses had been absent until recently.8

For the original RDC/TMD Axis II instruments, good evidence for their reliability and validity for measuring psychosocial status and pain-related disability already existed when the classification system was published.9–13 Subsequently, a variety of studies have demonstrated the significance and utility of the original RDC/TMD biobehavioral measures in such areas as predicting outcomes of clinical trials, escalation from acute to chronic pain, and experimental laboratory settings.14–20

Other studies have shown that the original RDC/TMD biobehavioral measures are incomplete in terms of prediction of disease course.21–23 The overall utility of the biobehavioral measures in routine clinical settings has, however, yet to be demonstrated, in part because most studies have to date focused on Axis I diagnoses rather than Axis II biobehavioral factors.24

The aims of this article are to present the evidence-based new Axis I and Axis II DC/TMD to be used in both clinical and research settings, as well as present the processes related to their development.

Diagnostic Criteria for Temporomandibular Disorders (DC/TMD) for Clinical and Research Applications: recommendations of the International RDC/TMD Consortium Network* and Orofacial Pain Special Interest Group†

国際生活機能分類(International Classification of Functioning, Disability and Health: ICF)にみた福祉・保健・医療の専門職協働における連携に関する貢献と課題

Chronic pain has been recognized as pain that persists past normal healing time5 and hence lacks the acute warning function of physiological nociception.35 Usually pain is regarded as chronic when it lasts or recurs for more than 3 to 6 months.29 Chronic pain is a frequent condition, affecting an estimated 20% of people worldwide6,13,14,18 and accounting for 15% to 20% of physician visits.25,28 Chronic pain should receive greater attention as a global health priority because adequate pain treatment is a human right, and it is the duty of any health care system to provide it.4,13

The current version of the International Classification of Diseases (ICD) of the World Health Organization (WHO) includes some diagnostic codes for chronic pain conditions, but these diagnoses do not reflect the actual epidemiology of chronic pain, nor are they categorized in a systematic manner. The ICD is the preeminent tool for coding diagnoses and documenting investigations or therapeutic measures within the health care systems of many countries. In addition, ICD codes are commonly used to report target diseases and comorbidities of participants in clinical research. Consequently, the current lack of adequate coding in the ICD makes the acquisition of accurate epidemiological data related to chronic pain difficult, prevents adequate billing for health care expenses related to pain treatment, and hinders the development and implementation of new therapies.10,11,16,23,27,31,37

Responding to these shortcomings, the International Association for the Study of Pain (IASP) contacted the WHO and established a Task Force for the Classification of Chronic Pain. The IASP Task Force, which comprises pain experts from across the globe,19 has developed a new and pragmatic classification of chronic pain for the upcoming 11th revision of the ICD. The goal is to create a classification system that is applicable in primary care and in clinical settings for specialized pain management.

A major challenge in this process was finding a rational principle of classification that suits the different types of chronic pain and fits into the general ICD-11 framework. Pain categories are variably defined based on the perceived location (headache), etiology (cancer pain), or the primarily affected anatomical system (neuropathic pain). Some diagnoses of pain defy these classification principles (fibromyalgia).

This problem is not unique to the classification of pain, but exists throughout the ICD. The IASP Task Force decided to give first priority to pain etiology, followed by underlying pathophysiological mechanisms, and finally the body site. Developing this multilayered classification was greatly facilitated by a novel principle of assigning diagnostic codes in ICD-11, termed “multiple parenting.” Multiple parenting allows the same diagnosis to be subsumed under more than 1 category (for a glossary of ICD terms refer to Table ​Table1).1). Each diagnosis retains 1 category as primary parent, but is cross-referenced to other categories that function as secondary parents.



Table 1

Glossary of ICD-11 terms.



The new ICD category for “Chronic Pain” comprises the most common clinically relevant disorders. These disorders were divided into 7 groups (Fig. ​(Fig.1):1): (1) chronic primary pain, (2) chronic cancer pain, (3) chronic posttraumatic and postsurgical pain, (4) chronic neuropathic pain, (5) chronic headache and orofacial pain, (6) chronic visceral pain, and (7) chronic musculoskeletal pain. Experts assigned to each group are responsible for the definition of diagnostic criteria and the selection of the diagnoses to be included under these subcategories of chronic pain. Thanks to Bedirhan Ustun and Robert Jakob of the WHO, these pain diagnoses are now integrated in the beta version of ICD-11 (http://id.who.int/icd/entity/1581976053). The Task Force is generating content models for single entities to describe their clinical characteristics. After peer review overseen by the WHO Steering Committee,39 the classification of chronic pain will be voted into action by the World Health Assembly in 2017.



Figure 1

Organizational chart of Task Force, IASP, and WHO interactions. The IASP Task Force was created by the IASP council and its scope defined in direct consultation of the chairs (R.D.T. and W.R.) with WHO representatives in 2012. The Task Force reports to ...




2. Classification of chronic pain
Chronic pain was defined as persistent or recurrent pain lasting longer than 3 months. This definition according to pain duration has the advantage that it is clear and operationalized.

Optional specifiers for each diagnosis record evidence of psychosocial factors and the severity of the pain. Pain severity can be graded based on pain intensity, pain-related distress, and functional impairment.

2.1. Chronic primary pain
Chronic primary pain is pain in 1 or more anatomic regions that persists or recurs for longer than 3 months and is associated with significant emotional distress or significant functional disability (interference with activities of daily life and participation in social roles) and that cannot be better explained by another chronic pain condition. This is a new phenomenological definition, created because the etiology is unknown for many forms of chronic pain. Common conditions such as, eg, back pain that is neither identified as musculoskeletal or neuropathic pain, chronic widespread pain, fibromyalgia, and irritable bowel syndrome will be found in this section and biological findings contributing to the pain problem may or may not be present. The term “primary pain” was chosen in close liaison with the ICD-11 revision committee, who felt this was the most widely acceptable term, in particular, from a nonspecialist perspective.

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A classification of chronic pain for ICD-11.

Aims: The original Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD) Axis I diagnostic algorithms have been demonstrated to be reliable. However, the Validation Project determined that the RDC/TMD Axis I validity was below the target sensitivity of ≥ 0.70 and specificity of ≥ 0.95. Consequently, these empirical results supported the development of revised RDC/TMD Axis I diagnostic algorithms that were subsequently demonstrated to be valid for the most common pain-related TMD and for one temporomandibular joint (TMJ) intra-articular disorder. The original RDC/TMD Axis II instruments were shown to be both reliable and valid. Working from these findings and revisions, two international consensus workshops were convened, from which recommendations were obtained for the finalization of new Axis I diagnostic algorithms and new Axis II instruments. Methods: Through a series of workshops and symposia, a panel of clinical and basic science pain experts modified the revised RDC/TMD Axis I algorithms by using comprehensive searches of published TMD diagnostic literature followed by review and consensus via a formal structured process. The panel’s recommendations for further revision of the Axis I diagnostic algorithms were assessed for validity by using the Validation Project’s data set, and for reliability by using newly collected data from the ongoing TMJ Impact Project—the follow-up study to the Validation Project. New Axis II instruments were identified through a comprehensive search of the literature providing valid instruments that, relative to the RDC/TMD, are shorter in length, are available in the public domain, and currently are being used in medical settings. Results: The newly recommended Diagnostic Criteria for TMD (DC/TMD) Axis I protocol includes both a valid screener for detecting any pain-related TMD as well as valid diagnostic criteria for differentiating the most common pain-related TMD (sensitivity ≥ 0.86, specificity ≥ 0.98) and for one intra-articular disorder (sensitivity of 0.80 and specificity of 0.97). Diagnostic criteria for other common intra-articular disorders lack adequate validity for clinical diagnoses but can be used for screening purposes. Inter-examiner reliability for the clinical assessment associated with the validated DC/TMD criteria for pain-related TMD is excellent (kappa ≥ 0.85). Finally, a comprehensive classification system that includes both the common and less common TMD is also presented. The Axis II protocol retains selected original RDC/TMD screening instruments augmented with new instruments to assess jaw function as well as behavioral and additional psychosocial factors. The Axis II protocol is divided into screening and comprehensive selfreport instrument sets. The screening instruments' 41 questions assess pain intensity, pain-related disability, psychological distress, jaw functional limitations, and parafunctional behaviors, and a pain drawing is used to assess locations of pain. The comprehensive instruments, composed of 81 questions, assess in further detail jaw functional limitations and psychological distress as well as additional constructs of anxiety and presence of comorbid pain conditions. Conclusion: The recommended evidence-based new DC/TMD protocol is appropriate for use in both clinical and research settings. More comprehensive instruments augment short and simple screening instruments for Axis I and Axis II. These validated instruments allow for identification of patients with a range of simple to complex TMD presentations. J Oral Facial Pain Headache 2014;28:6–27. doi: 10.11607/jop.1151

/pdf/diagnostic-criteria-for-temporomandibular-disorders-dc-tmd-4e7m5vom0o.pdf

Diagnostic Criteria for Temporomandibular Disorders (DC/TMD) for Clinical and Research Applications: Recommendations of the International RDC/TMD Consortium Network* and Orofacial Pain

Plaguing humans for more than two millennia, manifest on every continent studied, and with more than one billion patients having an attack in any year, migraine stands as the sixth most common cause of disability on the planet. The pathophysiology of migraine has emerged from a historical consideration of the "humors" through mid-20th century distraction of the now defunct Vascular Theory to a clear place as a neurological disorder. It could be said there are three questions: why, how, and when? Why: migraine is largely accepted to be an inherited tendency for the brain to lose control of its inputs. How: the now classical trigeminal durovascular afferent pathway has been explored in laboratory and clinic; interrogated with immunohistochemistry to functional brain imaging to offer a roadmap of the attack. When: migraine attacks emerge due to a disorder of brain sensory processing that itself likely cycles, influenced by genetics and the environment. In the first, premonitory, phase that precedes headache, brain stem and diencephalic systems modulating afferent signals, light-photophobia or sound-phonophobia, begin to dysfunction and eventually to evolve to the pain phase and with time the resolution or postdromal phase. Understanding the biology of migraine through careful bench-based research has led to major classes of therapeutics being identified: triptans, serotonin 5-HT1B/1D receptor agonists; gepants, calcitonin gene-related peptide (CGRP) receptor antagonists; ditans, 5-HT1F receptor agonists, CGRP mechanisms monoclonal antibodies; and glurants, mGlu5 modulators; with the promise of more to come. Investment in understanding migraine has been very successful and leaves us at a new dawn, able to transform its impact on a global scale, as well as understand fundamental aspects of human biology.

Pathophysiology of Migraine: A Disorder of Sensory Processing

CO39 Patient Preferences for Attributes of Advanced Migraine Prevention Medications: Findings from a Discrete Choice Experiment

DWD has been an advisory board consultant for Merck, Allergan, Endo, Pfi zer, Coherex, Neuralieve, MAP Pharmaceuticals, and Minster Pharmaceuticals. He has received research support from ANS, Medtronic, and St Jude, and was the principal investigator for the ESCAPE study (Eff ect of Septal Closure of Atrial PFO on Events of Migraine With Premere). TS has received research support from the National Institutes of Health and National Headache Foundation and has consulted for VerusMed. He has particpated in industry-sponsored research from Allergan, GlaxoSmithKline, and AGA Medical.

Paediatric neurology: advances on many fronts

Multicenter and multi scanner imaging studies might be needed to provide sample sizes large enough for developing accurate predictive models. However, multicenter studies, which likely include confounding factors due to subtle differences in research participant characteristics, MRI scanners, and imaging acquisition protocols, might not yield generalizable machine learning models, that is, models developed using one dataset may not be applicable to a different dataset. The generalizability of classification models is key for multi-scanner and multicenter studies, and for providing reproducible results. This study developed a data harmonization strategy to identify healthy controls with similar (homogenous) characteristics from multicenter studies to validate the generalization of machine-learning techniques for classifying individual migraine patients and healthy controls using brain MRI data. The Maximum Mean Discrepancy (MMD) was used to compare the two datasets represented in Geodesic Flow Kernel (GFK) space, capturing the data variabilities for identifying a "healthy core". A set of homogeneous healthy controls can assist in overcoming some of the unwanted heterogeneity and allow for the development of classification models that have high accuracy when applied to new datasets. Extensive experimental results show that the utilization of a healthy core. One dataset consists of 120 individuals (66 with migraine and 54 healthy controls) and another dataset consists of 76 (34 with migraine and 42 healthy controls) individuals. A homogeneous dataset derived from a cohort of healthy controls improves the performance of classification models by about 25% accuracy improvements for both episodic and chronic migraineurs.

/pdf/harmonizing-healthy-cohorts-to-support-multicenter-studies-19s1xqol.pdf

Todd J. Schwedt

Papers

CO39 Patient Preferences for Attributes of Advanced Migraine Prevention Medications: Findings from a Discrete Choice Experiment

Paediatric neurology: advances on many fronts

Harmonizing Healthy Cohorts to Support Multicenter Studies on Migraine Classification using Brain MRI Data

Medication Overuse Headache in the Emergency Department

Preclinical Assessment of OnabotulinumtoxinA for the Treatment of Mild Traumatic Brain Injury–Related Acute and Persistent Cephalic Allodynia