International consensus on the most useful physical examination tests used by physiotherapists for patients with headache: A Delphi study

Luedtke, Kerstin; Boissonnault, William G.; Caspersen, N; Castien, René; Chaibi, Aleksander; Falla, Deborah; Fernández‐de‐las‐Peñas, César; Hall, Toby; Hirsvang, JR; Horre, Thomas; Hurley, Deirdre A.; Jull, Gwendolen; Krøll, LS; Madsen, B.; Mallwitz, Joachim; Miller, Caroline; Schäfer, Benjamin; Schöttker-Königer, Thomas; Starke, W; Piekartz, Harry von; Watson, Daniel; Westerhuis, Pieter; May, Arne

doi:10.1016/j.math.2016.02.010

Cited by 91 publications

(68 citation statements)

References 80 publications

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“…The subgroup of migraine sufferers identified within the RF model were younger and had a lower JPSE in cervical rotation, greater cervical mobility in rotation and flexion, lower FRT scores (positive), positive PAIVMs reproducing migraine symptoms, normal PPTs over the tibialis anterior, a shorter migraine history, and a lower cranio-vertebral angle while standing as compared to other migraine intensity subgroups. The association of these variables with migraine is not new, since some previous studies have investigated the presence of cervical musculoskeletal disorders in this population, [20][21][22][23][24][25] although their association is still questioned. In fact, a recent meta-analysis concluded that, among several cervical spine musculoskeletal impairments, individuals with migraine exhibit minimally reduced CROM with no differences in head posture or JPSE as compared to headache-free people.…”

Section: Discussionmentioning

confidence: 99%

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Subgrouping Factors Influencing Migraine Intensity in Women: A Semi‐automatic Methodology Based on Machine Learning and Information Geometry

et al. 2019

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Background Migraine is a heterogeneous condition with multiple clinical manifestations. Machine learning algorithms permit the identification of population groups, providing analytical advantages over other modeling techniques. Objective The aim of this study was to analyze critical features that permit the differentiation of subgroups of patients with migraine according to the intensity and frequency of attacks by using machine learning algorithms. Methods Sixty‐seven women with migraine participated. Clinical features of migraine, related disability (Migraine Disability Assessment Scale), anxiety/depressive levels (Hospital Anxiety and Depression Scale), anxiety state/trait levels (State‐Trait Anxiety Inventory), and pressure pain thresholds (PPTs) over the temporalis, neck, second metacarpal, and tibialis anterior were collected. Physical examination included the flexion‐rotation test, cervical range of cervical motion, forward head position while sitting and standing, passive accessory intervertebral movements (PAIVMs) with headache reproduction, and joint positioning sense error. Subgrouping was based on machine learning algorithms by using the nearest neighbors algorithm, multisource variability assessment, and random forest model. Results For migraine intensity, group 2 (women with a regular migraine headache intensity score of 7 on an 11‐point Numeric Pain Rating Scale [where 0 = no pain and 10 = maximum pain]) were younger and had lower joint positioning sense error in cervical rotation, greater cervical mobility in rotation and flexion, lower flexion‐rotation test scores, positive PAIVMs reproducing migraine, normal PPTs over the tibialis anterior, shorter migraine history, and lower cranio‐vertebral angles while standing than the remaining migraine intensity subgroups. The most discriminative variable was the flexion‐rotation test score of the symptomatic side. For migraine frequency, no model was able to identify differences between groups (ie, patients with episodic or chronic migraine). Conclusions A subgroup of women with migraine who had common migraine intensity was identified with machine learning algorithms.

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Section: Discussionmentioning

confidence: 99%

“…Physical examination included the musculoskeletal impairments most commonly associated with patients with headache: cervical flexion‐rotation test (FRT) scores, active range of cervical motion, forward head posture, passive accessory intervertebral movements with head pain reproduction, and JPSE.…”

Section: Methodsmentioning

confidence: 99%

Subgrouping Factors Influencing Migraine Intensity in Women: A Semi‐automatic Methodology Based on Machine Learning and Information Geometry

et al. 2019

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“…Zur Indikationsstellung wird genügend Zeit für eine ausführliche Untersuchung benötigt. Die Befundung orientiert sich an den empfohlenen Assessments für Kopfschmerz-Patienten [12]. Getreu dem Konzept "Hilfe zur Selbsthilfe" sollten passive Maßnahmen zur Muskeldetonisierung und Mobilisation nur eingesetzt werden, wenn eine Indikation hierfür besteht.…”

Section: Indikationsstellungunclassified

Die Verbindung von Psychotherapie und Physiotherapie

Liesering-Latta¹,

Schäfer²

2018

Der Schmerzpatient

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“…Die Physiotherapie sollte demnach auf einem ausführlichen Assessment beruhen (z. B. nach Lüdtke) [21] und sich auch konsequent danach richten. Patienten mit langer Krankenanamnese, vielen gescheiterten Therapieversuchen sowie relevanter Komorbidität werden im Rahmen einer 5-tägigen intensivierten ambulanten Versorgung betreut (Modul 2).…”

Section: Physiotherapieunclassified

Integrierte Versorgung Kopfschmerz

et al. 2017

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Zusammenfassung Kopfschmerzerkrankungen geh?ren zu den h?ufigsten neurologischen Krankheitsbildern. Zudem besteht oft eine erhebliche Einschr?nkung der Lebensqualit?t mit auch gro?er sozio?konomischer Belastung. Dieses spiegelte sich in den Versorgungsstrukturen nur eingeschr?nkt wider. Aufgrund der resultierenden Unterversorgung wurde seit Mitte der 90er Jahre das Konzept der Integrierten Versorgung f?r Kopfschmerzpatienten punktuell in Deutschland etabliert und ausgebaut. Dabei ist die Multidisziplinarit?t sowohl f?r das Patienten-Assessment als auch f?r die Therapie der zentrale Bestandteil dieser Versorgungsstruktur. Dieser Artikel gibt detaillierte Einblicke in die Zusammenarbeit von ?rzten, Psychologen und Physiotherapeuten in der Behandlung von Kopfschmerzpatienten. Dabei werden Grunds?tze und Details der Versorgung sowie Outcome-Daten der beteiligten Zentren in Essen, M?nchen, Jena, Berlin und Kiel strukturiert dargestellt. Aufbauend auf den Erfahrungen der IV sollte die zuk?nftige Versorgung sektoren?bergreifend, multidisziplin?r mit koordiniertem Behandlungsablauf organisiert werden.

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International consensus on the most useful physical examination tests used by physiotherapists for patients with headache: A Delphi study

Abstract: Background

Cited by 91 publications

References 80 publications

Subgrouping Factors Influencing Migraine Intensity in Women: A Semi‐automatic Methodology Based on Machine Learning and Information Geometry

Subgrouping Factors Influencing Migraine Intensity in Women: A Semi‐automatic Methodology Based on Machine Learning and Information Geometry

Die Verbindung von Psychotherapie und Physiotherapie

Integrierte Versorgung Kopfschmerz

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