Development of a computer application for headache diagnosis: The headache diagnostic system

Andrew, Michael E.; Penzien, Donald; Rains, Jeanetta; Knowlton, Glenn E.; McAnulty, Richard D.

doi:10.1016/0020-7101(92)90050-3

Cited by 44 publications

(50 citation statements)

References 2 publications

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“…These participants underwent the Structured Diagnostic Interview for Headache, a validated computer-based algorithm [3], and were assigned a headache diagnosis based on the 1988 ICHD-I criteria [14]. The data previously described in Smitherman and Kolivas [50] were obtained from a sample of 1886 college students, ages 18–30, who were offered the opportunity to earn extra credit in a psychology course as compensation for their participation (i.e., these were not treatment seeking individuals).…”

Section: Methodsmentioning

confidence: 99%

“…The data previously described in Smitherman and Kolivas [50] were obtained from a sample of 1886 college students, ages 18–30, who were offered the opportunity to earn extra credit in a psychology course as compensation for their participation (i.e., these were not treatment seeking individuals). These students completed an online survey battery pertaining to headache and psychiatric symptoms including a web-administered version of the Structured Diagnostic Interview for Headache [3] revised to be consistent with ICHD-II criteria [16]. …”

Section: Methodsmentioning

confidence: 99%

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Are migraine and tension-type headache diagnostic types or points on a severity continuum? An exploration of the latent taxometric structure of headache

Turner

Smitherman

Black

et al. 2015

Pain

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The objective of this study was to assess whether migraine and tension-type headache (TTH) are best viewed as discrete entities or points on a severity continuum using taxometric analysis. Historically, classification systems have conceptualized the primary headache disorders of migraine and TTH as fundamentally different disorders that are differentiated by their characteristic symptom profiles and, as such, imply differing pathophysiologies and required treatments. Despite this categorical nosology, findings continue to emerge suggesting that migraine and TTH instead reflect dimensions of severity within the same headache construct. However, few studies have assessed this issue using taxometric statistical analyses or investigated how this taxonomic structure varies as a function of age and headache frequency. We conducted a latent-mode factor analysis of headache symptomatology obtained from 3449 individuals with headache from 2 previous, large-scale cross-sectional studies of primary headache sufferers (Martin et al., 2005, and Smitherman and Kolivas, 2013). Stratified taxometric analyses suggest that the validity of a categorical vs dimensional classification varies as a function of sample characteristics. Specifically, graphical results revealed that high headache frequency (≥ 15 d/mo) and younger age (≤ 24 years old) were associated with unimodal distributions suggestive of a dimensional construct of primary headache, whereas lower headache frequency and older age were associated with bimodal distributions characteristic of discrete diagnostic entities. Conceptualizing primary headache as a severity continuum was supported for young adults and those with frequent headaches. The distinctions of a categorical classification system were supported for adults (> 24 years old) and those with infrequent headache.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Are migraine and tension-type headache diagnostic types or points on a severity continuum? An exploration of the latent taxometric structure of headache

Turner

Smitherman

Black

et al. 2015

Pain

Self Cite

View full text Add to dashboard Cite

show abstract

“…The structured interview was designed to capture the clinical characteristics of each headache type and was previously validated to diagnose migraine, tension-type, and other primary headache disorders (15). Interviews were performed by a trained research co-ordinator at the time of an office visit to the practice or by telephone at a later date.…”

Section: Headache Diagnosismentioning

confidence: 99%

Joint hypermobility syndrome: A common clinical disorder associated with migraine in women

et al. 2011

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Preliminary studies suggested that headache disorders are more common in patients with joint hypermobility syndrome (JHS). The objectives of this study were to determine if the prevalence, frequency, and disability of migraine differ between female patients with JHS and a control population. Twenty-eight patients with JHS and 232 controls participated in the case-cohort study. Participants underwent a structured verbal interview and were assigned a diagnosis of migraine based on criteria of the International Classification of Headache Disorders, 2nd Edition. The primary outcome measures were the prevalence, frequency, and headache-related disability of migraine. Logistic regression was used for the prevalence analysis and Poisson regression for the frequency and disability analyses. Results indicated that the prevalence of migraine was 75% in JHS patients and 43% in controls. The adjusted odds ratio for the prevalence of migraine was 3.19 (95% CI 1.24, 8.21] in JHS patients. The rate ratios for migraine frequency and headache-related disability were 1.67 (95% CI 1.01, 2.76) and 2.99 (95% CI 1.66, 5.38), respectively, for JHS patients. Our study suggests that JHS is a clinical disorder strongly associated with an increased prevalence, frequency, and disability of migraine in females.

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“…There have been many studies of headache diagnosis as shown in Table 5. Some of these systems did not explain the number of attributes or patients [5,6,8,11,15]. Moreover, the accuracy rate is not clear in some of them [5,8,10,11,19].…”

Section: Discussionmentioning

confidence: 99%

An ant colony optimization algorithm-based classification for the diagnosis of primary headaches using a website questionnaire expert system

Çelik¹,

Yurtay²

2017

Turk J Elec Eng & Comp Sci

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Abstract:The purpose of this research was to evaluate the classification accuracy of the ant colony optimization algorithm for the diagnosis of primary headaches using a website questionnaire expert system that was completed by patients. This cross-sectional study was conducted in 850 headache patients who randomly applied to hospital from three cities in Turkey with the assistance of a neurologist in each city. The patients filled in a detailed web-based headache questionnaire. Finally, neurologists' diagnosis results were compared with the classification results of an ant colony optimization-based classification algorithm. The ant colony algorithm for diagnosis classified patients with 96.9412% overall accuracy. Diagnosis accuracies of migraine, tension-type, and cluster headaches were 98.2%, 92.4%, and 98.2% respectively. The ant colony optimization-based algorithm has a successful classification potential on headache diagnosis.On the other hand, headache diagnosis using a website-based algorithm will be useful for neurologists in order to gather quick and precise results as well as tracking patients for their headache symptoms and medication usage by using electronic records from the Internet.

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Development of a computer application for headache diagnosis: The headache diagnostic system

Cited by 44 publications

References 2 publications

Are migraine and tension-type headache diagnostic types or points on a severity continuum? An exploration of the latent taxometric structure of headache

Are migraine and tension-type headache diagnostic types or points on a severity continuum? An exploration of the latent taxometric structure of headache

Joint hypermobility syndrome: A common clinical disorder associated with migraine in women

An ant colony optimization algorithm-based classification for the diagnosis of primary headaches using a website questionnaire expert system

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