e-Migraine: Development of a comprehensive tool to estimate Migraine Comorbidity Index Score

Yıl 2020, , 1 - 6, 31.03.2020

Didem Derici Yıldırım Bahar Taşdelen Tufan Mengi Aynur Özge Hamit Genç

https://doi.org/10.22399/ijcesen.623854

Öz

e-Migraine is a validated tool to estimate the
severity of headache based on Migraine Comorbidity Index (MigCI) that includes
comorbidities of migraine, age, baseline duration of headache (hours) and
baseline frequency of headache (day/month). The aim of this study is to
introduce the prediction tool for physicians to calculate the MigCI score
easily. Our study sample consisted of 2012 patients enrolled in the Turkish
Headache Database examined by neurologists between 2000 and 2015. Comorbidities
were modeled according to posterior probabilities obtained from Latent Class
Analysis. The score ranges of the baseline duration and frequency of migraine
were determined according to previous studies and histogram charts. Age groups
were designated by the classification of World Health Organization. An index
formula was created by using all these variables and total score was
calculated. The range of MigCI score was 1.02 and 17.22. The median value with
the 25^th and 75^th percentiles were 4.44[2.96-6.00]. The
MCI introduced in this study is the first to estimate the headache score
considering the posterior probabilities as weights. e-Migraine is a practical
tool that may help physicians to detect the headache score and suggest a
treatment or care to the patients according to the score.

Anahtar Kelimeler

e-Migraine, web-tool, Migraine Comorbidity Index

Kaynakça

• Referans1. Yeh WZ, Blizzard L, Taylor BV. “What is the actual prevalence of migraine?” Brain and Behaviour 8(6),1-6(2018).
• Referans2. Schera AI, Bigalb ME, Lipton RB. “Comorbidity of migraine” Curr Opin Neurol 18(3),305-310(2005).
• Referans3. Wang SJ, Chen PK, Fuh JL. “Comorbidities of migraine” Front Neurol 1(16),1-9(2010).
• Referans4. Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. “Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study”Lancet 380,37-43 (2012).
• Referans5. Valderas JM, Starfield B, Sibbald B, Salisbury C, Roland M. “Defining Comorbidity: Implications for Understanding Health and Health Services”The Annals of Family Medicine 7(4),357–363(2009).
• Referans6. Feinstein AR. “The pre-therapeutic classification of co-morbidity in chronic disease” J Chronic Dis 23(7),455-468(1970).
• Referans7. Groot V, Beckerman H, Lankhorst GJ, Bouter LM. “How to Measure Comorbidity: A Critical Review of Avaliable Methods” J Clin Epidemiol 56(3),221-229(2003).
• Referans8. Sarfati D. “Review of methods used to measure comorbidity in cancer populations: No gold standard exists” J Clin Epidemiol 65,924-33(2012).
• Referans9. Schneeweiss S, Maclure M. “Use of comorbidity scores for control of confounding in studies using administrative databases” International Journal of Epidemiology 29(5),891-898(2000).
• Referans10. Klabunde CN, Legler JML, Warren JL, Baldwin LM, Schrag D. “A refined comorbidity measurement algorithm for claims-based studies of breast, prostate, colorectal and lung cancer patients” Ann Epidemiol 17(8),584-90(2007).
• Referans11. Klabunde CN, Potosky AL, Legler JML, Warren JL. “Development of a comorbidity index using physician claims data” Journal of Clinical Epidemiology 53(12),1258-67(2000).
• Referans12. Hall SF. “A user’s guide to selecting a comorbidity index for clinical research” Journal of Clinical Epidemiology 59(8),849-55(2006).
• Referans13. Bateman BT, Mhyre JM, Hernandez-Diaz S, Huybrechts KF, Fischer MA, Creanga AA et al. “Development of a comorbidity index for use in obstetric” Obstet Gynecol 122(5),957-965(2013).
• Referans14. Laith A, Dodds P, Hutchings HA, Russel IT, Watkins A, Williams JG. “Development and validation of a new disease severity index: the inflammatory Bowel Disease Index (IBDEX)” Frontline Gastroenterol 6(3),161- 168(2015).
• Referans15. Rozzini R, Sabatini T, Barbisoni P, Trabucchi M, De Groot V, Beckerman H et al. “How to measure comorbidity in elderly persons (multiple letters)” Journal of Clinical Epidemiology 57(3),321-322 (2004).
• Referans16. Charlson ME, Pompei P, Ales KL, Mackenzie CR. “A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation” J Chron Dis 40(5),373-383(1987).
• Referans17. Extermann M. “Measuring comorbidity in older cancer patients” European Journal of Cancer 36(4),453–471(2000).
• Referans18. Grunau GL, Sheps S, Goldner EM, Ratner PA. “Specific comorbidity risk adjustment was a better predictor of 5-year acute myocardial infarction mortality than general methods” Journal of Clinical Epidemiology 59(3),274–280(2006).
• Referans19. Derici Yıldırım D, Taşdelen B, Uludüz D, Özge A, Yoloğlu S. “Impact of a new migraine-specific comorbidity index on prognosis: A methodology study” Neurol Sci Neurophysiol 35(4),183-188(2018).
• Referans20. Aguilera A, Muench F. “There is an App for That: Information Technology Applications for Cognitive Behavioral Practitioners” Behav Ther 35(4),65-73(2012).
• Referans21. Tasdelen B, Ozge A, Kaleagasi H, Erdogan S, Mengi T. “Determining of migraine prognosis using latent growth mixture models” Chinese Medical Journal 124(7),1044-1049(2011).
• Referans22. Goddman LA. “Exploratory latent structure analysis using both identifiable and unidentifiable models” Biometrika 61,215-231(1974).
• Referans23. Linzer DA, Lewis J. “poLCA: an R Package for Polytomous Variable Latent Class Analysis” Journal of Statistical Software 42(10),1-29(2011).
• Referans24. Hooshmand B, Polvikoski T, Kivipelto M, Tanskanen M, Myllykangas L, Makela M et al. “CAIDE Dementia Risk Score, Alzheimer and Cerebrovascular pathology: A population-based autopsy study” J Intern Med 283(6),597-603(2018).