Table 1 Characteristics of clinical studies focused on the relationship between hypertension and migraine
From: Arterial hypertension in the chronic evolution of migraine: bystander or risk factor? An overview
Author, year | Study design | Aims | Sample size | Population | Identified risk factors (OR) | Limitations |
|---|---|---|---|---|---|---|
Bigal, 2002 [84] | Randomized case–control design | To identify risk factors for CM evolution | 791 | CM – MOH CM EM cPTH | HT prevalence higher in CM compared to EM and cPTH CM vs EM OR 6.9 (95% CI 3.1—15.9) CM vs cPTH OR 5.1 (95% CI 2.7 – 11.1) |  |
Bigal, 2010 [78] | Cross-sectional | To profile CV risk in migraine and ascertain CV events in migraine vs controls | 6 102 migraineurs 5 243 controls | MwA MA HC | Migraineurs have higher risk of developing HT OR 1.4 (95% CI 1.3–1.6) | • Self-reported data • No collection of concomitant CV risk factors • Cross-sectional |
Buse, 2010 [79] | Cross-sectional | To assess differences in comorbidities between CM and EM | 24 000 | CM EM | HT prevalence higher in CM 1.23 (95% CI 1.03–1.47) | • Self-reported data • Cross-sectional |
Gipponi, 2010 [87] | Cross-sectional | To identify risk factors for CM evolution | 1 483 | EM CM—MOH cTTH | HT prevalence higher in CM CM 16.2% vs EM 7.3% and vs cTTH 6.6%, p < 0.01 | • Cross-sectional |
Manzoni, 2012 [88] | Retrospective (10-year follow up) | To evaluate risk factor for CM evolution | 315 | MwA → MwA MwA → CM | HT prevalence higher in pts with evolution to CM 38.7% vs 17.9%, p < 0.01 | • Retrospective • Mostly women • Small sample size |
Entonen, 2014 [77] | Prospective (5-year follow-up) | To identify association between migraine and HT evolution | 13 454 | Random sample of Finnish population | Higher risk of developing HT in migraine pts OR 1.4 (95% CI 12–1.7) | • Self-reported data • No evaluation of concomitant CV risk factors |
Fagernæs, 2015 [89] | Prospective (11-year follow up) | To evaluate association between migraine and HT | 13 852 | Random sample of the Nord-Trondelag County | Inverse correlation between HT and migraine development Per 10 mmHg increase in Systolic BP: OR 0.8 (95% CI 0.8–0.9); Diastolic BP: OR 0.98 (95% CI 0.8–1.2) | • Self-reported data • No data on medications • Selection bias (low % of pts who completed the final questionnaires) |
Gardener, 2016 [81] | Cross-sectional | To investigate association between migraine and HT | 1 338 | Random sample of the Northern Manhattan community | HT higher prevalence in migraine OR 1.76 (95% CI 1.2—2.5) | • Self-reported data • Cross-sectional design |
Rist, 2018 [83] | To evaluate association between migraine and incident HT | To evaluate risk of incident HT in migraine | 29 040 (all women) | MA MwA HC | Higher risk of developing HT in women with migraine MA RR 1.09 (95% CI 1.0 -1.2) MwA RR 1.21 (95% CI 1.1 -1.3) | • Self-reported data • Observation bias • women only |
Buse, 2020 [80] | Cross-sectional | Better understanding of migraine comorbidities | 92 586 | Migraine HC | Higher prevalence of HT in migraine 15–20 days OR 1.52 (1.3, 1.8), > 21 days OR 1.37 (1.1, 1.7); reference 1–4 days | • Self-reported data • Cross-sectional • Selection bias |
Cotta Ramusino, 2022 [90] | Cross-sectional | To investigate HT contribution to CM evolution | 48 | CM EM HC | Altered brain vessel wall reactivity in CM and HT pts. Greater decrease in cerebral blood flow velocity in EM pts with associated HT p = 0.037 | • Cross-sectional • Ongoing treatments |
Faubion, 2023 [82] | Cross-sectional | To assess association between migraine and hypertension | 5 708 (all women) | Random sample on data registry | Higher prevalence of HT in migraine aOR 1.31 (95% CI 1.1 – 1.6) | • Self-reported data • Cross-sectional • women only |