Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

medicine

Characteristics of headache attributed to COVID-19 infection and predictors of its frequency and intensity: A cross sectional study

Cephalalgia, Volume 40, No. 13, Year 2020

Objective: To study the characteristics of headache attributed to COVID-19 infection and predictors of its severity. Methods: A cross-sectional study involved 172 individuals who had headache due to COVID-19 infection. A detailed analysis of such headache was done through a face-to-face interview. Patients with any other form of secondary headache were excluded. Labs, including lymphocytic count, C-reactive protein, D-dimer and ferritin and chest imaging, were made available. Results: The: majority of our patients had a diffuse headache (52.9%). It was pressing in 40.7%, with median intensity of 7 (assessed by visual analogue scale) and median frequency of 7 days/week. Patients with preexisting primary headache (52.9%) had significantly more frequent COVID-19 related headache than those without (47.1%) (p = 0.001). Dehydrated patients (64.5%) had more frequent COVID-19 related headache than those who were not dehydrated (35.5%) (p = 0.029). Patients with fever (69.8%) had significantly higher frequency and intensity of COVID-19 related headache compared to those without fever (30.2%) (p = 0.003, 0.012). Patients with comorbidities (19.8%) had significantly higher frequency and intensity of headache than those without comorbidities (80.2%) (p = 0.006, 0.003). After multiple linear regression, primary headache disorders, dehydration and comorbidities were considered predictors of frequency of COVID-19 related headache. Meanwhile, fever and dehydration were predictors of pain intensity. Conclusion: Healthcare providers of COVID-19 patients need to be aware of frequency and intensity predictors of COVID-19 related headache: Primary headache disorders, fever, dehydration, and comorbidities.
Statistics
Citations: 46
Authors: 7
Affiliations: 3
Identifiers
Research Areas
Covid
Health System And Policy
Study Design
Cross Sectional Study
Study Approach
Quantitative