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Alopecia in patients with COVID-19: A systematic review and meta-analysis.
Nguyen, Betty; Tosti, Antonella.
  • Nguyen B; Dr. Phillip Frost Department of Dermatology and Cutaneous Surgery, University of Miami Miller School of Medicine, Miami, Florida.
  • Tosti A; University of California Riverside School of Medicine, Riverside, California.
JAAD Int ; 7: 67-77, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1703008
ABSTRACT

BACKGROUND:

COVID-19 is associated with androgenetic alopecia (AGA), telogen effluvium (TE), and alopecia areata (AA). No studies have analyzed the aggregate data to date.

OBJECTIVE:

We conducted a systematic review to characterize the types, incidence, timing, and clinical outcomes of COVID-19-associated alopecia.

METHODS:

We searched PubMed/MEDLINE, Scopus, and Embase for articles published between November 2019 and August 2021 using the key words "alopecia" or "hair" and COVID-19-related search terms, identifying 41 original articles describing patients with alopecia and COVID-19.

RESULTS:

The current review included 1826 patients with alopecia and COVID-19 (mean age, 54.5 years; 54.3% male). The most common types of alopecia identified were AGA (30.7%, 86.4% male), TE (19.8%, 19.3% male), and AA (7.8%, 40.0% male). AGA preceded COVID-19 symptoms. TE was usually newly triggered by COVID-19 (93.6%). AA usually occurred in patients with preexisting disease (95.1%).

LIMITATIONS:

Definitions of COVID-19 onset varied. Studies differed in methodology and were susceptible to reporting and sampling bias. Studies with large sample sizes may exert a disproportionate influence on data.

CONCLUSION:

AGA may be a risk factor for severe COVID-19, whereas TE presents as a sequela of COVID-19. AA generally occurs as a relapse in patients with preexisting alopecia.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study / Reviews / Systematic review/Meta Analysis Topics: Long Covid Language: English Journal: JAAD Int Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study / Reviews / Systematic review/Meta Analysis Topics: Long Covid Language: English Journal: JAAD Int Year: 2022 Document Type: Article