June 2021 in “Journal of The American Academy of Dermatology” New scale reliably assesses male hair loss with female pattern.
May 2011 in “Value in Health” CP-690,550 significantly reduced itching in patients with moderate-to-severe plaque psoriasis.
1 citations
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May 2025 in “International Journal of Dermatology”
SH-SY5Y cell lysate is effective for diagnosing Satoyoshi syndrome.
December 2010 in “OhioLink ETD Center (Ohio Library and Information Network)” Sry may regulate fatty acid metabolism and shows different expression levels in rat tissues.
April 2021 in “Journal of Investigative Dermatology” Spironolactone safely and effectively treats hair loss in female scarring alopecia patients.
November 2021 in “Circulation” SCAD can indicate ANA-negative lupus, especially in women with unusual symptoms.
December 2024 in “Journal of Clinical Medicine” Assessing blood flow can improve skin graft success.
January 2025 in “International Journal of Dermatology Research” Higher MPV and CRP levels may indicate more severe alopecia areata.
July 2024 in “Journal of Investigative Dermatology” Machine learning can use blood tests to help predict moderate-to-severe alopecia areata.
8 citations
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November 2024 in “Acta Dermato Venereologica” The Dermatology Life Quality Index is reliable and consistent but needs more diverse participant studies.
June 2020 in “Annals of the Rheumatic Diseases” Patients with Systemic Sclerosis have much higher levels of GDF-15, which could help predict organ involvement and guide treatment.
45 citations
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January 1999 in “Dermatology” The VQ-Dermato is a reliable French questionnaire for measuring quality of life in chronic skin disorder patients.
November 2024 in “SKIN The Journal of Cutaneous Medicine” Ritlecitinib effectively reduces severe hair loss in alopecia areata over 24 months.
3 citations
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September 2002 in “Dermatologic Surgery” The evaluation system improved patient selection for hair loss surgery, leading to better results and satisfaction.
19 citations
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December 2008 in “Arthritis Care & Research” The decision board effectively helps lupus nephritis patients in Brazil choose treatments by clearly presenting options and side effects.
November 2024 in “Skin Appendage Disorders” Telogen effluvium most affects quality of life in alopecia patients.
September 2018 in “Value in Health” Orphan drug benefit scores in Germany are influenced by phase III data and lack of alternatives, but not linked to price or discounts.
October 2024 in “The Journal of Dermatology” Intravenous corticosteroid therapy is effective for long-term hair regrowth in alopecia areata, and a scoring system helps predict treatment success and relapse.
13 citations
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January 2018 in “Annals of Dermatology” Alopecia areata and androgenetic alopecia affect quality of life similarly.
1 citations
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March 2025 in “Pediatric Dermatology” New tools help doctors better assess and treat alopecia areata in kids by considering more than just hair loss.
June 2025 in “British Journal of Dermatology” Certain hair and scalp features can predict the severity of alopecia areata.
2 citations
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November 2024 in “PLoS ONE” Genomic prediction can improve breeding strategies for Korean Sapsaree dogs.
August 2018 in “Journal of The American Academy of Dermatology” The study concluded that a new method can effectively assess scalp sun damage in balding men, which increases with age and sun exposure.
9 citations
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November 2022 in “International Journal of Molecular Sciences” The new LC-MS/MS method is more accurate and reliable than traditional immunoassays for measuring steroids in serum.
May 2024 in “Asian Journal of Medicine and Health” Sickle cell disease affects BMI and pain frequency, with HbSS patients having more pain and unhealthy BMI.
The C-CAT tool helps assess and improve treatment for central centrifugal cicatricial alopecia.
Hair cortisol may help identify adrenal insufficiency in sickle cell disease patients.
December 2022 in “International Journal of Women's Dermatology” The Sinclair Shedding Scale is effective for diagnosing Alopecia Areata Incognita and monitoring treatment success.
April 2019 in “The journal of investigative dermatology/Journal of investigative dermatology” Machine learning can predict how well patients with alopecia areata will respond to certain treatments.