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Enregistrement W4220977774 · doi:10.1111/jdv.18054

Maskne prevalence and associated factors in Irish healthcare workers during the COVID‐19 pandemic

2022· letter· en· W4220977774 sur OpenAlexaboutno aff
Lisa Kiely, Cathal O’Connor, G. O’Briain, Cillian O'Briain, J. Gallagher, J.F. Bourke

Notice bibliographique

RevueJournal of the European Academy of Dermatology and Venereology · 2022
Typeletter
Langueen
DomaineMedicine
ThématiqueInfection Control and Ventilation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineIrishPersonal protective equipmentPandemicHealth careQuarter (Canadian coin)Family medicineCoronavirus disease 2019 (COVID-19)Health professionalsDiseaseInfectious disease (medical specialty)

Résumé

récupéré en direct d'OpenAlex

In early 2020, mask usage was mandated for healthcare workers (HCWs) to limit the transmission of COVID-19.1, 2 Since then, dermatoses related to personal protective equipment (PPE) have become well-recognized and widely reported, predominantly related to pressure-related damage and irritant contact dermatitis (ICD).3 A previous Irish study showed that 82% of staff developed ICD, with 26% reporting PPE-related facial dermatoses.4 We sought to evaluate the prevalence and contributory factors in ‘maskne’ development amongst Irish HCWs during the COVID-19 pandemic. In April-May 2021, 700 self-administered questionnaires were distributed to staff in three university hospitals in Cork, Ireland. The questionnaire enquired about history of acne, PPE exposure, maskne development, contributing/alleviating factors and whether advice/treatment was sought. In total, 337 completed the questionnaire (48% response rate). Most (84.6%, n = 285) were female. Forty-nine per cent were aged between 20 and 30 years, 27.6% between 31 and 40 years and 23.3% were over 40 years. Nursing staff comprised 64.1% of participants, doctors 22%, healthcare assistants (HCAs) 4.7% and allied health professionals 3.9%. Most respondents (72.5%) worked on general wards, 10% on COVID-19 wards, 4.5% in intensive care units and 3.2% in emergency departments. A quarter (26%, n = 87) had a previous history of acne, and a quarter (25.5%, n = 84) had a family history of acne (first degree relative). The majority were White (82.7%; n = 278) followed by South Asian (7.7%; n = 26), East Asian (3.3%; n = 11) and Black (2.2%; 7). As per the Fitzpatrick scale, most (52.7%) participants reported type I (19.2%, n = 64) or type II (33.5%, n = 112) skin. More darkly pigmented skin types were reported in 47.8% [type III 22.5% (n = 75); type IV 13.8% (n = 46); type V 9.9% (n = 33) and 1.2% (n = 4) type VI]. Over half (53.4%, n = 180) of respondents reported developing maskne since the onset of the COVID-19 pandemic. The majority were (85.5%, n = 154) self-reported papulopustular eruptions, 46% (n = 83) comedonal breakouts and 22.5% (n = 44) nodulocystic lesions. Only 12.8% of HCW with maskne sought medical advice (Fig. 1). Factors associated with increased rates of maskne included female gender (OR 4.26; 95% CI 2.11–8.20; P < 0.001), younger age [64.1% of 20–30 year olds compared with 48.8% and 46.7% of the 31–40 and >40 year categories respectively (P = 0.037)], history of acne (OR 2.16 95% CI 1.28–3.64; P = 0.004), family history of acne (OR 1.7 95% CI 1.02–2.89; P = 0.04), working in a ‘hot and sweaty’ environment (OR 1.89; 95% CI 1.14–3.15; P = 0.014), use of emollients under the masks (OR 1.89; CI 1.21–2.95; P = 0.005) and use of face shields and goggles (OR 1.59; 95% CI 0.97–2.60; P = 0.031; Table 1). There was no correlation with duration of mask use (P = 0.097), number of shifts worked per week (P = 0.52), job description (P = 0.793), use of hormonal contraception amongst female staff members (P = 0.474), Fitzpatrick skin type (P = 0.844) or ethnicity (P = 0.22). Over half of our HCWs developed maskne since the onset of the COVID-19. Our findings suggest that female HCW, younger HCW and those with a personal or family history of acne are at increased risk. The reduction in duration of usage may not prevent maskne, but application of emollients under masks should not be recommended.5 Limitations of our study include self-reporting of maskne. Our study was vulnerable to responder bias. However, with 55% of the 48% respondents reporting maskne, even if all non-respondents did not develop maskne, the overall prevalence would still have been at least 26%. We did not account for confounding variables such as the use of other comedogenic products, such as make-up. This study highlights the pervasiveness of maskne in the COVID-19 era. Most HCW with maskne do not seek medical attention, so the impact of this occupational dermatosis may be under-estimated. None declared by LK, COC, GOB, COB, JG and JB. The data are available on request.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesIntégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,309
Score d'incertitude au seuil0,998

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,004
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,040
Tête enseignante GPT0,304
Écart entre enseignants0,263 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations10
Publié2022
Routes d'admission1
Résumé présentoui

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