Bedside Clinical Observations Stimulate COVID-19-Related Re-examination
Notice bibliographique
Résumé
We are already more than halfway through the year, and we continue to explore themes of diversity and the shift back to in-person practice while retaining the benefits of virtual and hybrid healthcare-delivery models. Diversity can have many different meanings. In this month’s issue, diversity includes having articles by authors from five countries: Brazil, Canada, China, Italy, and the United States. These authors offer insights on a variety of patient populations (eg, neonatal/pediatric, adult) and wound types (eg, hospital-acquired pressure injuries, incontinence-associated dermatitis, peristomal wounds), and report on unusual cases and new care strategies. In keeping with themes of diversity and inclusion, there has been increasing interest in assessing people across the full spectrum of Fitzpatrick skin tone classifications. Girasol and colleagues provide new skin tone data from 18 participants. They evaluated the intra-examiner and inter-examiner reliability of two raters using a low-cost commercial device to measure skin tone, moisture, and oiliness. They also explored associations with the Fitzpatrick scale and reported moderate to high reliability (0.747–0.971). Between the examiners there were moderate to large associations for skin tone but lower co-rater association for moisture level documentation. Heerschap and Wiesenfeld report on the learning preferences of acute care nurses (N = 47). Nurses tended to prefer one-on-one bedside education and described the importance of varying educational techniques by topic, ensuring appropriate time of day for education, and preferring shorter educational sessions over time. The most reported learning styles were active, sensing, visual, and a balanced approach to sequential and global learning. The one-on-one clinical teaching model is well suited for mentorship and could be possible with blended models of clinical education but would require increased staffing for patient care responsibilities. Delmore and colleagues designed three questionnaires to examine COVID-19 challenges for pressure injury (PI) care. Two of these surveys were directed at manufacturers, distributors, and other supply chain personnel. The first survey examined support surface acquisition and products for institutions and the second survey addressed challenges in meeting supply chain needs with limited access to healthcare institutions. The third survey was designed to be answered by individuals in an acute care facility who had a role in procuring, obtaining, or using support surfaces and skin and wound care products. This survey focused on healthcare worker’s experiences with support surface and skin and wound care product availability and solutions to prevent and treat PIs in US hospitals. From the 174 respondents three themes emerged: differences in expectations of supply chain staff and nurses, inappropriate product substitution without consulting clinical staff, and preparedness. This month’s continuing education article discusses the important topic of periwound wound dermatitis with particular emphasis on allergic contact dermatitis to common allergens including fragrances and preservatives. The author reviews the role of patch testing to diagnose and identify causative allergens and provide a helpful algorithm to simplify the process of identifying and treating lower leg dermatitis. If patch tests are not feasible (eg, during the COVID-19 pandemic), providers can use the repeat open application test on normal skin of the flexural aspect of the forearm. Use a skin marker to make a circle the size of a silver dollar. Apply the suspected topical preparation twice a day for 48 to 72 hours. If a red tuberculin-test-like reaction occurs, that is a positive result for contact allergy to one of the components and the preparation should be avoided; perform subsequent patch tests identifying the causative agent(s). We hope our readers will keep sharing their clinical strategies so that patients worldwide will benefit.Elizabeth A. Ayello, PhD, MS, RN, CWON, MAPWCA, FAANR. Gary Sibbald, MD, MEd, FRCPC, FAAD, MAPWCA, JM
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».