Variations in Personal Protective Equipment Preparedness in Intensive Care Units during the COVID-19 Pandemic: A Survey of Asia-Pacific Countries
Notice bibliographique
Résumé
Abstract Objectives To evaluate PPE-preparedness across intensive care units (ICUs) in 6 Asia-Pacific countries. PPE-preparedness was defined as the adherence to guidelines, training HCWs, procuring PPE stocks and responding appropriately to a suspected case (transportation and admission to hospital). Design Cross-sectional web-based survey. Setting ICUs in Australia, New Zealand (NZ), Singapore, Hong Kong (HK), India and Philippines with a 24/7 Emergency/Casualty Department, and capable of mechanically ventilating patients for >24 hours. Interventions Questionnaire sent to intensivists in 633 Level ll/lll ICUs in 6 Asia-Pacific countries by email, WhatsApp™ and text messaging. Main outcome measures 263 intensivists responded, of whom 231 were eligible for analysis. Response rates were 68%-100% in all countries except India, where it was 24%. 97% either conformed to or exceeded WHO recommendations for PPE-practice. 59% employed airborne precautions irrespective of aerosol-generation-procedures. There were variations in negative-pressure room use (highest in HK/Singapore), training (best in NZ), and PPE stock-awareness (best in HK/Singapore/NZ). High-flow-nasal-oxygenation and non-invasive ventilation were not options in most HK (66.7%, 83.3% respectively) and Singapore ICUs (50%, 80% respectively), but were considered in other countries to a greater extent. 38% reported not having specialized airway teams. Showering and “buddy-systems” were underutilized. Clinical waste disposal training was suboptimal (38%). Conclusions Most intensivists from six Asia-Pacific countries appeared to be aware of the WHO PPE-guidelines by either conforming to/exceeding the recommendations. Despite this, there were widespread variabilities across ICUs and countries in several domains, particularly related to PPE-training and preparedness. Standardising PPE guidelines may translate to better training, better compliance and policies that improve HCW safety. Adopting low-cost approaches such as buddy-systems should be encouraged. More importantly, better pandemic preparedness and building systems with deeply embedded culture of safety is essential to ensure the safety and well-being of HCWs during such pandemics. Author Contributorship Summary Box What is already known on this topic Personal-protective equipment (PPE) is the cornerstone to preventing HCW- infections. A search was done on March 23, 2020 on PubMed, Embase or Google Scholar using the mesh terms “personal protective equipment”, “PPE”, “preparedness OR practice OR training”. It revealed no previous studies on PPE preparedness in intensive care units (ICUs). No filters were used for the search. Several guidelines/recommendations issued by health organisations on PPE practice exist What are the new findings As the first study to evaluate PPE-preparedness in ICUs, it demonstrated major concerns on PPE-preparedness across several ICUs, particularly in Australia, India and Philippines. There was suboptimal PPE-training, under-utilisation of low-cost interventions such as buddy-systems/team-training, and stock-awareness. The guidelines by health organisations on PPE practice have several conflicting recommendations. How might it impact on clinical practice in the foreseeable future Standardising PPE guidelines by health organisations may translate to better training, better compliance and policies that improve HCW safety. To ensure the safety and well-being of HCWs, urgent measures are needed to improve PPE-preparedness and building systems with deeply embedded culture of safety. By helping ICUs evaluate and improve their current state of PPE preparedness, the study may help prevent healthcare worker infections and save lives.
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 | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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 | 0,001 |
| 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 ».