Projects

Optimizing respiratory care in coronavirus disease-2019: A comprehensive, protocolized, evidence-based, algorithmic approach

Groups and Associations Sagar Sinha, Indrani Sardesai1, Sagar C. Galwankar, P.W.B. Nanayakkara, Dindigal Ramakrishnan Narasimhan, Joydeep Grover, Harry L. Anderson III, Lorenzo Paladino, David F. Gaieski, Salvatore Di Somma, Stanislaw P. Stawicki
International Journal of Critical Illness and Injury Science | 2020

Respiratory management of patients with corona virus disease 2019 (COVID-19) is both complex and highly nuanced.[1] Although most patients with COVID-19 develop mild or no symptoms, a smaller proportion (up to 15%) experience progressive hypoxic respiratory failure requiring escalating levels of oxygen support.[2] Significant accumulated experience in caring for patients with SARS-CoV-2 pulmonary illness resulted in the recognition of major respiratory failure patterns, the benefits of early proning, and the importance of a step-wise escalation in levels of invasiveness across the entire spectrum from nasal cannula to extracorporeal support.[2-4] Given substantial heterogeneity among various algorithmic approaches to oxygen therapy and the need for both standardization and optimization of clinical management methodologies, the Joint ACAIM-WACEM COVID-19 Clinical Management Taskforce (CCMT) set out to establish and publish a unified approach to the patient who presents with SARS-CoV-2 lower respiratory tract infection (LRTI). In addition, the CCMT hopes that a protocol-driven strategy will lead to conservation of precious healthcare resources, such as intensive care beds and ventilators, by eliminating unnecessary interventions and various other process inefficiencies.                                                                                                                                                                                                   Key Words: Coronavirus disease 2019, respiratory care optimization, clinical algorithm, SARS-CoV-2, evidence-based guideline, resource-sparing strategie

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