Alternative CPAP methods for the treatment of secondary serious respiratory failure due to pneumonia by COVID-19

Mateos-Rodríguez, Alonso; Ortega-Anselmi, Justo; Candel-González, Francisco Javier; Canora-Lebrato, Jesús; Fragiel-Saavedra, Marcos; Hernández-Píriz, Alba; Behzadi-Koocahni, Navid; Castillo, Juan González-Del; Pérez-Alonso, Antonio; Cruz, Maria Luisa de la; Casasola, Gonzalo García-de; Marco-Martínez, Javier; Zapatero-Gaviria, Antonio

doi:10.1016/j.medcle.2020.09.003

Cited by 3 publications

(3 citation statements)

References 14 publications

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“…Over time, other forms of respiratory support that were more available and less demanding than invasive mechanical ventilation (IMV), such as high-ow nasal oxygen (HFNO) 8 and noninvasive ventilation (NIV) 9 , became advocated. NIV e cacy is clearly validated in various diseases that cause respiratory failure, such as cardiogenic pulmonary edema or exacerbation of chronic obstructive pulmonary disease (COPD) 10 . Although controversial, use of NIV has also been supported in cases of ARDS and community acquired pneumonia, by improving clinically relevant outcomes such as progression to intubation 11,12 .…”

Section: Introductionmentioning

confidence: 99%

Prediction of noninvasive ventilation failure in COVID-19 patients: A retrospective observational study

Silva

Fernandes

Costa

et al. 2022

Preprint

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Background: In COVID-19, there are no available tools or guidelines for the difficult task of recognizing which patients do not benefit from keeping advanced respiratory support, such as noninvasive ventilation (NIV). Identifying failure is crucial to deliver the best possible care and optimize resources in overloaded healthcare systems. Therefore, this study aimed to build a model that predicts NIV failure and consequent death in COVID-19 patients.Methods: This is a retrospective observational study with critical COVID-19 patients who needed NIV but were not candidates or did not need invasive mechanical ventilation, admitted between 1st October 2020 and 31st March 2021, in a tertiary Portuguese hospital. The measure of interest was NIV failure, defined as COVID-19 related in-hospital death. A binary logistic regression was performed, where the outcome (dead vs alive) was set as the dependent variable. Using the independent variables of the logistic regression a decision tree classification model was implemented. Results: The 103 patients included had a mean age of 66.3 years old (SD=14.9), 38.8% were female and 82.5% autonomous. The developed prediction model was statistically significant (X2= 119.865; p< .001) with an area under the curve (AUC) of 0.994. Higher age, higher number of days with increases on FiO2, higher number of days of maximum expiratory positive airway pressure, lower number of days on NIV, and lower number of days from disease onset to hospital admission were, with statistical significance, associated with increased odds of death. A decision-tree classification model was obtained to achieve the best combination of variables to predict the outcome of interest. Conclusions: This study presents a model to predict death in COVID-19 patients treated with NIV (AUC of 0.994), including easily applicable variables that mainly reflect patients’ evolution during hospitalization. Along with the decision-tree classification model, these original findings have the potential to help clinicians define the best therapeutical approach to each patient and optimize medical resources. However, further research is needed on this subject of treatment failure, not only to understand if these results are reproducible but also, in a broader sense, to help fill this gap in modern medicine guidelines.

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Section: Introductionmentioning

confidence: 99%

Prediction of noninvasive ventilation failure in COVID-19 patients: A retrospective observational study

Silva

Fernandes

Costa

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Over time, other forms of respiratory support that were more available and less demanding than invasive mechanical ventilation (IMV), such as high-flow nasal oxygen (HFNO) and noninvasive ventilation (NIV), became advocated [8,9]. NIV efficacy is clearly validated in various diseases that cause respiratory failure, such as cardiogenic pulmonary edema or exacerbation of chronic obstructive pulmonary disease (COPD) [10]. Although controversial, the use of NIV has also been supported in cases of ARDS and community-acquired pneumonia, by improving clinically relevant outcomes such as progression to intubation [11,12].…”

Section: Introductionmentioning

confidence: 99%

“…NIV efficacy is clearly validated in various diseases that cause respiratory failure, such as cardiogenic pulmonary edema or exacerbation of chronic obstructive pulmonary disease (COPD) [ 10 ]. Although controversial, the use of NIV has also been supported in cases of ARDS and community-acquired pneumonia, by improving clinically relevant outcomes such as progression to intubation [ 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Noninvasive Ventilation Failure in COVID-19 Patients: When Shall We Stop?

Silva¹,

Fernandes²,

Costa³

et al. 2022

Cureus

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Introduction: In coronavirus disease 2019 , there are no tools available for the difficult task of recognizing which patients do not benefit from maintaining respiratory support, such as noninvasive ventilation (NIV). Identifying treatment failure is crucial to provide the best possible care and optimizing resources. Therefore, this study aimed to build a model that predicts NIV failure in patients who did not progress to invasive mechanical ventilation (IMV).Methods: This retrospective observational study included critical COVID-19 patients treated with NIV who did not progress to IMV. Patients were admitted to a Portuguese tertiary hospital between October 1, 2020, and March 31, 2021. The outcome of interest was NIV failure, defined as COVID-19-related in-hospital death. A binary logistic regression was performed, where the outcome (mortality) was the dependent variable. Using the independent variables of the logistic regression a decision-tree classification model was implemented.Results: The study sample, composed of 103 patients, had a mean age of 66.3 years (SD=14.9), of which 38.8% (40 patients) were female. Most patients (82.5%) were autonomous for basic activities of daily living. The prediction model was statistically significant with an area under the curve of 0.994 and a precision of 0.950. Higher age, a higher number of days with increases in the fraction of inspired oxygen (FiO 2 ), a higher number of days of maximum expiratory positive airway pressure, a lower number of days on NIV, and a lower number of days from disease onset to hospital admission were, with statistical significance, associated with increased odds of death. A decision-tree classification model was then obtained to achieve the best combination of variables to predict the outcome of interest.Conclusions: This study presents a model to predict death in COVID-19 patients treated with NIV in patients who did not progress to IMV, based on easily applicable variables that mainly reflect patients' evolution during hospitalization. Along with the decision-tree classification model, these original findings may help clinicians define the best therapeutical approach to each patient, prioritizing life-comforting measures when adequate, and optimizing resources, which is crucial within limited or overloaded healthcare systems. Further research is needed on this subject of treatment failure, not only to understand if these results are reproducible but also, in a broader sense, helping to fill this gap in modern medicine guidelines.

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Temporary hospitals in times of the COVID pandemic. An example and a practical view

Candel

Canora²,

Zapatero³

et al. 2021

Rev Esp Quimioter

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We describe the most widely used temporary hospital in Europe during the first pandemic wave, its structure, function, and achievements. Other models of care developed during the pandemic around the world were reviewed including their capacity, total bed/ICU bed ratio and time of use. We particularly analyzed the common and differential characteristics of this type of facilities. IFEMA Exhibition Center was transformed into a temporary 1,300-bed hospital, which was in continuous operation for 42 days. A total of 3,817 people were treated, generally patients with mild to moderate COVID-19, 91% of whom had pneumonia. The average length of stay was 5 to 36 days. The most frequent comorbidities were hypertension (16.5%), diabetes mellitus (9.1%), COPD (6%), asthma (4.6%), obesity (2.9%) and dementia (1.6%). A total of 113 patients (3%) were transferred to another centers for aggravation, 19 (0.5%) were admitted to ICU and 16 patients (0.4%) died. An element of great help to reducing the overload of care in large hospitals during peaks of health emergencies could be these flexible structures capable of absorbing the excess of patients. These must be safe, breaking domestic transmission and guarantee social and emotional needs of patients. The success of these structures depends on delimitation in admission criteria taking into account the proportion of patients who may require, during admission, assistance in the critical care area.

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Alternative CPAP methods for the treatment of secondary serious respiratory failure due to pneumonia by COVID-19

Cited by 3 publications

References 14 publications

Prediction of noninvasive ventilation failure in COVID-19 patients: A retrospective observational study

Prediction of noninvasive ventilation failure in COVID-19 patients: A retrospective observational study

Prediction of Noninvasive Ventilation Failure in COVID-19 Patients: When Shall We Stop?

Temporary hospitals in times of the COVID pandemic. An example and a practical view

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