Risk factors for invasive and non-invasive ventilatory support and mortality in hospitalized patients with COVID-19

Chebotareva, Natalia; Berns, Svetlana; Tatyana, Androsova; Moiseev, Sergey

doi:10.1016/j.medin.2021.04.002

Cited by 5 publications

(2 citation statements)

References 4 publications

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“…The models can also prioritize which populations to vaccinate or to urge to receive booster doses to maximize lives saved and reduce the load on hospitalization facilities. Several attempts have already been made to build predictive models for COVID-19 severity, notably [4,9,19,[35][36][37][38]. Among the five models cited in the preceding sentence, only the models of Iannou and colleagues [4] and of Experton and colleagues [27] predict at least one of risk of hospitalization or risk of death in a newly infected individual.…”

Section: Discussionmentioning

confidence: 99%

A Calculator for COVID-19 Severity Prediction Based on Patient Risk Factors and Number of Vaccines Received

et al. 2022

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Vaccines have allowed for a significant decrease in COVID-19 risk, and new antiviral medications can prevent disease progression if given early in the course of the disease. The rapid and accurate estimation of the risk of severe disease in new patients is needed to prioritize the treatment of high-risk patients and maximize lives saved. We used electronic health records from 101,039 individuals infected with SARS-CoV-2, since the beginning of the pandemic and until 30 November 2021, in a national healthcare organization in Israel to build logistic models estimating the probability of subsequent hospitalization and death of newly infected patients based on a few major risk factors (age, sex, body mass index, hemoglobin A1C, kidney function, and the presence of hypertension, pulmonary disease, and malignancy) and the number of BNT162b2 mRNA vaccine doses received. The model’s performance was assessed by 10-fold cross-validation: the area under the curve was 0.889 for predicting hospitalization and 0.967 for predicting mortality. A total of 50%, 80%, and 90% of death events could be predicted with respective specificities of 98.6%, 95.2%, and 91.2%. These models enable the rapid identification of individuals at high risk for hospitalization and death when infected, and they can be used to prioritize patients to receive scarce medications or booster vaccination. The calculator is available online.

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Section: Discussionmentioning

confidence: 99%

A Calculator for COVID-19 Severity Prediction Based on Patient Risk Factors and Number of Vaccines Received

et al. 2022

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“…Chen et al have used metrics from respiratory mechanics as 60-day outcome predictors in ARDS patients utilizing artificial intelligence techniques [ 8 ]. Russian researchers have identified the systemic inflammatory response, coagulation disorders and arterial hypertension as risk factors for non-invasive mechanical ventilation or even tracheal intubation in Covid-19 patients [ 9 ], whereas, in a large Spanish study from 30 Intensive Care Units during the Covid-19 pandemic [ 10 ], the following risk factors led to poor outcomes: Older age, high APACHE II score, acute kidney injury (grades II and III) and presence of septic shock. Overall ICU mortality was reported at 31%.…”

Section: Introductionmentioning

confidence: 99%

Back to the future: the novel art of digital auscultation applied in a prospective observational study of critically ill Covid-19 patients

Kaimakamis,

Kotoulas,

Tzimou

et al. 2024

Pneumonia

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Background The Covid-19 pandemic has caused immense pressure on Intensive Care Units (ICU). In patients with severe ARDS due to Covid-19, respiratory mechanics are important for determining the severity of lung damage. Lung auscultation could not be used during the pandemic despite its merit. The main objective of this study was to investigate associations between lung auscultatory sound features and lung mechanical properties, length of stay (LOS) and survival, in adults with severe Covid-19 ARDS. Methods Consecutive patients admitted to a large ICU between 2020 and 2021 (n = 173) were included. Digital stethoscopes obtained auscultatory sounds and stored them in an on-line database for replay and further processing using advanced AI techniques. Correlation and regression analysis explored relationships between digital auscultation findings and lung mechanics or the ICU outcome. The resulting annotated lung sounds database is also publicly available as supplementary material. Results The presence of squawks was associated with the ICU LOS, outcome and 90-day mortality. Other features (age, SOFA score & oxygenation index upon admission, minimum crackle entropy) had significant impact on outcome. Additional features affecting the 90-d survival were age and mean crackle entropy. Multivariate logistic regression showed that survival was affected by age, baseline SOFA, baseline oxygenation index and minimum crackle entropy. Conclusions Respiratory mechanics were associated with various adventitious sounds, whereas the lung sound analytics and the presence of certain adventitious sounds correlated with the ICU outcome and the 90-d survival. Spectral features of crackles sounds can serve as prognostic factors for survival, highlighting the importance of digital auscultation.

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Predictors of mechanical ventilation and mortality in critically ill patients with COVID-19 pneumonia

Muñoz Lezcano,

Armengol de la Hoz,

Corbi

et al. 2024

Medicina Intensiva

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Risk factors for invasive and non-invasive ventilatory support and mortality in hospitalized patients with COVID-19

Cited by 5 publications

References 4 publications

A Calculator for COVID-19 Severity Prediction Based on Patient Risk Factors and Number of Vaccines Received

A Calculator for COVID-19 Severity Prediction Based on Patient Risk Factors and Number of Vaccines Received

Back to the future: the novel art of digital auscultation applied in a prospective observational study of critically ill Covid-19 patients

Predictors of mechanical ventilation and mortality in critically ill patients with COVID-19 pneumonia

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