Prognosis of COVID-19 pneumonia can be early predicted combining Age-adjusted Charlson Comorbidity Index, CRB score and baseline oxygen saturation.
Autor: | Nuevo-Ortega P; Intensive Care Unit, Hospital Universitario Virgen de la Victoria, Málaga, Spain. pilarnuevoortega@gmail.com.; Instituto de Investigación Biomédica de Málaga, Málaga, Spain. pilarnuevoortega@gmail.com., Reina-Artacho C; Intensive Care Unit, Hospital Universitario Virgen de la Victoria, Málaga, Spain.; Instituto de Investigación Biomédica de Málaga, Málaga, Spain., Dominguez-Moreno F; Intensive Care Unit, Hospital Universitario Virgen de la Victoria, Málaga, Spain.; Instituto de Investigación Biomédica de Málaga, Málaga, Spain., Becerra-Muñoz VM; Intensive Care Unit, Hospital Universitario Virgen de la Victoria, Málaga, Spain.; Instituto de Salud Carlos III, Madrid, Spain., Ruiz-Del-Fresno L; Intensive Care Unit, Hospital Universitario Virgen de la Victoria, Málaga, Spain.; Instituto de Investigación Biomédica de Málaga, Málaga, Spain., Estecha-Foncea MA; Intensive Care Unit, Hospital Universitario Virgen de la Victoria, Málaga, Spain.; Instituto de Investigación Biomédica de Málaga, Málaga, Spain. |
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Jazyk: | angličtina |
Zdroj: | Scientific reports [Sci Rep] 2022 Feb 11; Vol. 12 (1), pp. 2367. Date of Electronic Publication: 2022 Feb 11. |
DOI: | 10.1038/s41598-022-06199-3 |
Abstrakt: | In potentially severe diseases in general and COVID-19 in particular, it is vital to early identify those patients who are going to progress to severe disease. A recent living systematic review dedicated to predictive models in COVID-19, critically appraises 145 models, 8 of them focused on prediction of severe disease and 23 on mortality. Unfortunately, in all 145 models, they found a risk of bias significant enough to finally "not recommend any for clinical use". Authors suggest concentrating on avoiding biases in sampling and prioritising the study of already identified predictive factors, rather than the identification of new ones that are often dependent on the database. Our objective is to develop a model to predict which patients with COVID-19 pneumonia are at high risk of developing severe illness or dying, using basic and validated clinical tools. We studied a prospective cohort of consecutive patients admitted in a teaching hospital during the "first wave" of the COVID-19 pandemic. Follow-up to discharge from hospital. Multiple logistic regression selecting variables according to clinical and statistical criteria. 404 consecutive patients were evaluated, 392 (97%) completed follow-up. Mean age was 61 years; 59% were men. The median burden of comorbidity was 2 points in the Age-adjusted Charlson Comorbidity Index, CRB was abnormal in 18% of patients and basal oxygen saturation on admission lower than 90% in 18%. A model composed of Age-adjusted Charlson Comorbidity Index, CRB score and basal oxygen saturation can predict unfavorable evolution or death with an area under the ROC curve of 0.85 (95% CI 0.80-0.89), and 0.90 (95% CI 0.86 to 0.94), respectively. Prognosis of COVID-19 pneumonia can be predicted without laboratory tests using two classic clinical tools and a pocket pulse oximeter. (© 2022. The Author(s).) |
Databáze: | MEDLINE |
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