Abstract
Introduction: The pandemic caused by the coronavirus disease 2019 represented a framework of health, social and economic crisis at a global level, generating great human losses, which is why the need arises to determine the prognostic factors, including some accessible, rapid and low-cost, which may be useful in predicting potentially serious cases. Objective: Determine if the neutrophil-lymphocyte ratio predicts the severity of COVID-19 according to the severity classification of the Ministry of Health. Materials and methods: A retrospective cohort study was carried out, using consecutive sampling, 200 patients with a confirmed diagnosis of COVID-19 were included upon admission for emergencies at Hospital III EsSalud Chimbote, whose recruitment period was from February to May 2021 with a 30-day follow-up. An multivariate analysis was performed with binary logistic regression in the R Commander version 4.0.5 program, developing a training model to predict the risk of COVID-19 severity during hospitalization. Results: With a stepwise construction strategy from back to front, a model was obtained that included the neutrophil lymphocyte ratio (OR: 1.14) adjusted to lactate dehydrogenase and age as predictors of severe COVID-19; showing an accuracy of 74% for a high-risk threshold greater than 40% and an area under the curve (AUC) of 0.83 (95%CI:0.78-0.88). Conclusion: The neutrophil-lymphocyte ratio was an independent predictor of the risk of developing severe COVID-19.
| Translated title of the contribution | Neutrophil lymphocyte ratio as a predictor of severity in patients with COVID-19 |
|---|---|
| Original language | Spanish |
| Journal | Revista del Cuerpo Medico Hospital Nacional Almanzor Aguinaga Asenjo |
| Volume | 17 |
| Issue number | 4 |
| DOIs | |
| State | Published - 2024 |
Bibliographical note
Publisher Copyright:© 2024 Publicado por Cuerpo Médico Hospital Nacional Almanzor Aguinaga Asenjo. Este es un artículo de libre acceso. Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0. https://creativecommons.org/licenses/by/4.0/