Abstract

Background and objectiveChronic obstructive pulmonary disease (COPD) is a condition in which the expiratory airflow is restricted and is characterized by inflammation. Recently, inflammation-related biomarkers such as neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and monocyte-lymphocyte ratio (MLR) have been used to predict the prognosis in COPD. The aim of this study was to evaluate the role of biomarkers such as NLR, PLR, and MLR in COPD patients in intensive care and to examine the ability of these markers to predict the prognosis [length of stay in hospital (LOSH), duration of mechanical ventilation (MV), length of stay in ICU (LOS ICU), and mortality].MethodsA total of 562 patients who were treated in the ICU between 2018 and 2019 were retrospectively reviewed. Among them, 369 were patients with COPD. We evaluated clinical data including patient demographics, Charlson Comorbidity Index (CCI), Acute Physiology and Chronic Health Evaluation II (APACHE II) score, Sequential Organ Failure Assessment (SOFA) score, LOS ICU, LOSH, duration of MV, as well as NLR, PLR, and MLR values. Data on patient deaths (30-day mortality) was obtained from the Death Notification System.ResultsAge, LOSH, CCI, and SOFA were found to predict mortality in COPD patients. In cases with mortality, age, inotropic use, MV duration, LOS ICU, APACHE II, CCI, SOFA, lymphocyte count, neutrophil count, platelet count, monocyte count, NLR, PLR, and MLR levels were statistically significantly higher than those in cases without mortality. There was a positive and low statistically significant relationship of NLR, PLR, and MLR with prognostic factors like MV duration, APACHE II scores, and SOFA scores.ConclusionThe NLR, PLR, and MLR values may be used as prognostic indicators in COPD patients in intensive care. Although there are many studies endorsing the use of biomarkers such as NLR, PLR, and MLR as prognostic indicators, further comparative studies on this subject are still required to gain deeper insights into the topic.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.