Background Neutrophil-to-lymphocyte ratio (NLR) has been used to predict the prognosis of patients with sepsis with inconsistent results. This meta-analysis aimed to clarify the prognostic value of NLR in patients with sepsis. Methods A comprehensive literature search for relevant studies, published prior to March 2019, was conducted using PubMed, Web of Science, and the China National Knowledge. Infrastructure database. Standard mean differences (SMDs) with 95% confidence intervals (CI) were used to evaluate the NLR of patients with sepsis retrospectively. Hazard ratios (HRs) with 95% CIs were used to evaluate the prognostic value of NLR in patients with sepsis. Results Patients from 14 studies (n = 11,564) were selected for evaluation. Nine studies (1371 patients) analyzed the NLR in these patients. The pooled results showed significantly higher NLR in non-survivors than in survivors (random-effects model: SMD = 1.18, 95% CI; 0.42–1.94). Nine studies (10,685 patients) evaluated the prognostic value of NLR for sepsis; the pooled results showed that higher NLR was associated with poor prognosis in patients with sepsis (fixed-effects model: HR = 1.75, 95% CI; 1.56–1.97). Subgroup analysis revealed that study design, cut-off NLR, or primary outcome did not affect the prognostic value of NLR in patients with sepsis. Conclusion This meta-analysis indicates that NLR may be a helpful prognostic biomarker of patients with sepsis and that higher NLR values may indicate unfavorable prognoses in these patients.

Prognostic value of neutrophil-to-lymphocyte ratio in sepsis: A meta-analysis.

Rationale: Some patients with coronavirus disease 2019 (COVID-19) rapidly develop respiratory failure or even die, underscoring the need for early identification of patients at elevated risk of severe illness. This study aims to quantify pneumonia lesions by computed tomography (CT) in the early days to predict progression to severe illness in a cohort of COVID-19 patients. Methods: This retrospective cohort study included confirmed COVID-19 patients. Three quantitative CT features of pneumonia lesions were automatically calculated using artificial intelligence algorithms, representing the percentages of ground-glass opacity volume (PGV), semi-consolidation volume (PSV), and consolidation volume (PCV) in both lungs. CT features, acute physiology and chronic health evaluation II (APACHE-II) score, neutrophil-to-lymphocyte ratio (NLR), and d-dimer, on day 0 (hospital admission) and day 4, were collected to predict the occurrence of severe illness within a 28-day follow-up using both logistic regression and Cox proportional hazard models. Results: We included 134 patients, of whom 19 (14.2%) developed any severe illness. CT features on day 0 and day 4, as well as their changes from day 0 to day 4, showed predictive capability. Changes in CT features from day 0 to day 4 performed the best in the prediction (area under the receiver operating characteristic curve = 0.93, 95% confidence interval [CI] 0.87~0.99; C-index=0.88, 95% CI 0.81~0.95). The hazard ratios of PGV and PCV were 1.39 (95% CI 1.05~1.84, P=0.023) and 1.67 (95% CI 1.17~2.38, P=0.005), respectively. CT features, adjusted for age and gender, on day 4 and in terms of changes from day 0 to day 4 outperformed APACHE-II, NLR, and d-dimer. Conclusions: CT quantification of pneumonia lesions can early and non-invasively predict the progression to severe illness, providing a promising prognostic indicator for clinical management of COVID-19.

CT quantification of pneumonia lesions in early days predicts progression to severe illness in a cohort of COVID-19 patients.

A new coronavirus-CoV-2 virus has caused disease outbreaks in many countries, and the number of cases is increasing rapidly through transmission from person to person. Clinical acoustics for SARS-CoV-2 patients are crucial to distinguish them from other respiratory infections. Symptomatic sufferers can also have pulmonary lesions on the photographs. A computerized tomography study in patients with suspected COVID-19 pneumonia consists of using a high-resolution approach (HRCT). Artificial intelligence applications need to be useful in categorizing the illness to an awesome severity and integrating the structured file, organized consistent with subjective issues, with objective and quantitative checks of the amount of the lesions. Data indicate the statistical document of the world in trendy. This method, with the aid of a coloring map, identifies floor glass in submission processing and separates it from consolidation and units it as a percentage in respect to the balanced weight loss program.

Quantitative Analysis of COVID-19 Patients: A Preliminary Statistical Result of Deep Learning Artificial Intelligence Framework

Inflammation plays a major role in cancer development and progression and has the potential to be used as a prognostic marker in cancer. Previous studies have attempted to evaluate Platelet-to-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR) or monocyte-lymphocyte ratio (MLR) as indicators of inflammation/prognostic markers in cancer, but there is no common consensus on their application in clinical practice. The aim of this systematic review and meta-analysis is to (a) assess the prognostic efficacy of all three prognostic markers in comparison to each other and (b) investigate the prognostic potential of these three markers in HNC. The study followed PRISMA guidelines, with the literature being collated from multiple bibliographic databases. Preliminary and secondary screening were carried out using stringent inclusion/exclusion criteria. Meta-analysis was carried out on selected studies using CMA software and HR as the pooled effect size metric. A total of 49 studies were included in the study. The pooled HR values of PLR, NLR and MLR indicated that they were significantly correlated with poorer OS. The pooled effect estimates for PLR, NLR and MLR were 1.461 (95% CI 1.329-1.674), 1.639 (95% CI 1.429-1.880) and 1.002 (95% CI 0.720-1.396), respectively. Significant between-study heterogeneity was observed in the meta-analysis of all three. The results of this study suggest that PLR, NLR and MLR ratios can be powerful prognostic markers in head and neck cancers that can guide treatment. Further evidence from large-scale clinical studies on patient cohorts are required before they can be incorporated as a part of the clinical method. PROSPERO Registration ID: CRD42019121008.

Prognostic Utility of Platelet-Lymphocyte Ratio, Neutrophil-Lymphocyte Ratio and Monocyte-Lymphocyte Ratio in Head and Neck Cancers: A Detailed PRISMA Compliant Systematic Review and Meta-Analysis.

Background:Despite the survival advantage, not all metastatic renal cell carcinoma (mRCC) patients achieve a long-term benefit from immunotherapy. Moreover, the identification of prognostic biomark...

https://journals.sagepub.com/doi/pdf/10.1177/17588359211019642

Inflammatory indices and clinical factors in metastatic renal cell carcinoma patients treated with nivolumab: the development of a novel prognostic score (Meet-URO 15 study)

Royam Madhav Madurantakam

Papers

Prognostic significance of blood inflammatory biomarkers NLR, PLR, and LMR in cancer-A protocol for systematic review and meta-analysis.