There is a deep need for mortality predictors that allow clinicians to quickly triage patients with severe coronavirus disease 2019 (Covid-19) into intensive care units at the time of hospital admission. Thus, we examined the efficacy of the lymphocyte-to-neutrophil ratio (LNR) and neutrophil-to-monocyte ratio (NMR) as predictors of in-hospital death at admission in patients with severe Covid-19. A total of 54 Mexican adult patients with Covid-19 that met hospitalization criteria were retrospectively enrolled, followed-up daily until hospital discharge or death, and then assigned to survival or non-survival groups. Clinical, demographic, and laboratory parameters were recorded at admission. A total of 20 patients with severe Covid-19 died, and 75% of them were men older than 62.90 ± 14.18 years on average. Type 2 diabetes, hypertension, and coronary heart disease were more prevalent in non-survivors. As compared to survivors, LNR was significantly fourfold decreased while NMR was twofold increased. LNR ≤ 0.088 predicted in-hospital mortality with a sensitivity of 85.00% and a specificity of 74.19%. NMR ≥ 17.75 was a better independent risk factor for mortality with a sensitivity of 89.47% and a specificity of 80.00%. This study demonstrates for the first time that NMR and LNR are accurate predictors of in-hospital mortality at admission in patients with severe Covid-19.
A better understanding of the molecular mechanisms of low-grade systemic inflammation in promoting cardio-metabolic diseases is necessary, in order to further design novel anti-inflammatory therapies that take into consideration clinical data, as well as the circulating levels of cytokines, immune cells, and metabolic damage-associated molecular patterns in each patient.
Background
It has been observed that subjects with comorbidities related to metabolic syndrome (MetS) as hypertension, obesity, cardiovascular disease (CVD), and diabetes mellitus (DM2) show severe cases and a higher mortality by COVID-19. To date, there is little information available on the impact of the interaction between these comorbidities in the risk of death by COVID-19.
Aim of the Study
To evaluate the impact of the combinations of MetS components in overall survival (OS) and risk of death among COVID-19 patients.
Methods
Using public data of the Ministry of Health, suspected, and confirmed COVID-19 cases from February 25–June 6, 2020 was analyzed. Mortality odds ratio (OR) was calculated with a univariate analysis (95% CI) and attributable risk. Interactions between components and survival curves were analyzed and a multivariate logistics regression analysis was conducted.
Results
The analysis included 528,651 cases out of which 202,951 were confirmed for COVID-19. Probabilities of OS among confirmed patients were 0.93, 0.89, 0.87, 0.86, and 0.83 while the OR of multivariate analysis was 1.83 (1.77–1.89), 2.58 (2.48–2.69), 2.83 (2.66–3.01), and 3.36 (2.83–3.99) for zero, one, two, three, and four MetS components, respectively. The combination with the highest risk was DM2 + hypertension at 2.22 (2.15–2.28), and the attributable risk for any component was 9.35% (9.21–9.49). Only the combination obesity + CVD showed no significant interaction.
Conclusion
The presence of one MetS component doubles the risk of death by COVID-19, which was higher among patients with DM2 + hypertension. Only obesity and CVD do not interact significantly.
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