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.
Background
COVID-19 is primarily a respiratory disease; however, there is also evidence that it causes endothelial damage in the microvasculature of several organs. The aim of the present study is to characterize in vivo the microvascular reactivity in peripheral skeletal muscle of severe COVID-19 patients.
Methods
This is a prospective observational study carried out in Spain, Mexico and Brazil. Healthy subjects and severe COVID-19 patients admitted to the intermediate respiratory (IRCU) and intensive care units (ICU) due to hypoxemia were studied. Local tissue/blood oxygen saturation (StO2) and local hemoglobin concentration (THC) were non-invasively measured on the forearm by near-infrared spectroscopy (NIRS). A vascular occlusion test (VOT), a three-minute induced ischemia, was performed in order to obtain dynamic StO2 parameters: deoxygenation rate (DeO2), reoxygenation rate (ReO2), and hyperemic response (HAUC). In COVID-19 patients, the severity of ARDS was evaluated by the ratio between peripheral arterial oxygen saturation (SpO2) and the fraction of inspired oxygen (FiO2) (SF ratio).
Results
Healthy controls (32) and COVID-19 patients (73) were studied. Baseline StO2 and THC did not differ between the two groups. Dynamic VOT-derived parameters were significantly impaired in COVID-19 patients showing lower metabolic rate (DeO2) and diminished endothelial reactivity. At enrollment, most COVID-19 patients were receiving invasive mechanical ventilation (MV) (53%) or high-flow nasal cannula support (32%). Patients on MV were also receiving sedative agents (100%) and vasopressors (29%). Baseline StO2 and DeO2 negatively correlated with SF ratio, while ReO2 showed a positive correlation with SF ratio. There were significant differences in baseline StO2 and ReO2 among the different ARDS groups according to SF ratio, but not among different respiratory support therapies.
Conclusion
Patients with severe COVID-19 show systemic microcirculatory alterations suggestive of endothelial dysfunction, and these alterations are associated with the severity of ARDS. Further evaluation is needed to determine whether these observations have prognostic implications. These results represent interim findings of the ongoing HEMOCOVID-19 trial.
Trial registration ClinicalTrials.gov NCT04689477. Retrospectively registered 30 December 2020.
We introduce a methodology for acquisition and analysis of infrared (IR) images, picturing the metabolic heat emission from the human skin. Then we analyze the radiometric asymmetries in the patients with DM2 in comparison to the natural asymmetries, represented by the control group. In this regard, we introduce three indices (TAI, SAI, TtAI) with conditions for disclosing asymmetries displayed on images acquired in passive mode (the natural thermal emission, NTE). Then, the indices are adapted for analysis of IR-images acquired in what we brand as active mode (the NTE is altered by means of a controlled external stimulus). Out of the passive mode, the TAI and TtAI indices show the best diagnostic performance, with values of sensitivity and specificity of 89% and 72%, and 83% and 78%, respectively. Instead, from the active mode analysis we get 86% of sensitivity and 83% of specificity for the TRI index. We report data obtained form IR-images of 36 patients with Diabetes Mellitus Type II (DM2) and 18 non-diabetic controls. For both groups the image acquisition is made in passive and active mode, picturing the anterior and posterior views of the lower limbs. With this analysis, we manage to unveil the contra-lateral radiometric asymmetries of the legs, along with the differences between patients and controls. Finally, we report the consistency of these indices with glucose and glycated hemoglobin (HbA1c), known to be the golden clinical variables used to diagnose DM2.
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