Objective: to screen putative associations between liver markers and proinflammatory-related features concerning infectious morbidity and fatal outcomes in COVID-19 patients. Methods: a total of 2094 COVID-19 positive patients from the COVID-DATA-SAFE-LIFES cohort (HM hospitals consortium) were classified according to median values of hepatic, inflammatory, and clinical indicators. Logistic regression models were fitted and ROC cures were generated to explain disease severity and mortality. Results: intensive care unit (ICU) assistance plus death outcomes were associated with liver dysfunction, hyperinflammation, respiratory insufficiency, and higher associated comorbidities. Four models including age, sex, neutrophils, D-dimer, oxygen saturation lower than 92%, C-reactive protein (CRP), Charlson Comorbidity Index (CCI), FIB-4 and interactions with CRP, neutrophils, and CCI explained ICU plus death variance in more than 28%. The predictive values of ROC curves were: FIB-4 (0.7339), AST/ALT ratio (0.7107), CRP (0.7003), CCI index (0.6778), neutrophils (0.6772), and platelets (0.5618) concerning ICU plus death outcomes. Conclusions: the results of this research revealed that liver and proinflammatory features are important determinants of COVID-19 morbidity and fatal outcomes, which could improve the current understanding of the COVID-19 physiopathology as well as to facilitate the clinical management and therapy decision-making of this disease under a personalized medicine scope.
Introducción: Todavía no se comprende si el desarrollo político, científico y médico en un país se asocia a mejores resultados clínicos de los pacientes con COVID-19 según el sexo. Objetivo: Determinar las tendencias de mortalidad hospitalaria asociada a COVID-19 en mujeres y hombres entre marzo de 2020 y febrero de 2022. Métodos: Se utilizaron los datos clínicos de todos los pacientes con COVID-19 atendidos en 21 hospitales españoles, tanto de quienes fueron dados de alta como de quienes fallecieron durante el ingreso. La asociación entre la fecha del ingreso y la mortalidad se analizó con modelos de regresión logística. Resultados: Fueron incluidos 7974 pacientes, de los cuales 3234 fueron mujeres y 928 fallecieron. Se encontró una tendencia significativa y decreciente en la mortalidad según avanzaba la fecha del ingreso. Cuando el análisis se realizó por sexos, no se halló una tendencia significativa en las mujeres ], p = 0.239), pero sí en los hombres , p < 0.001). Conclusión: Las políticas de salud, junto con las intervenciones clínicas y preventivas, pueden dar cuenta de los resultados. Diferencias en la respuesta al tratamiento o en los comportamientos pueden explicar por qué la mortalidad no disminuye en las mujeres.
The association between elevated liver enzymes or FIB-4 (fibrosis index 4) and outcome in patients with venous thromboembolism (VTE) has not been evaluated. Data from patients in RIETE ( R egistro I nformatizado E nfermedad T rombo E mbólica) were used to assess the association between elevated liver enzymes or FIB-4 levels and the rates of major bleeding or death in apparent liver disease-free patients with acute VTE under anticoagulation therapy. A total of 6206 patients with acute VTE and without liver disease were included. Of them, 92 patients had major bleeding and 168 died under anticoagulation therapy. On multivariable analysis, patients with elevated liver enzymes were at increased mortality risk (HR: 1.58; 95% CI: 1.10–2.28), while those with FIB-4 levels > 2.67 points were at increased risk for major bleeding (HR: 1.69; 95% CI: 1.04–2.74). Evaluation of liver enzymes and FIB-4 index at baseline in liver disease-free patients with VTE may provide additional information on the risk for major bleeding or death during anticoagulation. Supplementary Information The online version contains supplementary material available at 10.1007/s11739-021-02858-x.
COVID-19 has overloaded health system worldwide; thus, it demanded a triage method for an efficient and early discrimination of patients with COVID-19. The objective of this research was to perform a model based on commonly requested hematological variables for an early featuring of patients with COVID-19 form other viral pneumonia. This investigation enrolled 951 patients (mean of age 68 and 56% of male) who underwent a PCR test for respiratory viruses between January 2019 and January 2020, and those who underwent a PCR test for detection of SARS-CoV-2 between February 2020 and October 2020. A comparative analysis of the population according to PCR tests and logistic regression model was performed. A total of 10 variables were found for the characterization of COVID-19: age, sex, anemia, immunosuppression, C-reactive protein, chronic obstructive pulmonary disease, cardiorespiratory disease, metastasis, leukocytes and monocytes. The ROC curve revealed a sensitivity and specificity of 75%. A deep analysis showed low levels of leukocytes in COVID-19-positive patients, which could be used as a primary outcome of COVID-19 detection. In conclusion, this investigation found that commonly requested laboratory variables are able to help physicians to distinguish COVID-19 and perform a quick stratification of patients into different prognostic categories.
Introducción: Todavía no se comprende si el desarrollo político, científico y médico en un país se asocia a mejores resultados clínicos de los pacientes con COVID-19 según el sexo. Objetivo: Determinar las tendencias de mortalidad hospitalaria asociada a COVID-19 en mujeres y hombres entre marzo de 2020 y febrero de 2022. Métodos: Se utilizaron los datos clínicos de todos los pacientes con COVID-19 atendidos en 21 hospitales españoles, tanto de quienes fueron dados de alta como de quienes fallecieron durante el ingreso. La asociación entre la fecha del ingreso y la mortalidad se analizó con modelos de regresión logística. Resultados: Fueron incluidos 7974 pacientes, de los cuales 3234 fueron mujeres y 928 fallecieron. Se encontró una tendencia significativa y decreciente en la mortalidad según avanzaba la fecha del ingreso. Cuando el análisis se realizó por sexos, no se halló una tendencia significativa en las mujeres ], p = 0.239), pero sí en los hombres , p < 0.001). Conclusión: Las políticas de salud, junto con las intervenciones clínicas y preventivas, pueden dar cuenta de los resultados. Diferencias en la respuesta al tratamiento o en los comportamientos pueden explicar por qué la mortalidad no disminuye en las mujeres.
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