Association of blood group A with hospital comorbidity in patients infected by SARS-CoV-2.

Background and objectives: In the pandemic caused by SARS-CoV-2, identifying which risk factors are associated with the most serious forms of the disease is important. Blood group A has been presented in various studies as a poor prognostic factor. The objective of this study was to evaluate whether patients with blood group A were associated with more important comorbidities, measured by the Charlson Index, which may explain their worse clinical evolution. Patients and methods: A prospective and consecutive study examined 100 patients diagnosed with COVID-19 and admitted in March 2020. A multivariate linear regression model was used to evaluate the association of blood group A with the Charlson Index. Results: Patients in group A had a higher Charlson Index (P = .037), rate of lymphopenia (P = .039) and thrombopenia (P = .014), and hospital mortality (P = .044). Blood group A was an independent factor associated with the Charlson Index (B 0.582, 95% CI 0.02-1.14, P = .041). Conclusions: Group A was independently associated with greater comorbidity, associated with an increase of 0.582 points in the Charlson Index compared to other blood groups. It was also associated with lower hospital mortality.

Fundamento y objetivos: En la pandemia provocada por SARS-CoV-2, es importante identificar qué factores de riesgo se asocian a las formas más graves de la enfermedad. El grupo sanguíneo A se ha presentado en diversos estudios como factor de mal pronóstico. El objetivo de este estudio radica en evaluar si los pacientes de grupo sanguíneo O asocian comorbilidades más importantes, medido por el Índice de Charlson, que puedan justificar también su peor evolución clínica. Pacientes y método: Estudio prospectivo y consecutivo con 100 pacientes diagnosticados de COVID-19 ingresados en marzo de 2020. Se empleó un modelo de regresión lineal multivariante para evaluar la asociación del grupo sanguíneo A con el Índice de Charlson. Resultados: Los pacientes del grupo A presentaron mayor Índice de Charlson (P = .037), linfopenia (P = .039), trombopenia (P = .014) y mortalidad hospitalaria (P = .044).El grupo sanguíneo A demostró ser un factor independiente asociado a dicho índice [B 0.582, IC 95% (0.02­1.14), P = .041]. Conclusiones: El grupo A se asocia de forma independiente a mayor comorbilidad, asociando un incremento de 0.582 puntos en el índice de Charlson con respecto al resto de grupos sanguíneos. Además, asocia una tendencia de menor mortalidad hospitalaria.

Association of blood group A with hospital comorbidity in patients infected by SARS-CoV-2. / Asociación del grupo sanguíneo A con mayor comorbilidad hospitalaria en pacientes infectados por SARS-CoV-2.

BACKGROUND AND OBJECTIVES: In the pandemic caused by SARS-CoV-2, identifying which risk factors are associated with the most serious forms of the disease is important. Blood group A has been presented in various studies as a poor prognostic factor. The objective of this study was to evaluate whether patients with blood group A were associated with more important comorbidities, measured by the Charlson Index, which may explain their worse clinical evolution. PATIENTS AND METHODS: A prospective and consecutive study examined 100 patients diagnosed with COVID-19 and admitted in March 2020. A multivariate linear regression model was used to evaluate the association of blood group A with the Charlson Index. RESULTS: Patients in group A had a higher Charlson Index (P=.037), rate of lymphopenia (P=.039) and thrombopenia (P=.014), and hospital mortality (P=.044). Blood group A was an independent factor associated with the Charlson Index (B 0.582, 95% CI 0.02-1.14, P=0.041). CONCLUSIONS: Group A was independently associated with greater comorbidity, associated with an increase of 0.582 points in the Charlson Index compared to other blood groups. It was also associated with lower hospital mortality.

The importance of association of comorbidities on COVID-19 outcomes: a machine learning approach.

BACKGROUND: The individual influence of a variety of comorbidities on COVID-19 patient outcomes has already been analyzed in previous works in an isolated way. We aim to determine if different associations of diseases influence the outcomes of inpatients with COVID-19. METHODS: Retrospective cohort multicenter study based on clinical practice. Data were taken from the SEMI-COVID-19 Registry, which includes most consecutive patients with confirmed COVID-19 hospitalized and discharged in Spain. Two machine learning algorithms were applied in order to classify comorbidities and patients (Random Forest -RF algorithm, and Gaussian mixed model by clustering -GMM-). The primary endpoint was a composite of either, all-cause death or intensive care unit admission during the period of hospitalization. The sample was randomly divided into training and test sets to determine the most important comorbidities related to the primary endpoint, grow several clusters with these comorbidities based on discriminant analysis and GMM, and compare these clusters. RESULTS: A total of 16,455 inpatients (57.4% women and 42.6% men) were analyzed. According to the RF algorithm, the most important comorbidities were heart failure/atrial fibrillation (HF/AF), vascular diseases, and neurodegenerative diseases. There were six clusters: three included patients who met the primary endpoint (clusters 4, 5, and 6) and three included patients who did not (clusters 1, 2, and 3). Patients with HF/AF, vascular diseases, and neurodegenerative diseases were distributed among clusters 3, 4 and 5. Patients in cluster 5 also had kidney, liver, and acid peptic diseases as well as a chronic obstructive pulmonary disease; it was the cluster with the worst prognosis. CONCLUSION: The interplay of several comorbidities may affect the outcome and complications of inpatients with COVID-19.

The nutritional status of the elderly patient infected with COVID-19: the forgotten risk factor?

BACKGROUND: Since the first cases of COVID-19 were reported in Wuhan, the nutritional status of individuals infected with the virus has not been included in the risk profiles prepared. However, nutritional status, along with other factors, is decisive in the evolution of patients with other infectious diseases. The nutritional status of individuals is considered an indicator of health status. Furthermore, optimal nutritional status transcends the individual, and poor diet in a population can be considered a group risk factor. Evidence exists on the influence that diet has on the immune system and susceptibility to disease. OBJECTIVE: To evaluate the nutritional status of patients older than 65 years who were admitted due to COVID-19 and how this has influenced the evolution of patients. DESIGN: This prospective and observational study was performed in patients with COVID-19 infection confirmed by real-time polymerase chain reaction. Data were collected from the first 24 h of admission. All patients admitted during one month to the wards assigned to COVID-19 infection were included. RESULTS: A total of 83 patients were studied. The statistical study of mortality showed associations with age (p = .005), living in a nursing home (p = .022), a high Charlson Comorbidity Index (p = .039), hypertension (p = .032), comorbidities of dementia (p = .019) and cerebral vascular disease (p = .041), and Barthel Index (p = .010). The analysis of the influence of the nutritional state on mortality revealed a statistical association between malnutrition and mortality in the pooled data analysis (p = .005) and analysis by degrees of malnutrition (p = .27). CONCLUSIONS: Malnutrition was a risk factor as powerful as others such as hypertension, age, and different comorbidities. We must evaluate and treat the nutritional status of elderly patients with COVID-19 infection since it directly affects their evolution.