Incidencia, Características y Evolución de las Endocarditis Nosocomiales Durante la Pandemia COVID-19

Introducción: La pandemia COVID-19 ha podido tener influencia en la incidencia de endocarditis infecciosa nosocomial (EIN). Objetivos: Describir la incidencia, características y evolución de la EIN durante la pandemia COVID-19. Material y métodos: Estudio retrospectivo unicéntrico incluyendo las EIN definidas, según los criterios de Duke, desde marzo 2020 hasta marzo 2021. Se dividieron a los pacientes en ingreso por COVID-19 (grupo COVID) o por otros motivos (grupo no COVID). Se comparó la incidencia de EIN con el mismo periodo de 2019-2020. Resultados: Durante el periodo de estudio se diagnosticaron 22 EIN, 7 (31,8%) en COVID, 15 (68,2%) en no COVID. La incidencia fue 9,7 casos/10.000 ingresos (22/22.596). La incidencia en el mismo periodo 2019-2020 fue 4,6/10.000 (10/21.668), siendo la diferencia significativa (OR 1,91, IC95% 1,03-3,96, p = 0,038). Durante el periodo 2020-2021, la incidencia de EIN en COVID fue 24,6/10.000 (7/2.846) frente a 7,5/10.000 (15/19.750) en no COVID, siendo la diferencia significativa (OR 3,23 IC95% 1,32-7,95, p < 0,001). La mediana de edad fue 75 años (RIQ 68-80), siendo varones 68,2%. La mediana de Índice de Charlson fue 5 (RIQ 4-6). Un 36,4% presentaban válvula protésica, mientras un 22,7% valvulopatías significativa no protésica. Los pacientes COVID habían recibido más frecuentemente inmunosupresores (71,4% vs. 13,3%, p = 0,014), sin otras diferencias entre grupos. El foco primario fue considerado vascular en 86,4% (19/22;10 por vía periférica (VP), 5 por catéter venoso central (CVC), 4 no se pudo diferenciar origen entre VP o CVC). 3 pacientes presentaron foco no vascular (1 genitourinario, 2 gastrointestinal). No hubo diferencias entre grupos. Las manifestaciones fueron: fiebre 95,5%;insuficiencia cardiaca 68,2%;embolismos 45,5%;ictus 40,9%;insuficiencia renal 40,9%;bacteriemia persistente 38,1%;y shock séptico 14,3%. Los pacientes no COVID presentaron con más frecuencia clínica subaguda (0 vs. 46,7%, p = 0,042), sin otras diferencias estadísticamente significativas. La etiología fue: estafilococos coagulasa negativo 6 (27,3%);Enterococcus faecalis 6 (27,3%);Staphylococcus aureus 4 (18,2%);Candida albicans 3 (13,6%). En 3 casos no hubo aislamiento microbiológico (13.6%). No hubo diferencias entre grupos. La mortalidad a 30 días fue 45,5%, siendo la EIN o sus complicaciones la causa en todos los casos salvo 1 (no COVID). No hubo diferencias de mortalidad entre grupos (28,6% vs. 53,3%, p = 0,381). Conclusiones: La incidencia de EIN ha aumentado durante la pandemia, especialmente en pacientes ingresados por COVID-19. El foco primario de las EIN fue predominantemente vascular. Afectaron frecuentemente a pacientes con comorbilidad y patología valvular previa. Las manifestaciones, etiología y evolución fueron similares en COVID y no COVID, destacando una elevada frecuencia de eventos embólicos, especialmente ictus. Las EIN asocian elevada morbimortalidad y es importante extremar las medidas de prevención.

Biomarker's usefulness to predict the efficacy of IL6 inhibitors and corticosteroids in the treatment of COVID19

Objective: Proper identification of patients at risk of developing serious disease in the context of SARS-CoV-2 infection, as well as the initiation of early treatment, is essential for COVID19 successful management. The main objective of this study was to evaluate the usefulness of serum biomarkers (i.e., neutrophils, lymphocytes, Creactive protein, lactate dehydrogenase, D-dimer, ferritin and interleukin-6) to predict the early response to immunosuppressant therapy in COVID19 patients. Material and/or methods: This is a case-control study nested in a retrospective cohort, which included hospitalized patients with COVID19 pneumonia and presented elevation of some pro-inflammatory parameters. Each of the individuals who died during the 28-day follow-up was defined as a case. For each case, four controls were selected, matched by age, sex and comorbidities. Results: Overall, 856 patients were included in the initial cohort. The incidence of therapeutic failure in the cohort was 14%, thus a total of 119 cases were identified. After applying a Cox regression model, high serum concentrations of LDH (>451 IU/L), ferritin (>1014 ng/mL) and D-Dimer (>1300 ng/mL) were identified as predictors of poor response to treatment. High-specific cut-off points could not be established for any of these biomarkers. Conclusions: Some inflammatory biomarkers, such as LDH, ferritin and D-dimer, may be helpful in identifying patients for whom an early immunomodulatory therapeutic intervention should be considered in the treatment of COVID19 patients with pneumonia.

International Multicenter Study Comparing Cancer to Non-Cancer Patients with COVID-19: Impact of Risk Factors and Treatment Modalities on Outcome

Background. Given the limited collaborative international studies that evaluated COVID-19 in patients with cancer in comparison to patients without cancer, we aimed to determine the independent risk factors associated with increased 30-day mortality and the impact of novel treatment modalities in a large group of cancer and non-cancer patients with COVID-19 from multiple countries. Methods. We retrospectively collected de-identified data on cancer and non-cancer patients diagnosed with COVID-19 between January and November 2020, at 16 centers in Asia, Australia, Europe, North America, and South America. A logistic regression model was used to identify independent predictors of all-cause mortality within 30 days after COVID-19 diagnosis. Results. Of the total 4015 COVID-19 confirmed patients entered, we analyzed 3966 patients, 1115 cancer and 2851 non-cancer patients. Cancer patients were older than non-cancer patients (median age, 61 vs 50 years;p< 0.0001);more likely to be pancytopenic , had pulmonary disorders, hypertension, diabetes mellitus. In addition, they were more likely to present with higher inflammatory biomarkers (D-dimer, ferritin and procalcitonin), but were less likely to present with clinical symptoms. By multivariable logistic regression analysis, cancer was an independent risk factor for 30-day mortality (OR 1.46;95% CI 1.03 to 2.07;p=0.035). Older age (≥65 years) was the strongest predictor of 30-day mortality in all patients (OR 4.55;95% CI 3.34 to 6.20;p< 0.0001). Remdesivir was the only therapeutic agent independently associated with decreased 30-day mortality (OR 0.58;CI 0.39-0.88;p=0.009). Among patients on lowflow oxygen at admission, patients who received remdesivir had a lower 30-day mortality rate than those who were on high flow oxygen (5.9% vs 17.6%;p=0.03). Patients transfused with convalescent plasma within 1 day of diagnosis had a lower 30-day mortality rate than those transfused later (1% vs 7%, p=0.04). Conclusion. Cancer is an independent risk factor for increased 30-day all-cause mortality from COVID-19. Remdesivir, particularly in patients receiving low-flow oxygen, can reduce 30-day all-cause mortality, as well as convalescent plasma given early after COVID-19 diagnosis.

Lung Cancer and Hematologic Malignancy ( HM) Patients Are Associated with the Highest Risk of Progressing to Severe Disease and Mortality in Cancer Patients with COVID-19

Background. Several studies have shown that underlying cancer is a risk factor for progression of COVID-19 to severe illness and fatal outcome but there is very little data that specifies which underlying cancer puts this patient population at the highest risk. Methods. We retrospectively collected de-identified data on 1115 cancer patients diagnosed with COVID-19 between January and November 2020, at 12 centers in Asia, Australia, Europe, North America, and South America. Patient characteristics including age, type of malignancy (hematologic malignancy [HM], lung cancer, and non-lung cancer were determined in association with severe illness as well as all-cause mortality within 30 days after COVID-19 diagnosis. Results. By multivariable logistic regression analysis, independent risk factors for 30-day mortality in cancer patients included age > 65 (OR 6.64;95% CI 3.351to 12.55;p< 0.0001), ALC < 0.5 K/microliter (OR 2.10;95% CI 1.16 to 3.79;p=0.014), and anemia at < 10g/dl (OR 2.41;95% CI 1.30 to 4.44;p=0.005). Among cancer patients, the 30-day mortality rate was significantly higher in patients with lung cancer than in patients with non-lung cancer solid tumors, including those with lung metastases (22% vs 9%;p=0.001). Patients with HM tended to have higher 30-day mortality than patients with non-lung cancer solid tumors (13% vs 9% p=0.07) and tended to have a lower mortality rate than patients with lung cancer (p=0.07). Furthermore, HM patients were more likely to be lymphopenic and anemic at diagnosis as well as progress to LRTI and be placed on ventilatory support compared to non-lung cancer solid tumor patients ( p= or < 0.01). In addition, lung cancer and HM patients were more likely to develop hypoxia and require hospital admission than non-lung cancer solid tumor patients ( p=0.01). Conclusion. Lung cancer and HM patients are associated with the highest risk of progressing to severe disease and mortality in cancer patients with COVID-19. Hence, cancer patient population should be given the highest priority as far as prevention [vaccination with boosters if needed] as well as preemptive early therapy with monoclonal antibodies right after the onset of COVID-19.