20 research outputs found

    Hospitalization budget impact during the COVID-19 pandemic in Spain

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    To Mrs. Anne Murray for her support to translate the manuscript. This article is part of the doctoral thesis of Laura Álvarez as part of the Doctoral Program in Pharmacy, Granada University (Spain).Objectives: The aim was to determine the direct impact of the COVID-19 pandemic on Spain’s health budget. Methods: Budget impact analyses based on retrospective data from patients with suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) admitted to a Spanish hospital between February 26 and May 21, 2020. Direct medical costs from the perspective of the hospital were calculated. We analyzed diagnostic tests, drugs, medical and nursing care, and isolation ward and ICU stays for three cohorts: patients seen in the emergency room only, hospitalized patients who tested positive for SARS-CoV-2, and patients who tested negative. Results: The impact on the hospital’s budget for the 3 months was calculated at €15,633,180, 97.4% of which was related to health care and hospitalization. ICU stays accounted for 5.3% of the total costs. The mean cost per patient was €10,744. The main costs were staffing costs (10,131 to 11,357 €/patient for physicians and 10,274 to 11,215 €/patient for nurses). Scenario analysis showed that the range of hospital expenditure was between €14,693,256 and €16,524,924. The median impact of the pandemic on the Spanish health budget in the sensitivity analysis using bootstrapped individual data was €9357 million (interquartile range [IQR], 9071 to 9689) for the conservative scenario (113,588 hospital admissions and 11,664 ICU admissions) and €10,385 million (IQR, 110,030 to 10,758) for the worst-case scenario (including suspected cases). Conclusion: The impact of COVID-19 on the Spanish public health budget (12.3% of total public health expenditure) is greater than multiple sclerosis, cancer and diabetes cost

    SARS-CoV-2 viral load in nasopharyngeal swabs is not an independent predictor of unfavorable outcome

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    The aim was to assess the ability of nasopharyngeal SARS-CoV-2 viral load at first patient’s hospital evaluation to predict unfavorable outcomes. We conducted a prospective cohort study including 321 adult patients with confirmed COVID-19 through RT-PCR in nasopharyngeal swabs. Quantitative Synthetic SARS-CoV-2 RNA cycle threshold values were used to calculate the viral load in log10 copies/mL. Disease severity at the end of follow up was categorized into mild, moderate, and severe. Primary endpoint was a composite of intensive care unit (ICU) admission and/or death (n = 85, 26.4%). Univariable and multivariable logistic regression analyses were performed. Nasopharyngeal SARS-CoV-2 viral load over the second quartile (≥ 7.35 log10 copies/mL, p = 0.003) and second tertile (≥ 8.27 log10 copies/mL, p = 0.01) were associated to unfavorable outcome in the unadjusted logistic regression analysis. However, in the final multivariable analysis, viral load was not independently associated with an unfavorable outcome. Five predictors were independently associated with increased odds of ICU admission and/or death: age ≥ 70 years, SpO2, neutrophils > 7.5 × 103/µL, lactate dehydrogenase ≥ 300 U/L, and C-reactive protein ≥ 100 mg/L. In summary, nasopharyngeal SARS-CoV-2 viral load on admission is generally high in patients with COVID-19, regardless of illness severity, but it cannot be used as an independent predictor of unfavorable clinical outcome

    Dendritic cell deficiencies persist seven months after SARS-CoV-2 infection

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    Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV)-2 infection induces an exacerbated inflammation driven by innate immunity components. Dendritic cells (DCs) play a key role in the defense against viral infections, for instance plasmacytoid DCs (pDCs), have the capacity to produce vast amounts of interferon-alpha (IFN-α). In COVID-19 there is a deficit in DC numbers and IFN-α production, which has been associated with disease severity. In this work, we described that in addition to the DC deficiency, several DC activation and homing markers were altered in acute COVID-19 patients, which were associated with multiple inflammatory markers. Remarkably, previously hospitalized and nonhospitalized patients remained with decreased numbers of CD1c+ myeloid DCs and pDCs seven months after SARS-CoV-2 infection. Moreover, the expression of DC markers such as CD86 and CD4 were only restored in previously nonhospitalized patients, while no restoration of integrin β7 and indoleamine 2,3-dyoxigenase (IDO) levels were observed. These findings contribute to a better understanding of the immunological sequelae of COVID-19

    Role of age and comorbidities in mortality of patients with infective endocarditis

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    Purpose: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. Methods: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015. Patients were stratified into three age groups:<65 years, 65 to 80 years, and = 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. Results: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 = 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients =80 years who underwent surgery were significantly lower compared with other age groups (14.3%, 65 years; 20.5%, 65-79 years; 31.3%, =80 years). In-hospital mortality was lower in the <65-year group (20.3%, <65 years;30.1%, 65-79 years;34.7%, =80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%, =80 years; p = 0.003).Independent predictors of mortality were age = 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI = 3 (HR:1.62; 95% CI:1.39–1.88), and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared, the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. Conclusion: There were no differences in the clinical presentation of IE between the groups. Age = 80 years, high comorbidity (measured by CCI), and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

    Influencia del perfil clínico del donante, receptor y tiempo de isquemia en la supervivencia del trasplante cardíaco. Subanálisis del Registro Español de Trasplante Cardíaco

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    Introducción y objetivos: Los órganos cardíacos deben ser priorizados hacia pacientes en los que se vaya a obtener máxima supervivencia con menor morbilidad. El objetivo del estudio fue analizar la influencia del receptor, el donante y e tiempo de isquemia del órgano en la mortalidad. Métodos: Se consideraron todos los trasplantes cardíacos realizados en España hasta diciembre del 2011 (6.528 TC). Se excluyeron: 1) trasplantes previos al año 2000; 2) edad < 16 años; 3) combinados con otros órganos, y 4) retrasplantes. Los pacientes analizados fueron 3.006. Se definieron las categorías de óptimo/subóptimo para las variables del receptor, donante y tiempo de isquemia. Se compararon y se realizaron curvas de supervivencia para donante, receptor, tiempo de isquemia y combinaciones. Resultados: Se comparó el porcentaje de pacientes fallecidos. Las diferencias (p < 0,05) mostraron: 1) receptor óptimo: edad < 60 años, IMC < 30, no diabetes, enfermedad vascular periférica, neoplasia ni cirugía previa, no disfunción renal ni hepática, trasplante no urgente; 2) donante óptimo: edad < 40 años, no utilización de dobutamina, dopamina < 5 μ/kg/min, y 3) tiempo de isquemia óptimo: < 240 m. Las curvas de supervivencia mostraron diferencias entre óptimos vs. no óptimo (p < 0,05) y entre las distintas combinaciones (p < 0,05). Así, la implantación de corazón óptimo en receptor óptimo con isquemia < 240 m mostró una probabilidad de supervivencia a los 30 días del 94% y al 1.er, 5.° y 10.° año del el 87, el 81 y el 71%, respectivamente. Conclusiones: Muchas características del donante y el receptor, así como el tiempo de isquemia, influyen en la supervivencia del TC. El acúmulo de variables consideradas no óptimas repercutirá negativamente y de forma significativa en la supervivencia del TC

    Defining the scope of the European Antimicrobial Resistance Surveillance network in Veterinary medicine (EARS-Vet): A bottom-up and One Health approach

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    Background: Building the European Antimicrobial Resistance Surveillance network in Veterinary medicine (EARS-Vet) was proposed to strengthen the European One Health antimicrobial resistance (AMR) surveillance approach. Objectives: To define the combinations of animal species/production types/age categories/bacterial species/specimens/antimicrobials to be monitored in EARS-Vet. Methods: The EARS-Vet scope was defined by consensus between 26 European experts. Decisions were guided by a survey of the combinations that are relevant and feasible to monitor in diseased animals in 13 European countries (bottom-up approach). Experts also considered the One Health approach and the need for EARS-Vet to complement existing European AMR monitoring systems coordinated by the ECDC and the European Food Safety Authority (EFSA). Results: EARS-Vet plans to monitor AMR in six animal species [cattle, swine, chickens (broilers and laying hens), turkeys, cats and dogs], for 11 bacterial species (Escherichia coli, Klebsiella pneumoniae, Mannheimia haemolytica, Pasteurella multocida, Actinobacillus pleuropneumoniae, Staphylococcus aureus, Staphylococcus pseudintermedius, Staphylococcus hyicus, Streptococcus uberis, Streptococcus dysgalactiae and Streptococcus suis). Relevant antimicrobials for their treatment were selected (e.g. tetracyclines) and complemented with antimicrobials of more specific public health interest (e.g. carbapenems). Molecular data detecting the presence of ESBLs, AmpC cephalosporinases and methicillin resistance shall be collected too. Conclusions: A preliminary EARS-Vet scope was defined, with the potential to fill important AMR monitoring gaps in the animal sector in Europe. It should be reviewed and expanded as the epidemiology of AMR changes, more countries participate and national monitoring capacities improve
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