The impact of frailty on intra-hospital survival in older patients with COVID-19 infection: the importance of early identification. SEMI-COVID National Registry.

BACKGROUND: Emerging evidence suggests that frailty may be a significant predictor of poor outcomes in older individuals hospitalized due to COVID-19. This study aims to determine the prognostic value of frailty on intrahospital patient survival. METHODS: This observational, multicenter, nationwide study included patients aged 70 years and older who were hospitalized due to COVID-19 in Spain between March 1 and December 31, 2020. Patient data were obtained from the SEMI-COVID-19 Registry of the Spanish Society of Internal Medicine. Frailty was assessed using the Clinical Frailty Scale. The primary outcome was hospital survival. Cox proportional hazards models were used to assess predictors of survival. RESULTS: A total of 1,878 participants (52% men and 48% women) were included, with 1,351 (71.9%) survivors and 527 (28.1%) non-survivors. The non-survivor group had higher mean age (83.5 vs. 81 years), comorbidities (6.3 vs. 5.3 points on the Charlson index), degree of dependency (26.8% vs. 12.4% severely dependent patients), and frailty (34.5% vs. 14.7% severely frail patients) compared to survivors. However, there were no differences in terms of sex. Our results demonstrate that a moderate-severe degree of frailty is the primary factor independently associated with shorter survival [HR 2.344 (1.437-3.823; p<0.001) for CFS 5-6 and 3.694 (2.155-6.330; p<0.001) for CFS 7-9]. CONCLUSION: Frailty is the main predictor of adverse outcomes in older patients with COVID-19. The utilization of tools such as the Clinical Frailty Scale is crucial for early detection in this population.

[Impact of days elapsed from the onset of symptoms to hospitalization in COVID-19 in-hospital mortality: Time matters]. / Impacto de los días transcurridos desde el inicio de los síntomas hasta la hospitalización en la mortalidad hospitalaria por COVID-19: el tiempo importa.

Background: COVID-19 shows different clinical and pathophysiological stages over time. Theeffect of days elapsed from the onset of symptoms (DEOS) to hospitalization on COVID-19prognostic factors remains uncertain. We analyzed the impact on mortality of DEOS to hospital-ization and how other independent prognostic factors perform when taking this time elapsedinto account. Methods: This retrospective, nationwide cohort study, included patients with confirmed COVID-19 from February 20th and May 6th, 2020. The data was collected in a standardized online datacapture registry. Univariate and multivariate COX-regression were performed in the generalcohort and the final multivariate model was subjected to a sensitivity analysis in an earlypresenting (EP; < 5 DEOS) and late presenting (LP; ≥5 DEOS) group. Results: 7915 COVID-19 patients were included in the analysis, 2324 in the EP and 5591 in theLP group. DEOS to hospitalization was an independent prognostic factor of in-hospital mortalityin the multivariate Cox regression model along with other 9 variables. Each DEOS incrementaccounted for a 4.3% mortality risk reduction (HR 0.957; 95% CI 0.93---0.98). Regarding variationsin other mortality predictors in the sensitivity analysis, the Charlson Comorbidity Index onlyremained significant in the EP group while D-dimer only remained significant in the LP group. Conclusion: When caring for COVID-19 patients, DEOS to hospitalization should be consideredas their need for early hospitalization confers a higher risk of mortality. Different prognosticfactors vary over time and should be studied within a fixed timeframe of the disease.

Impact of days elapsed from the onset of symptoms to hospitalization in COVID-19 in-hospital mortality: time matters.

BACKGROUND: COVID-19 shows different clinical and pathophysiological stages over time. The effect of days elapsed from the onset of symptoms (DEOS) to hospitalization on COVID-19 prognostic factors remains uncertain. We analyzed the impact on mortality of DEOS to hospitalization and how other independent prognostic factors perform when taking this time elapsed into account. METHODS: This retrospective, nationwide cohort study, included patients with confirmed COVID-19 from February 20th and May 6th, 2020. The data was collected in a standardized online data capture registry. Univariate and multivariate COX-regression were performed in the general cohort and the final multivariate model was subjected to a sensitivity analysis in an early presenting (EP; <5 DEOS) and late presenting (LP; ≥5 DEOS) group. RESULTS: 7915 COVID-19 patients were included in the analysis, 2324 in the EP and 5591 in the LP group. DEOS to hospitalization was an independent prognostic factor of in-hospital mortality in the multivariate Cox regression model along with other 9 variables. Each DEOS increment accounted for a 4.3% mortality risk reduction (HR 0.957; 95% CI 0.93-0.98). Regarding variations in other mortality predictors in the sensitivity analysis, the Charlson Comorbidity Index only remained significant in the EP group while D-dimer only remained significant in the LP group. CONCLUSION: When caring for COVID-19 patients, DEOS to hospitalization should be considered as their need for early hospitalization confers a higher risk of mortality. Different prognostic factors vary over time and should be studied within a fixed timeframe of the disease.

Derivación y validación de una puntuación de riesgo de ingreso en la Unidad de Cuidados Intensivos para pacientes con COVID-19 / Derivation and validation of a risk score for admission to the Intensive Care Unit in patients with COVID-19

Fundamento: Identificar y validar una escala de riesgo de ingreso en las unidades de cuidados intensivos (UCI) en pacientes hospitalizados con enfermedad por coronavirus 2019 (COVID-19). Métodos: Realizamos una regla de derivación y otra de validación para ingreso en UCI, utilizando los datos de un registro nacional de cohortes de pacientes con infección confirmada por SARS-CoV-2 ingresados entre marzo y agosto del año 2020 (n = 16.298). Analizamos variables demográficas, clínicas, radiológicas y de laboratorio disponibles en el ingreso hospitalario. Evaluamos el rendimiento de la escala de riesgo mediante estimación del área bajo la curva de característica operativa del receptor (AROC). Utilizamos los coeficientes β del modelo de regresión para elaborar una puntuación (0 a 100 puntos) asociada con ingreso en UCI. Resultados: La edad media de los pacientes fue de 67 años; 57% varones. Un total de 1.420 (8,7%) pacientes ingresaron en la UCI. Las variables independientes asociadas con el ingreso en UCI fueron: edad, disnea, índice de comorbilidad de Charlson, cociente neutrófilos-linfocitos, lactato deshidrogenasa e infiltrados difusos en la radiografía de tórax. El modelo mostró un AROC de 0,780 (IC: 0,763-0,797) en la cohorte de derivación y un AROC de 0,734 (IC: 0,708-0,761) en la cohorte de validación. Una puntuación > 75 se asoció con una probabilidad de ingreso en UCI superior a un 30%, mientras que una puntuación < 50 redujo la probabilidad de ingreso en UCI al 15%. Conclusiós: Una puntuación de predicción simple proporcionó una herramienta útil para predecir la probabilidad de ingreso en la UCI con un alto grado de precisión (AU)

Background: This work aims to identify and validate a risk scale for admission to intensive care units (ICU) in hospitalized patients with coronavirus disease 2019 (COVID-19). Methods: We created a derivation rule and a validation rule for ICU admission using data from a national registry of a cohort of patients with confirmed SARS-CoV-2 infection who were admitted between March and August 2020 (n = 16,298). We analyzed the available demographic, clinical, radiological, and laboratory variables recorded at hospital admission. We evaluated the performance of the risk score by estimating the area under the receiver operating characteristic curve (AUROC). Using the β coefficients of the regression model, we developed a score (0 to 100 points) associated with ICU admission. Results: The mean age of the patients was 67 years; 57% were men. A total of 1,420 (8.7%) patients were admitted to the ICU. The variables independently associated with ICU admission were age, dyspnea, Charlson Comorbidity Index score, neutrophil-to-lymphocyte ratio, lactate dehydrogenase levels, and presence of diffuse infiltrates on a chest X-ray. The model showed an AUROC of 0.780 (CI: 0.763-0.797) in the derivation cohort and an AUROC of 0.734 (CI: 0.708-0.761) in the validation cohort. A score of greater than 75 points was associated with a more than 30% probability of ICU admission while a score of less than 50 points reduced the likelihood of ICU admission to 15%. Conclusion: A simple prediction score was a useful tool for forecasting the probability of ICU admission with a high degree of precision (AU)

Derivation and validation of a risk score for admission to the Intensive Care Unit in patients with COVID-19.

BACKGROUND: This work aims to identify and validate a risk scale for admission to intensive care units (ICU) in hospitalized patients with coronavirus disease 2019 (COVID-19). METHODS: We created a derivation rule and a validation rule for ICU admission using data from a national registry of a cohort of patients with confirmed SARS-CoV-2 infection who were admitted between March and August 2020 (N = 16,298). We analyzed the available demographic, clinical, radiological, and laboratory variables recorded at hospital admission. We evaluated the performance of the risk score by estimating the area under the receiver operating characteristic curve (AUROC). Using the ß coefficients of the regression model, we developed a score (0-100 points) associated with ICU admission. RESULTS: The mean age of the patients was 67 years; 57% were men. A total of 1420 (8.7%) patients were admitted to the ICU. The variables independently associated with ICU admission were age, dyspnea, Charlson Comorbidity Index score, neutrophil-to-lymphocyte ratio, lactate dehydrogenase levels, and presence of diffuse infiltrates on a chest X-ray. The model showed an AUROC of 0.780 (CI: 0.763-0.797) in the derivation cohort and an AUROC of 0.734 (CI: 0.708-0.761) in the validation cohort. A score of greater than 75 points was associated with a more than 30% probability of ICU admission while a score of less than 50 points reduced the likelihood of ICU admission to 15%. CONCLUSION: A simple prediction score was a useful tool for forecasting the probability of ICU admission with a high degree of precision.

[Derivation and validation of a risk score for admission to the Intensive Care Unit in patients with COVID-19]. / Derivación y validación de una puntuación de riesgo de ingreso en la Unidad de Cuidados Intensivos para pacientes con COVID-19.

BACKGROUND: This work aims to identify and validate a risk scale for admission to intensive care units (ICU) in hospitalized patients with coronavirus disease 2019 (COVID-19). METHODS: We created a derivation rule and a validation rule for ICU admission using data from a national registry of a cohort of patients with confirmed SARS-CoV-2 infection who were admitted between March and August 2020 (n = 16,298). We analyzed the available demographic, clinical, radiological, and laboratory variables recorded at hospital admission. We evaluated the performance of the risk score by estimating the area under the receiver operating characteristic curve (AUROC). Using the ß coefficients of the regression model, we developed a score (0 to 100 points) associated with ICU admission. RESULTS: The mean age of the patients was 67 years; 57% were men. A total of 1,420 (8.7%) patients were admitted to the ICU. The variables independently associated with ICU admission were age, dyspnea, Charlson Comorbidity Index score, neutrophil-to-lymphocyte ratio, lactate dehydrogenase levels, and presence of diffuse infiltrates on a chest X-ray. The model showed an AUROC of 0.780 (CI: 0.763-0.797) in the derivation cohort and an AUROC of 0.734 (CI: 0.708-0.761) in the validation cohort. A score of greater than 75 points was associated with a more than 30% probability of ICU admission while a score of less than 50 points reduced the likelihood of ICU admission to 15%. CONCLUSION: A simple prediction score was a useful tool for forecasting the probability of ICU admission with a high degree of precision.

Experience with the use of siltuximab in patients with SARS-CoV-2 infection.

OBJECTIVE: The study aims to describe characteristics and clinical outcome of patients with SARS-CoV-2 infection that received siltuximab according to a protocol that aimed to early block the activity of IL-6 to avoid the progression of the inflammatory flare. METHODS: Retrospective review of the first 31 patients with SARS-CoV-2 treated with siltuximab, in Hospital Clinic of Barcelona or Hospital Universitario Salamanca, from March to April 2020 with positive polymerase-chain reaction (PCR) from a nasopharyngeal swab. RESULTS: The cohort included 31 cases that received siltuximab with a median (IQR) age of 62 (56-71) and 71% were males. The most frequent comorbidity was hypertension (48%). The median dose of siltuximab was 800 mg ranging between 785 and 900 mg. 7 patients received siltuximab as a salvage therapy after one dose of tocilizumab. At the end of the study, a total of 26 (83.9) patients had been discharged alive and the mortality rate was 16.1% but only 1 out of 24 that received siltuximab as a first line option (4%). CONCLUSIONS: Siltuximab is a well-tolerated alternative to tocilizumab when administered as a first line option in patients with COVID-19 pneumonia within the first 10 days from symptoms onset and high C-reactive protein.

[Therapeutic behavior to follow in the following clinical case: treatment of type 2 diabetes]. / Conducta terapéutica en la diabetes tipo 2. Cuanto más breve, mejor.

A 62-year old woman with obesity, high blood pressure and type 2 diabetes mellitus (DM2) was referred to a Vascular Risk Unit of the Internal Medicine Department due to elevated HbA1C (8.1%) in spite of having taken metformin (850 mg/12h) and glipizide (10 mg/12 h) regularly. She tries to exercise daily (walking 30 min) and has lost weight (from 5 to 12 kg) several times, but always regains what she has lost. Furthermore, she monitors her glucose levels in fasting every two weeks and generally has between 120 and 160 mg/dL. Her high blood pressure is being treated with enalapril/HCTZ and she also takes aspirin 100mg/day and simvastatin 20 mg/day. It is seen in her family background that one brother died suddenly at 50 years of age. Her physical examination shows a BMI of 32.4 Kg/m(2), and she has no edemas in the lower limbs. Her BP is 154/82 mmHg and creatinine 0.9 mg/dL. She has no microalbuminuria and her liver function is normal. What treatment do you think would be the more appropriate? 1 - Add glitazones. 2 - Add incretin mimetics (GLP 1/ DPP-4). 3 - Slow acting insulin.

Conducta terapéutica a seguir en el siguiente caso clínico: tratamiento de la diabetes tipo 2 / Therapeutic behavior to follow in the following clinical case: treatment of type 2 diabetes

Una mujer de 62 años con obesidad, hipertensión arterial y diabetes mellitus tipo 2 es remitida a una unidad de riesgo vascular del servicio de medicina interna porque su HbA1c está elevada (8,1%) a pesar de tomar regularmente metformina (850mg/12h) y glipizida (10mg/12h). Trata de hacer ejercicio cada día (caminar 30min) y ha adelgazado (de 5 a 12kg) en varias ocasiones, pero siempre ha vuelto a ganar lo perdido. Además se controla su glucemia en ayunas cada dos semanas y suele tener entre 120 y 160mg/dl. Su hipertensión arterial está siendo tratada con enalapril/HCTZ y además toma aspirina (100mg/día) y simvastatina (20mg/día). En su historia familiar se recoge que un hermano falleció súbitamente a los 50 años. En la exploración física presenta un IMC de 32,4kg/m2 y no tiene edemas en los MMII. Su PA es de 154/82mmHg y la creatinina de 0,9mg/dl. No presenta microalbuminuria y su función hepática es normal.¿Qué tratamiento le parece a Vd. más indicado?1. Añadir glitazonas.2. Añadir incretín miméticos (GLP1/inhibidores de la DPP-4).3. Añadir insulina de acción lenta(AU)

A 62-year old woman with obesity, high blood pressure and type 2 diabetes mellitus (DM2) was referred to a Vascular Risk Unit of the Internal Medicine Department due to elevated HbA1C (8.1%) in spite of having taken metformin (850mg/12h) and glipizide (10mg/12h) regularly. She tries to exercise daily (walking 30min) and has lost weight (from 5 to 12kg) several times, but always regains what she has lost. Furthermore, she monitors her glucose levels in fasting every two weeks and generally has between 120 and 160mg/dL. Her high blood pressure is being treated with enalapril/HCTZ and she also takes aspirin 100mg/day and simvastatin 20mg/day. It is seen in her family background that one brother died suddenly at 50 years of age. Her physical examination shows a BMI of 32.4Kg/m2, and she has no edemas in the lower limbs. Her BP is 154/82mmHg and creatinine 0.9mg/dL. She has no microalbuminuria and her liver function is normal.What treatment do you think would be the more appropriate?1 - Add glitazones.2 - Add incretin mimetics (GLP 1/ DPP-4).3 - Slow acting insulin(AU)

Síndrome de Wallemberg en paciente joven sin factores de riesgo vascular / No disponible

No disponible

[Elderly population and campaigns for the prevention of hypercholesterolemia in Salamanca]. / Población anciana y campañas para la prevención de la hipercolesterolemia en Salamanca.

OBJECTIVE: To analyze the cardiovascular risk profile of the persons older than 65 years of age who participated in different "Days on Cholesterol and Atherosclerosis" organized during 1999 in different towns of the province of Salamanca. MATERIAL AND METHODS: The volunteers of any age were subjected to a questionnaire and to several clinical and laboratory measurements. RESULTS: The age of 267 volunteers (40.8% males) attending the campaign was > or = 65 years. The mean values of the studied parameters were: age = 72.3 +/- 6.5 years; body mass index (BMI) = 26.8 +/- 4.5 kg/m2; systolic blood pressure (SBP) = 139.8 +/- 20.6 mmHg; dystolic blood pressure (DBP) = 80.0 +/- 10.1 mmHg; and total cholesterol (TC) = 226.2 +/- 44.9 mg/dl. The percentage of smoking habit was 5.2%. The figures of SBP showed positive significant correlation with those of age (p < 0.05) and DBP (p < 0.01). Among males, the age evolved inversely to the numbers of TC (p < 0.01). Globally, 203 volunteers (76.0%) had concentrations of TC > or = 200 mg/dl; 78 (29.2%) > or = 250 mg/dl; and 12 (4.5%) concentrations > or = 300 mg/dl. We detected blood pressure levels of SBP > or = 140 mmHg in 143 (53.6%) individuals; SBP > or = 180 mmHg in 11 (4.1%); DBP > or = 90 mmHg in 72 (27.0%); and DBP > or = 110 mmHg in 4 (1.5%). The BMI was > or = 30 kg/m2 in 54 (20.2%) people of the study. 90.8% of the volunteers with previous cardiovascular disease carried, at least, another not controlled cardiovascular risk factor; 24.1% had at least two risk factors; and 9.1% had, at least, three. In 38.5% they showed high levels of TC and DBP, simultaneously. CONCLUSIONS: Our data, together with the current evidences about the benefit of the control of cardiovascular risk factors in the elderly, suggest the necessity to establish strategies for a better control of the cardiovascular risk in this group of age in our province.

[Analysis of the HFE gene in a large Spanish kindred with hereditary hemochromatosis]. / Estudio del gen HFE en una familia española con hemocromatosis hereditaria.

BACKGROUND: Hereditary hemochromatosis (HH) is an inborn error of iron metabolism that is inherited as an autosomal recessive trait. Recently, it has been shown that the HFE gene, located telomeric to HLA-A on chromosome 6 is mutated in most patients with HH. Moreover, the phenotypic expression of hereditary hemochromatosis is influenced by sex and environmental agents such as alcohol and dietary iron intake. SUBJECTS AND METHOD: We have studied 40 subjects from a family some of which members have HH. DNA was obtained from nucleated peripheral blood cells, and exons 2 and 4 and intron 5 of the HFE gene were amplified by PCR and digested with specific restriction enzymes. RESULTS: Analysis of the HFE gene revealed that 29 members of the family carry some of the three HFE mutations (C282Y, H63D and S65C). Nevertheless, only those homozygous for the C282Y mutation develop HH. In this family, the allele 187G of exon 2 mutation is cosegregated with the allele IVS5-47 A in intron 5. CONCLUSIONS: Analysis of the HFE gene in the members of a large Spanish kindred, living in the same geographical area, shows that only those homozygous for the C282Y mutation develop hemochromatosis.

Correlation of high levels of hyaluronan and cytokines (IL-1beta, IL-6, and TGF-beta) in ascitic fluid of cirrhotic patients.

Our objective was to investigate the relationship between endotoxin and hyaluronan synthesis and release in serum and ascitic fluid from cirrhotic patients. We studied hyaluronan, endotoxin, albumin, and creatinine levels in ascitic fluid and plasma and cytokine levels (IL-1beta, IL-6, TGF-beta) in ascitic fluid. TGF-beta, IL-6, and IL-1beta correlation analyses indicated a strong dependence of the production of these cytokines on endotoxin levels. Correlation analyses for TGF-beta and IL-6 indicated a strong dependence of the production of hyaluronan on cytokine levels and, to a lesser extent, on IL-1beta levels. Hyaluronan analysis indicated that a certain glycosaminoglycan level is required in ascites before its appearance in plasma. Our results disclosed elevated plasma hyaluronan concentrations. The simultaneous increased hyaluronan levels in ascitic fluid do not seem to be derived from the systemic circulation. In conclusion, the high hyaluronan-ascites/hyaluronan-plasma ratio suggests an intrinsic hyaluronan production from peritoneal cells induced by endotoxins.

Antiphosphatidylserine antibodies in patients with autoimmune diseases and HIV-infected patients: effects of Tween 20 and relationship with antibodies to beta2-glycoprotein I.

Antiphospholipid antibodies (aPL) react with negatively charged phospholipids, which may often be complexed with a protein cofactor such as beta2 glycoprotein (beta2GPI) and prothrombin. Cofactor requirements may be assessed by measuring antibodies to beta2GPI or by adding Tween 20 to some reagents in the assays for aPL (anticardiolipin and antiphosphatidyIserine). We have measured anticardiolipin antibodies (aCL), antiphosphatidylserine antibodies (aPS), and anti beta2 glycoprotein antibodies (abeta2GPI) in the serum of 10 normal subjects, 20 patients with systemic autoimmune diseases (SAD) diagnosed as having systemic lupus erythematosus (SLE) or antiphospholipid syndrome (APS), and 12 patients with HIV infection. Adding Tween 20 to aPS, the assay couldn't differentiate protein cofactor dependent from independent antibodies, but this can be done by measuring abeta2GPI (P= 0.0008). There was a significant correlation between aCL and a(beta)2GPI in the control group and in the patients with SAD, but not in the HIV-positive (HIV+) patients. After excluding the HIV+ patients, the best Spearman correlation was obtained between a(beta)2GPI and aCL (0.64, P< 0.0005). In 3 out of 7 patients with positive a(beta)2GPI and in 5 out of 6 patients with moderate or high positive aCL of the group of SAD, there was a history of venous thrombosis. The presence of moderate or high values of aCL either alone or together with a(beta)2GPI was significantly associated with a history of venous thrombosis (P < 0.05). Moderate or high aCL concentrations and their association with a(beta)2GPI seems to be useful for the assessment of the risk of venous thrombosis in unselected patients with SLE or APS.

[Brucellar meningitis as a peculiar form of clear fluid meningitis. Clinical study]. / La meningitis brucelar como forma peculiar de meningitis de líquido claro. Estudio clínico.

Out of 200 patients diagnosed of acute of chronic brucellosis, cases were first selected who had neurologic involvement (14%) and then those who had brucellar meningitis (CDC criteria) which corresponds to 4% of the total of the series. The clinical course, evolution time, neurologic manifestations and serologic and bacteriologic characteristics in blood and specifically in the cerebrospinal fluid (CSF). This study was contrasted with the literature review and the conclusion is reached that brucellar meningitis is a peculiar form of clear fluid meningitis, not exceptional in our environment considering the prevalence of brucellosis.