Prevalence and impact of cerebrovascular risk factors in patients with giant cell arteritis: An observational study from the Spanish national registry / Prevalencia e impacto de los factores de riesgo cerebrovascular en pacientes con arteritis de células gigantes: un estudio observacional del registro nacional español

Objective To assess the prevalence and impact of cerebrovascular risk factors (CRF) on cerebrovascular events (CVE) in patients with giant cell arteritis (GCA). Methods Analysis of the patients diagnosed with GCA identified in the Spanish Hospital Discharge Database between 2016 and 2018. Results 8,474 hospital admissions from patients diagnosed with GCA were identified. 3.4% of the admissions were motivated by CVE (stroke in 2.8% and transient ischemic attack in 0.6%). When compared with the admissions due to other causes, the patients who suffered from CVE presented a higher rate of male sex (36.2% vs 43.5%, p=0.007), hypertension (66.9% vs 74.4%, p=0.004), diabetes (27.6% vs 33.7%, p=0.016) and atherosclerosis (6.6% vs 10.2%, p=0.0.017). After adjustment, male sex (OR=1.35, 95% CI 1.06–1.72) and mainly hypertension (OR=1.44, 95% CI 1.11–1.90) were associated with a higher risk of CVE. Conclusion Hypertension, along with male sex, was the strongest risk factor for cerebrovascular events in GCA patients. In these high-risk patients, antiplatelet therapy should be re-considered and evaluated in prospective studies (AU)

Objetivo Evaluar la prevalencia e impacto de los factores de riesgo cerebrovasculares en los episodios cerebrovasculares (ECV) de pacientes con arteritis de células gigantes (ACG). Métodos Análisis de los pacientes diagnosticados con ACG identificados en la base de altas hospitalarias española entre 2016 y 2018. Resultados Se identificaron 8.474 ingresos hospitalarios en pacientes diagnosticados de ACG. El 3,4% de los ingresos se atribuyó a ECV (ictus en 2,8% y accidente isquémico transitorio en 0,6%). En comparación con los ingresos por otras causas, los pacientes que presentaron ECV mostraron una mayor tasa de sexo masculino (36,2 frente a 43,5%, p=0,007), hipertensión (66,9 frente a 74,4%, p=0,004), diabetes (27,6 frente a 33,7%, p=0,016) y aterosclerosis (6,6 frente a 10,2%, p=0,0017). Tras el ajuste, el sexo masculino (OR=1,35, IC 95% 1,06-1,72) y principalmente la hipertensión (OR=1,44, IC 95% 1,11-1,90) se asociaron con un mayor riesgo de ECV. Conclusión La hipertensión, junto con el sexo masculino, fueron los principales factores de riesgo de ECV en los pacientes con ACG. En estos pacientes de alto riesgo, el tratamiento con antiagregantes debería reconsiderarse y evaluarse en estudios prospectivos (AU)

Prevalence and impact of cerebrovascular risk factors in patients with giant cell arteritis: An observational study from the Spanish national registry.

OBJECTIVE: To assess the prevalence and impact of cerebrovascular risk factors (CRF) on cerebrovascular events (CVE) in patients with giant cell arteritis (GCA). METHODS: Analysis of the patients diagnosed with GCA identified in the Spanish Hospital Discharge Database between 2016 and 2018. RESULTS: 8,474 hospital admissions from patients diagnosed with GCA were identified. 3.4% of the admissions were motivated by CVE (stroke in 2.8% and transient ischemic attack in 0.6%). When compared with the admissions due to other causes, the patients who suffered from CVE presented a higher rate of male sex (36.2% vs 43.5%, p=0.007), hypertension (66.9% vs 74.4%, p=0.004), diabetes (27.6% vs 33.7%, p=0.016) and atherosclerosis (6.6% vs 10.2%, p=0.0.017). After adjustment, male sex (OR=1.35, 95% CI 1.06-1.72) and mainly hypertension (OR=1.44, 95% CI 1.11-1.90) were associated with a higher risk of CVE. CONCLUSION: Hypertension, along with male sex, was the strongest risk factor for cerebrovascular events in GCA patients. In these high-risk patients, antiplatelet therapy should be re-considered and evaluated in prospective studies.

Red blood cell distribution width as a marker of hyperinflammation and mortality in COVID-19.

BACKGROUND: Red blood cell distribution width (RDW) could reflect interleukin-6 (IL-6) systemic activity since anisocytosis represents the inhibition of erythropoiesis, leaded by the hyperinflammatory background. Our objective was to analyze RDW performance to predict outcome in coronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS). METHODS: Retrospective observational study including 173 patients with COVID-19-associated ARDS. Data was analyzed at hospital admission, inclusion in the TOCICOV Study (day 0), days 1, 3, 7 and 15 post-inclusion. RESULTS: Overall, 57% patients received tocilizumab. Overall mortality was 20.8%. RDW was higher in non-survivors compared to survivors at admission (13.53% vs. 14.35, P=0.0016), day 0 (13.60% vs. 14.42, P=0.026), day 3 (13.43% vs. 14.36, P<0.001) and day 7 (13.41% vs. 14.31, P=0.046), presenting better discrimination ability for mortality than other prognostic markers [area under the curve-receiver operating characteristic (AUC-ROC) =0.668 for admission RDW, 0.680 for day 0 RDW, 0.695 for day 3 RDW and 0.666 for day 7 RDW]. RDW values did not vary significantly according to tocilizumab treatment. When adjusted by hemoglobin and tocilizumab treatment, only RDW at admission, day 0, day 3 and C reactive protein (CRP) at day 0 and day 1 were associated with mortality (P<0.05). Only in non-tocilizumab treated patients, IL-6 levels at day 0 were correlated with day 3 RDW (r=0.733, P=0.004) and with day 3 CRP (r=0.727, P=0.022). Both parameters showed significant statistical correlation (r=0.255 for day 1 RDW and CRP in the overall cohort and r=0.358 for day 3 RDW and CRP in patients not treated with tocilizumab, P<0.015). CONCLUSIONS: RDW predicts COVID-19-associated ARDS mortality and reflects the hyperinflammatory background and the effects of cytokines such as IL-6, irrespective of tocilizumab treatment.

Higher mortality of hospitalized haematologic patients with COVID-19 compared to non-haematologic is driven by thrombotic complications and development of ARDS: An age-matched cohorts study.

BACKGROUND AND OBJECTIVES: The characteristics of COVID-19 in haematologic patients compared to non-haematologic patients have seldom been analyzed. Our aim was to analyze whether there are differences in clinical characteristics and outcome of haematologic patients with COVID-19 as compared to non-haematologic. PATIENTS AND METHODS: Retrospective cohort study in 2 University hospitals of patients admitted with laboratory-confirmed COVID-19 included in the SEMICOVID19 database. The cohort with underlying haematologic disease was compared to a cohort of age and date-of-COVID-19-matched controls without haematologic disease (1:2). RESULTS: 71 cases and 142 controls were included from March-May 2020.Twenty (28.1%) had received recent chemotherapy. Twelve (16.9%) were stem cell transplant recipients (SCT). Eleven (15.5%) were neutropenic concurrently with COVID-19 diagnosis.Haematologic patients presented ARDS (58.5 vs 20.7%, p = 0.0001), thrombotic complications (15.7 vs 2.1%, p = 0.002), DIC (5.7 vs 0.0%, p = 0.011), heart failure (14.3 vs 4.9%, p = 0.029) and required ICU admission (15.5 vs 2.8%, p = 0.001), MV (14.1% vs 2.1%, p 0.001), steroid (64.8 vs 33.1%, p = 0.0001), tocilizumab (33.8 vs 8.5%, p = 0.0001) or anakinra treatment (9.9% vs 0%, p = 0.0001) more often. In-hospital mortality was significantly higher (38.0% vs 18.3%, p = 0.002). CONCLUSIONS: Our results suggest COVID-19 has worse outcomes in haematologic patients than in non-haematologic, independently of age, and that the development of ARDS and thrombotic complications drive the higher in-hospital mortality.

Combination of Tocilizumab and Steroids to Improve Mortality in Patients with Severe COVID-19 Infection: A Spanish, Multicenter, Cohort Study.

BACKGROUND: We aimed to determine the impact of tocilizumab use on severe COVID-19 (coronavirus disease 19) pneumonia mortality. METHODS: We performed a multicentre retrospective cohort study in 18 tertiary hospitals in Spain from March to April 2020. Consecutive patients admitted with severe COVID-19 treated with tocilizumab were compared to patients not treated with tocilizumab, adjusting by inverse probability of the treatment weights (IPTW). Tocilizumab's effect in patients receiving steroids during the 48 h following inclusion was analysed. RESULTS: During the study period, 506 patients with severe COVID-19 fulfilled the inclusion criteria. Among them, 268 were treated with tocilizumab and 238 patients were not. Median time to tocilizumab treatment from onset of symptoms was 11 days [interquartile range (IQR) 8-14]. Global mortality was 23.7%. Mortality was lower in patients treated with tocilizumab than in controls: 16.8% versus 31.5%, hazard ratio (HR) 0.514 [95% confidence interval (95% CI) 0.355-0.744], p < 0.001; weighted HR 0.741 (95% CI 0.619-0.887), p = 0.001. Tocilizumab treatment reduced mortality by 14.7% relative to no tocilizumab treatment [relative risk reduction (RRR) 46.7%]. We calculated a number necessary to treat of 7. Among patients treated with steroids, mortality was lower in those treated with tocilizumab than in those treated with steroids alone [10.9% versus 40.2%, HR 0.511 (95% CI 0.352-0.741), p = 0.036; weighted HR 0.6 (95% CI 0.449-0.804), p < 0.001] (interaction p = 0.094). CONCLUSIONS: These results show that survival of patients with severe COVID-19 is higher in those treated with tocilizumab than in those not treated and that tocilizumab's effect adds to that of steroids administered to non-intubated patients with COVID-19 during the first 48 h of presenting with respiratory failure despite oxygen therapy. Randomised controlled studies are needed to confirm these results. TRIAL REGISTRATION: European Union electronic Register of Post-Authorization Studies (EU PAS Register) identifier, EUPAS34415.

A Retrospective Controlled Cohort Study of the Impact of Glucocorticoid Treatment in SARS-CoV-2 Infection Mortality.

Evidence to support the use of steroids in coronavirus disease 2019 (COVID-19) pneumonia is lacking. We aim to determine the impact of steroid use for COVID-19 pneumonia on hospital mortality. We performed a single-center retrospective cohort study in a university hospital in Madrid, Spain, during March of 2020. To determine the role of steroids in in-hospital mortality, patients admitted with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia and treated with steroids were compared to patients not treated with steroids, and we adjusted with a propensity score for patients on steroid treatment. Survival times were compared using the log rank test. Different steroid regimens were compared and adjusted with a second propensity score. During the study period, 463 out of 848 hospitalized patients with COVID-19 pneumonia fulfilled inclusion criteria. Among them, 396 (46.7%) patients were treated with steroids and 67 patients were not. Global mortality was 15.1%. The median time to steroid treatment from symptom onset was 10 days (interquartile range [IQR], 8 to 13 days). In-hospital mortality was lower in patients treated with steroids than in controls (13.9% [55/396] versus 23.9% [16/67]; hazard ratio [HR], 0.51 [95% confidence interval, 0.27 to 0.96]; P = 0.044). Steroid treatment reduced mortality by 41.8% relative to the mortality with no steroid treatment (relative risk reduction, 0.42 [95% confidence interval, 0.048 to 0.65]). Initial treatment with 1 mg/kg of body weight/day of methylprednisolone versus steroid pulses was not associated with in-hospital mortality (13.5% [42/310] versus 15.1% [13/86]; odds ratio [OR], 0.880 [95% confidence interval, 0.449 to 1.726]; P = 0.710). Our results show that the survival of patients with SARS-CoV-2 pneumonia is higher in patients treated with glucocorticoids than in those not treated. Rates of in-hospital mortality were not different between initial regimens of 1 mg/kg/day of methylprednisolone and glucocorticoid pulses.

Propuesta de una nueva calificación para determinar el riesgo de infección de dispositivos cardiacos implantables / Proposal for a novel score to determine the risk of cardiac implantable electronic device infection

Introducción y objetivos: El uso de dispositivos cardiacos implantables (DCI) se ha expandido en los últimos años. La infección relacionada con estos dispositivos es una de las principales complicaciones y se asocia con grandes morbilidad, mortalidad y costes. El objetivo del estudio es construir una puntuación predictiva del riesgo de infección del DCI. Métodos: Se diseñó un estudio retrospectivo de casos y controles anidado. Tanto los casos como los controles pertenecían a una cohorte que incluía a todos los pacientes sometidos a un procedimiento relacionado con un DCI entre enero de 2009 y diciembre de 2015. Los casos se definieron como pacientes con infección, y se seleccionó aleatoriamente a 3 controles de la cohorte por cada caso incluido. Resultados: Durante el periodo de estudio, se realizaron 2.323 procedimientos. Se identificaron en total 33 infecciones relacionadas con el DCI. Se seleccionó como controles a 99 pacientes. Se identificaron como factores de riesgo independientes el índice de Charlson (OR=1,33; IC95%, 1,07-1,67), la anticoagulación oral (OR=3,51; IC95%, 1,44-8,54), la revisión o el reemplazo de un dispositivo anterior (OR=2,75; IC95%, 1,12-6,71) y la presencia de más de 2 cables (OR=3,42; IC95%, 1,25-9,37). Se generó una escala de riesgo predictivo y se denominó CIED-AI (índice de Charlson, más de 2 cables/electrodos, revisión/reemplazo del dispositivo, anticoagulación oral, infección previa). Esta puntuación presentó un área bajo la curva receiver operating characteristic de 0,79 (IC95%, 0,71-0,88). Conclusiones: La puntuación CIED-AI puede ayudar a identificar a los pacientes con mayor riesgo de infección que serían candidatos a medidas de prevención intensivas

Introduction and objectives: The use of cardiac implantable electronic devices (CIEDs) has expanded in recent years. Infection related to these devices constitutes one of the main complications and is associated with high morbidity, mortality, and financial cost. The aim of this study was to construct a predictive risk score of acquiring CIED infection. Methods: We designed a retrospective, nested case-control study. Both cases and controls belonged to a cohort that included all patients who underwent a CIED-related procedure between January 2009 and December 2015. Cases were defined as patients with infection, and 3 infection-free controls were randomly selected from the cohort for each case included. Results: During the study period, 2323 procedures were performed. A total of 33 CIED-related infections were identified. Ninety-nine patients were selected as controls. Independent risk factors were the Charlson index (OR, 1.33; 95%CI, 1.07-1.67), oral anticoagulation (OR, 3.51; 95%CI, 1.44-8.54), revision or replacement of a previous device (OR, 2.75; 95%CI, 1.12-6.71) and the presence of more than 2 leads (OR, 3.42; 95%CI, 1.25-9.37). A predictive risk score was generated and denominated CIED-AI (Charlson Index, more than 2 leads/Electrodes, Device revision/replacement, oral Anticoagulation, previous Infection). This score had an area under the receiver operating characteristic curve of 0.79 (95%CI, 0.71-0.88). Conclusions: The CIED-AI score may help to identify patients at higher risk of infection, who could be candidates for intensive preventive measures

Proposal for a Novel Score to Determine the Risk of Cardiac Implantable Electronic Device Infection.

INTRODUCTION AND OBJECTIVES: The use of cardiac implantable electronic devices (CIEDs) has expanded in recent years. Infection related to these devices constitutes one of the main complications and is associated with high morbidity, mortality, and financial cost. The aim of this study was to construct a predictive risk score of acquiring CIED infection. METHODS: We designed a retrospective, nested case-control study. Both cases and controls belonged to a cohort that included all patients who underwent a CIED-related procedure between January 2009 and December 2015. Cases were defined as patients with infection, and 3 infection-free controls were randomly selected from the cohort for each case included. RESULTS: During the study period, 2323 procedures were performed. A total of 33 CIED-related infections were identified. Ninety-nine patients were selected as controls. Independent risk factors were the Charlson index (OR, 1.33; 95%CI, 1.07-1.67), oral anticoagulation (OR, 3.51; 95%CI, 1.44-8.54), revision or replacement of a previous device (OR, 2.75; 95%CI, 1.12-6.71) and the presence of more than 2 leads (OR, 3.42; 95%CI, 1.25-9.37). A predictive risk score was generated and denominated CIED-AI (Charlson Index, more than 2 leads/Electrodes, Device revision/replacement, oral Anticoagulation, previous Infection). This score had an area under the receiver operating characteristic curve of 0.79 (95%CI, 0.71-0.88). CONCLUSIONS: The CIED-AI score may help to identify patients at higher risk of infection, who could be candidates for intensive preventive measures.