Prognostic factors at admission on patients with cancer and COVID-19: Analysis of HOPE registry data.

BACKGROUND: Previous works seem to agree in the higher mortality of cancer patients with COVID-19. Identifying potential prognostic factors upon admission could help identify patients with a poor prognosis. METHODS: We aimed to explore the characteristics and evolution of COVID-19 cancer patients admitted to hospital in a multicenter international registry (HOPE COVID-19).Our primary objective is to define those characteristics that allow us to identify cancer patients with a worse prognosis (mortality within 30 days after the diagnosis of COVID-19). RESULTS: 5838 patients have been collected in this registry, of whom 770 had cancer among their antecedents. In hospital mortality reached 258 patients (33.51%). The median was 75 years (65-82). Regarding the distribution by sex, 34.55% of the patients (266/770) were women.The distribution by type of cancer: genitourinary 238/745 (31.95%), digestive 124/745 (16.54%), hematologic 95/745 (12.75%).In multivariate regression analysis, factors that are independently associated with mortality at admission are: renal impairment (OR 3.45, CI 97.5% 1.85-6.58), heart disease (2.32, 1.47-3.66), liver disease (4.69, 1.94-11.62), partial dependence (2.41, 1.34-4.33), total dependence (7.21, 2.60-21.82), fatigue (1.84, 1.16-2.93), arthromialgias (0.45, 0.26-0.78), SatO2 < 92% (4.58, 2.97-7.17), elevated LDH (2.61, 1.51-4.69) and abnormal decreased Blood Pressure (3.57, 1.81-7.15). Analitical parameters are also significant altered. CONCLUSION: In patients with cancer from the HOPE registry, 30-day mortality from any cause is high and is associated with easily identifiable clinical factors upon arrival at the hospital. Identifying these patients can help initiate more intensive treatments from the start and evaluate the prognosis of these patients.

ANTECEDENTES: Trabajos previos parecen coincidir en la mayor mortalidad de los pacientes con cáncer y COVID-19. La identificación de posibles factores pronósticos en el momento del ingreso podría ayudar a identificar a los pacientes con mal pronóstico. MÉTODOS: Nos propusimos explorar las características y la evolución de los pacientes con cáncer y COVID-19 ingresados en un registro internacional multicéntrico (HOPE COVID-19).Nuestro objetivo principal es definir aquellas características que nos permitan identificar a los pacientes con cáncer de peor pronóstico (mortalidad en los 30 días siguientes al diagnóstico de COVID-19). RESULTADOS: En este registro se ha recogido a 5.838 pacientes, de los cuales 770 tenían cáncer entre sus antecedentes. La mortalidad hospitalaria alcanzó a 258 pacientes (33,51%). La mediana fue de 75 años (65-82). En cuanto a la distribución por sexo, el 34,55% de los pacientes eran mujeres (266/770).La distribución por tipo de cáncer: genitourinario 238/745 (31,95%), digestivo 124/745 (16,54%) y hematológico 95/745 (12,75%).En el análisis de regresión multivariante, los factores que se asocian de forma independiente con la mortalidad al ingreso son: insuficiencia renal (OR 3,45; IC 97,5%: 1,85-6,58), cardiopatía (2,32; 1,47-3,66), hepatopatía (4,69; 1,94-11,62), dependencia parcial (2,41; 1,34-4,33), dependencia total (7,21; 2,60-21,82), fatiga (1,84, 1;16-2,93), artromialgias (0,45; 0,26-0,78), SatO2 < 92% (4,58; 2,97-7,17), LDH elevada (2,61; 1,51-4,69) y disminución anormal de la presión arterial (3,57; 1,81-7,15). Los parámetros analíticos también están significativamente alterados. CONCLUSIÓN: En los pacientes con cáncer del registro HOPE, la mortalidad a los 30 días por cualquier causa es elevada y se asocia a factores clínicos fácilmente identificables a su llegada al hospital. La identificación de estos pacientes puede ayudar a iniciar tratamientos más intensivos desde el principio y evaluar el pronóstico de estos pacientes.

Prognostic factors at admission on patients with cancer and COVID-19: Analysis of HOPE registry data.

BACKGROUND: Previous works seem to agree in the higher mortality of cancer patients with COVID-19. Identifying potential prognostic factors upon admission could help identify patients with a poor prognosis. METHODS: We aimed to explore the characteristics and evolution of COVID-19 cancer patients admitted to hospital in a multicenter international registry (HOPE COVID-19). Our primary objective is to define those characteristics that allow us to identify cancer patients with a worse prognosis (mortality within 30 days after the diagnosis of COVID-19). RESULTS: 5838 patients have been collected in this registry, of whom 770 had cancer among their antecedents. In hospital mortality reached 258 patients (33.51%). The median was 75 years (65-82). Regarding the distribution by sex, 34.55% of the patients (266/770) were women. The distribution by type of cancer: genitourinary 238/745 (31.95%), digestive 124/745 (16.54%), hematologic 95/745 (12.75%). In multivariate regression analysis, factors that are independently associated with mortality at admission are: renal impairment (OR 3.45, CI 97.5% 1.85-6.58), heart disease (2.32, 1.47-3.66), liver disease (4.69, 1.94-11.62), partial dependence (2.41, 1.34-4.33), total dependence (7.21, 2.60-21.82), fatigue (1.84, 1.16-2.93), arthromialgias (0.45, 0.26-0.78), SatO2<92% (4.58, 2.97-7.17), elevated LDH (2.61, 1.51-4.69) and abnormal decreased Blood Pressure (3.57, 1.81-7.15). Analitical parameters are also significant altered. CONCLUSION: In patients with cancer from the HOPE registry, 30-day mortality from any cause is high and is associated with easily identifiable clinical factors upon arrival at the hospital. Identifying these patients can help initiate more intensive treatments from the start and evaluate the prognosis of these patients.

Evaluation of atrial function after surgical ablation of atrial fibrillation: a Speckle tracking study.

AIM: AIM of our study was to assess atrial function in patients who underwent atrial fibrillation (AF) surgical ablation by a novel echocardiographic technique (speckle tracking). METHODS: From February 2006 to April 2008, in 11 consecutive pts with paroxysmal or persistent AF (6 males, mean age 69.6±9.7 years) undergoing cardiac surgery, concomitant AF surgical ablation was performed with bipolar radiofrequency clamp (Cobra_Bipolar® system). These pts, all in stable sinus rhythm (SR), were echoed after a mean follow-up of 14.6±9.3 months from surgery. Speckle tracking was used to estimate global LA strain, peak strain and the standard deviation of the time-to-peak (% of R-R' interval) of the deformation of 6 segments identified along the septum, the roof and the lateral wall of LA in a 4-chamber view. RESULTS: These patients showed a mild LA enlargement (mean volume 43.4±11.6 mL/sqm). In 5 of them (45.4%) no A waves were detected on MPWD and pulmonary venous flow, but speckle tracking showed preserved atrial function with a mean global strain of 5.5 ± 3.3 %, a mean peak strain of 10.4 ± 5.7 % and a TP-SD of 15.1±8.7 ms. CONCLUSION: Our study seems to show that surgical AF ablation has a lower impact on atrial function in comparison with data from literature about percutaneous catheter ablation. This is probably related to an higher sensitivity of this type of echocardiography evaluation, but this finding must be confirmed by other trials.

Tobacco smoke affects expression of peroxisome proliferator-activated receptor-gamma in monocyte/macrophages of patients with coronary heart disease.

BACKGROUND AND PURPOSE: Tobacco smoke represents a relevant risk factor for coronary heart disease (CHD). Although peroxisome proliferator-activated receptor (PPAR)gamma activation reduces inflammation and atherosclerosis, expression of PPARgamma in cells and its modulation by smoking are poorly investigated. We previously reported that monocyte/macrophages from healthy smokers exhibited an enhanced constitutive expression of PPARgamma. Here, we evaluated PPARgamma expression and basal cytokine release in monocytes and monocyte-derived macrophages (MDMs) from 85 CHD patients, classified by their smoking habit (smokers, non-smokers and ex-smokers), and assessed the role of PPARgamma ligands in this context. EXPERIMENTAL APPROACH: PPARgamma protein was detected by Western blot and semi-quantified by PPARgamma/beta-actin ratio; cytokine release was measured by elisa and nuclear factor-kappaB (NF-kappaB) translocation by electrophoretic mobility shift assays. KEY RESULTS: As compared to the other groups, MDMs from smoker CHD patients exhibited a reduced PPARgamma/beta-actin ratio and an increased spontaneous release of tumour necrosis factor-alpha (TNF-alpha) and interleukin-6, but with no major variations in monocytes. In cells from selected CHD patients, rosiglitazone inhibited TNF-alpha release and NF-kappaB translocation induced by phorbol-12-myristate 13-acetate. The selective PPARgamma antagonist GW9662 reversed these effects, with some variations related to smoking habit. CONCLUSIONS AND IMPLICATIONS: In CHD patients, exposure to tobacco smoke profoundly affected PPARgamma expression, and this was related to levels of secretion of pro-inflammatory cytokines. MDMs from CHD smokers showed the lowest PPARgamma expression and released more inflammatory cytokines. Moreover, rosiglitazone's ability to inhibit cytokine release and its reversal by GW9662 clearly indicated PPARgamma involvement in these changes in CHD patients.