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.

Aneurysm of the anterior leaflet of the mitral valve secondary to aortic valve endocarditis.

Aneurysm of the anterior mitral leaflet is a rare complication of infective aortic valve endocarditis, the natural evolution of which is generally its rupture, with subsequent acute and severe mitral regurgitation. Its presence cannot be recognized with transthoracic echocardiography and even in surgery. We describe a 78-year-old man with aortic valve endocarditis, in whom transesophageal echocardiography was essential for the diagnosis of this complication, its therapeutic management, and the postoperative follow-up after simple valve repair. In addition, the most appropriate surgical approach is discussed.

[A comparison of the clinical and angiographic evolution of diabetic and nondiabetic patients treated by conventional angioplasty versus stent implantation in native coronary arteries]. / Comparación de la evolución clínica y angiográfica de pacientes diabéticos y no diabéticos tratados con angioplastia convencional frente a implantación de stent en arterias coronarias nativas.

INTRODUCTION AND OBJECTIVES: Diabetic patients have a high restenosis risk after balloon coronary angioplasty. Stent implantation in these patients appears to be a potential beneficial therapeutic option. The aim of this study was to compare the clinical and angiographic outcome of diabetic patients vs non-diabetic patients, treated with conventional angioplasty vs stent implantation in lesions located in native coronary arteries. MATERIAL AND METHODS: A total of 302 patients (58 diabetics and 244 non-diabetics) underwent a coronary angioplasty of one vessel in native coronary arteries with initial success and after at least six months clinical and angiographic follow-up were included in the study. Of the total number of patients, 100 were treated with conventional balloon angioplasty and 202 with stent implantation. Major adverse clinical events and angiographic restenosis rate were evaluated at follow-up. RESULTS: Mean age of patients was 65 years and 74% were male. Angiographic restenosis rate was similar in diabetic vs non-diabetic patients with stent implantation (24% vs 23% respectively). Nevertheless, diabetic patients treated with balloon angioplasty compared to diabetic patients treated with stenting, evolved with a higher restenosis rate (64% vs 24%; p < 0.05), and at the end of follow-up diabetics had need a higher rate of target vessel revascularization (40% vs 24%; p < 0.05), a lower major event free survival (56% vs 70%; p < 0.05) and worse symptomatic status (72% vs 36%; p < 0.05). CONCLUSIONS: Diabetic patients treated with conventional one vessel coronary balloon angioplasty evolved with a high restenosis rate and a bad mid-term clinical outcome. Stent implantation was able reduce to the restenosis rate and improve the mid-term clinical outcome, in a comparable population of diabetic patients.

[The predictive factors of intra-stent restenosis]. / Factores predictores de reestenosis intra-stent.

INTRODUCTION AND OBJECTIVE: Stenting has contributed to improve the early angiographic result, the restenosis rate and the problem of acute and subacute coronary occlusion. In spite of this, the restenosis phenomenon still remains a problem to be completely solved. The aim of the study was to identify clinical, angiographical and procedural factors that are predictive of in-stent restenosis after successful implantation of coronary stent. MATERIAL AND METHODS: We retrospectively analyzed 202 lesions, in 176 consecutive patients who underwent stent implantation with success in our hospital between January 1995 and August 1998. All patients had a clinical follow-up and an angiography after six months of stent implantation. RESULTS: From 202 lesions evaluated, 47 evolved with restenosis (23%). The only independent predictive variables were: to be receiving hypolipemiant treatment before stenting (OR: 0.3; IC: 0.1-0.8), the use of high pressure for stent implantation (OR: 0.4; IC: 0.2-0.9), to implant stent in < 3.1 mm (OR: 2.2; IC: 1.1-4.5) and to have a residual stenosis > 30% after stenting (OR: 13; IC: 1.5-120). CONCLUSIONS: The only statistical variables associated with in-stent restenosis phenomenon were: be under hypolipemiant treatment before the procedure and the use of high pressures for stent implantation; while risk factors arose: to implant stent in vessels < 3.1 mm and suboptimal angiography result after stenting.