[Cardiac tumors in clinical practice]. / Les tumeurs cardiaques.

Cardiac tumors are rare in clinical practice but remain an essential part of the fast-growing field of cardio-oncology. They can be detected incidentally and consist of primary tumors (benign or malignant) and of the more prevalent secondary tumors (metastasis). They form a heterogeneous group of pathologies presenting with a wide panel of clinical symptoms according to their location and size. Multimodality cardiac imaging (echocardiography, CT, MRI and PET), in association with clinical and epidemiological factors, plays a key role in the diagnosis of cardiac tumors and a biopsy is therefore not systematically required. Treatment strategies for cardiac tumors vary depending on the malignancy and class of the tumor, but also consider associated symptoms, hemodynamic impact and embolic risk.

Les tumeurs cardiaques sont des pathologies rares mais elles ­appartiennent à un domaine en plein essor de la cardio-oncologie. Souvent découvertes fortuitement, elles comprennent les ­tumeurs cardiaques primaires (bénignes ou malignes) et, plus fréquemment, secondaires (métastases). Elles constituent un ­ensemble très hétérogène de pathologies, dont les manifestations cliniques varient en fonction de la taille et de la localisation. Le diagnostic repose sur une approche clinique, épidémiologique et plusieurs modalités d'imagerie (échocardiographie, CT, IRM et PET-CT), sans nécessité systématique de biopsie. La stratégie de traitement d'une tumeur cardiaque dépend de la symptomatologie du patient, du risque embolique ou hémodynamique lié à la masse, ainsi que de sa malignité.

Frailty to predict unplanned hospitalization, stroke, bleeding, and death in atrial fibrillation.

AIMS: Atrial fibrillation (AF) and frailty are common, and the prevalence is expected to rise further. We aimed to investigate the prevalence of frailty and the ability of a frailty index (FI) to predict unplanned hospitalizations, stroke, bleeding, and death in patients with AF. METHODS AND RESULTS: Patients with known AF were enrolled in a prospective cohort study in Switzerland. Information on medical history, lifestyle factors, and clinical measurements were obtained. The primary outcome was unplanned hospitalization; secondary outcomes were all-cause mortality, bleeding, and stroke. The FI was measured using a cumulative deficit approach, constructed according to previously published criteria and divided into three groups (non-frail, pre-frail, and frail). The association between frailty and outcomes was assessed using multivariable-adjusted Cox regression models. Of the 2369 included patients, prevalence of pre-frailty and frailty was 60.7% and 10.6%, respectively. Pre-frailty and frailty were associated with a higher risk of unplanned hospitalizations [adjusted hazard ratio (aHR) 1.82, 95% confidence interval (CI) 1.49-2.22; P < 0.001; and aHR 3.59, 95% CI 2.78-4.63, P < 0.001], all-cause mortality (aHR 5.07, 95% CI 2.43-10.59; P < 0.001; and aHR 16.72, 95% CI 7.75-36.05; P < 0.001), and bleeding (aHR 1.53, 95% CI 1.11-2.13; P = 0.01; and aHR 2.46, 95% CI 1.61-3.77; P < 0.001). Frailty, but not pre-frailty, was associated with a higher risk of stroke (aHR 3.29, 95% CI 1.2-8.39; P = 0.01). CONCLUSION: Over two-thirds of patients with AF are pre-frail or frail. These patients have a high risk for unplanned hospitalizations and other adverse events. These findings emphasize the need to carefully evaluate these patients. However, whether screening for pre-frailty and frailty and targeted prevention strategies improve outcomes needs to be shown in future studies. CLINICAL TRIAL REGISTRATION: Clinicaltrials.gov identifier number: NCT02105844.

Symptoms and quality of life in patients with coexistent atrial fibrillation and atrial flutter.

AIMS: Atrial fibrillation (AF) and atrial flutter (AFL) are two of the most common atrial arrhythmias and often coexist. Many patients with AF or AFL are symptomatic, which impacts their quality of life (QoL). The purpose of this study was to determine whether coexistent AFL represents an added burden for AF patients. METHODS: We combined baseline data from two large prospective, observational, multicenter cohort studies (BEAT-AF and Swiss-AF). All 3931 patients included in this analysis had documented AF. We obtained information on comorbidities, medication, and lifestyle factors. All participants had a clinical examination and a resting ECG. Symptom burden and QoL at the baseline examination were compared between patients with and without coexistent AFL using multivariable adjusted regression models. RESULTS: Overall, 809 (20.6%) patients had a history of AFL. Patients with coexistent AFL more often had history of heart failure (28% vs 23%, p = 0.01), coronary artery disease (30% vs 26%, p = 0.007), failed therapy with antiarrhythmic drugs (44% vs 29%, p < 0.001), and more often underwent AF-related interventions (36% vs 17%, p < 0.001). They were more often symptomatic (70% vs 66%, p = 0.04) and effort intolerant (OR: 1.14; 95% CI: 1.01-1.28; p = 0.04). Documented AFL on the baseline ECG was associated with more symptoms (OR: 2.30; 95% CI: 1.26-4.20; p = 0.007). CONCLUSION: Our data indicates that patients with coexistent AF and AFL are more often symptomatic and report poorer quality of life compared to patients suffering from AF only.

Prevalence and predictors of atrial fibrillation type among individuals with recent onset of atrial fibrillation.

OBJECTIVE: Atrial fibrillation (AF) is considered to be a progressive disease, starting with intermittent episodes that progress over time to more sustained events. However, little is known about the prevalence of and predictors for AF type among patients with recent-onset AF. We aimed to address these issues among a selected population of patients with AF. METHODS: The Basel atrial fibrillation cohort (BEAT-AF) study is an ongoing prospective multicentre cohort study among patients with AF. At baseline, we obtained information on the date of AF diagnosis, AF type, comorbidities, medication and lifestyle factors. For this analysis, 486 (31.4%) out of 1550 participants with recent-onset AF (defined as AF duration <24 months) were included. Predictors for AF type (non-paroxysmal vs paroxysmal) were obtained using multivariable adjusted logistic regression models. RESULTS: Mean age was 67 (59-75) years and 136 (28%) were women. Recent-onset paroxysmal AF was observed in 301 (62%) participants, 185 (38%) had non-paroxysmal AF - persistent AF in 148 (30.4%) and permanent AF in 37 (7.6%). In multivariable models, odds ratios for having non-paroxysmal AF around AF diagnosis were 1.03 per year increasing in age (95% confidence interval [CI] 1.01-1.05, p = 0.01); 2.70 (1.5-4.68, p = 0.0004) for history of heart failure; 3.82 (1.05-13.87, p = 0.04) for a history of hyperthyroidism and 1.04 (1.02-1.05, p <0.0001) per beat increase in heart rate. CONCLUSION: We found a substantial proportion of AF patients with the non-paroxysmal form shortly after diagnosis. Predictors for non-paroxysmal AF were increasing age, history of heart failure or hyperthyroidism, and a higher heart rate.