History Traditional cardiovascular risk factors in the general population are usually correlated to a better prognosis in patients with chronic heart failure (HF). HF for the management of their systolic HF (left ventricular ejection portion was 28?±?9?%). All patients underwent ambulatory blood pressure monitoring (systolic BP: 110?±?15; diastolic BP: 68?±?10 and pulse pressure: 42?±?11?mmHg) and the prognostic impact of BPV was collected with a mean follow-up of 4.4?±?3.1?years. Twenty-five (9?%) patients were missing for follow-up. Among GDC-0349 the others patients 70 (27?%) cardiovascular events (cardiac deaths: 24?%; heart transplantation: 2?%) were recorded. By multivariate analysis BPV daytime (OR?=?0.963 p?=?0.033) and severe NYHA class (OR?=?5.2 p?0.0001) were found as indie predictors of cardiac event. Patients with a systolic GDC-0349 daytime BPV under a cut-off value of 19?mmHg had the poorest prognosis with an Gsk3b OR for cumulative events of 1 1.65 (IC95 % 1.1-2.7; p?0.04). Conclusion BPV is simple tool and a predictor of cardiac events in patients with systolic HF. Keywords: Heart failure Blood pressure variability Prognosis Background If GDC-0349 high blood pressure GDC-0349 (BP) body mass index and cholesterolemia represent traditional cardiovascular risk factors in the general populace they are correlated to a better prognosis in patients with chronic heart failure (HF) [1-3]. In a meta-analysis Raphael and al emphasized the paradoxical effect of higher systolic BP on mortality of patients with chronic HF showing a decrease of 13?% in cardiovascular death for an increase of 10?mmHg in systolic BP . For the last decades the prognostic impact of each determinant of BP profile such as systolic BP diastolic BP pulse pressure (PP) BP variability (BPV) was essentially analyzed in patients with hypertension  but few in chronic HF. Thus Rothwell et al. showed in a hypertensive populace that this daytime BPV was a powerful predictor of stroke and coronary events . The aim of the present study was to assess the prognostic impact of short-term BPV in chronic systolic HF. Method Population Patients were retrospectively extracted from our local database of HF and including patients referred the exploration and the management of systolic HF in of the HF unit of the University or college Hospital of Toulouse from 1999 to 2006. Inclusion criterions were: age over 18?years old 1 systolic HF event in life systolic dysfunction defined by left ventricular ejection portion <45?% GDC-0349 ambulatory monitoring of BP in at admission. Exclusion criterions were: patients with low circulation or treated with intravenous drugs such as inotropic support contamination dialysis and incomplete ambulatory monitoring of BP. The study was approved by our local ethics committee. Twenty-four-hour ABPM Twenty-four-hour ambulatory BP monitoring (ABPM) was performed as previous explained in chronic HF  using the oscillometric method (Spacelabs 90207 device? ). Successive BP methods had been performed every 15?min during day time (7?am. to 9:59?pm.) and every 30?min during nighttime (10?pm. to 6:59?am.). BP methods had been portrayed in millimetres of mercury (mmHg). All gadgets for ABPM had been placed on the proper arms by a tuned nurse 24-h after entrance. Patients had been instructed to relax the cuffed arm through the measure and received a journal to record unforeseen events. The evaluation of ABPM information had been performed using Spacelabs software program permitting us to extract systolic BP diastolic BP PP BPV and Dip percentage daytime and nighttime BPV was determined using the average difference between maxima and minima from each systolic BP measure to another. Nighttime BP dipping can be quantified as the percentage of mean nighttime (sleep) BP to mean daytime (awake) BP. The calculation method was: GDC-0349 BPV?=?(maximum systolic BP - minimum amount systolic BP)/2. Follow-up Follow up was carried out using physician patient or family telephone contacts. Patients without news within the last month after the AMBP were considered as missing for follow-up. The composite endpoint was defined by the event of cardiovascular events: cardiac death or heart transplantation. Statistical analysis Continuous variables with a normal.