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Background: Diastolic dysfunction (DD) assessment in heart failure is still challenging. Peak atrial longitudinal strain (PALS) is strongly related to end-diastolic pressure and prognosis, but it is still not part of standard DD assessment. We tested the hypothesis that a machine learning approach would be useful to include PALS in DD classification and refine prognostic stratification. Methods: In a derivation cohort of 864 heart failure patients in sinus rhythm (age, 66.6±12 years; heart failure with reduced ejection fraction, n=541; heart failure with mildly reduced ejection fraction, n=129; heart failure with preserved ejection fraction, n=194), machine learning techniques were retrospectively applied to PALS and guideline-recommended diastolic variables. Outcome (death/heart failure rehospitalization) of the identified DD-clusters was compared with that by guidelines-based classification. To identify the best combination of variables able to classify patients in one of the identified DD-clusters, classification and regression tree analysis was applied (with DD-clusters as dependent variable and PALS plus guidelines-recommended diastolic variables as explanatory variables). The algorithm was subsequently validated in a prospective cohort of 189 heart failure outpatients (age, 65±13 years). Results: Three distinct echocardiographic DD-clusters were identified (cluster-1, n=212; cluster-2, n=376; cluster-3 DD, n=276), with modest agreement with guidelines-recommended classification (kappa=0.40; P P =0.033; net reclassification improvement 0.166 [95% CI, 0.035–0.276], P =0.013), without interaction with ejection fraction category. In the validation cohort (median follow-up: 18.5 months), cluster-based classification better predicted outcome than guideline-based classification (C-index 0.80 versus 0.78, P =0.093). Conclusions: Integrating PALS by machine learning algorithm in DD classification improves risk stratification over recommended current criteria, regardless of ejection fraction status. This proof of concept study needs further validation of the proposed algorithm to assess generalizability to other populations.

Aims: Sacubitril/valsartan has changed the treatment of heart failure with reduced ejection fraction (HFrEF), due to the positive effects on morbidity and mortality, partly mediated by left ventricular (LV) reverse remodelling (LVRR). The aim of this multicenter study was to identify echocardiographic predictors of LVRR after sacubitril/valsartan administration. Methods and results: Patients with HFrEF requiring therapy with sacubitril/valsartan from 13 Italian centres were included. Echocardiographic parameters including LV global longitudinal strain (GLS) and global peak atrial longitudinal strain by speckle tracking echocardiography were measured to find the predictors of LVRR [=LV end-systolic volume reduction ≥10% and ejection fraction (LVEF) improvement ≥10% at follow-up] at 6month follow-up as the primary endpoint. Changes in symptoms [New York Heart Association (NYHA) class] and neurohormonal activations [N-terminal pro-brain natriuretic peptide (NT-proBNP)] were also evaluated as secondary endpoints; 341 patients (excluding patients with poor acoustic windows and missing data) were analysed (mean age: 65±10years; 18% female, median LVEF 30% [inter-quartile range: 25-34]). At 6month follow-up, 82 (24%) patients showed early complete response (LVRR and LVEF≥35%), 55 (16%) early incomplete response (LVRR and LVEF&nbsp

Aims: In patients with heart failure with reduced ejection fraction (HFrEF), an association between left atrial (LA) dilatation and dysfunction is expected, but the degree of coexistence of the two abnormalities and their relative prognostic role is not known. Methods and results: A total of 626 HFrEF patients formed the study population. All of them underwent a comprehensive echocardiographic evaluation. LA maximal volume was indexed to body surface area (LAVi); LA function was assessed using strain analysis during the reservoir phase: peak atrial longitudinal strain (PALS) analysis. Study primary endpoint was overall mortality or hospitalization for worsening heart failure. Four groups of patients were included in this study according to LAVi (≤34 or >34 mL/m2 ) and PALS (≤23% or >23%); 61 (10%) patients had normal LA volume and function (Group 1), 58 (9%) had LA dilatation but normal function (Group 2), 100 (16%) had normal volume but abnormal function (Group 3), and 407 (65%) had enlarged left atrium and abnormal function (Group 4). PALS was associated with primary endpoint in patients with both normal-size [Groups 1 and 3: hazard ratio (HR) 0.92, 95% confidence interval (CI) 0.88-0.96; P = 0.0006] and dilated left atria (Groups 2 and 4: HR 0.93, 95% CI 0.91-0.96; P < 0.0001). In contrast, LAVi was associated with the primary endpoint in patients with abnormal LA function (Groups 3 and 4: HR 1.018, 95% CI 1.011-1.024; P < 0.00001) but not in those with normal PALS (Groups 1 and 2: HR 1.023, 95% CI 0.99-1.057; P = 0.1). Conclusions: Left atrial dilatation and dysfunction frequently but not invariably coexist. PALS emerged as a significant prognostic parameter in HFrEF even in the absence of LA dilation.

Background Validation of administrative databases for cerebrovascular diseases is crucial for epidemiological, outcome, and health services research. The aim of this study was to validate ICD-9 codes for hemorrhagic or ischemic stroke in administrative databases, to use them for a comprehensive assessment of the burden of disease in terms of major outcomes, such as mortality, hospital readmissions, and use of healthcare resources. Methods We considered the hospital discharge abstract database of the Umbria Region (890,000 residents). Source population was represented by patients aged >18 discharged from hospital with a diagnosis of hemorrhagic or ischemic stroke between 2012 and 2014 using ICD-9-CM codes in primary position. We randomly selected and reviewed medical charts of cases and non-cases from hospitals. For case ascertainment we considered symptoms and instrumental tests reported in the medical charts. Diagnostic accuracy measures were computed using 2x2 tables. Results We reviewed 767 medical charts for cases and 78 charts for non-cases. Diagnostic accuracy measures were: subarachnoid hemorrhage: sensitivity (SE) 100% (95% CI: 97%-100%), specificity (SP) 96% (90–99), positive predictive value (PPV) 98% (93–100), negative predictive value (NPV) 100% (95–100); intracerebral hemorrhage: SE 100% (97–100), SP 98% (91–100), PPV 98% (94–100), NPV 100% (95–100); other and unspecified intracranial hemorrhage: SE 100% (97–100), SP 96% (90–99), PPV 98% (93–100), NPV 100% (95–100); ischemic stroke due to occlusion and stenosis of precerebral arteries: SE 99% (94–100), SP 66 (57–75), PPV 70% (61–77), NPV 99% (93–100); occlusion of cerebral arteries: SE 100% (97–100), SP 87% (78–93), PPV 91% (84–95), NPV 100% (95–100); acute, but ill-defined, cerebrovascular disease: SE 100% (97–100), SP 78% (69–86), PPV % 83 (75–89), NPV 100% (95–100). Conclusions Case ascertainment for both ischemic and hemorrhagic stroke showed good or high levels of accuracy within the regional healthcare databases in Umbria. This database can confidently be employed for epidemiological, outcome, and health services research related to any type of stroke.

BackgroundAdministrative healthcare databases are useful and inexpensive tools that can provide a comprehensive assessment of the burden of diseases in terms of major outcomes, such as mortality, hospital readmissions, and use of healthcare resources. However, a crucial issue is the reliability of information gathered. The aim of this study was to validate ICD-9 codes for several major cardiovascular conditions, i.e., acute myocardial infarction (AMI), atrial fibrillation/flutter (AF), and heart failure (HF), in order to use them for epidemiological, outcome, and health services research.MethodsData from the centralised administrative database of the Umbria Region (890,000 residents, located in Central Italy) were considered. Patients with a first hospital discharge for AMI, AF/flutter, and HF, between 2012 and 2014, were identified using ICD-9-CM codes in primary position. A sample of cases and non-cases was randomly selected, and the corresponding medical charts reviewed by specifically trained investigators. For each disease, case ascertainment was based on all clinical, laboratory, and instrumental examinations available in medical charts. Sensitivity, specificity, and predictive values with 95% confidence intervals (CIs), were calculated.ResultsWe reviewed 458 medical charts, 128 for AMI, 127 for AF/flutter, 127 for HF, and 76 of non-cases for each condition. Diagnostic accuracy measures of the original discharge diagnosis were as follows. AMI: sensitivity 98% (95% CI, 94-100%), specificity 91% (95% CI, 83-97%), positive predictive value (PPV) 95% (95% CI, 89-98%), negative predictive value (NPV) 97% (95% CI, 91-100%). AF/flutter: sensitivity 95% (95% CI, 90-98%), specificity 95% (95% CI, 87-99%), PPV 97% (95% CI, 92-99%), NPV 92% (95% CI, 84-97%). HF: sensitivity 96% (95% CI, 91-99%), specificity 90% (95% CI, 81-96%), PPV 94% (95% CI, 88-97%), NPV 93% (95% CI, 85-98%).ConclusionThe case ascertainment for AMI, AF and flutter, and HF, showed a high level of accuracy (≥ 90%). The healthcare administrative database of the Umbria Region can be confidently used for epidemiological, outcome, and health services research.

Background and aims Elevated serum uric acid (sUA) concentrations have been associated with worse prognosis in heart failure (HF) but little is known about elderly patients. We aimed to assess long-term additive prognostic value of sUA in elderly patients hospitalized for HF. Methods and results Clinical and echocardiographic characteristics of 310 consecutive elderly patients hospitalized for HF were collected. During index period, 206 had sUA concentrations available, which were obtained within 24 h prior to discharge; 10 patients were lost to follow-up, leaving 196 patients available. Patients had a median age of 77 (IQR 69–83) years, and were mostly male (64.5%). sUA ranges for tertiles I–III were: 1.5–6.1, 6.2–8.3, and 8.4–18.9 mg/dl, respectively. During a median follow-up of 27 months (IQR 10.5–39.5), 122 combined events occurred (87 deaths and 73 HF rehospitalizations). Four-year event-free survival for the combined endpoint was 46 ± 7% for tertile I, 34 ± 7% for tertile II, and 21 ± 5% for tertile III (P = 0.001). By multivariable Cox backward analysis, sUA was retained as a significant predictor. Compared with the lowest sUA tertile, tertile III showed a strong association with outcome, also after adjustment for other predictors (HR 1.84, 95% CI 1.16–2.93; P = 0.01). Importantly, addition of sUA to the other significant predictors of outcome resulted in improved risk classification (net reclassification improvement 0.19, P = 0.017). Conclusions High sUA at discharge is a strong predictor of adverse outcome in elderly hospitalized for HF, and it significantly improves risk classification. Measuring sUA can be a simple and useful tool to identify high-risk elderly hospitalized for HF.

Myocardial reflectivity, as assessed by calibrated integrated backscatter (cIB) analysis, is a non-invasive surrogate for the amount of left ventricular (LV) fibrosis. The aim of this study was to assess the myocardial reflectivity pattern in patients with heart failure and preserved ejection fraction (HFpEF), and to evaluate its relationship with longitudinal systolic deformation of LV by 2D-speckle tracking echocardiography, and degree of diastolic dysfunction. Transthoracic echocardiography, myocardial Doppler-derived systolic (Sm) and early diastolic velocity (E'), global longitudinal strain (GLS), and tissue characterization by cIB, were obtained in 86 subjects, 46 with HFpEF, and 40 controls. GLS was significantly impaired in HFpEF patients (-15.4 ± 3.5 % vs -21.5 ± 2.9 % in controls; P