BackgroundThe independent prognostic impact of diabetes mellitus (DM) and prediabetes mellitus (pre‐DM) on survival outcomes in patients with chronic heart failure has been investigated in observational registries and randomized, clinical trials, but the results have been often inconclusive or conflicting. We examined the independent prognostic impact of DM and pre‐DM on survival outcomes in the GISSI‐HF (Gruppo Italiano per lo Studio della Sopravvivenza nella Insufficienza Cardiaca‐Heart Failure) trial.Methods and ResultsWe assessed the risk of all‐cause death and the composite of all‐cause death or cardiovascular hospitalization over a median follow‐up period of 3.9 years among the 6935 chronic heart failure participants of the GISSI‐HF trial, who were stratified by presence of DM (n=2852), pre‐DM (n=2013), and non‐DM (n=2070) at baseline. Compared with non‐DM patients, those with DM had remarkably higher incidence rates of all‐cause death (34.5% versus 24.6%) and the composite end point (63.6% versus 54.7%). Conversely, both event rates were similar between non‐DM patients and those with pre‐DM. Cox regression analysis showed that DM, but not pre‐DM, was associated with an increased risk of all‐cause death (adjusted hazard ratio, 1.43; 95% CI, 1.28–1.60) and of the composite end point (adjusted hazard ratio, 1.23; 95% CI, 1.13–1.32), independently of established risk factors. In the DM subgroup, higher hemoglobin A1c was also independently associated with increased risk of both study outcomes (all‐cause death: adjusted hazard ratio, 1.21; 95% CI, 1.02–1.43; and composite end point: adjusted hazard ratio, 1.14; 95% CI, 1.01–1.29, respectively).ConclusionsPresence of DM was independently associated with poor long‐term survival outcomes in patients with chronic heart failure.Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT00336336.

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The flow downstream from aortic stenoses 1 is characterised by the onset of shear-induced turbulence that 2 leads to irreversible pressure losses. These extra losses represent 3 an increased resistance that impacts cardiac efficiency. A novel 4 approach is suggested in this study to accurately evaluate 5 the pressure gradient profile along the aorta centreline using 6 modelling of haemodynamic stress at scales that are smaller 7 than the typical resolution achieved in experiments. Methods: We 8 use benchmark data obtained from direct numerical simulation 9 (DNS) along with results from in silico and in vitro three-10 dimensional particle tracking velocimetry (3D-PTV) at three 11 voxel sizes, namely 750 µm, 1 mm and 1.5 mm. A differential 12 equation is derived for the pressure gradient, and the subvoxel-13 scale (SVS) stresses are closed using the Smagorinsky and a 14 new refined model. Model constants are optimised using DNS 15 and in silico PTV data and validated based on pulsatile in 16 vitro 3D-PTV data and pressure catheter measurements. Results: 17 The Smagorinsky-based model was found to be more accurate 18 for SVS stress estimation but also more sensitive to errors 19 especially at lower resolution, whereas the new model was found 20 to more accurately estimate the projected pressure gradient even 21 for larger voxel size of 1.5mm albeit at the cost of increased 22 sensitivity at this voxel size. A comparison with other methods 23 in the literature shows that the new approach applied to in 24 vitro PTV measurements estimates the irreversible pressure 25 drop by decreasing the errors by at least 20%. Conclusion: 26 Our novel approach based on the modelling of subvoxel stress 27 offers a validated and more accurate way to estimate pressure 28 gradient, irreversible pressure loss and SVS stress. Significance: 29 We anticipate that the approach may potentially be applied to 30 image-based in vivo, in vitro 4D flow data or in silico data with 31 limited spatial resolution to assess pressure loss and SVS stresses 32 in disturbed aortic blood flow.

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