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- Cosmi, F., et al.
(author)
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Treatment with insulin is associated with worse outcome in patients with chronic heart failure and diabetes
- 2018
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In: European Journal of Heart Failure. - : Wiley. - 1388-9842. ; 20:5, s. 888-895
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Journal article (peer-reviewed)abstract
- Aims Up to one-third of patients with diabetes mellitus and heart failure (HF) are treated with insulin. As insulin causes sodium retention and hypoglycaemia, its use might be associated with worse outcomes. Methods and results We examined two datasets: 24 012 patients with HF from four large randomized trials and an administrative database of 4 million individuals, 103 857 of whom with HF. In the former, survival was examined using Cox proportional hazards models adjusted for baseline variables and separately for propensity scores. Fine-Gray competing risk regression models were used to assess the risk of hospitalization for HF. For the latter, a case-control nested within a population-based cohort study was conducted with propensity score. Prevalence of diabetes mellitus at study entry ranged from 25.5% to 29.5% across trials. Insulin alone or in combination with oral hypoglycaemic drugs was prescribed at randomization to 24.4% to 34.5% of the patients with diabetes. The rates of death from any cause and hospitalization for HF were higher in patients with vs. without diabetes, and highest of all in patients prescribed insulin [propensity score pooled hazard ratio for all-cause mortality 1.27 (1.16-1.38), for HF hospitalization 1.23 (1.13-1.33)]. In the administrative registry, insulin prescription was associated with a higher risk of all-cause death [odds ratio (OR) 2.02, 95% confidence interval (CI) 1.87-2.19] and rehospitalization for HF (OR 1.42, 95% CI 1.32-1.53). Conclusions Whether insulin use is associated with poor outcomes in HF should be investigated further with controlled trials, as should the possibility that there may be safer alternative glucose-lowering treatments for patients with HF and type 2 diabetes mellitus.
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- Schwarz, E, et al.
(author)
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Reproducible grey matter patterns index a multivariate, global alteration of brain structure in schizophrenia and bipolar disorder
- 2019
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In: Translational psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 9:1, s. 12-
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Journal article (peer-reviewed)abstract
- Schizophrenia is a severe mental disorder characterized by numerous subtle changes in brain structure and function. Machine learning allows exploring the utility of combining structural and functional brain magnetic resonance imaging (MRI) measures for diagnostic application, but this approach has been hampered by sample size limitations and lack of differential diagnostic data. Here, we performed a multi-site machine learning analysis to explore brain structural patterns of T1 MRI data in 2668 individuals with schizophrenia, bipolar disorder or attention-deficit/ hyperactivity disorder, and healthy controls. We found reproducible changes of structural parameters in schizophrenia that yielded a classification accuracy of up to 76% and provided discrimination from ADHD, through it lacked specificity against bipolar disorder. The observed changes largely indexed distributed grey matter alterations that could be represented through a combination of several global brain-structural parameters. This multi-site machine learning study identified a brain-structural signature that could reproducibly differentiate schizophrenia patients from controls, but lacked specificity against bipolar disorder. While this currently limits the clinical utility of the identified signature, the present study highlights that the underlying alterations index substantial global grey matter changes in psychotic disorders, reflecting the biological similarity of these conditions, and provide a roadmap for future exploration of brain structural alterations in psychiatric patients.
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- Abdul-Rahim, A. H., et al.
(author)
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Risk of Stroke in Chronic Heart Failure Patients Without Atrial Fibrillation: Analysis of the Controlled Rosuvastatin in Multinational Trial Heart Failure (CORONA) and the Gruppo Italiano per lo Studio della Sopravvivenza nell'Insufficienza Cardiaca-Heart Failure (GISSI-HF) Trials
- 2015
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In: Circulation. - : Ovid Technologies (Wolters Kluwer Health). - 0009-7322 .- 1524-4539. ; 131:17
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Journal article (peer-reviewed)abstract
- BACKGROUND: Our aim was to describe the incidence and predictors of stroke in patients who have heart failure without atrial fibrillation (AF). METHODS AND RESULTS: We pooled 2 contemporary heart failure trials, the Controlled Rosuvastatin in Multinational Trial Heart Failure (CORONA) and the Gruppo Italiano per lo Studio della Sopravvivenza nell'Insufficienza cardiaca-Heart Failure trial (GISSI-HF). Of the 9585 total patients, 6054 did not have AF. Stroke occurred in 165 patients (4.7%) with AF and in 206 patients (3.4%) without AF (rates 16.8/1000 patient-years and 11.1/1000 patient-years, respectively). Using Cox proportional-hazards models, we identified the following independent predictors of stroke in patients without AF (ranked by chi(2) value): age (hazard ratio, 1.34; 95% confidence interval, 1.18-1.63 per 10 years), New York Heart Association class (1.60, 1.21-2.12 class III/IV versus II), diabetes mellitus treated with insulin (1.87, 1.22-2.88), body mass index (0.74, 0.60-0.91 per 5 kg/m(2) up to 30), and previous stroke (1.81, 1.19-2.74). N-terminal pro B-type natriuretic peptide (available in 2632 patients) was also an independent predictor of stroke (hazard ratio, 1.31; 1.11-1.57 per log unit) when added to this model. With the use of a risk score formulated from these predictors, we found that patients in the upper third of risk had a rate of stroke that approximated the risk in patients with AF. CONCLUSIONS: A small number of demographic and clinical variables identified a subset of patients who have heart failure without AF at a high risk of stroke.
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