Factors determining disease duration in Alzheimer's disease:a postmortem study of 103 cases using the Kaplan-Meier estimator and Cox regression

Factors associated with duration of dementia in a consecutive series of 103 Alzheimer's disease (AD) cases were studied using the Kaplan-Meier estimator and Cox regression analysis (proportional hazard model). Mean disease duration was 7.1 years (range: 6 weeks-30 years, standard deviation = 5.18); 25% of cases died within four years, 50% within 6.9 years, and 75% within 10 years. Familial AD cases (FAD) had a longer duration than sporadic cases (SAD), especially cases linked to presenilin (PSEN) genes. No significant differences in duration were associated with age, sex, or apolipoprotein E (Apo E) genotype. Duration was reduced in cases with arterial hypertension. Cox regression analysis suggested longer duration was associated with an earlier disease onset and increased senile plaque (SP) and neurofibrillary tangle (NFT) pathology in the orbital gyrus (OrG), CA1 sector of the hippocampus, and nucleus basalis of Meynert (NBM). The data suggest shorter disease duration in SAD and in cases with hypertensive comorbidity. In addition, degree of neuropathology did not influence survival, but spread of SP/NFT pathology into the frontal lobe, hippocampus, and basal forebrain was associated with longer disease duration. © 2014 R. A. Armstrong.

Bayesian neural network approach for determining the risk of re-intervention after endovascular aortic aneurysm repair

This article proposes a Bayesian neural network approach to determine the risk of re-intervention after endovascular aortic aneurysm repair surgery. The target of proposed technique is to determine which patients have high chance to re-intervention (high-risk patients) and which are not (low-risk patients) after 5 years of the surgery. Two censored datasets relating to the clinical conditions of aortic aneurysms have been collected from two different vascular centers in the United Kingdom. A Bayesian network was first employed to solve the censoring issue in the datasets. Then, a back propagation neural network model was built using the uncensored data of the first center to predict re-intervention on the second center and classify the patients into high-risk and low-risk groups. Kaplan-Meier curves were plotted for each group of patients separately to show whether there is a significant difference between the two risk groups. Finally, the logrank test was applied to determine whether the neural network model was capable of predicting and distinguishing between the two risk groups. The results show that the Bayesian network used for uncensoring the data has improved the performance of the neural networks that were built for the two centers separately. More importantly, the neural network that was trained with uncensored data of the first center was able to predict and discriminate between groups of low risk and high risk of re-intervention after 5 years of endovascular aortic aneurysm surgery at center 2 (p = 0.0037 in the logrank test).

Lack of effect of aspirin in primary CV prevention in type 2 diabetic patients with nephropathy:results from 8 years follow-up of NID-2 study

The risk-to-benefit ratio for the use of low dose of aspirin in primary cardiovascular (CV) prevention in patients with diabetes mellitus remains to be clarified. We assessed the effect of aspirin on risk of CV events in type 2 diabetic patients with nephropathy, in order to verify the usefulness of Guidelines in clinical practice. We carried out a prospective multicentric study in 564 patients with type 2 diabetic nephropathy free of CV disease attending outpatient diabetes clinics. A total of 242 patients received antiplatelet treatment with aspirin 100 mg/day (group A), and 322 were not treated with antiplatelet drugs (group B). Primary end point was the occurrence of total major adverse cardio-vascular events (MACE). Secondary end points were the relative occurrence of fatal MACE. The average follow-up was 8 years. Total MACE occurred in 49 patients from group A and in 52 patients from group B. Fatal MACE occurred in 22 patients from group A and in 20 from group B; nonfatal MACE occurred in 27 patients from group A and in 32 patients from group B. Kaplan-Meier analysis did not show a statistically significant difference of cumulative MACE between the two groups. A not statistically significant difference in the incidence of both fatal (p = 0.225) and nonfatal CV events (p = 0.573) between the two groups was observed. These results were confirmed after adjustment for confounders (HR for MACE 1.11, 95 % CI 0.91-1.35). These findings suggest that low dose of aspirin is ineffective in primary prevention for patients with nephropathy. © 2014 Springer-Verlag Italia.

An artificial neural network stratifies the risks of reintervention and mortality after endovascular aneurysm repair:a retrospective observational study

Background Lifelong surveillance after endovascular repair (EVAR) of abdominal aortic aneurysms (AAA) is considered mandatory to detect potentially life-threatening endograft complications. A minority of patients require reintervention but cannot be predictively identified by existing methods. This study aimed to improve the prediction of endograft complications and mortality, through the application of machine-learning techniques. Methods Patients undergoing EVAR at 2 centres were studied from 2004-2010. Pre-operative aneurysm morphology was quantified and endograft complications were recorded up to 5 years following surgery. An artificial neural networks (ANN) approach was used to predict whether patients would be at low- or high-risk of endograft complications (aortic/limb) or mortality. Centre 1 data were used for training and centre 2 data for validation. ANN performance was assessed by Kaplan-Meier analysis to compare the incidence of aortic complications, limb complications, and mortality; in patients predicted to be low-risk, versus those predicted to be high-risk. Results 761 patients aged 75 +/- 7 years underwent EVAR. Mean follow-up was 36+/- 20 months. An ANN was created from morphological features including angulation/length/areas/diameters/ volume/tortuosity of the aneurysm neck/sac/iliac segments. ANN models predicted endograft complications and mortality with excellent discrimination between a low-risk and high-risk group. In external validation, the 5-year rates of freedom from aortic complications, limb complications and mortality were 95.9% vs 67.9%; 99.3% vs 92.0%; and 87.9% vs 79.3% respectively (p0.001) Conclusion This study presents ANN models that stratify the 5-year risk of endograft complications or mortality using routinely available pre-operative data.

A Bayesian neural network algorithm identifies patients in whom post-EVAR surveillance may be unnecessary

Lifelong surveillance is not cost-effective after endovascular aneurysm repair (EVAR), but is required to detect aortic complications which are fatal if untreated (type 1/3 endoleak, sac expansion, device migration). Aneurysm morphology determines the probability of aortic complications and therefore the need for surveillance, but existing analyses have proven incapable of identifying patients at sufficiently low risk to justify abandoning surveillance. This study aimed to improve the prediction of aortic complications, through the application of machine-learning techniques. Patients undergoing EVAR at 2 centres were studied from 2004–2010. Aneurysm morphology had previously been studied to derive the SGVI Score for predicting aortic complications. Bayesian Neural Networks were designed using the same data, to dichotomise patients into groups at low- or high-risk of aortic complications. Network training was performed only on patients treated at centre 1. External validation was performed by assessing network performance independently of network training, on patients treated at centre 2. Discrimination was assessed by Kaplan-Meier analysis to compare aortic complications in predicted low-risk versus predicted high-risk patients. 761 patients aged 75 +/− 7 years underwent EVAR in 2 centres. Mean follow-up was 36+/− 20 months. Neural networks were created incorporating neck angu- lation/length/diameter/volume; AAA diameter/area/volume/length/tortuosity; and common iliac tortuosity/diameter. A 19-feature network predicted aor- tic complications with excellent discrimination and external validation (5-year freedom from aortic complications in predicted low-risk vs predicted high-risk patients: 97.9% vs. 63%; p < 0.0001). A Bayesian Neural-Network algorithm can identify patients in whom it may be safe to abandon surveillance after EVAR. This proposal requires prospective study.

Survival in the pre-senile dementia frontotemporal lobar degeneration with TDP-43 proteinopathy:effects of genetic, demographic and neuropathological variables

Factors associated with survival were studied in 84 neuropathologically documented cases of the pre-senile dementia frontotemporal dementia lobar degeneration (FTLD) with transactive response (TAR) DNA-binding protein of 43 kDa (TDP-43) proteinopathy (FTLD-TDP). Kaplan-Meier survival analysis estimated mean survival as 7.9 years (range: 1-19 years, SD = 4.64). Familial and sporadic cases exhibited similar survival, including progranulin (GRN) gene mutation cases. No significant differences in survival were associated with sex, disease onset, Braak disease stage, or disease subtype, but higher survival was associated with lower post-mortem brain weight. Survival was significantly reduced in cases with associated motor neuron disease (FTLD-MND) but increased with Alzheimer's disease (AD) or hippocampal sclerosis (HS) co-morbidity. Cox regression analysis suggested that reduced survival was associated with increased densities of neuronal cytoplasmic inclusions (NCI) while increased survival was associated with greater densities of enlarged neurons (EN) in the frontal and temporal lobes. The data suggest that: (1) survival in FTLD-TDP is more prolonged than typical in pre-senile dementia but shorter than some clinical subtypes such as the semantic variant of primary progressive aphasia (svPPA), (2) MND co-morbidity predicts poor survival, and (3) NCI may develop early and EN later in the disease. The data have implications for both neuropathological characterization and subtyping of FTLD-TDP.

Moderate-intensity statin therapy seems ineffective in primary cardiovascular prevention in patients with type 2 diabetes complicated by nephropathy:a multicenter prospective 8 years follow up study

Background: Although numerous studies and metanalysis have shown the beneficial effect of statin therapy in CVD secondary prevention, there is still controversy such the use of statins for primary CVD prevention in patients with DM. The purpose of this study was to evaluate the occurrence of total major adverse cardio-vascular events (MACE) in a cohort of patients with type 2 diabetes complicated by nephropathy treated with statins, in order to verify real life effect of statin on CVD primary prevention. Methods: We conducted an observational prospective multicenter study on 564 patients with type 2 diabetic nephropathy free of cardiovascular disease attending 21 national outpatient diabetes clinics and followed them up for 8 years. 169 of them were treated with statins (group A) while 395 were not on statins (group B). Results: Notably, none of the patients was treated with a high-intensity statin therapy according to last ADA position statement. Total MACE occurred in 32 patients from group A and in 68 patients from group B. Fatal MACE occurred in 13 patients from group A and in 30 from group B; nonfatal MACE occurred in 19 patients from group A and in 38 patients from group B. The analysis of the Kaplan-Meier survival curves showed a not statistically significant difference in the incidence of total (p 0.758), fatal (p 0.474) and nonfatal (p 0.812) MACE between the two groups. HbA1c only showed a significant difference in the incidence of MACE between the two groups (HR 1.201, CI 1.041-1.387, p 0.012). Conclusions: These findings suggest that, in a real clinical setting, moderate-intensity statin treatment is ineffective in cardiovascular primary prevention for patients with diabetic nephropathy.