Systematic review and meta-analysis of the growth and rupture rates of small abdominal aortic aneurysms: implications for surveillance intervals and their cost-effectiveness.

BACKGROUND: Small abdominal aortic aneurysms (AAAs; 3.0-5.4 cm in diameter) are usually asymptomatic and managed by regular ultrasound surveillance until they grow to a diameter threshold (commonly 5.5 cm) at which surgical intervention is considered. The choice of appropriate surveillance intervals is governed by the growth and rupture rates of small AAAs, as well as their relative cost-effectiveness. OBJECTIVES: The aim of this series of studies was to inform the evidence base for small AAA surveillance strategies. This was achieved by literature review, collation and analysis of individual patient data, a focus group and health economic modelling. DATA SOURCES: We undertook systematic literature reviews of growth rates and rupture rates of small AAAs. The databases MEDLINE, EMBASE on OvidSP, Cochrane Central Register of Controlled Trials 2009 Issue 4, ClinicalTrials.gov, and controlled-trials.com were searched from inception up until the end of 2009. We also obtained individual data on 15,475 patients from 18 surveillance studies. REVIEW METHODS: Systematic reviews of publications identified 15 studies providing small AAA growth rates, and 14 studies with small AAA rupture rates, up to December 2009 (later updated to September 2012). We developed statistical methods to analyse individual surveillance data, including the effects of patient characteristics, to inform the choice of surveillance intervals and provide inputs for health economic modelling. We updated an existing health economic model of AAA screening to address the cost-effectiveness of different surveillance intervals. RESULTS: In the literature reviews, the mean growth rate was 2.3 mm/year and the reported rupture rates varied between 0 and 1.6 ruptures per 100 person-years. Growth rates increased markedly with aneurysm diameter, but insufficient detail was available to guide surveillance intervals. Based on individual surveillance data, for each 0.5-cm increase in AAA diameter, growth rates increased by about 0.5 mm/year and rupture rates doubled. To control the risk of exceeding 5.5 cm to below 10% in men, on average a 7-year surveillance interval is sufficient for a 3.0-cm aneurysm, whereas an 8-month interval is necessary for a 5.0-cm aneurysm. To control the risk of rupture to below 1%, the corresponding estimated surveillance intervals are 9 years and 17 months. Average growth rates were higher in smokers (by 0.35 mm/year) and lower in patients with diabetes (by 0.51 mm/year). Rupture rates were almost fourfold higher in women than men, doubled in current smokers and increased with higher blood pressure. Increasing the surveillance interval from 1 to 2 years for the smallest aneurysms (3.0-4.4 cm) decreased costs and led to a positive net benefit. For the larger aneurysms (4.5-5.4 cm), increasing surveillance intervals from 3 to 6 months led to equivalent cost-effectiveness. LIMITATIONS: There were no clear reasons why the growth rates varied substantially between studies. Uniform diagnostic criteria for rupture were not available. The long-term cost-effectiveness results may be susceptible to the modelling assumptions made. CONCLUSIONS: Surveillance intervals of several years are clinically acceptable for men with AAAs in the range 3.0-4.0 cm. Intervals of around 1 year are suitable for 4.0-4.9-cm AAAs, whereas intervals of 6 months would be acceptable for 5.0-5.4-cm AAAs. These intervals are longer than those currently employed in the UK AAA screening programmes. Lengthening surveillance intervals for the smallest aneurysms was also shown to be cost-effective. Future work should focus on optimising surveillance intervals for women, studying whether or not the threshold for surgery should depend on patient characteristics, evaluating the usefulness of surveillance for those with aortic diameters of 2.5-2.9 cm, and developing interventions that may reduce the growth or rupture rates of small AAAs. FUNDING: The National Institute for Health Research Health Technology Assessment programme

Discrete Event Simulation for Decision Modeling in Health Care: Lessons from Abdominal Aortic Aneurysm Screening

Markov models are often used to evaluate the cost-effectiveness of new healthcare interventions but they are sometimes not flexible enough to allow accurate modeling or investigation of alternative scenarios and policies. A Markov model previously demonstrated that a one-off invitation to screening for abdominal aortic aneurysm (AAA) for men aged 65 y in the UK and subsequent follow-up of identified AAAs was likely to be highly cost-effective at thresholds commonly adopted in the UK (£20,000 to £30,000 per quality adjusted life-year). However, new evidence has emerged and the decision problem has evolved to include exploration of the circumstances under which AAA screening may be cost-effective, which the Markov model is not easily able to address. A new model to handle this more complex decision problem was needed, and the case of AAA screening thus provides an illustration of the relative merits of Markov models and discrete event simulation (DES) models. An individual-level DES model was built using the R programming language to reflect possible events and pathways of individuals invited to screening v. those not invited. The model was validated against key events and cost-effectiveness, as observed in a large, randomized trial. Different screening protocol scenarios were investigated to demonstrate the flexibility of the DES. The case of AAA screening highlights the benefits of DES, particularly in the context of screening studies

Murine and human myogenic cells identified by elevated aldehyde dehydrogenase activity: Implications for muscle regeneration and repair

Background: Despite the initial promise of myoblast transfer therapy to restore dystrophin in Duchenne muscular dystrophy patients, clinical efficacy has been limited, primarily by poor cell survival post-transplantation. Murine muscle derived stem cells (MDSCs) isolated from slowly adhering cells (SACs) via the preplate technique, induce greater muscle regeneration than murine myoblasts, primarily due to improved post-transplantation survival, which is conferred by their increased stress resistance capacity. Aldehyde dehydrogenase (ALDH) represents a family of enzymes with important morphogenic as well as oxidative damage mitigating roles and has been found to be a marker of stem cells in both normal and malignant tissue. In this study, we hypothesized that elevated ALDH levels could identify murine and human muscle derived cell (hMDC) progenitors, endowed with enhanced stress resistance and muscle regeneration capacity. Methodology/Principal Findings: Skeletal muscle progenitors were isolated from murine and human skeletal muscle by a modified preplate technique and unfractionated enzymatic digestion, respectively. ALDHhisubpopulations isolated by fluorescence activate cell sorting demonstrated increased proliferation and myogenic differentiation capacities compared to their ALDHlocounterparts when cultivated in oxidative and inflammatory stress media conditions. This behavior correlated with increased intracellular levels of reduced glutathione and superoxide dismutase. ALDHhimurine myoblasts were observed to exhibit an increased muscle regenerative potential compared to ALDHlomyoblasts, undergo multipotent differentiation (osteogenic and chondrogenic), and were found predominately in the SAC fraction, characteristics that are also observed in murine MDSCs. Likewise, human ALDHhihMDCs demonstrated superior muscle regenerative capacity compared to ALDHlohMDCs. Conclusions: The methodology of isolating myogenic cells on the basis of elevated ALDH activity yielded cells with increased stress resistance, a behavior that conferred increased regenerative capacity of dystrophic murine skeletal muscle. This result demonstrates the critical role of stress resistance in myogenic cell therapy as well as confirms the role of ALDH as a marker for rapid isolation of murine and human myogenic progenitors for cell therapy. © 2011 Vella et al

Limb amputations in fixed dystonia: a form of body integrity identity disorder?

Fixed dystonia is a disabling disorder mainly affecting young women who develop fixed abnormal limb postures and pain after apparently minor peripheral injury. There is continued debate regarding its pathophysiology and management. We report 5 cases of fixed dystonia in patients who sought amputation of the affected limb. We place these cases in the context of previous reports of patients with healthy limbs and patients with chronic regional pain syndrome who have sought amputation. Our cases, combined with recent data regarding disorders of mental rotation in patients with fixed dystonia, as well as previous data regarding body integrity identity disorder and amputations sought by patients with chronic regional pain syndrome, raise the possibility that patients with fixed dystonia might have a deficit in body schema that predisposes them to developing fixed dystonia and drives some to seek amputation. The outcome of amputation in fixed dystonia is invariably unfavorable

Memory fMRI predicts verbal memory decline after anterior temporal lobe resection.

To develop a clinically applicable memory functional MRI (fMRI) method of predicting postsurgical memory outcome in individual patients

Using multiple classifiers for predicting the risk of endovascular aortic aneurysm repair re-intervention through hybrid feature selection.

Feature selection is essential in medical area; however, its process becomes complicated with the presence of censoring which is the unique character of survival analysis. Most survival feature selection methods are based on Cox's proportional hazard model, though machine learning classifiers are preferred. They are less employed in survival analysis due to censoring which prevents them from directly being used to survival data. Among the few work that employed machine learning classifiers, partial logistic artificial neural network with auto-relevance determination is a well-known method that deals with censoring and perform feature selection for survival data. However, it depends on data replication to handle censoring which leads to unbalanced and biased prediction results especially in highly censored data. Other methods cannot deal with high censoring. Therefore, in this article, a new hybrid feature selection method is proposed which presents a solution to high level censoring. It combines support vector machine, neural network, and K-nearest neighbor classifiers using simple majority voting and a new weighted majority voting method based on survival metric to construct a multiple classifier system. The new hybrid feature selection process uses multiple classifier system as a wrapper method and merges it with iterated feature ranking filter method to further reduce features. Two endovascular aortic repair datasets containing 91% censored patients collected from two centers were used to construct a multicenter study to evaluate the performance of the proposed approach. The results showed the proposed technique outperformed individual classifiers and variable selection methods based on Cox's model such as Akaike and Bayesian information criterions and least absolute shrinkage and selector operator in p values of the log-rank test, sensitivity, and concordance index. This indicates that the proposed classifier is more powerful in correctly predicting the risk of re-intervention enabling doctor in selecting patients' future follow-up plan

Vacuolating cytotoxin (vacA) alleles of Helicobacter pylori comprise two geographically widespread types, m1 and m2, and have evolved through limited recombination

Vacuolating cytotoxin (vacA) alleles of Helicobacter pylori vary, particularly in their mid region (which may be type m1 or m2) and their signal peptide coding region (type s1 or s2). We investigated nucleotide diversity among vacA alleles in strains from several locales in Asia, South America, and the USA. Phylogenetic analysis of vacA mid region sequences from 18 strains validated the division into two main groups (m1 and m2) and showed further significant divisions within these groups. Informative site analysis demonstrated one example of recombination between m1 and m2 alleles, and several examples of recombination among alleles within these groups. Recombination was not sufficiently extensive to destroy phylogenetic structure entirely. Synonymous nucleotide substitution rates were markedly different between regions of vacA, suggesting different evolutionary divergence times and implying horizontal transfer of genetic elements within vacA. Non-synonymous/synonymous rate ratios were greater between m1 and m2 sequences than among m1 sequences, consistent with m1 and m2 alleles encoding functions fitting strains for slightly different ecological niches

Value of risk scores in the decision to palliate patients withruptured abdominal aortic aneurysm

Background: The aim of this study was to develop a 48‐h mortality risk score, which included morphology data, for patients with ruptured abdominal aortic aneurysm presenting to an emergency department, and to assess its predictive accuracy and clinical effectiveness in triaging patients to immediate aneurysm repair, transfer or palliative care. Methods: Data from patients in the IMPROVE (Immediate Management of the Patient With Ruptured Aneurysm: Open Versus Endovascular Repair) randomized trial were used to develop the risk score. Variables considered included age, sex, haemodynamic markers and aortic morphology. Backwards selection was used to identify relevant predictors. Predictive performance was assessed using calibration plots and the C‐statistic. Validation of the newly developed and other previously published scores was conducted in four external populations. The net benefit of treating patients based on a risk threshold compared with treating none was quantified. Results: Data from 536 patients in the IMPROVE trial were included. The final variables retained were age, sex, haemoglobin level, serum creatinine level, systolic BP, aortic neck length and angle, and acute myocardial ischaemia. The discrimination of the score for 48‐h mortality in the IMPROVE data was reasonable (C‐statistic 0·710, 95 per cent c.i. 0·659 to 0·760), but varied in external populations (from 0·652 to 0·761). The new score outperformed other published risk scores in some, but not all, populations. An 8 (95 per cent c.i. 5 to 11) per cent improvement in the C‐statistic was estimated compared with using age alone. Conclusion: The assessed risk scores did not have sufficient accuracy to enable potentially life‐saving decisions to be made regarding intervention. Focus should therefore shift to offering repair to more patients and reducing non‐intervention rates, while respecting the wishes of the patient and family

FooPar: A Functional Object Oriented Parallel Framework in Scala

We present FooPar, an extension for highly efficient Parallel Computing in the multi-paradigm programming language Scala. Scala offers concise and clean syntax and integrates functional programming features. Our framework FooPar combines these features with parallel computing techniques. FooPar is designed modular and supports easy access to different communication backends for distributed memory architectures as well as high performance math libraries. In this article we use it to parallelize matrix matrix multiplication and show its scalability by a isoefficiency analysis. In addition, results based on a empirical analysis on two supercomputers are given. We achieve close-to-optimal performance wrt. theoretical peak performance. Based on this result we conclude that FooPar allows to fully access Scala's design features without suffering from performance drops when compared to implementations purely based on C and MPI