Intracranial Aneurysms: Wall Motion Analysis for Prediction of Rupture.

Intracranial aneurysms are a common pathologic condition with a potential severe complication: rupture. Effective treatment options exist, neurosurgical clipping and endovascular techniques, but guidelines for treatment are unclear and focus mainly on patient age, aneurysm size, and localization. New criteria to define the risk of rupture are needed to refine these guidelines. One potential candidate is aneurysm wall motion, known to be associated with rupture but difficult to detect and quantify. We review what is known about the association between aneurysm wall motion and rupture, which structural changes may explain wall motion patterns, and available imaging techniques able to analyze wall motion.

Validation of and comparison between a semidistributed rainfall-runoff hydrological model (PREVAH) and a spatially distributed snow-evolution model (SnowModel) for snow cover prediction in mountain ecosystems

Snow cover is an important control in mountain environments and a shift of the snow-free period triggered by climate warming can strongly impact ecosystem dynamics. Changing snow patterns can have severe effects on alpine plant distribution and diversity. It thus becomes urgent to provide spatially explicit assessments of snow cover changes that can be incorporated into correlative or empirical species distribution models (SDMs). Here, we provide for the first time a with a lower overestimation comparison of two physically based snow distribution models (PREVAH and SnowModel) to produce snow cover maps (SCMs) at a fine spatial resolution in a mountain landscape in Austria. SCMs have been evaluated with SPOT-HRVIR images and predictions of snow water equivalent from the two models with ground measurements. Finally, SCMs of the two models have been compared under a climate warming scenario for the end of the century. The predictive performances of PREVAH and SnowModel were similar when validated with the SPOT images. However, the tendency to overestimate snow cover was slightly lower with SnowModel during the accumulation period, whereas it was lower with PREVAH during the melting period. The rate of true positives during the melting period was two times higher on average with SnowModel with a lower overestimation of snow water equivalent. Our results allow for recommending the use of SnowModel in SDMs because it better captures persisting snow patches at the end of the snow season, which is important when modelling the response of species to long-lasting snow cover and evaluating whether they might survive under climate change.

Prediction of Complications After Pancreaticoduodenectomy: Validation of a Postoperative Complication Score.

OBJECTIVES: Pancreatic surgery remains associated with important morbidity. Efforts are most commonly concentrated on decreasing postoperative morbidity, but early detection of patients at risk could be another valuable strategy. A simple prognostic score has recently been published. This study aimed to validate this score and discuss possible clinical implications. METHODS: From 2000 to 2012, 245 patients underwent a pancreaticoduodenectomy. Complications were graded according to the Dindo-Clavien Classification. The Braga score is based on American Society of Anesthesiologists score, pancreatic texture, Wirsung duct diameter, and blood loss. An overall risk score (0-15) can be calculated for each patient. Score discriminant power was calculated using a receiver operating characteristic curve. RESULTS: Major complications occurred in 31% of patients compared with 17% in Braga's data. Pancreatic texture and blood loss were independently statistically significant for increased morbidity. Areas under the curve were 0.95 and 0.99 for 4-risk categories and for individual scores, respectively. CONCLUSIONS: The Braga score discriminates well between minor and major complications. Our validation suggests that it can be used as a prognostic tool for major complications after pancreaticoduodenectomy. The clinical implications, that is, whether postoperative treatment strategies should be adapted according to the patient's individual risk, remain to be elucidated.

Prediction in transformed images

The study is related to lossless compression of greyscale images. The goal of the study was to combine two techniques of lossless image compression, i.e. Integer Wavelet Transform and Differential Pulse Code Modulation to attain better compression ratio. This is an experimental study, where we implemented Integer Wavelet Transform, Differential Pulse Code Modulation and an optimized predictor model using Genetic Algorithm. This study gives encouraging results for greyscale images. We achieved a better compression ration in term of entropy for experiments involving quadrant of transformed image and using optimized predictor coefficients from Genetic Algorithm. In an other set of experiments involving whole image, results are encouraging and opens up many areas for further research work like implementing Integer Wavelet Transform on multiple levels and finding optimized predictor at local levels.

IFRS-standardeihin siirtymisen vaikutus aineettoman omaisuuden käsittelyyn ja tasearvoon suomalaisissa julkisesti noteeratuissa yrityksissä

Tutkielmassa tarkastellaan kansainvälisiin tilinpäätösstandardeihin (IFRS-standardit) siirtymisen vaikutusta aineettoman omaisuuden tasearvoon suomalaisissa julkisesti noteeratuissa yrityksissä, jotka aiemmin tekivät tilinpäätöksensä suomalaista kirjanpitolakia ja tilinpäätöskäytäntöä noudattaen. Työssä käsitellään aineettoman omaisuuden määritelmät, tilinpäätöksen laadintaperiaatteet, arvostus- ja jaksotuskäytönnöt molempien säännöstöjen näkökulmasta, jotta IFRS-standardeihin siirtymisen vaikutusta taseen arvoon voidaan arvioida. Tutkielma on luonteeltaan kvalitatiivinen, jossa materiaalina on käytetty IFRS-standardistoa, kirjanpitolakia sekä muita tilinpäätöskäytäntöjä määrittävää aineistoa. Muutoksen vaikutuksia taseen arvoon tutkittiin perehtymällä yritysten tilinpäätösmateriaaliin. Työntuloksissa esitellään kuinka tilinpäätöskäytännöstä toiseen siirtyminen vaikutti aineettomien hyödykkeiden sekä liikearvon tase-eriin työssä havainnoiduissa yrityksissä.

Mergers and difference-in-difference estimator : why firms do not increase prices?

Difference-in-Difference (DiD) methods are being increasingly used to analyze the impact of mergers on pricing and other market equilibrium outcomes. Using evidence from an exogenous merger between two retail gasoline companies in a specific market in Spain, this paper shows how concentration did not lead to a price increase. In fact, the conjectural variation model concludes that the existence of a collusive agreement before and after the merger accounts for this result, rather than the existence of efficient gains. This result may explain empirical evidence reported in the literature according to which mergers between firms do not have significant effects on prices.

The difference of disease perception by juvenile idiopathic arthritis patients and their parents : analysis of the JAMAR questionnaire.

BACKGROUND: The JAMAR (Juvenile Arthritis Multidimensional Assessment Report) has been developed to evaluate the perception of the patient and his parents on different items: well-being, pain, functional status, quality of life, disease activity, disease course, side effects of medication, therapeutic compliance and satisfaction with illness outcome. Our aim was to compare disease's perception by JIA patients and their parents. METHODS: We included into the study 100 consecutive patients over 7 years of age. We asked both parent and child to complete the JAMAR questionnaire. For each patient we recorded demographic and disease related data. We examined the level of disagreement between children and parents for the quantitative items of the JAMAR: VAS Pain, VAS Disease Activity, VAS Well Being, Juvenile Arthritis Functional Score, HRQoL. Then we looked for a relation between discordance-rate and demographic and clinical variables. RESULTS: Children and parents' median scores for all five items were similar. Individual dyads agreement was low, with a large amount of pairs (80) discordant for at least one item. We found higher MD VAS and JADAS in more discordant dyads, suggesting that when the disease is more active discordance between child and parent increase. CONCLUSION: The JAMAR questionnaire is an important tool that helps clinicians to detect divergent child and parent's disease perceptions. It is essential that both patients and parents fill the JAMAR questionnaire for a complete clinical and psychosocial evaluation.

Prediction of the economic cost of individual long-term care in the Spanish population

Pensions together with savings and investments during active life are key elements of retirement planning. Motivation for personal choices about the standard of living, bequest and the replacement ratio of pension with respect to last salary income must be considered. This research contributes to the financial planning by helping to quantify long-term care economic needs. We estimate life expectancy from retirement age onwards. The economic cost of care per unit of service is linked to the expected time of needed care and the intensity of required services. The expected individual cost of long-term care from an onset of dependence is estimated separately for men and women. Assumptions on the mortality of the dependent people compared to the general population are introduced. Parameters defining eligibility for various forms of coverage by the universal public social care of the welfare system are addressed. The impact of the intensity of social services on individual predictions is assessed, and a partial coverage by standard private insurance products is also explored. Data were collected by the Spanish Institute of Statistics in two surveys conducted on the general Spanish population in 1999 and in 2008. Official mortality records and life table trends were used to create realistic scenarios for longevity. We find empirical evidence that the public long-term care system in Spain effectively mitigates the risk of incurring huge lifetime costs. We also find that the most vulnerable categories are citizens with moderate disabilities that do not qualify to obtain public social care support. In the Spanish case, the trends between 1999 and 2008 need to be further explored.

Association between parental history and genetic risk scores for coronary heart disease prediction: The population-based CoLaus study.

BACKGROUND AND AIMS: Parental history (PH) and genetic risk scores (GRSs) are separately associated with coronary heart disease (CHD), but evidence regarding their combined effects is lacking. We aimed to evaluate the joint associations and predictive ability of PH and GRSs for incident CHD. METHODS: Data for 4283 Caucasians were obtained from the population-based CoLaus Study, over median follow-up time of 5.6 years. CHD was defined as incident myocardial infarction, angina, percutaneous coronary revascularization or bypass grafting. Single nucleotide polymorphisms for CHD identified by genome-wide association studies were used to construct unweighted and weighted versions of three GRSs, comprising of 38, 53 and 153 SNPs respectively. RESULTS: PH was associated with higher values of all weighted GRSs. After adjustment for age, sex, smoking, diabetes, systolic blood pressure, low and high density lipoprotein cholesterol, PH was significantly associated with CHD [HR 2.61, 95% CI (1.47-4.66)] and further adjustment for GRSs did not change this estimate. Similarly, one standard deviation change of the weighted 153-SNPs GRS was significantly associated with CHD [HR 1.50, 95% CI (1.26-1.80)] and remained so, after further adjustment for PH. The weighted, 153-SNPs GRS, but not PH, modestly improved discrimination [(C-index improvement, 0.016), p = 0.048] and reclassification [(NRI improvement, 8.6%), p = 0.027] beyond cardiovascular risk factors. After including both the GRS and PH, model performance improved further [(C-index improvement, 0.022), p = 0.006]. CONCLUSION: After adjustment for cardiovascular risk factors, PH and a weighted, polygenic GRS were jointly associated with CHD and provided additive information for coronary events prediction.

Cerebral oximetry and return of spontaneous circulation after cardiac arrest: A systematic review and meta-analysis.

AIM: The prediction of return of spontaneous circulation (ROSC) during resuscitation of patients suffering of cardiac arrest (CA) is particularly challenging. Regional cerebral oxygen saturation (rSO2) monitoring through near-infrared spectrometry is feasible during CA and could provide guidance during resuscitation. METHODS: We conducted a systematic review and meta-analysis on the value of rSO2 in predicting ROSC both after in-hospital (IH) or out-of-hospital (OH) CA. Our search included MEDLINE (PubMed) and EMBASE, from inception until April 4th, 2015. We included studies reporting values of rSO2 at the beginning of and/or during resuscitation, according to the achievement of ROSC. RESULTS: A total of nine studies with 315 patients (119 achieving ROSC, 37.7%) were included in the meta-analysis. The majority of those patients had an OHCA (n=225, 71.5%; IHCA: n=90, 28.5%). There was a significant association between higher values of rSO2 and ROSC, both in the overall calculation (standardized mean difference, SMD -1.03; 95%CI -1.39,-0.67; p<0.001), and in the subgroups analyses (rSO2 at the beginning of resuscitation: SMD -0.79; 95%CI -1.29,-0.30; p=0.002; averaged rSO2 value during resuscitation: SMD -1.28; 95%CI -1.74,-0.83; p<0.001). CONCLUSIONS: Higher initial and average regional cerebral oxygen saturation values are both associated with greater chances of achieving ROSC in patients suffering of CA. A note of caution should be made in interpreting these results due to the small number of patients and the heterogeneity in study design: larger studies are needed to clinically validate cut-offs for guiding cardiopulmonary resuscitation.

Predicting recurrence after unprovoked venous thromboembolism: prospective validation of the updated Vienna Prediction Model.

The updated Vienna Prediction Model for estimating recurrence risk after an unprovoked venous thromboembolism (VTE) has been developed to identify individuals at low risk for VTE recurrence in whom anticoagulation (AC) therapy may be stopped after 3 months. We externally validated the accuracy of the model to predict recurrent VTE in a prospective multicenter cohort of 156 patients aged ≥65 years with acute symptomatic unprovoked VTE who had received 3 to 12 months of AC. Patients with a predicted 12-month risk within the lowest quartile based on the updated Vienna Prediction Model were classified as low risk. The risk of recurrent VTE did not differ between low- vs higher-risk patients at 12 months (13% vs 10%; P = .77) and 24 months (15% vs 17%; P = 1.0). The area under the receiver operating characteristic curve for predicting VTE recurrence was 0.39 (95% confidence interval [CI], 0.25-0.52) at 12 months and 0.43 (95% CI, 0.31-0.54) at 24 months. In conclusion, in elderly patients with unprovoked VTE who have stopped AC, the updated Vienna Prediction Model does not discriminate between patients who develop recurrent VTE and those who do not. This study was registered at www.clinicaltrials.gov as #NCT00973596.

Prediction of preeclampsia by means of Doppler flowmetry of uterine artery and flow-mediated dilation of brachial artery

Objective To evaluate the association of Doppler of uterine artery and flow-mediated dilation of brachial artery (FMD) in the assessment of placental perfusion and endothelial function to predict preeclampsia. Materials and Methods A total of 91 patients considered as at risk for developing preeclampsia were recruited at the prenatal unit of the authors' institution. All the patients underwent FMD and Doppler of uterine arteries between their 24th and 28th gestational weeks. Calculations of sensitivity and specificity for both isolated and associated methods were performed. Results Nineteen out of the 91 patients developed preeclampsia, while the rest remained normotensive. Doppler flowmetry of uterine arteries with presence of bilateral protodiastolic notch had sensitivity of 63.1% and specificity of 87.5% for the prediction of preeclampsia. Considering a cutoff value of 6.5%, FMD showed sensitivity of 84.2% and specificity of 73.6%. In a parallel analysis, as the two methods were associated, sensitivity was 94.2% and specificity, 64.4%. Conclusion The association of Doppler study of uterine arteries and FMD has proved to be an interesting clinical strategy for the prediction of preeclampsia, which may represent a positive impact on prenatal care of patients considered as at high-risk for developing such a condition.

Equating accelerometer estimates among youth: The Rosetta Stone 2.

OBJECTIVES: Different accelerometer cutpoints used by different researchers often yields vastly different estimates of moderate-to-vigorous intensity physical activity (MVPA). This is recognized as cutpoint non-equivalence (CNE), which reduces the ability to accurately compare youth MVPA across studies. The objective of this research is to develop a cutpoint conversion system that standardizes minutes of MVPA for six different sets of published cutpoints. DESIGN: Secondary data analysis. METHODS: Data from the International Children's Accelerometer Database (ICAD; Spring 2014) consisting of 43,112 Actigraph accelerometer data files from 21 worldwide studies (children 3-18 years, 61.5% female) were used to develop prediction equations for six sets of published cutpoints. Linear and non-linear modeling, using a leave one out cross-validation technique, was employed to develop equations to convert MVPA from one set of cutpoints into another. Bland Altman plots illustrate the agreement between actual MVPA and predicted MVPA values. RESULTS: Across the total sample, mean MVPA ranged from 29.7MVPAmind(-1) (Puyau) to 126.1MVPAmind(-1) (Freedson 3 METs). Across conversion equations, median absolute percent error was 12.6% (range: 1.3 to 30.1) and the proportion of variance explained ranged from 66.7% to 99.8%. Mean difference for the best performing prediction equation (VC from EV) was -0.110mind(-1) (limits of agreement (LOA), -2.623 to 2.402). The mean difference for the worst performing prediction equation (FR3 from PY) was 34.76mind(-1) (LOA, -60.392 to 129.910). CONCLUSIONS: For six different sets of published cutpoints, the use of this equating system can assist individuals attempting to synthesize the growing body of literature on Actigraph, accelerometry-derived MVPA.