Tactile sensibility of single-tooth implants and natural teeth

AIM: The purpose of this randomized split-mouth clinical trial was to determine the active tactile sensibility between single-tooth implants and opposing natural teeth and to compare it with the tactile sensibility of pairs of natural teeth on the contralateral side in the same mouth (intraindividual comparison). MATERIAL AND METHODS: The hypothesis was that the active tactile sensibilities of the implant side and control side are equivalent. Sixty two subjects (n=36 from Bonn, n=26 from Bern) with single-tooth implants (22 anterior and 40 posterior dental implants) were asked to bite on narrow copper foil strips varying in thickness (5-200 microm) and to decide whether or not they were able to identify a foreign body between their teeth. Active tactile sensibility was defined as the 50% threshold of correct answers estimated by means of the Weibull distribution. RESULTS: The results obtained for the interocclusal perception sensibility differed between subjects far more than they differed between natural teeth and implants in the same individual [implant/natural tooth: 16.7+/-11.3 microm (0.6-53.1 microm); natural tooth/natural tooth: 14.3+/-10.6 microm (0.5-68.2 microm)]. The intraindividual differences only amounted to a mean value of 2.4+/-9.4 microm (-15.1 to 27.5 microm). The result of our statistical calculations showed that the active tactile sensibility of single-tooth implants, both in the anterior and posterior region of the mouth, in combination with a natural opposing tooth is similar to that of pairs of opposing natural teeth (double t-test, equivalence margin: +/-8 microm, P<0.001, power >80%). Hence, the implants could be integrated in the stomatognathic control circuit.

Prognostic importance of anaemia in HIV type-1-infected patients starting antiretroviral therapy: collaborative analysis of prospective cohort studies

BACKGROUND: In HIV type-1-infected patients starting highly active antiretroviral therapy (HAART), the prognostic value of haemoglobin when starting HAART, and of changes in haemoglobin levels, are not well defined. METHODS: We combined data from 10 prospective studies of 12,100 previously untreated individuals (25% women). A total of 4,222 patients (35%) were anaemic: 131 patients (1.1%) had severe (<8.0 g/dl), 1,120 (9%) had moderate (male 8.0-<11.0 g/dl and female 8.0- < 10.0 g/dl) and 2,971 (25%) had mild (male 11.0- < 13.0 g/ dl and female 10.0- < 12.0 g/dl) anaemia. We separately analysed progression to AIDS or death from baseline and from 6 months using Weibull models, adjusting for CD4+ T-cell count, age, sex and other variables. RESULTS: During 48,420 person-years of follow-up 1,448 patients developed at least one AIDS event and 857 patients died. Anaemia at baseline was independently associated with higher mortality: the adjusted hazard ratio (95% confidence interval) for mild anaemia was 1.42 (1.17-1.73), for moderate anaemia 2.56 (2.07-3.18) and for severe anaemia 5.26 (3.55-7.81). Corresponding figures for progression to AIDS were 1.60 (1.37-1.86), 2.00 (1.66-2.40) and 2.24 (1.46-3.42). At 6 months the prevalence of anaemia declined to 26%. Baseline anaemia continued to predict mortality (and to a lesser extent progression to AIDS) in patients with normal haemoglobin or mild anaemia at 6 months. CONCLUSIONS: Anaemia at the start of HAART is an important factor for short- and long-term prognosis, including in patients whose haemoglobin levels improved or normalized during the first 6 months of HAART.

EVALUATING INFRASTRUCTURE PERFORMANCE TO ASSIST FACILITY MANAGEMENT TOWARD SUSTAINABLE SYSTEMS

Civil infrastructure provides essential services for the development of both society and economy. It is very important to manage systems efficiently to ensure sound performance. However, there are challenges in information extraction from available data, which also necessitates the establishment of methodologies and frameworks to assist stakeholders in the decision making process. This research proposes methodologies to evaluate systems performance by maximizing the use of available information, in an effort to build and maintain sustainable systems. Under the guidance of problem formulation from a holistic view proposed by Mukherjee and Muga, this research specifically investigates problem solving methods that measure and analyze metrics to support decision making. Failures are inevitable in system management. A methodology is developed to describe arrival pattern of failures in order to assist engineers in failure rescues and budget prioritization especially when funding is limited. It reveals that blockage arrivals are not totally random. Smaller meaningful subsets show good random behavior. Additional overtime failure rate is analyzed by applying existing reliability models and non-parametric approaches. A scheme is further proposed to depict rates over the lifetime of a given facility system. Further analysis of sub-data sets is also performed with the discussion of context reduction. Infrastructure condition is another important indicator of systems performance. The challenges in predicting facility condition are the transition probability estimates and model sensitivity analysis. Methods are proposed to estimate transition probabilities by investigating long term behavior of the model and the relationship between transition rates and probabilities. To integrate heterogeneities, model sensitivity is performed for the application of non-homogeneous Markov chains model. Scenarios are investigated by assuming transition probabilities follow a Weibull regressed function and fall within an interval estimate. For each scenario, multiple cases are simulated using a Monte Carlo simulation. Results show that variations on the outputs are sensitive to the probability regression. While for the interval estimate, outputs have similar variations to the inputs. Life cycle cost analysis and life cycle assessment of a sewer system are performed comparing three different pipe types, which are reinforced concrete pipe (RCP) and non-reinforced concrete pipe (NRCP), and vitrified clay pipe (VCP). Life cycle cost analysis is performed for material extraction, construction and rehabilitation phases. In the rehabilitation phase, Markov chains model is applied in the support of rehabilitation strategy. In the life cycle assessment, the Economic Input-Output Life Cycle Assessment (EIO-LCA) tools are used in estimating environmental emissions for all three phases. Emissions are then compared quantitatively among alternatives to support decision making.

A study of acoustic emission technique for concrete damage detection

The Acoustic emission (AE) technique, as one of non-intrusive and nondestructive evaluation techniques, acquires and analyzes the signals emitting from deformation or fracture of materials/structures under service loading. The AE technique has been successfully applied in damage detection in various materials such as metal, alloy, concrete, polymers and other composite materials. In this study, the AE technique was used for detecting crack behavior within concrete specimens under mechanical and environmental frost loadings. The instrumentations of the AE system used in this study include a low-frequency AE sensor, a computer-based data acquisition device and a preamplifier linking the AE sensor and the data acquisition device. The AE system purchased from Mistras Group was used in this study. The AE technique was applied to detect damage with the following laboratory tests: the pencil lead test, the mechanical three-point single-edge notched beam bending (SEB) test, and the freeze-thaw damage test. Firstly, the pencil lead test was conducted to verify the attenuation phenomenon of AE signals through concrete materials. The value of attenuation was also quantified. Also, the obtained signals indicated that this AE system was properly setup to detect damage in concrete. Secondly, the SEB test with lab-prepared concrete beam was conducted by employing Mechanical Testing System (MTS) and AE system. The cumulative AE events and the measured loading curves, which both used the crack-tip open displacement (CTOD) as the horizontal coordinate, were plotted. It was found that the detected AE events were qualitatively correlated with the global force-displacement behavior of the specimen. The Weibull distribution was vii proposed to quantitatively describe the rupture probability density function. The linear regression analysis was conducted to calibrate the Weibull distribution parameters with detected AE signals and to predict the rupture probability as a function of CTOD for the specimen. Finally, the controlled concrete freeze-thaw cyclic tests were designed and the AE technique was planned to investigate the internal frost damage process of concrete specimens.

Prognosis of HIV-associated non-Hodgkin lymphoma in patients starting combination antiretroviral therapy

OBJECTIVE: We examined survival and prognostic factors of patients who developed HIV-associated non-Hodgkin lymphoma (NHL) in the era of combination antiretroviral therapy (cART). DESIGN AND SETTING: Multicohort collaboration of 33 European cohorts. METHODS: We included all cART-naive patients enrolled in cohorts participating in the Collaboration of Observational HIV Epidemiological Research Europe (COHERE) who were aged 16 years or older, started cART at some point after 1 January 1998 and developed NHL after 1 January 1998. Patients had to have a CD4 cell count after 1 January 1998 and one at diagnosis of the NHL. Survival and prognostic factors were estimated using Weibull models, with random effects accounting for heterogeneity between cohorts. RESULTS: Of 67 659 patients who were followed up during 304 940 person-years, 1176 patients were diagnosed with NHL. Eight hundred and forty-seven patients (72%) from 22 cohorts met inclusion criteria. Survival at 1 year was 66% [95% confidence interval (CI) 63-70%] for systemic NHL (n = 763) and 54% (95% CI: 43-65%) for primary brain lymphoma (n = 84). Risk factors for death included low nadir CD4 cell counts and a history of injection drug use. Patients developing NHL on cART had an increased risk of death compared with patients who were cART naive at diagnosis. CONCLUSION: In the era of cART two-thirds of patients diagnosed with HIV-related systemic NHL survive for longer than 1 year after diagnosis. Survival is poorer in patients diagnosed with primary brain lymphoma. More advanced immunodeficiency is the dominant prognostic factor for mortality in patients with HIV-related NHL.

Switching to second-line antiretroviral therapy in resource-limited settings: comparison of programmes with and without viral load monitoring

BACKGROUND: In high-income countries, viral load is routinely measured to detect failure of antiretroviral therapy (ART) and guide switching to second-line ART. Viral load monitoring is not generally available in resource-limited settings. We examined switching from nonnucleoside reverse transcriptase inhibitor (NNRTI)-based first-line regimens to protease inhibitor-based regimens in Africa, South America and Asia. DESIGN AND METHODS: Multicohort study of 17 ART programmes. All sites monitored CD4 cell count and had access to second-line ART and 10 sites monitored viral load. We compared times to switching, CD4 cell counts at switching and obtained adjusted hazard ratios for switching (aHRs) with 95% confidence intervals (CIs) from random-effects Weibull models. RESULTS: A total of 20 113 patients, including 6369 (31.7%) patients from 10 programmes with access to viral load monitoring, were analysed; 576 patients (2.9%) switched. Low CD4 cell counts at ART initiation were associated with switching in all programmes. Median time to switching was 16.3 months [interquartile range (IQR) 10.1-26.6] in programmes with viral load monitoring and 21.8 months (IQR 14.0-21.8) in programmes without viral load monitoring (P < 0.001). Median CD4 cell counts at switching were 161 cells/microl (IQR 77-265) in programmes with viral load monitoring and 102 cells/microl (44-181) in programmes without viral load monitoring (P < 0.001). Switching was more common in programmes with viral load monitoring during months 7-18 after starting ART (aHR 1.38; 95% CI 0.97-1.98), similar during months 19-30 (aHR 0.97; 95% CI 0.58-1.60) and less common during months 31-42 (aHR 0.29; 95% CI 0.11-0.79). CONCLUSION: In resource-limited settings, switching to second-line regimens tends to occur earlier and at higher CD4 cell counts in ART programmes with viral load monitoring compared with programmes without viral load monitoring.

Integration of Truncated Distributions in Exponential Family with Simulation Models of Logistics and Supply Chain Management

Truncated distributions of the exponential family have great influence in the simulation models. This paper discusses the truncated Weibull distribution specifically. The truncation of the distribution is achieved by the Maximum Likelihood Estimation method or combined with the expectation and variance expressions. After the fitting of distribution, the goodness-of-fit tests (the Chi-Square test and the Kolmogorov-Smirnov test) are executed to rule out the rejected hypotheses. Finally the distributions are integrated in various simulation models, e. g. shipment consolidation model, to compare the influence of truncated and original versions of Weibull distribution on the model.

Prognosis of Children with HIV-1 Infection Starting Antiretroviral Therapy in Southern Africa: A Collaborative Analysis of Treatment Programs

BACKGROUND: Prognostic models for children starting antiretroviral therapy (ART) in Africa are lacking. We developed models to estimate the probability of death during the first year receiving ART in Southern Africa. METHODS: We analyzed data from children ≤10 years old who started ART in Malawi, South Africa, Zambia or Zimbabwe from 2004-2010. Children lost to follow-up or transferred were excluded. The primary outcome was all-cause mortality in the first year of ART. We used Weibull survival models to construct two prognostic models: one with CD4%, age, WHO clinical stage, weight-for-age z-score (WAZ) and anemia and one without CD4%, because it is not routinely measured in many programs. We used multiple imputation to account for missing data. RESULTS: Among 12655 children, 877 (6.9%) died in the first year of ART. 1780 children were lost to follow-up/transferred and excluded from main analyses; 10875 children were included. With the CD4% model probability of death at 1 year ranged from 1.8% (95% CI: 1.5-2.3) in children 5-10 years with CD4% ≥10%, WHO stage I/II, WAZ ≥-2 and without severe anemia to 46.3% (95% CI: 38.2-55.2) in children <1 year with CD4% <5%, stage III/IV, WAZ< -3 and severe anemia. The corresponding range for the model without CD4% was 2.2% (95% CI: 1.8-2.7) to 33.4% (95% CI: 28.2-39.3). Agreement between predicted and observed mortality was good (C-statistics=0.753 and 0.745 for models with and without CD4% respectively). CONCLUSION: These models may be useful to counsel children/caregivers, for program planning and to assess program outcomes after allowing for differences in patient disease severity characteristics.

SURVIVAL PREDICTION FOR BRAIN TUMOR PATIENTS USING GENE EXPRESSION DATA

Brain tumor is one of the most aggressive types of cancer in humans, with an estimated median survival time of 12 months and only 4% of the patients surviving more than 5 years after disease diagnosis. Until recently, brain tumor prognosis has been based only on clinical information such as tumor grade and patient age, but there are reports indicating that molecular profiling of gliomas can reveal subgroups of patients with distinct survival rates. We hypothesize that coupling molecular profiling of brain tumors with clinical information might improve predictions of patient survival time and, consequently, better guide future treatment decisions. In order to evaluate this hypothesis, the general goal of this research is to build models for survival prediction of glioma patients using DNA molecular profiles (U133 Affymetrix gene expression microarrays) along with clinical information. First, a predictive Random Forest model is built for binary outcomes (i.e. short vs. long-term survival) and a small subset of genes whose expression values can be used to predict survival time is selected. Following, a new statistical methodology is developed for predicting time-to-death outcomes using Bayesian ensemble trees. Due to a large heterogeneity observed within prognostic classes obtained by the Random Forest model, prediction can be improved by relating time-to-death with gene expression profile directly. We propose a Bayesian ensemble model for survival prediction which is appropriate for high-dimensional data such as gene expression data. Our approach is based on the ensemble "sum-of-trees" model which is flexible to incorporate additive and interaction effects between genes. We specify a fully Bayesian hierarchical approach and illustrate our methodology for the CPH, Weibull, and AFT survival models. We overcome the lack of conjugacy using a latent variable formulation to model the covariate effects which decreases computation time for model fitting. Also, our proposed models provides a model-free way to select important predictive prognostic markers based on controlling false discovery rates. We compare the performance of our methods with baseline reference survival methods and apply our methodology to an unpublished data set of brain tumor survival times and gene expression data, selecting genes potentially related to the development of the disease under study. A closing discussion compares results obtained by Random Forest and Bayesian ensemble methods under the biological/clinical perspectives and highlights the statistical advantages and disadvantages of the new methodology in the context of DNA microarray data analysis.

Non-exponential return time distributions for vorticity extremes explained by fractional Poisson processes

Serial correlation of extreme midlatitude cyclones observed at the storm track exits is explained by deviations from a Poisson process. To model these deviations, we apply fractional Poisson processes (FPPs) to extreme midlatitude cyclones, which are defined by the 850 hPa relative vorticity of the ERA interim reanalysis during boreal winter (DJF) and summer (JJA) seasons. Extremes are defined by a 99% quantile threshold in the grid-point time series. In general, FPPs are based on long-term memory and lead to non-exponential return time distributions. The return times are described by a Weibull distribution to approximate the Mittag–Leffler function in the FPPs. The Weibull shape parameter yields a dispersion parameter that agrees with results found for midlatitude cyclones. The memory of the FPP, which is determined by detrended fluctuation analysis, provides an independent estimate for the shape parameter. Thus, the analysis exhibits a concise framework of the deviation from Poisson statistics (by a dispersion parameter), non-exponential return times and memory (correlation) on the basis of a single parameter. The results have potential implications for the predictability of extreme cyclones.

Saddlepoint approximations to sensitivities of tail probabilities of random sums and comparisons with Monte Carlo estimators

This article proposes computing sensitivities of upper tail probabilities of random sums by the saddlepoint approximation. The considered sensitivity is the derivative of the upper tail probability with respect to the parameter of the summation index distribution. Random sums with Poisson or Geometric distributed summation indices and Gamma or Weibull distributed summands are considered. The score method with importance sampling is considered as an alternative approximation. Numerical studies show that the saddlepoint approximation and the method of score with importance sampling are very accurate. But the saddlepoint approximation is substantially faster than the score method with importance sampling. Thus, the suggested saddlepoint approximation can be conveniently used in various scientific problems.

Characterization of surface winds over the Iberian Peninsula

This work presents a characterization of the surface wind climatology over the Iberian Peninsula (IP). For this objective, an unprecedented observational database has been developed. The database covers a period of 6years (2002–2007) and consists of hourly wind speed and wind direction data recorded at 514 automatic weather stations. Theoriginal observations underwent a quality control process to remove rough errors from the data set. In the first step, the annual and seasonal mean behaviour of the wind field are presented. This analysis shows the high spatial variability of the wind as a result of its interaction with the main orographic features of the IP. In order to simplify the characterization of the wind, a clustering procedure was applied to group the observational sites with similar temporal wind variability. A total of 20 regions are identified. These regions are strongly related to the main landforms of the IP. The wind behaviour of each region, characterized by the wind rose (WR), annual cycle (AC) and wind speed histogram, is explained as the response of each region to the main circulation types (CTs) affecting the IP. Results indicate that the seasonal variability of the synoptic scale is related with intra-annual variability and modulated by local features in the WRs variability. The wind speed distribution not always fit to a unimodal Weibull distribution consequence of interactions at different atmospheric scales. This work contributes to a deeper understanding of the temporal and spatial variability of surface winds. Taken together, the wind database created, the methodology used and the conclusion extracted are a benchmark for future works based on the wind behaviour.

Modelling zero-inflated count data when exposure varies: with an application to tumor counts)

This paper is concerned with the analysis of zero-inflated count data when time of exposure varies. It proposes a modified zero-inflated count data model where the probability of an extra zero is derived from an underlying duration model with Weibull hazard rate. The new model is compared to the standard Poisson model with logit zero inflation in an application to the effect of treatment with thiotepa on the number of new bladder tumors.

Low Risk of Death, but Substantial Program Attrition, in Pediatric HIV Treatment Cohorts in Sub-Saharan Africa

BACKGROUND: To date, an estimated 10% of children eligible for antiretroviral treatment (ART) receive it, and the frequency of retention in programs is unknown. We evaluated the 2-year risks of death and loss to follow-up (LTFU) of children after ART initiation in a multicenter study in sub-Saharan Africa. METHODS: Pooled analysis of routine individual data from 16 participating clinics produced overall Kaplan-Meier estimates of the probabilities of death or LTFU after ART initiation. Risk factors analysis used Weibull regression, accounting for between-cohort heterogeneity. RESULTS: The median age of 2405 children at ART initiation was 4.9 years (12%, younger than 12 months), 52% were male, 70% had severe immunodeficiency, and 59% started ART with a nonnucleoside reverse transcriptase inhibitor. The 2-year risk of death after ART initiation was 6.9% (95% confidence interval [CI]: 5.9 to 8.1), independently associated with baseline severe anemia (adjusted hazard ratio [aHR]: 4.10 [CI: 2.36 to 7.13]), immunodeficiency (adjusted aHR: 2.95 [CI: 1.49 to 5.82]), and severe clinical status (adjusted aHR: 3.64 [CI: 1.95 to 6.81]); the 2-year risk of LTFU was 10.3% (CI: 8.9 to 11.9), higher in children with severe clinical status. CONCLUSIONS: Once on treatment, the 2-year risk of death is low but the LTFU risk is substantial. ART is still mainly initiated at advanced disease stage in African children, reinforcing the need for early HIV diagnosis, early initiation of ART, and procedures to increase program retention.

Independent at heart: persistent association of altitude with ischaemic heart disease mortality after consideration of climate, topography and built environment.

BACKGROUND Living at higher altitude was dose-dependently associated with lower risk of ischaemic heart disease (IHD). Higher altitudes have different climatic, topographic and built environment properties than lowland regions. It is unclear whether these environmental factors mediate/confound the association between altitude and IHD. We examined how much of the altitude-IHD association is explained by variations in exposure at place of residence to sunshine, temperature, precipitation, aspect, slope and distance to main road. METHODS We included 4.2 million individuals aged 40-84 at baseline living in Switzerland at altitudes 195-2971 m above sea level (ie, full range of residence), providing 77 127 IHD deaths. Mortality data 2000-2008, sociodemographic/economic information and coordinates of residence were obtained from the Swiss National Cohort, a longitudinal, census-based record linkage study. Environment information was modelled to residence level using Weibull regression models. RESULTS In the model not adjusted for other environmental factors, IHD mortality linearly decreased with increasing altitude resulting in a lower risk (HR, 95% CI 0.67, 0.60 to 0.74) for those living >1500 m (vs<600 m). This association remained after adjustment for all other environmental factors 0.74 (0.66 to 0.82). CONCLUSIONS The benefit of living at higher altitude was only partially confounded by variations in climate, topography and built environment. Rather, physical environment factors appear to have an independent effect and may impact on cardiovascular health in a cumulative way. Inclusion of additional modifiable factors as well as individual information on traditional IHD risk factors in our combined environmental model could help to identify strategies for the reduction of inequalities in IHD mortality.