913 resultados para Poisson regression model
Resumo:
BACKGROUND: Gemcitabine plus cisplatin (GC) has been adopted as a neoadjuvant regimen for muscle-invasive bladder cancer despite the lack of Level I evidence in this setting. METHODS: Data were collected using an electronic data-capture platform from 28 international centers. Eligible patients had clinical T-classification 2 (cT2) through cT4aN0M0 urothelial cancer of the bladder and received neoadjuvant GC or methotrexate, vinblastine, doxorubicin, plus cisplatin (MVAC) before undergoing cystectomy. Logistic regression was used to compute propensity scores as the predicted probabilities of patients being assigned to MVAC versus GC given their baseline characteristics. These propensity scores were then included in a new logistic regression model to estimate an adjusted odds ratio comparing the odds of attaining a pathologic complete response (pCR) between patients who received MVAC and those who received GC. RESULTS: In total, 212 patients (146 patients in the GC cohort and 66 patients in the MVAC cohort) met criteria for inclusion in the analysis. The majority of patients in the MVAC cohort (77%) received dose-dense MVAC. The median age of patients was 63 years, they were predominantly men (74%), and they received a median of 3 cycles of neoadjuvant chemotherapy. The pCR rate was 29% in the MVAC cohort and 31% in the GC cohort. There was no significant difference in the pCR rate when adjusted for propensity scores between the 2 regimens (odds ratio, 0.91; 95% confidence interval, 0.48-1.72; P = .77). In an exploratory analysis evaluating survival, the hazard ratio comparing hazard rates for MVAC versus GC adjusted for propensity scores was not statistically significant (hazard ratio, 0.78; 95% confidence interval, 0.40-1.54; P = .48). CONCLUSIONS: Patients who received neoadjuvant GC and MVAC achieved comparable pCR rates in the current analysis, providing evidence to support what has become routine practice. Cancer 2015;121:2586-2593. © 2015 American Cancer Society.
Resumo:
BACKGROUND: Transmitted human immunodeficiency virus type 1 (HIV) drug resistance (TDR) mutations are transmitted from nonresponding patients (defined as patients with no initial response to treatment and those with an initial response for whom treatment later failed) or from patients who are naive to treatment. Although the prevalence of drug resistance in patients who are not responding to treatment has declined in developed countries, the prevalence of TDR mutations has not. Mechanisms causing this paradox are poorly explored. METHODS: We included recently infected, treatment-naive patients with genotypic resistance tests performed ≤1 year after infection and before 2013. Potential risk factors for TDR mutations were analyzed using logistic regression. The association between the prevalence of TDR mutations and population viral load (PVL) among treated patients during 1997-2011 was estimated with Poisson regression for all TDR mutations and individually for the most frequent resistance mutations against each drug class (ie, M184V/L90M/K103N). RESULTS: We included 2421 recently infected, treatment-naive patients and 5399 patients with no response to treatment. The prevalence of TDR mutations fluctuated considerably over time. Two opposing developments could explain these fluctuations: generally continuous increases in the prevalence of TDR mutations (odds ratio, 1.13; P = .010), punctuated by sharp decreases in the prevalence when new drug classes were introduced. Overall, the prevalence of TDR mutations increased with decreasing PVL (rate ratio [RR], 0.91 per 1000 decrease in PVL; P = .033). Additionally, we observed that the transmitted high-fitness-cost mutation M184V was positively associated with the PVL of nonresponding patients carrying M184V (RR, 1.50 per 100 increase in PVL; P < .001). Such association was absent for K103N (RR, 1.00 per 100 increase in PVL; P = .99) and negative for L90M (RR, 0.75 per 100 increase in PVL; P = .022). CONCLUSIONS: Transmission of antiretroviral drug resistance is temporarily reduced by the introduction of new drug classes and driven by nonresponding and treatment-naive patients. These findings suggest a continuous need for new drugs, early detection/treatment of HIV-1 infection.
Resumo:
Notre consommation en eau souterraine, en particulier comme eau potable ou pour l'irrigation, a considérablement augmenté au cours des années. De nombreux problèmes font alors leur apparition, allant de la prospection de nouvelles ressources à la remédiation des aquifères pollués. Indépendamment du problème hydrogéologique considéré, le principal défi reste la caractérisation des propriétés du sous-sol. Une approche stochastique est alors nécessaire afin de représenter cette incertitude en considérant de multiples scénarios géologiques et en générant un grand nombre de réalisations géostatistiques. Nous rencontrons alors la principale limitation de ces approches qui est le coût de calcul dû à la simulation des processus d'écoulements complexes pour chacune de ces réalisations. Dans la première partie de la thèse, ce problème est investigué dans le contexte de propagation de l'incertitude, oú un ensemble de réalisations est identifié comme représentant les propriétés du sous-sol. Afin de propager cette incertitude à la quantité d'intérêt tout en limitant le coût de calcul, les méthodes actuelles font appel à des modèles d'écoulement approximés. Cela permet l'identification d'un sous-ensemble de réalisations représentant la variabilité de l'ensemble initial. Le modèle complexe d'écoulement est alors évalué uniquement pour ce sousensemble, et, sur la base de ces réponses complexes, l'inférence est faite. Notre objectif est d'améliorer la performance de cette approche en utilisant toute l'information à disposition. Pour cela, le sous-ensemble de réponses approximées et exactes est utilisé afin de construire un modèle d'erreur, qui sert ensuite à corriger le reste des réponses approximées et prédire la réponse du modèle complexe. Cette méthode permet de maximiser l'utilisation de l'information à disposition sans augmentation perceptible du temps de calcul. La propagation de l'incertitude est alors plus précise et plus robuste. La stratégie explorée dans le premier chapitre consiste à apprendre d'un sous-ensemble de réalisations la relation entre les modèles d'écoulement approximé et complexe. Dans la seconde partie de la thèse, cette méthodologie est formalisée mathématiquement en introduisant un modèle de régression entre les réponses fonctionnelles. Comme ce problème est mal posé, il est nécessaire d'en réduire la dimensionnalité. Dans cette optique, l'innovation du travail présenté provient de l'utilisation de l'analyse en composantes principales fonctionnelles (ACPF), qui non seulement effectue la réduction de dimensionnalités tout en maximisant l'information retenue, mais permet aussi de diagnostiquer la qualité du modèle d'erreur dans cet espace fonctionnel. La méthodologie proposée est appliquée à un problème de pollution par une phase liquide nonaqueuse et les résultats obtenus montrent que le modèle d'erreur permet une forte réduction du temps de calcul tout en estimant correctement l'incertitude. De plus, pour chaque réponse approximée, une prédiction de la réponse complexe est fournie par le modèle d'erreur. Le concept de modèle d'erreur fonctionnel est donc pertinent pour la propagation de l'incertitude, mais aussi pour les problèmes d'inférence bayésienne. Les méthodes de Monte Carlo par chaîne de Markov (MCMC) sont les algorithmes les plus communément utilisés afin de générer des réalisations géostatistiques en accord avec les observations. Cependant, ces méthodes souffrent d'un taux d'acceptation très bas pour les problèmes de grande dimensionnalité, résultant en un grand nombre de simulations d'écoulement gaspillées. Une approche en deux temps, le "MCMC en deux étapes", a été introduite afin d'éviter les simulations du modèle complexe inutiles par une évaluation préliminaire de la réalisation. Dans la troisième partie de la thèse, le modèle d'écoulement approximé couplé à un modèle d'erreur sert d'évaluation préliminaire pour le "MCMC en deux étapes". Nous démontrons une augmentation du taux d'acceptation par un facteur de 1.5 à 3 en comparaison avec une implémentation classique de MCMC. Une question reste sans réponse : comment choisir la taille de l'ensemble d'entrainement et comment identifier les réalisations permettant d'optimiser la construction du modèle d'erreur. Cela requiert une stratégie itérative afin que, à chaque nouvelle simulation d'écoulement, le modèle d'erreur soit amélioré en incorporant les nouvelles informations. Ceci est développé dans la quatrième partie de la thèse, oú cette méthodologie est appliquée à un problème d'intrusion saline dans un aquifère côtier. -- Our consumption of groundwater, in particular as drinking water and for irrigation, has considerably increased over the years and groundwater is becoming an increasingly scarce and endangered resource. Nofadays, we are facing many problems ranging from water prospection to sustainable management and remediation of polluted aquifers. Independently of the hydrogeological problem, the main challenge remains dealing with the incomplete knofledge of the underground properties. Stochastic approaches have been developed to represent this uncertainty by considering multiple geological scenarios and generating a large number of realizations. The main limitation of this approach is the computational cost associated with performing complex of simulations in each realization. In the first part of the thesis, we explore this issue in the context of uncertainty propagation, where an ensemble of geostatistical realizations is identified as representative of the subsurface uncertainty. To propagate this lack of knofledge to the quantity of interest (e.g., the concentration of pollutant in extracted water), it is necessary to evaluate the of response of each realization. Due to computational constraints, state-of-the-art methods make use of approximate of simulation, to identify a subset of realizations that represents the variability of the ensemble. The complex and computationally heavy of model is then run for this subset based on which inference is made. Our objective is to increase the performance of this approach by using all of the available information and not solely the subset of exact responses. Two error models are proposed to correct the approximate responses follofing a machine learning approach. For the subset identified by a classical approach (here the distance kernel method) both the approximate and the exact responses are knofn. This information is used to construct an error model and correct the ensemble of approximate responses to predict the "expected" responses of the exact model. The proposed methodology makes use of all the available information without perceptible additional computational costs and leads to an increase in accuracy and robustness of the uncertainty propagation. The strategy explored in the first chapter consists in learning from a subset of realizations the relationship between proxy and exact curves. In the second part of this thesis, the strategy is formalized in a rigorous mathematical framework by defining a regression model between functions. As this problem is ill-posed, it is necessary to reduce its dimensionality. The novelty of the work comes from the use of functional principal component analysis (FPCA), which not only performs the dimensionality reduction while maximizing the retained information, but also allofs a diagnostic of the quality of the error model in the functional space. The proposed methodology is applied to a pollution problem by a non-aqueous phase-liquid. The error model allofs a strong reduction of the computational cost while providing a good estimate of the uncertainty. The individual correction of the proxy response by the error model leads to an excellent prediction of the exact response, opening the door to many applications. The concept of functional error model is useful not only in the context of uncertainty propagation, but also, and maybe even more so, to perform Bayesian inference. Monte Carlo Markov Chain (MCMC) algorithms are the most common choice to ensure that the generated realizations are sampled in accordance with the observations. Hofever, this approach suffers from lof acceptance rate in high dimensional problems, resulting in a large number of wasted of simulations. This led to the introduction of two-stage MCMC, where the computational cost is decreased by avoiding unnecessary simulation of the exact of thanks to a preliminary evaluation of the proposal. In the third part of the thesis, a proxy is coupled to an error model to provide an approximate response for the two-stage MCMC set-up. We demonstrate an increase in acceptance rate by a factor three with respect to one-stage MCMC results. An open question remains: hof do we choose the size of the learning set and identify the realizations to optimize the construction of the error model. This requires devising an iterative strategy to construct the error model, such that, as new of simulations are performed, the error model is iteratively improved by incorporating the new information. This is discussed in the fourth part of the thesis, in which we apply this methodology to a problem of saline intrusion in a coastal aquifer.
Resumo:
UNLABELLED: The relationship between bone quantitative ultrasound (QUS) and fracture risk was estimated in an individual level data meta-analysis of 9 prospective studies of 46,124 individuals and 3018 incident fractures. Low QUS is associated with an increase in fracture risk, including hip fracture. The association with osteoporotic fracture decreases with time. INTRODUCTION: The aim of this meta-analysis was to investigate the association between parameters of QUS and risk of fracture. METHODS: In an individual-level analysis, we studied participants in nine prospective cohorts from Asia, Europe and North America. Heel broadband ultrasonic attenuation (BUA dB/MHz) and speed of sound (SOS m/s) were measured at baseline. Fractures during follow-up were collected by self-report and in some cohorts confirmed by radiography. An extension of Poisson regression was used to examine the gradient of risk (GR, hazard ratio per 1 SD decrease) between QUS and fracture risk adjusted for age and time since baseline in each cohort. Interactions between QUS and age and time since baseline were explored. RESULTS: Baseline measurements were available in 46,124 men and women, mean age 70 years (range 20-100). Three thousand and eighteen osteoporotic fractures (787 hip fractures) occurred during follow-up of 214,000 person-years. The summary GR for osteoporotic fracture was similar for both BUA (1.45, 95 % confidence intervals (CI) 1.40-1.51) and SOS (1.42, 95 % CI 1.36-1.47). For hip fracture, the respective GRs were 1.69 (95 % CI, 1.56-1.82) and 1.60 (95 % CI, 1.48-1.72). However, the GR was significantly higher for both fracture outcomes at lower baseline BUA and SOS (p < 0.001). The predictive value of QUS was the same for men and women and for all ages (p > 0.20), but the predictive value of both BUA and SOS for osteoporotic fracture decreased with time (p = 0.018 and p = 0.010, respectively). For example, the GR of BUA for osteoporotic fracture, adjusted for age, was 1.51 (95 % CI 1.42-1.61) at 1 year after baseline, but at 5 years, it was 1.36 (95 % CI 1.27-1.46). CONCLUSIONS: Our results confirm that quantitative ultrasound is an independent predictor of fracture for men and women particularly at low QUS values.
Resumo:
OBJECTIVES: We studied the incidence and prevalence of, and co-factors for depression in the Swiss HIV Cohort Study. METHODS: Depression-specific items were introduced in 2010 and prospectively collected at semiannual cohort visits. Clinical, laboratory and behavioral co-factors of incident depression among participants free of depression at the first two visits in 2010 or thereafter were analyzed with Poisson regression. Cumulative prevalence of depression at the last visit was analyzed with logistic regression. RESULTS: Among 4,422 participants without a history of psychiatric disorders or depression at baseline, 360 developed depression during 9,348 person-years (PY) of follow-up, resulting in an incidence rate of 3.9 per 100 PY (95% confidence interval (CI) 3.5-4.3). Cumulative prevalence of depression during follow-up was recorded for 1,937/6,756 (28.7%) participants. Incidence and cumulative prevalence were higher in injection drug users (IDU) and women. Older age, preserved work ability and higher physical activity were associated with less depression episodes. Mortality (0.96 per 100 PY, 95% CI 0.83-1.11) based upon 193 deaths over 20,102 PY was higher among male IDU (2.34, 1.78-3.09), female IDU (2.33, 1.59-3.39) and white heterosexual men (1.32, 0.94-1.84) compared to white heterosexual women and homosexual men (0.53, 0.29-0.95; and 0.71, 0.55-0.92). Compared to participants free of depression, mortality was slightly elevated among participants with a history of depression (1.17, 0.94-1.45 vs. 0.86, 0.71-1.03, P = 0.033). Suicides (n = 18) did not differ between HIV transmission groups (P = 0.50), but were more frequent among participants with a prior diagnosis of depression (0.18 per 100 PY, 95%CI 0.10-0.31; vs. 0.04, 0.02-0.10; P = 0.003). CONCLUSIONS: Depression is a frequent co-morbidity among HIV-infected persons, and thus an important focus of care.
Resumo:
Background. Although acquired immune deficiency syndrome-associated morbidity has diminished due to excellent viral control, multimorbidity may be increasing among human immunodeficiency virus (HIV)-infected persons compared with the general population. Methods. We assessed the prevalence of comorbidities and multimorbidity in participants of the Swiss HIV Cohort Study (SHCS) compared with the population-based CoLaus study and the primary care-based FIRE (Family Medicine ICPC-Research using Electronic Medical Records) records. The incidence of the respective endpoints were assessed among SHCS and CoLaus participants. Poisson regression models were adjusted for age, sex, body mass index, and smoking. Results. Overall, 74 291 participants contributed data to prevalence analyses (3230 HIV-infected; 71 061 controls). In CoLaus, FIRE, and SHCS, multimorbidity was present among 26%, 13%, and 27% of participants. Compared with nonsmoking individuals from CoLaus, the incidence of cardiovascular disease was elevated among smoking individuals but independent of HIV status (HIV-negative smoking: incidence rate ratio [IRR] = 1.7, 95% confidence interval [CI] = 1.2-2.5; HIV-positive smoking: IRR = 1.7, 95% CI = 1.1-2.6; HIV-positive nonsmoking: IRR = 0.79, 95% CI = 0.44-1.4). Compared with nonsmoking HIV-negative persons, multivariable Poisson regression identified associations of HIV infection with hypertension (nonsmoking: IRR = 1.9, 95% CI = 1.5-2.4; smoking: IRR = 2.0, 95% CI = 1.6-2.4), kidney (nonsmoking: IRR = 2.7, 95% CI = 1.9-3.8; smoking: IRR = 2.6, 95% CI = 1.9-3.6), and liver disease (nonsmoking: IRR = 1.8, 95% CI = 1.4-2.4; smoking: IRR = 1.7, 95% CI = 1.4-2.2). No evidence was found for an association of HIV-infection or smoking with diabetes mellitus. Conclusions. Multimorbidity is more prevalent and incident in HIV-positive compared with HIV-negative individuals. Smoking, but not HIV status, has a strong impact on cardiovascular risk and multimorbidity.
Resumo:
Already in ancient Greece, Hippocrates postulated that disease showed a seasonal pattern characterised by excess winter mortality. Since then, several studies have confirmed this finding, and it was generally accepted that the increase in winter mortality was mostly due to respiratory infections and seasonal influenza. More recently, it was shown that cardiovascular disease (CVD) mortality also displayed such seasonality, and that the magnitude of the seasonal effect increased from the poles to the equator. The recent study by Yang et al assessed CVD mortality attributable to ambient temperature using daily data from 15 cities in China for years 2007-2013, including nearly two million CVD deaths. A high temperature variability between and within cities can be observed (figure 1). They used sophisticated statistical methodology to account for the complex temperature-mortality relationship; first, distributed lag non-linear models combined with quasi-Poisson regression to obtain city-specific estimates, taking into account temperature, relative humidity and atmospheric pressure; then, a meta-analysis to obtain the pooled estimates. The results confirm the winter excess mortality as reported by the Eurowinter3 and other4 groups, but they show that the magnitude of ambient temperature.
Resumo:
Objectives: We present the retrospective analysis of a single-institution experience for radiosurgery (RS) in brain metastasis (BM) with Gamma Knife (GK) and Linac. Methods: From July 2010 to July 2012, 28 patients (with 83 lesions) had RS with GK and 35 patients (with 47 lesions) with Linac. The primary outcome was the local progression-free survival (LPFS). The secondary outcome was the overall survival (OS). Apart a standard statistical analysis, we included a Cox regression model with shared frailty, to modulate the within-patient correlation (preliminary evaluation showed a significant frailty effect, meaning that the correlation within patient could be ignored). Results: The mean follow-up period was 11.7 months (median 7.9, 1.7-22.7) for GK and 18.1 (median 17, 7.5-28.7) for Linac. The median number of lesions per patient was 2.5 (1-9) in GK compared with 1 (1-3) in Linac. There were more radioresistant lesions (melanoma) and more lesions located in functional areas for the GK group. The median dose was 24 Gy (GK) compared with 20 Gy (Linac). The LPFS actuarial rate was as follows: for GK at 3, 6, 9, 12, and 17 months: 96.96, 96.96, 96.96, 88.1, and 81.5%, and remained stable till 32 months; for Linac at 3, 6, 12, 17, 24, and 33 months, it was 91.5, 91.5, 91.5, 79.9, 55.5, and 17.1%, respectively (p = 0.03, chi-square test). After the Cox regression analysis with shared frailty, the p-value was not statistically significant between groups. The median overall survival was 9.7 months for GK and 23.6 months for Linac group. Uni- and multivariate analysis showed a lower GPA score and noncontrolled systemic status were associated with lower OS. Cox regression analysis adjusting for these two parameters showed comparable OS rate. Conclusions: In this comparative report between GK and Linac, preliminary analysis showed that more difficult cases are treated by GK, with patients harboring more lesions, radioresistant tumors, and highly functional located. The groups look, in this sense, very heterogeneous at baseline. After a Cox frailty model, the LPFS rates seemed very similar (p < 0.05). The OS was similar, after adjusting for systemic status and GPA score (p < 0.05). The technical reasons for choosing GK instead of Linac were the anatomical location related to highly functional areas, histology, technical limitations of Linac movements, especially lower posterior fossa locations, or closeness of multiple lesions to highly functional areas optimal dosimetry with Linac
Resumo:
Over the past few decades, age estimation of living persons has represented a challenging task for many forensic services worldwide. In general, the process for age estimation includes the observation of the degree of maturity reached by some physical attributes, such as dentition or several ossification centers. The estimated chronological age or the probability that an individual belongs to a meaningful class of ages is then obtained from the observed degree of maturity by means of various statistical methods. Among these methods, those developed in a Bayesian framework offer to users the possibility of coherently dealing with the uncertainty associated with age estimation and of assessing in a transparent and logical way the probability that an examined individual is younger or older than a given age threshold. Recently, a Bayesian network for age estimation has been presented in scientific literature; this kind of probabilistic graphical tool may facilitate the use of the probabilistic approach. Probabilities of interest in the network are assigned by means of transition analysis, a statistical parametric model, which links the chronological age and the degree of maturity by means of specific regression models, such as logit or probit models. Since different regression models can be employed in transition analysis, the aim of this paper is to study the influence of the model in the classification of individuals. The analysis was performed using a dataset related to the ossifications status of the medial clavicular epiphysis and results support that the classification of individuals is not dependent on the choice of the regression model.
Resumo:
The decision to settle a motor insurance claim by either negotiation or trial is analysed. This decision may depend on how risk and confrontation adverse or pessimistic the claimant is. The extent to which these behavioural features of the claimant might influence the final compensation amount are examined. An empirical analysis, fitting a switching regression model to a Spanish database, is conducted in order to analyze whether the choice of the conflict resolution procedure is endogenous to the compensation outcomes. The results show that compensations awarded by courts are always higher, although 95% of cases are settled by negotiation. We show that this is because claimants are adverse to risk and confrontation, and are pessimistic about their chances at trial. By contrast, insurers are risk - confrontation neutral and more objective in relation to the expected trial compensation. During the negotiation insurers accept to pay the subjective compensation values of claimants, since these values are lower than their estimates of compensations at trial.
Factors affecting hospital admission and recovery stay duration of in-patient motor victims in Spain
Resumo:
Hospital expenses are a major cost driver of healthcare systems in Europe, with motor injuries being the leading mechanism of hospitalizations. This paper investigates the injury characteristics which explain the hospitalization of victims of traffic accidents that took place in Spain. Using a motor insurance database with 16.081 observations a generalized Tobit regression model is applied to analyse the factors that influence both the likelihood of being admitted to hospital after a motor collision and the length of hospital stay in the event of admission. The consistency of Tobit estimates relies on the normality of perturbation terms. Here a semi-parametric regression model was fitted to test the consistency of estimates, concluding that a normal distribution of errors cannot be rejected. Among other results, it was found that older men with fractures and injuries located in the head and lower torso are more likely to be hospitalized after the collision, and that they also have a longer expected length of hospital recovery stay.
Resumo:
BACKGROUND: Delirium and frailty - both potentially reversible geriatric syndromes - are seldom studied together, although they often occur jointly in older patients discharged from hospitals. This study aimed to explore the relationship between delirium and frailty in older adults discharged from hospitals. METHODS: Of the 221 patients aged >65 years, who were invited to participate, only 114 gave their consent to participate in this study. Delirium was assessed using the confusion assessment method, in which patients were classified dichotomously as delirious or nondelirious according to its algorithm. Frailty was assessed using the Edmonton Frailty Scale, which classifies patients dichotomously as frail or nonfrail. In addition to the sociodemographic characteristics, covariates such as scores from the Mini-Mental State Examination, Instrumental Activities of Daily Living scale, and Cumulative Illness Rating Scale for Geriatrics and details regarding polymedication were collected. A multidimensional linear regression model was used for analysis. RESULTS: Almost 20% of participants had delirium (n=22), and 76.3% were classified as frail (n=87); 31.5% of the variance in the delirium score was explained by frailty (R (2)=0.315). Age; polymedication; scores of the Confusion Assessment Method (CAM), instrumental activities of daily living, and Cumulative Illness Rating Scale for Geriatrics; and frailty increased the predictability of the variance of delirium by 32% to 64% (R (2)=0.64). CONCLUSION: Frailty is strongly related to delirium in older patients after discharge from the hospital.
Resumo:
In a cohort study of 182 consecutive patients with active endogenous Cushing's syndrome, the only predictor of fracture occurrence after adjustment for age, gender bone mineral density (BMD) and trabecular bone score (TBS) was 24-h urinary free cortisol (24hUFC) levels with a threshold of 1472 nmol/24 h (odds ratio, 3.00 (95 % confidence interval (CI), 1.52-5.92); p = 0.002). INTRODUCTION: The aim was to estimate the risk factors for fracture in subjects with endogenous Cushing's syndrome (CS) and to evaluate the value of the TBS in these patients. METHODS: All enrolled patients with CS (n = 182) were interviewed in relation to low-traumatic fractures and underwent lateral X-ray imaging from T4 to L5. BMD measurements were performed using a DXA Prodigy device (GEHC Lunar, Madison, Wisconsin, USA). The TBS was derived retrospectively from existing BMD scans, blinded to clinical outcome, using TBS iNsight software v2.1 (Medimaps, Merignac, France). Urinary free cortisol (24hUFC) was measured by immunochemiluminescence assay (reference range, 60-413 nmol/24 h). RESULTS: Among enrolled patients with CS (149 females; 33 males; mean age, 37.8 years (95 % confidence interval, 34.2-39.1); 24hUFC, 2370 nmol/24 h (2087-2632), fractures were confirmed in 81 (44.5 %) patients, with 70 suffering from vertebral fractures, which were multiple in 53 cases; 24 patients reported non-vertebral fractures. The mean spine TBS was 1.207 (1.187-1.228), and TBS Z-score was -1.86 (-2.07 to -1.65); area under the curve (AUC) was used to predict fracture (mean spine TBS) = 0.548 (95 % CI, 0.454-0.641)). In the final regression model, the only predictor of fracture occurrence was 24hUFC levels (p = 0.001), with an increase of 1.041 (95 % CI, 1.019-1.063), calculated for every 100 nmol/24-h cortisol elevation (AUC (24hUFC) = 0.705 (95 % CI, 0.629-0.782)). CONCLUSIONS: Young patients with CS have a low TBS. However, the only predictor of low traumatic fracture is the severity of the disease itself, indicated by high 24hUFC levels.
Resumo:
AIMS: There is no standard test to determine the fatigue resistance of denture teeth. With the increasing number of patients with implant-retained dentures the mechanical strength of the denture teeth requires more attention and valid laboratory test set-ups. The purpose of the present study was to determine the fatigue resistance of various denture teeth using a dynamic load testing machine. METHODS: Four denture teeth were used: Bonartic II (Candulor), Physiodens (Vita), SR Phonares II (Ivoclar Vivadent) and Trubyte (Dentsply). For dynamic load testing, first upper molars with a similar shape and cusp inclination were selected. The molar teeth were embedded in cylindrical steel molds with denture base material (ProBase, Ivoclar Vivadent). Dynamic fatigue loading was carried out on the mesio-buccal cusp at a 45° angle using dynamic testing machines and 2,000,000 cycles at 2Hz in water (37°C). Three specimens per group and load were submitted to decreasing load levels (at least 4) until all the three specimens no longer showed any failures. All the specimens were evaluated under a stereo microscope (20× magnification). The number of cycles reached before observing a failure, and its dependence on the load and on the material, has been modeled using a parametric survival regression model with a lognormal distribution. This allowed to estimate the fatigue resistance for a given material as the maximal load for which one would observe less than 1% failure after 2,000,000 cycles. RESULTS: The failure pattern was similar for all denture teeth, showing a large chipping of the loaded mesio-buccal cusp. In our regression model, there were statistically significant differences among the different materials, with SR Phonares II and Bonartic II showing a higher resistance than Physiodens and Trubyte, the fatigue resistance being estimated at around 110N for the former two, and at about 60N for the latter two materials. CONCLUSION: The fatigue resistance may be a useful parameter to assess and to compare the clinical risk of chipping and fracture of denture tooth materials.
Resumo:
BACKGROUND: Despite important controversy in its efficacy, prostate cancer (PCa) screening has become widespread. Important socioeconomic screening disparities have been reported. However, trends in PCa screening and social disparities have not been investigated in Switzerland, a high risk country for PCa. We used data from five waves (from 1992-2012) of the population-based Swiss Health Interview Survey to evaluate trends in PCa screening and its association with socioeconomic indicators. METHODS: We used multivariable Poisson regression to estimate prevalence ratios (PR) and 95% Confidence Intervals (CI) adjusting for demographics, health status, and use of healthcare. RESULTS: The study included 12,034 men aged ≥50 years (mean age: 63.9). Between 1992 and 2012, ever use of PCa screening increased from 55.3% to 70.0% and its use within the last two years from 32.6% to 42.4% (p-value <0.05). Income, education, and occupational class were independently associated with PCa screening. PCa screening within the last two years was greater in men with the highest (>$6,000/month) vs. lowest income (≤$2,000) (46.5% vs. 38.7% in 2012, PR for overall period =1.29, 95%CI: 1.13-1.48). These socioeconomic disparities did not significantly change over time. CONCLUSIONS: This study shows that about half of Swiss men had performed at least one PCa screening. Men belonging to high socioeconomic status are clearly more frequently screened than those less favored. Given the uncertainty of the usefulness of PCa screening, men, including those with high socioeconomic status, should be clearly informed about benefits and harms of PCa screening, in particular, the adverse effect of over-diagnosis and of associated over-treatment.