891 resultados para Predicting treatment time


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Bupropion is a dopamine (DA) and norepinephrine (NE) reuptake inhibitor used as smoking cessation and antidepressant drug with a lower incidence of male sexual dysfunction. We showed previously that sibutramine, a norepinephrine/serotonine reuptake inhibitor, reduced male rat fertility. As there are no studies evaluating the impact of bupropion treatment on spermatic parameters and male fertility, we evaluated the effects of bupropion treatment (15 and 30 mg kg(-1), 30 days) on sexual behavior, spermatic parameters and fertility of male Wistar rats and on the epididymal duct in vitro contractility. Bupropion 15 mg kg(-1) increased the serum luteinizing hormone level and the epididymal duct contractility, but the sperm quality was not affected. At 30 mg kg(-1) bupropion impaired sperm quality increasing the incidence of non-progressive sperm. The male sexual behavior and fertility were not modified at both bupropion doses. These results, in rats, suggest the importance of studies evaluating the effects of bupropion on the human male sperm quality.

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In most patients, postoperative endoscopic recurrence (PER) occurs 1 year after abdominal resection for Crohn’s disease (CD). Preventing PER is essential for disease control, as most patients develop further clinical and surgical recurrences. Conventional therapy with nitroimidazoles, aminosalicylates, and immunomodulators have limited efficacy for preventing PER. Initial trials with biological therapy (infliximab and adalimumab) showed promising results in preventing PER, and the efficacy of these drugs seems higher than that with conventional therapy. The aim of this review is to outline the results of studies that used infliximab or adalimumab for preventing and treating PER in CD patients. Data with both agents are available, and a few, small prospective trials have shown the efficacy of these drugs in patients with a high risk for recurrence. We believe that, in 2013, biological agents will be better accepted for the prevention PER in CD patients, in addition to the already existing data. Larger trials are still underway, and their results will certainly determine the role of these agents in PER, which develops after bowel resection for CD.

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Background: The aim of the present study is to evaluate the clinical and microbiologic changes resulting from non-surgical periodontal treatment associated with amoxicillin and metronidazole in individuals with aggressive periodontitis. Methods: Fifteen individuals with aggressive periodontitis received non-surgical periodontal treatment and 45 days after completion of treatment were treated with antibiotics. Clinical data and samples of subgingival plaque were collected at baseline, 45 days after the non-surgical periodontal treatment, and 1 month after the use of antimicrobial agents. After 3 and 6 months, only clinical data were collected. The presence and quantification of Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis (Pg), Tannerella forsythia (Tf), Treponema denticola (Td), and Dialister pneumosintes were determined by real-time polymerase chain reaction. Results: All clinical parameters, with the exception of clinical attachment level (CAL), had significantly (P<0.05) improved at the end of the third month after non-surgical therapy associated with antibiotics. There was significant (P<0.05) reduction in the quantities of Td and Tf. After 1 month, there were significant (P<0.05) reductions in the frequencies of Pg and Tf. Conclusion: Non-surgical mechanical treatment associated with the use of amoxicillin and metronidazole led to an improvement in all clinical parameters studied, except for CAL, and significantly reduced the amount of subgingival Tf and Td. J Periodontal 2012;83:744-752.

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An imaging biomarker that would provide for an early quantitative metric of clinical treatment response in cancer patients would provide for a paradigm shift in cancer care. Currently, nonimage based clinical outcome metrics include morphology, clinical, and laboratory parameters, however, these are obtained relatively late following treatment. Diffusion-weighted MRI (DW-MRI) holds promise for use as a cancer treatment response biomarker as it is sensitive to macromolecular and microstructural changes which can occur at the cellular level earlier than anatomical changes during therapy. Studies have shown that successful treatment of many tumor types can be detected using DW-MRI as an early increase in the apparent diffusion coefficient (ADC) values. Additionally, low pretreatment ADC values of various tumors are often predictive of better outcome. These capabilities, once validated, could provide for an important opportunity to individualize therapy thereby minimizing unnecessary systemic toxicity associated with ineffective therapies with the additional advantage of improving overall patient health care and associated costs. In this report, we provide a brief technical overview of DW-MRI acquisition protocols, quantitative image analysis approaches and review studies which have implemented DW-MRI for the purpose of early prediction of cancer treatment response.

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The traumatic experience of a heart attack may evolve into symptoms of posttraumatic stress disorder, which can be diagnosed at the earliest 1 month after myocardial infarction (MI). While several predictors of posttraumatic stress in the first year after MI have been described, we particularly sought to identify longer-term predictors and predictors of change in posttraumatic stress over time.

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When estimating the effect of treatment on HIV using data from observational studies, standard methods may produce biased estimates due to the presence of time-dependent confounders. Such confounding can be present when a covariate, affected by past exposure, is both a predictor of the future exposure and the outcome. One example is the CD4 cell count, being a marker for disease progression for HIV patients, but also a marker for treatment initiation and influenced by treatment. Fitting a marginal structural model (MSM) using inverse probability weights is one way to give appropriate adjustment for this type of confounding. In this paper we study a simple and intuitive approach to estimate similar treatment effects, using observational data to mimic several randomized controlled trials. Each 'trial' is constructed based on individuals starting treatment in a certain time interval. An overall effect estimate for all such trials is found using composite likelihood inference. The method offers an alternative to the use of inverse probability of treatment weights, which is unstable in certain situations. The estimated parameter is not identical to the one of an MSM, it is conditioned on covariate values at the start of each mimicked trial. This allows the study of questions that are not that easily addressed fitting an MSM. The analysis can be performed as a stratified weighted Cox analysis on the joint data set of all the constructed trials, where each trial is one stratum. The model is applied to data from the Swiss HIV cohort study.

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The impact of a semiquantitative commercially available test based on DNA-strip technology (microIDent®, Hain Lifescience, Nehren, Germany) on diagnosis and treatment of severe chronic periodontitis of 25 periodontitis patients was evaluated in comparison with a quantitative in-house real-time PCR. Subgingival plaque samples were collected at baseline as well as at 3, 6, and 12 months later. After extracting DNA, Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, and several other periodontopathogens were determined by both methods. The results obtained by DNA-strip technology were analyzed semiquantitatively and additionally quantitatively by densitometry. The results for the 4 major periodontopathogenic bacterial species correlated significantly between the 2 methods. Samples detecting a high bacterial load by one method and negative by the other were always found in less than 2% of the total samples. Both technologies showed the impact of treatment on microflora. Especially the semiquantitative DNA-strip technology clearly analyzed the different loads of periodontopathogens after therapy and is useful in microbial diagnostics for patients in dental practices.

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Background and purpose Intra-arterial treatment (IAT) is effective when performed within 6 h of symptom onset in selected stroke patients (‘T < 6H’). Its safety and efficacy is unclear when the patient has had symptoms for more than 6 h (‘T > 6H’) or for an unknown time (unclear-onset stroke, UOS), or woke up with a stroke (wake-up stroke, WUS). In this study we compared the safety of IAT in these four patient groups. Methods Eight-hundred and fifty-nine patients treated with IAT were enrolled. The main outcome parameters were clinical outcome [excellent: modified Rankin Scale (mRS) 0 or 1; or favorable: mRS 0–2] or mortality 3 months after treatment. Further outcome parameters were the rates of vessel recanalization, and cerebral and systemic hemorrhage. Results Six-hundred and fifty-four patients were treated before (T < 6H) and 205 after 6 h or an unknown time (128 T > 6H, 55 WUS and 22 UOS). NIHSS scores were higher in UOS patients than in T < 6H patients, vertebrobasilar occlusion was more common in T > 6H and UOS patients, and middle cerebral artery occlusions less common in T > 6H than in T < 6H patients. Other baseline characteristics were similar. There was no significant difference in clinical outcome and the rate of hemorrhage in multivariable regression analysis. Conclusions Clinical outcome of our four groups of patients was similar with no increase of hemorrhage rates in patients treated after awakening, after an unknown time or more than 6 h. Our preliminary data suggest that treatment of such patients may be performed safely. If confirmed in randomized trials, this would have major clinical implications.

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The positive and negative predictive value are standard measures used to quantify the predictive accuracy of binary biomarkers when the outcome being predicted is also binary. When the biomarkers are instead being used to predict a failure time outcome, there is no standard way of quantifying predictive accuracy. We propose a natural extension of the traditional predictive values to accommodate censored survival data. We discuss not only quantifying predictive accuracy using these extended predictive values, but also rigorously comparing the accuracy of two biomarkers in terms of their predictive values. Using a marginal regression framework, we describe how to estimate differences in predictive accuracy and how to test whether the observed difference is statistically significant.