970 resultados para Location-Allocation Models


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Objective: Bronchial typical carcinoid tumors are tow-grade malignancies. However, metastases are diagnosed in some patients. Predicting the individual risk of these metastases to determine patients eligible for a radical lymphadenectomy and patients to be followed-up because of distant metastasis risk is relevant. Our objective was to screen for predictive criteria of bronchial typical carcinoid tumor aggressiveness based on a logistic regression model using clinical, pathological and biomolecular data. Methods: A multicenter retrospective cohort study, including 330 consecutive patients operated on for bronchial typical carcinoid tumors and followed-up during a period more than 10 years in two university hospitals was performed. Selected data to predict the individual risk for both nodal and distant metastasis were: age, gender, TNM staging, tumor diameter and location (central/peripheral), tumor immunostaining index of p53 and Ki67, Bcl2 and the extracellular density of neoformed microvessels and of collagen/elastic extracellular fibers. Results: Nodal and distant metastasis incidence was 11% and 5%, respectively. Univariate analysis identified all the studied biomarkers as related to nodal metastasis. Multivariate analysis identified a predictive variable for nodal metastasis: neo angiogenesis, quantified by the neoformed pathological microvessels density. Distant metastasis was related to mate gender. Discussion: Predictive models based on clinical and biomolecular data could be used to predict individual risk for metastasis. Patients under a high individual risk for lymph node metastasis should be considered as candidates to mediastinal lymphadenectomy. Those under a high risk of distant metastasis should be followed-up as having an aggressive disease. Conclusion: Individual risk prediction of bronchial typical carcinoid tumor metastasis for patients operated on can be calculated in function of biomolecular data. Prediction models can detect high-risk patients and help surgeons to identify patients requiring radical lymphadenectomy and help oncologists to identify those as having an aggressive disease requiring prolonged follow-up. (C) 2008 European Association for Cardio-Thoracic Surgery. Published by Elsevier B.V. All rights reserved.

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Background: Positive surgical margin (PSM) after radical prostatectomy (RP) has been shown to be an independent predictive factor for cancer recurrence. Several investigations have correlated clinical and histopathologic findings with surgical margin status after open RP. However, few studies have addressed the predictive factors for PSM after robot-assisted laparoscopic RP (RARP). Objective: We sought to identify predictive factors for PSMs and their locations after RARP. Design, setting, and participants: We prospectively analyzed 876 consecutive patients who underwent RARP from January 2008 to May 2009. Intervention: All patients underwent RARP performed by a single surgeon with previous experience of > 1500 cases. Measurements: Stepwise logistic regression was used to identify potential predictive factors for PSM. Three logistic regression models were built: (1) one using preoperative variables only, (2) another using all variables (preoperative, intraoperative, and postoperative) combined, and (3) one created to identify potential predictive factors for PSM location. Preoperative variables entered into the models included age, body mass index (BMI), prostate-specific antigen, clinical stage, number of positive cores, percentage of positive cores, and American Urological Association symptom score. Intra-and postoperative variables analyzed were type of nerve sparing, presence of median lobe, percentage of tumor in the surgical specimen, gland size, histopathologic findings, pathologic stage, and pathologic Gleason grade. Results and limitations: In the multivariable analysis including preoperative variables, clinical stage was the only independent predictive factor for PSM, with a higher PSM rate for T3 versus T1c (odds ratio [OR]: 10.7; 95% confidence interval [CI], 2.6-43.8) and for T2 versus T1c (OR: 2.9; 95% CI, 1.9-4.6). Considering pre-, intra-, and postoperative variables combined, percentage of tumor, pathologic stage, and pathologic Gleason score were associated with increased risk of PSM in the univariable analysis (p < 0.001 for all variables). However, in the multivariable analysis, pathologic stage (pT2 vs pT1; OR: 2.9; 95% CI, 1.9-4.6) and percentage of tumor in the surgical specimen (OR: 8.7; 95% CI, 2.2-34.5; p = 0.0022) were the only independent predictive factors for PSM. Finally, BMI was shown to be an independent predictive factor(OR: 1.1; 95% CI, 1.0-1.3; p = 0.0119) for apical PSMs, with increasing BMI predicting higher incidence of apex location. Because most of our patients were referred from other centers, the biopsy technique and the number of cores were not standardized in our series. Conclusions: Clinical stage was the only preoperative variable independently associated with PSM after RARP. Pathologic stage and percentage of tumor in the surgical specimen were identified as independent predictive factors for PSMs when analyzing pre-, intra-, and postoperative variables combined. BMI was shown to be an independent predictive factor for apical PSMs. (C) 2010 European Association of Urology. Published by Elsevier B. V. All rights reserved.

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Background and objective: Tuberculosis (TB) and cancer are two of the main causes of pleural effusions which frequently share similar clinical features and pleural fluid profiles. This study aimed to identify diagnostic models based on clinical and laboratory variables to differentiate tuberculous from malignant pleural effusions. Methods: A retrospective study of 403 patients (200 with TB; 203 with cancer) was undertaken. Univariate analysis was used to select the clinical variables relevant to the models composition. Variables beta coefficients were used to define a numerical score which presented a practical use. The performances of the most efficient models were tested in a sample of pleural exudates (64 new cases). Results: Two models are proposed for the diagnosis of effusions associated with each disease. For TB: (i) adenosine deaminase (ADA), globulins and the absence of malignant cells in the pleural fluid; and (ii) ADA, globulins and fluid appearance. For cancer: (i) patient age, fluid appearance, macrophage percentage and presence of atypical cells in the pleural fluid; and (ii) as for (i) excluding atypical cells. Application of the models to the 64 pleural effusions showed accuracy higher than 85% for all models. Conclusions: The proposed models were effective in suggesting pleural tuberculosis or cancer.

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The pathogenic mechanisms of Leptospira interrogans, the causal agent of leptospirosis, remain largely unknown. This is mainly due to the lack of tools for genetically manipulating pathogenic Leptospira species. Thus, homologous recombination between introduced DNA and the corresponding chromosomal locus has never been demonstrated for this pathogen. Leptospiral immunoglobulin-like repeat (Lig) proteins were previously identified as putative Leptospira virulence factors. In this study, a ligB mutant was constructed by allelic exchange in L. interrogans; in this mutant a spectinomycin resistance (Spc(r)) gene replaced a portion of the ligB coding sequence. Gene disruption was confirmed by PCR, immunoblot analysis, and immunofluorescence studies. The ligB mutant did not show decrease virulence compared to the wild-type strain in the hamster model of leptospirosis. In addition, inoculation of rats with the ligB mutant induced persistent colonization of the kidneys. Finally, LigB was not required to mediate bacterial adherence to cultured cells. Taken together, our data provide the first evidence of site-directed homologous recombination in pathogenic Leptospira species. Furthermore, our data suggest that LigB does not play a major role in dissemination of the pathogen in the host and in the development of acute disease manifestations or persistent renal colonization.

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Excessive free-radical production due to various bacterial components released during bacterial infection has been linked to cell death and tissue injury. Peroxynitrite is a highly reactive oxidant produced by the combination of nitric oxide (NO) and superoxide anion, which has been implicated in cell death and tissue injury in various forms of critical illness. Pharmacological decomposition of peroxynitrite may represent a potential therapeutic approach in diseases associated with the overproduction of NO and superoxide. In the present study, we tested the effect of a potent peroxynitrite decomposition catalyst in murine models of endotoxemia and sepsis. Mice were injected i.p. with LPS 40 mg/kg with or without FP15 [Fe(III) tetrakis-2-(N-triethylene glycol monomethyl ether) pyridyl porphyrin] (0.1, 0.3, 1, 3, or 10 mg/kg per hour). Mice were killed 12 h later, followed by the harvesting of samples from the lung, liver, and gut for malondialdehyde and myeloperoxidase measurements. In other subsets of animals, blood samples were obtained by cardiac puncture at 1.5, 4, and 8 h after LPS administration for cytokine (TNF-alpha, IL-1 beta, and IL-10), nitrite/nitrate, alanine aminotransferase, and blood urea nitrogen measurements. Endotoxemic animals showed an increase in survival from 25% to 80% at the FP15 doses of 0.3 and 1 mg/kg per hour. The same dose of FP15 had no effect on plasma levels of nitrite/nitrate. There was a reduction in liver and lung malondialdehyde in the endotoxemic animals pretreated with FP15, as well as in hepatic myeloperoxidase and biochemical markers of liver and kidney damage (alanine aminotransferase and blood urea nitrogen). In a bacterial model of sepsis induced by cecal ligation and puncture, FP15 treatment (0.3 mg/kg per day) significantly protected against mortality. The current data support the view that peroxynitrite is a critical factor mediating liver, gut, and lung injury in endotoxemia and septic shock: its pharmacological neutralization may be of therapeutic benefit.

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The adenovirus type 5 (Ad5)-based vaccine developed by Merck failed to either prevent HIV-1 infection or suppress viral load in subsequently infected subjects in the STEP human Phase 2b efficacy trial. Analogous vaccines had previously also failed in the simian immunodeficiency virus (SIV) challenge-rhesus macaque model. In contrast, vaccine protection studies that used challenge with a chimeric simian-human immunodeficiency virus (SHIV89.6P) in macaques did not predict the human trial results. Ad5 vector -based vaccines did not protect macaques from infection after SHIV89.6P challenge but did cause a substantial reduction in viral load and a preservation of CD4(+) T cell counts after infection, findings that were not reproduced in the human trials. Although the SIV challenge model is incompletely validated, we propose that its expanded use can help facilitate the prioritization of candidate HIV-1 vaccines, ensuring that resources are focused on the most promising candidates. Vaccine designers must now develop T cell vaccine strategies that reduce viral load after heterologous challenge.