58 resultados para alternative p-values


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OBJECTIVE: Acute mental stress elicits blood hypercoagulability. Following a transactional stress model, we investigated whether individuals who anticipate stress as more threatening, challenging, and as exceeding their coping skills show greater stress reactivity of the coagulation activation marker D-dimer, indicating fibrin generation in plasma. METHODS: Forty-seven men (mean age 44 +/- 14 years; mean blood pressure [MBP] 101 +/- 12 mm Hg; mean body mass index [BMI] 26 +/- 3 kg/m(2)) completed the Primary Appraisal Secondary Appraisal (PASA) scale before undergoing the Trier Social Stress Test (combination of mock job interview and mental arithmetic task). Heart rate, blood pressure, plasma catecholamines, and D-dimer levels were measured before and after stress, and during recovery up to 60 minutes poststress. RESULTS: Hemodynamic measures, catecholamines, and D-dimer changed across all time points (p values <.001). The PASA "Stress Index" (integrated measure of transactional stress perception) correlated with total D-dimer area under the curve (AUC) between rest and 60 minutes poststress (r = 0.30, p = .050) and with D-dimer change from rest to immediately poststress (r = 0.29, p = .046). Primary appraisal (combined "threat" and "challenge") correlated with total D-dimer AUC (r = 0.37, p = .017), D-dimer stress change (r = 0.41, p = .004), and D-dimer recovery (r = 0.32, p = .042). "Challenge" correlated more strongly with D-dimer stress change than "threat" (p = .020). Primary appraisal (DeltaR(2) = 0.098, beta = 0.37, p = .019), and particularly its subscale "challenge" (DeltaR(2) = 0.138, beta = 0.40, p = .005), predicted D-dimer stress change independently of age, BP, BMI, and catecholamine change. CONCLUSIONS: Anticipatory cognitive appraisal determined the extent of coagulation activation to and recovery from stress in men. Particularly individuals who anticipated the stressor as more challenging and also more threatening had a greater fibrin stress response.

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BACKGROUND: Integrity of the abdominal aortic aneurysm (AAA) neck is crucial for the long-term success of endovascular AAA repair (EVAR). However, suitable tools for reliable assessment of changes in small aortic volumes are lacking. The purpose of this study was to assess the intraobserver and interobserver variability of software-enhanced 64-row computed tomographic angiography (CTA) AAA neck volume measurements in patients after EVAR. METHODS: A total of 25 consecutive patients successfully treated by EVAR underwent 64-row follow-up CTA in 1.5-mm collimation. Manual CTA measurements were performed twice by three blinded and independent readers in random order with at least a 4-week interval between readings. Maximum and minimum transverse aortic neck diameters were measured twice on two different levels within the proximal neck. Volumetry of the proximal aortic neck was performed by using dedicated software. Variability was calculated as 1.96 SD of the mean arithmetic difference according to Bland and Altman. Two-sided and paired t tests were used to compare measurements. P values <.05 were considered to indicate statistical significance. RESULTS: Intraobserver agreement was excellent for dedicated aneurysmal neck volumetry, with mean differences of less than 1 mL (P > .05), whereas it was poor for transverse aortic neck diameter measurements (P < .05). However, interobserver variability was statistically significant for both neck volumetry (P < .005) and neck diameter measurements (P < .015). CONCLUSIONS: The reliability of dedicated AAA neck volumetry by using 64-row CTA is excellent for serial measurements by individual readers, but not between different readers. Therefore, studies should be performed with aortic neck volumetry by a single experienced reader.

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The purpose of the study was to evaluate observer performance in the detection of pneumothorax with cesium iodide and amorphous silicon flat-panel detector radiography (CsI/a-Si FDR) presented as 1K and 3K soft-copy images. Forty patients with and 40 patients without pneumothorax diagnosed on previous and subsequent digital storage phosphor radiography (SPR, gold standard) had follow-up chest radiographs with CsI/a-Si FDR. Four observers confirmed or excluded the diagnosis of pneumothorax according to a five-point scale first on the 1K soft-copy image and then with help of 3K zoom function (1K monitor). Receiver operating characteristic (ROC) analysis was performed for each modality (1K and 3K). The area under the curve (AUC) values for each observer were 0.7815, 0.7779, 0.7946 and 0.7066 with 1K-matrix soft copies and 0.8123, 0.7997, 0.8078 and 0.7522 with 3K zoom. Overall detection of pneumothorax was better with 3K zoom. Differences between the two display methods were not statistically significant in 3 of 4 observers (p-values between 0.13 and 0.44; observer 4: p = 0.02). The detection of pneumothorax with 3K zoom is better than with 1K soft copy but not at a statistically significant level. Differences between both display methods may be subtle. Still, our results indicate that 3K zoom should be employed in clinical practice.

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Background: The information on bacterial colonization immediately after dental implant insertion is limited. Aims: (1) to assess the early colonization on titanium implants immediately post placement through the first12 post-surgical weeks , (2) to compare the microflora at interproximal subgingival implant and adjacent tooth sites. Material and Methods: Subgingival plaque samples from implant and neighbouring teeth were studied by checkerboard DNA-DNA hybridization before, 30 min. after implant placement , 1 week, 2 weeks, 4 weeks, 8 weeks, and 12 weerks after surgery. Results: Comparing bacterial loads at implant sites between 30 min. after placement with one week data showed that only the levels of V.parvula (p<0.05) differed with higher loads at week 1. Week 12 data demonstrated significantly higher bacterial loads for 15/40 species at tooth sites compared to pre-surgery (p < values varying between 0.05 and 0.01). Between immediately post-surgery and week 12 at implant sites 29/40 species were more commonly found at week 12. Included among these bacteria at implant sites were P.gingivalis (p< 0.05), T.forsythia, (p < 0.01), and T denticola (p<0.001). Immediately post-surgery 5.9% of implants, and 26.2% of teeth and at week 12, 15.0 % of implants, and 39.1% of teeth harbored S.aureus. Comparing tooth and implant sites, significantly higher bacterial loads were found at tooth sites for 27/40 species at the 30 minutes after placement interval. This difference increased to 35/40 species at week 12. Conclusions: The colonization of bacteria occurs within 30 minutes. Colonization patterns differed between implants and tooth surfaces.

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BACKGROUND: Information on bacterial colonization immediately after dental implant insertion is limited. AIMS: (1) To assess the early colonization on titanium implants immediately after placement and throughout the first 12 post-surgical weeks, (2) to compare the microbiota at interproximal subgingival implant and adjacent tooth sites. MATERIAL AND METHODS: Subgingival plaque samples from implant and neighbouring teeth were studied by checkerboard DNA-DNA hybridization before surgery, 30 min after implant placement, and 1, 2, 4, 8, and 12 weeks after surgery. RESULTS: Comparing bacterial loads at implant sites between 30 min after placement with 1-week data showed that only the levels of Veillonella parvula (P<0.05) differed with higher loads at week 1 post-surgically. Week 12 data demonstrated significantly higher bacterial loads for 15/40 species at tooth sites compared with pre-surgery (P-values varying between 0.05 and 0.01). Between the period immediately after surgery and 12 weeks at implant sites, 29/40 species was more commonly found at 12 weeks. Included among these bacteria at implant sites were Porphyromonas gingivalis (P<0.05), Tannerella forsythia, (P<0.01), and Treponema denticola (P<0.001). Immediately post-surgery 5.9% of implants, and 26.2% of teeth, and at week 12, 15% of implants, and 39.1% of teeth harbored Staphylococcus aureus. Comparing tooth and implant sites, significantly higher bacterial loads were found at tooth sites for 27/40 species after 30 min following implant placement. This difference increased to 35/40 species at 12 weeks post-surgically. CONCLUSIONS: Bacterial colonization occurred within 30 min after implant placement. Early colonization patterns differed between implant and tooth surfaces.

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Changes in the levels of female sex hormones during the menstrual cycle may cause cyclic differences in subgingival bacterial colonization patterns. The purpose of the present study was to test the hypothesis that hormonal changes in the menstrual cycle cause changes in the oral microbiota. METHODS: Bacterial plaque samples were collected in 20 systemically and periodontally healthy women using no hormonal contraceptives (test group) over a period of 6 weeks. Twenty age-matched systemically and periodontally healthy men were assigned to the control group. Samples were processed by checkerboard DNA-DNA hybridization assay, and 74 species were analyzed. RESULTS: No cyclic pattern of bacterial colonization was identified for any of the 74 species studied in women not using hormonal contraceptives. Aggregatibacter actinomycetemcomitans (previously Actinobacillus actinomycetemcomitans) (Y4) was common at the beginning of menstruation (mean: 32%) and increased during the following 2 weeks (36%) in women (P <0.05). No cyclic differences in bacterial presence were found among the men (P values varied between 0.14 and 0.98). Men presented with significantly higher bacterial counts for 40 of 74 species (P <0.001), including Staphylococcus aureus and Pseudomonas aeruginosa but not Porphyromonas gingivalis (P = 0.15) or Tannerella forsythia (previously T. forsythensis) (P = 0.42). CONCLUSIONS: During a menstruation period, cyclic variation in the subgingival microbiota of periodontally healthy women of child-bearing age who were not using oral hormonal contraceptives could not be confirmed. Male control subjects presented with higher levels of many species but also without a cyclic pattern.

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QUESTIONS UNDER STUDY: To assess whether the prevalence of HIV positive tests in clients at five anonymous testing sites in Switzerland had increased since the end of the 1990s, and ascertain whether there had been any concurrent change in the proportions of associated risk factors. METHODS: Baseline characteristics were analysed, by groups of years, over the eleven consecutive years of data collected from the testing sites. Numbers of HIV positive tests were presented as prevalence/1000 tests performed within each category. Multivariable analyses, stratified by African nationality and risk group of heterosexuals or men who have sex with men (MSM), were done controlling simultaneously for a series of variables. Odds ratios (ORs) were reported together with their 95% confidence intervals (CI). P values were calculated from likelihood ratio tests. RESULTS: There was an increase in the prevalence of positive tests in African heterosexuals between 1996-1999 and 2004-2006, rising from 54.2 to 86.4/1000 and from 5.6 to 25.2/1000 in females and males respectively. The proportion of MSM who knew that one or more of their sexual partners was infected with HIV increased from 2% to 17% and the proportion who reported having more than five sexual partners in the preceding two years increased from 44% to 51%. CONCLUSIONS: Surveillance data from anonymous testing sites continue to provide useful information on the changing epidemiology of HIV and thus inform public health strategies against HIV.

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OBJECTIVE: To examine whether excluding patients from the analysis of randomised trials are associated with biased estimates of treatment effects and higher heterogeneity between trials. DESIGN: Meta-epidemiological study based on a collection of meta-analyses of randomised trials. DATA SOURCES: 14 meta-analyses including 167 trials that compared therapeutic interventions with placebo or non-intervention control in patients with osteoarthritis of the hip or knee and used patient reported pain as an outcome. METHODS: Effect sizes were calculated from differences in means of pain intensity between groups at the end of follow-up, divided by the pooled standard deviation. Trials were combined by using random effects meta-analysis. Estimates of treatment effects were compared between trials with and trials without exclusions from the analysis, and the impact of restricting meta-analyses to trials without exclusions was assessed. RESULTS: 39 trials (23%) had included all patients in the analysis. In 128 trials (77%) some patients were excluded from the analysis. Effect sizes from trials with exclusions tended to be more beneficial than those from trials without exclusions (difference -0.13, 95% confidence interval -0.29 to 0.04). However, estimates of bias between individual meta-analyses varied considerably (tau(2)=0.07). Tests of interaction between exclusions from the analysis and estimates of treatment effects were positive in five meta-analyses. Stratified analyses indicated that differences in effect sizes between trials with and trials without exclusions were more pronounced in meta-analyses with high between trial heterogeneity, in meta-analyses with large estimated treatment benefits, and in meta-analyses of complementary medicine. Restriction of meta-analyses to trials without exclusions resulted in smaller estimated treatment benefits, larger P values, and considerable decreases in between trial heterogeneity. CONCLUSION: Excluding patients from the analysis in randomised trials often results in biased estimates of treatment effects, but the extent and direction of bias is unpredictable. Results from intention to treat analyses should always be described in reports of randomised trials. In systematic reviews, the influence of exclusions from the analysis on estimated treatment effects should routinely be assessed.

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The aim of this study was to compare standard plaster models with their digital counterparts for the applicability of the Index of Complexity, Outcome, and Need (ICON). Generated study models of 30 randomly selected patients: 30 pre- (T(0)) and 30 post- (T(1)) treatment. Two examiners, calibrated in the ICON, scored the digital and plaster models. The overall ICON scores were evaluated for reliability and reproducibility using kappa statistics and reliability coefficients. The values for reliability of the total and weighted ICON scores were generally high for the T(0) sample (range 0.83-0.95) but less high for the T(1) sample (range 0.55-0.85). Differences in total ICON score between plaster and digital models resulted in mostly statistically insignificant values (P values ranging from 0.07 to 0.19), except for observer 1 in the T(1) sample. No statistically different values were found for the total ICON score on either plaster or digital models. ICON scores performed on computer-based models appear to be as accurate and reliable as ICON scores on plaster models.

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OBJECTIVES To identify factors associated with discrepant outcome reporting in randomized drug trials. STUDY DESIGN AND SETTING Cohort study of protocols submitted to a Swiss ethics committee 1988-1998: 227 protocols and amendments were compared with 333 matching articles published during 1990-2008. Discrepant reporting was defined as addition, omission, or reclassification of outcomes. RESULTS Overall, 870 of 2,966 unique outcomes were reported discrepantly (29.3%). Among protocol-defined primary outcomes, 6.9% were not reported (19 of 274), whereas 10.4% of reported outcomes (30 of 288) were not defined in the protocol. Corresponding percentages for secondary outcomes were 19.0% (284 of 1,495) and 14.1% (334 of 2,375). Discrepant reporting was more likely if P values were <0.05 compared with P ≥ 0.05 [adjusted odds ratio (aOR): 1.38; 95% confidence interval (CI): 1.07, 1.78], more likely for efficacy compared with harm outcomes (aOR: 2.99; 95% CI: 2.08, 4.30) and more likely for composite than for single outcomes (aOR: 1.48; 95% CI: 1.00, 2.20). Cardiology (aOR: 2.34; 95% CI: 1.44, 3.79) and infectious diseases (aOR: 1.77; 95% CI: 1.01, 3.13) had more discrepancies compared with all specialties combined. CONCLUSION Discrepant reporting was associated with statistical significance of results, type of outcome, and specialty area. Trial protocols should be made freely available, and the publications should describe and justify any changes made to protocol-defined outcomes.

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We investigated patients with a primary diagnosis of peripheral artery disease (n = 69) and coronary heart disease (CAD; n = 520) at baseline and on changes in psychosocial risk factors (depression, anxiety, quality of life, negative and positive affect) during a cardiovascular rehabilitation program. Patients completed psychosocial questionnaires at the beginning and at discharge of a 12-week rehabilitation program. Depression and anxiety were measured with the Hospital Anxiety and Depression Scale (HADS), positive and negative affect with the Global Mood Scale, and health-related quality of life with the SF-36 Health Survey. Patients with PAD showed improvements in anxiety (p < 0.001), negative affect (p < 0.001) and bodily pain (p < 0.001). Patients with CAD reported significant improvements in all measured dimensions (all p-values < 0.001).

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OBJECTIVES In dental research multiple site observations within patients or taken at various time intervals are commonplace. These clustered observations are not independent; statistical analysis should be amended accordingly. This study aimed to assess whether adjustment for clustering effects during statistical analysis was undertaken in five specialty dental journals. METHODS Thirty recent consecutive issues of Orthodontics (OJ), Periodontology (PJ), Endodontology (EJ), Maxillofacial (MJ) and Paediatric Dentristry (PDJ) journals were hand searched. Articles requiring adjustment accounting for clustering effects were identified and statistical techniques used were scrutinized. RESULTS Of 559 studies considered to have inherent clustering effects, adjustment for this was made in the statistical analysis in 223 (39.1%). Studies published in the Periodontology specialty accounted for clustering effects in the statistical analysis more often than articles published in other journals (OJ vs. PJ: OR=0.21, 95% CI: 0.12, 0.37, p<0.001; MJ vs. PJ: OR=0.02, 95% CI: 0.00, 0.07, p<0.001; PDJ vs. PJ: OR=0.14, 95% CI: 0.07, 0.28, p<0.001; EJ vs. PJ: OR=0.11, 95% CI: 0.06, 0.22, p<0.001). A positive correlation was found between increasing prevalence of clustering effects in individual specialty journals and correct statistical handling of clustering (r=0.89). CONCLUSIONS The majority of studies in 5 dental specialty journals (60.9%) examined failed to account for clustering effects in statistical analysis where indicated, raising the possibility of inappropriate decreases in p-values and the risk of inappropriate inferences.

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OBJECTIVES Optical scanners combined with computer-aided design and computer-aided manufacturing (CAD/CAM) technology provide high accuracy in the fabrication of titanium (TIT) and zirconium dioxide (ZrO) bars. The aim of this study was to compare the precision of fit of CAD/CAM TIT bars produced with a photogrammetric and a laser scanner. METHODS Twenty rigid CAD/CAM bars were fabricated on one single edentulous master cast with 6 implants in the positions of the second premolars, canines and central incisors. A photogrammetric scanner (P) provided digitized data for TIT-P (n=5) while a laser scanner (L) was used for TIT-L (n=5). The control groups consisted of soldered gold bars (gold, n=5) and ZrO-P with similar bar design. Median vertical distance between implant and bar platforms from non-tightened implants (one-screw test) was calculated from mesial, buccal and distal scanning electron microscope measurements. RESULTS Vertical microgaps were not significantly different between TIT-P (median 16μm; 95% CI 10-27μm) and TIT-L (25μm; 13-32μm). Gold (49μm; 12-69μm) had higher values than TIT-P (p=0.001) and TIT-L (p=0.008), while ZrO-P (35μm; 17-55μm) exhibited higher values than TIT-P (p=0.023). Misfit values increased in all groups from implant position 23 (3 units) to 15 (10 units), while in gold and TIT-P values decreased from implant 11 toward the most distal implant 15. SIGNIFICANCE CAD/CAM titanium bars showed high precision of fit using photogrammetric and laser scanners. In comparison, the misfit of ZrO bars (CAM/CAM, photogrammetric scanner) and soldered gold bars was statistically higher but values were clinically acceptable.

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Coat color and pattern variations in domestic animals are frequently inherited as simple monogenic traits, but a number are known to have a complex genetic basis. While the analysis of complex trait data remains a challenge in all species, we can use the reduced haplotypic diversity in domestic animal populations to gain insight into the genomic interactions underlying complex phenotypes. White face and leg markings are examples of complex traits in horses where little is known of the underlying genetics. In this study, Franches-Montagnes (FM) horses were scored for the occurrence of white facial and leg markings using a standardized scoring system. A genome-wide association study (GWAS) was performed for several white patterning traits in 1,077 FM horses. Seven quantitative trait loci (QTL) affecting the white marking score with p-values p≤10(-4) were identified. Three loci, MC1R and the known white spotting genes, KIT and MITF, were identified as the major loci underlying the extent of white patterning in this breed. Together, the seven loci explain 54% of the genetic variance in total white marking score, while MITF and KIT alone account for 26%. Although MITF and KIT are the major loci controlling white patterning, their influence varies according to the basic coat color of the horse and the specific body location of the white patterning. Fine mapping across the MITF and KIT loci was used to characterize haplotypes present. Phylogenetic relationships among haplotypes were calculated to assess their selective and evolutionary influences on the extent of white patterning. This novel approach shows that KIT and MITF act in an additive manner and that accumulating mutations at these loci progressively increase the extent of white markings.

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The improvement of meat quality and production traits has high priority in the pork industry. Many of these traits show a low to moderate heritability and are difficult and expensive to measure. Their improvement by targeted breeding programs is challenging and requires knowledge of the genetic and molecular background. For this study we genotyped 192 artificial insemination boars of a commercial line derived from the Swiss Large White breed using the PorcineSNP60 BeadChip with 62,163 evenly spaced SNPs across the pig genome. We obtained 26 estimated breeding values (EBVs) for various traits including exterior, meat quality, reproduction, and production. The subsequent genome-wide association analysis allowed us to identify four QTL with suggestive significance for three of these traits (p-values ranging from 4.99×10⁻⁶ to 2.73×10⁻⁵). Single QTL for the EBVs pH one hour post mortem (pH1) and carcass length were on pig chromosome (SSC) 14 and SSC 2, respectively. Two QTL for the EBV rear view hind legs were on SSC 10 and SSC 16.