907 resultados para proportional odds logistic regression analysis


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In this study, the surface properties of and work required to remove 12 commercially available and developmental catheters from a model biological medium (agar), a measure of catheter lubricity, were characterised and the relationships between these properties were examined using multiple regression and correlation analysis. The work required for removal of catheter sections (7 cm) from a model biological medium (1% w/w agar) were examined using tensile analysis. The water wettability of the catheters were characterised using dynamic contact angle analysis, whereas surface roughness was determined using atomic force microscopy. Significant differences in the ease of removal were observed between the various catheters, with the silicone-based materials generally exhibiting the greatest ease of removal. Similarly, the catheters exhibited a range of advancing and receding contact angles that were dependent on the chemical nature of each catheter. Finally, whilst the microrugosities of the various catheters differed, no specific relationship to the chemical nature of the biomaterial was apparent. Using multiple regression analysis, the relationship between ease of removal, receding contact angle and surface roughness was defined as: Work done (N mm) 17.18 + 0.055 Rugosity (nm)-0.52 Receding contact angle (degrees) (r = 0.49). Interestingly, whilst the relationship between ease of removal and surface roughness was significant (r = 0.48, p = 0.0005), in which catheter lubricity increased as the surface roughness decreased, this was not the case with the relationship between ease of removal and receding contact angle (r = -0.18, p > 0.05). This study has therefore uniquely defined the contributions of each of these surface properties to catheter lubricity. Accordingly, in the design of urethral catheters. it is recommended that due consideration should be directed towards biomaterial surface roughness to ensure maximal ease of catheter removal. Furthermore, using the method described in this study, differences in the lubricity of the various catheters were observed that may be apparent in their clinical use. (C) 2003 Elsevier Ltd. All rights reserved.

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BACKGROUND: Deposition of beta-amyloid in the brains of patients with Alzheimer's disease is thought to precede a chain of events that leads to an inflammatory response by the brain. We postulated that genetic variation in the regulatory region of the gene for the proinflammatory cytokine tumour necrosis factor alpha (TNF-alpha) leads to increased risk of Alzheimer's disease and vascular dementia. METHODS: A polymorphism in the regulatory region of the TNF-alpha gene was analysed in a case-control study. The polymorphism (C-850T) was typed in 242 patients with sporadic Alzheimer's disease, 81 patients with vascular dementia, 61 stroke patients without dementia, and 235 normal controls. These groups of individuals were also genotyped for the apolipoprotein E polymorphism, and the vascular dementia and stroke groups were typed at the HLA-DR locus. FINDINGS: The distribution of TNF-alpha genotypes in the vascular dementia group differed significantly from that in the stroke and normal control groups, giving an odds ratio of 2.51 (95% CI 1.49-4.21) for the development of vascular dementia for individuals with a CT or TT genotype. Logistic regression analysis indicated that the possession of the T allele significantly increased the risk of Alzheimer's disease associated with carriage of the apolipoprotein E epsilon4 allele (odds ratio 2.73 [1.68-4.44] for those with apolipoprotein E epsilon4 but no TNF-alpha T, vs 4.62 [2.38-8.96] for those with apolipoprotein E epsilon4 and TNF-alpha T; p=0.03). INTERPRETATION: Possession of the TNF-alpha T allele significantly increases the risk of vascular dementia, and increases the risk of Alzheimer's disease associated with apolipoprotein E. Although further research is needed, these findings suggest a potential role for anti-inflammatory therapy in vascular dementia and Alzheimer's disease, and perhaps especially in patients who have had a stroke.

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Objective: Endothelial function may be impaired in critical illness. We hypothesized that impaired endothelium-dependent vasodilatation is a predictor of mortality in critically ill patients.
Design: Prospective observational cohort study.
Setting: Seventeen-bed adult intensive care unit in a tertiary referral university teaching hospital. Patients: Patients were recruited within 24 hrs of admission to the intensive care unit.
Interventions: The SphygmoCor Mx system was used to derive the aortic augmentation index from radial artery pulse pressure waveforms. Endothelium-dependent vasodilatation was calculated as the change in augmentation index in response to an endothelium-dependent vasodilator (salbutamol).
Measurements and Main Results: Demographics, severity of illness scores, and physiological parameters were collected. Statistically significant predictors of mortality identified using single regressor analysis were entered into a multiple logistic regression model. Receiver operator characteristic curves were generated. Ninety-four patients completed the study. There were 80 survivors and 14 nonsurvivors. The Simplified Acute Physiology Score II, the Sequential Organ Failure Assessment score, leukocyte count, and endothelium-dependent vasodilatation conferred an increased risk of mortality. In logistic regression analysis, endothelium-dependent vasodilatation was the only predictor of mortality with an adjusted odds ratio of 26.1 (95% confidence interval [CI], 4.3-159.5). An endothelium-dependent vasodilatation value of 0.5% or less predicted intensive care unit mortality with a sensitivity of 79% (CI, 59-88%) and specificity of 98% (CI, 94-99%).
Conclusions: In vivo bedside assessment of endothelium-dependent vasodilatation is an independent predictor of mortality in the critically ill. We have shown it to be superior to other validated severity of illness scores with high sensitivity and specificity.

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Aims: To examine whether job strain (ie, excessive demands combined with low control) is related to smoking cessation.

Methods: Prospective cohort study of 4928 Finnish employees who were baseline smokers. In addition to individual scores, coworker-assessed work unit level scores were calculated. A multilevel logistic regression analysis, with work units at the second level, was performed.

Results: At follow-up, 21% of baseline smokers had quit smoking. After adjustment for sex, age, employer and marital status, elevated odds ratios (ORs) for smoking cessation were found for the lowest vs the highest quartile of work unit level job strain (OR 1.43, 95% CI 1.17 to 1.75) and for the highest vs the lowest quartile of work unit level job control (OR 1.61, 95% CI 1.31 to 1.96). After additional adjustment for health behaviours and trait anxiety, similar results were observed. Further adjustment for socioeconomic position slightly attenuated these associations, but an additional adjustment for individual strain/control had little effect on the results. The association between job strain and smoking cessation was slightly stronger in light than in moderate/heavy smokers. The results for individual job strain and job control were in the same direction as the work unit models, although these relationships became insignificant after adjustment for socioeconomic position. Job demands were not associated with smoking cessation.

Conclusions: Smoking cessation may be less likely in workplaces with high strain and low control. Policies and programs addressing employee job strain and control might also contribute to the effectiveness of smoking cessation interventions.

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In a prospective cohort study of Finnish public sector employees, the authors examined the association between workplace social capital and depression. Data were obtained from 33,577 employees, who had no recent history of antidepressant treatment and who reported no history of physician-diagnosed depression at baseline in 2000-2002. Their risk of depression was measured with two indicators: recorded purchases of antidepressants until December 31, 2005, and self-reports of new-onset depression diagnosed by a physician in the follow-up survey in 2004-2005. Multilevel logistic regression analysis was used to explore whether self-reported and aggregate-level workplace social capital predicted indicators of depression at follow-up. The odds for antidepressant treatment and physician-diagnosed depression were 20-50% higher for employees with low self-reported social capital than for those reporting high social capital. These associations were not accounted for by sex, age, marital status, socioeconomic position, place of work, smoking, alcohol use, physical activity, and body mass index. The association between social capital and self-reported depression attenuated but remained significant after further adjustment for baseline psychological distress (a proxy for undiagnosed mental health problems). Aggregate-level social capital was not associated with subsequent depression.

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Trace elements have been cited as both inhibitory and causative agents of cancer but importantly exposure to them is potentially modifiable. Our study aimed to examine toenail trace element status and risk of Barrett's oesophagus (BO) and oesophageal adenocarcinoma (OAC). Toenail clippings from each hallux were obtained from 638 participants of the FINBAR (Factors Influencing the Barrett's Adenocarcinoma Relationship) study comprising 221 healthy controls, 98 reflux oesophagitis, 182 BO and 137 OAC cases. The concentrations of eight toenail trace elements were determined using instrumental neutron activation analysis. Using multivariable adjusted logistic regression analysis, odds ratios (OR) and 95% confidence intervals (CIs) were calculated within tertiles of trace element concentrations. A twofold increased risk of BO was observed, but not OAC, among individuals in the highest tertile of toenail zinc status OR 2.21 (95% CI, 1.11-4.40). A higher toenail selenium status was not associated with risk of OAC OR 0.94 (95% CI, 0.44-2.04) or BO OR 0.89 (95% CI, 0.37-2.12). A borderline significant increased risk of BO was detected with a higher toenail cobalt concentration, OR 1.97 (95% CI, 1.01-3.85). No association was found between toenail levels of chromium, cerium, mercury and OAC or BO risk. This is the first case-control study to investigate a variety of trace elements in relation to OAC and BO risk. Despite antioxidant and proapoptotic properties, no associations were found with selenium. Higher concentrations of toenail zinc and cobalt were associated with an increased BO risk, but not OAC. These findings need confirmation in prospective analysis.

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Discrete Conditional Phase-type (DC-Ph) models are a family of models which represent skewed survival data conditioned on specific inter-related discrete variables. The survival data is modeled using a Coxian phase-type distribution which is associated with the inter-related variables using a range of possible data mining approaches such as Bayesian networks (BNs), the Naïve Bayes Classification method and classification regression trees. This paper utilizes the Discrete Conditional Phase-type model (DC-Ph) to explore the modeling of patient waiting times in an Accident and Emergency Department of a UK hospital. The resulting DC-Ph model takes on the form of the Coxian phase-type distribution conditioned on the outcome of a logistic regression model.

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Background: We sought to determine if a common polymorphism can influence vulnerability to LDL cholesterol, and thereby influence the clinical benefit derived from therapies that reduce LDL cholesterol.

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BACKGROUND & AIMS: The risk of progression of Barrett's esophagus (BE) to esophageal adenocarcinoma (EAC) is low and difficult to calculate. Accurate tools to determine risk are needed to optimize surveillance and intervention. We assessed the ability of candidate biomarkers to predict which cases of BE will progress to EAC or high-grade dysplasia and identified those that can be measured in formalin-fixed tissues. METHODS: We analyzed data from a nested case-control study performed using the population-based Northern Ireland BE Register (1993-2005). Cases who progressed to EAC (n = 89) or high-grade dysplasia =6 months after diagnosis with BE were matched to controls (nonprogressors, n = 291), for age, sex, and year of BE diagnosis. Established biomarkers (abnormal DNA content, p53, and cyclin A expression) and new biomarkers (levels of sialyl Lewis(a), Lewis(x), and Aspergillus oryzae lectin [AOL] and binding of wheat germ agglutinin) were assessed in paraffin-embedded tissue samples from patients with a first diagnosis of BE. Conditional logistic regression analysis was applied to assess odds of progression for patients with dysplastic and nondysplastic BE, based on biomarker status. RESULTS: Low-grade dysplasia and all biomarkers tested, other than Lewis(x), were associated with risk of EAC or high-grade dysplasia. In backward selection, a panel comprising low-grade dysplasia, abnormal DNA ploidy, and AOL most accurately identified progressors and nonprogressors. The adjusted odds ratio for progression of patients with BE with low-grade dysplasia was 3.74 (95% confidence interval, 2.43-5.79) for each additional biomarker and the risk increased by 2.99 for each additional factor (95% confidence interval, 1.72-5.20) in patients without dysplasia. CONCLUSIONS: Low-grade dysplasia, abnormal DNA ploidy, and AOL can be used to identify patients with BE most likely to develop EAC or high-grade dysplasia.

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Many of the most interesting questions ecologists ask lead to analyses of spatial data. Yet, perhaps confused by the large number of statistical models and fitting methods available, many ecologists seem to believe this is best left to specialists. Here, we describe the issues that need consideration when analysing spatial data and illustrate these using simulation studies. Our comparative analysis involves using methods including generalized least squares, spatial filters, wavelet revised models, conditional autoregressive models and generalized additive mixed models to estimate regression coefficients from synthetic but realistic data sets, including some which violate standard regression assumptions. We assess the performance of each method using two measures and using statistical error rates for model selection. Methods that performed well included generalized least squares family of models and a Bayesian implementation of the conditional auto-regressive model. Ordinary least squares also performed adequately in the absence of model selection, but had poorly controlled Type I error rates and so did not show the improvements in performance under model selection when using the above methods. Removing large-scale spatial trends in the response led to poor performance. These are empirical results; hence extrapolation of these findings to other situations should be performed cautiously. Nevertheless, our simulation-based approach provides much stronger evidence for comparative analysis than assessments based on single or small numbers of data sets, and should be considered a necessary foundation for statements of this type in future.

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Neprilysin (NEP), also known as membrane metalloendopeptidase (MME), is considered amongst the most important ß-amyloid (Aß)-degrading enzymes with regard to prevention of Alzheimer's disease (AD) pathology. Variation in the NEP gene (MME) has been suggested as a risk factor for AD. We conducted a genetic association study of 7MME SNPs - rs1836914, rs989692, rs9827586, rs6797911, rs61760379, rs3736187, rs701109 - with respect to AD risk in a cohort of 1057 probable and confirmed AD cases and 424 age-matched non-demented controls from the United Kingdom, Italy and Sweden. We also examined the association of these MME SNPs with NEP protein level and enzyme activity, and on biochemical measures of Aß accumulation in frontal cortex - levels of total soluble Aß, oligomeric Aß(1-42), and guanidine-extractable (insoluble) Aß - in a sub-group of AD and control cases with post-mortem brain tissue. On multivariate logistic regression analysis one of the MME variants (rs6797911) was associated with AD risk (P = 0.00052, Odds Ratio (O.R. = 1.40, 95% confidence interval (1.16-1.70)). None of the SNPs had any association with Aß levels; however, rs9827586 was significantly associated with NEP protein level (p=0.014) and enzyme activity (p=0.006). Association was also found between rs701109 and NEP protein level (p=0.026) and a marginally non-significant association was found for rs989692 (p=0.055). These data suggest that MME variation may be associated with AD risk but we have not found evidence that this is mediated through modification of NEP protein level or activity.

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The aim of our study was to investigate whether dietary fat and meat intakes are associated with reflux esophagitis (RE), Barrett's esophagus (BE) and esophageal adenocarcinoma (EAC). In this all-Ireland case-control study, dietary intake data were collected using a food frequency questionnaire in 219 RE patients, 220 BE patients, 224 EAC patients and 256 frequency-matched controls between 2002 and 2005. Unconditional multiple logistic regression analysis was used to examine the association between dietary variables and disease risk using quartiles of intake, to attain odds ratios (ORs) and 95% confidence intervals (95% CIs), while adjusting for potential confounders. Patients in the highest quartile of total fat intake had a higher risk of RE (OR = 3.54; 95% CI = 1.32-9.46) and EAC (OR = 5.44; 95% CI = 2.08-14.27). A higher risk of RE and EAC was also reported for patients in the highest quartile of saturated fat intake (OR = 2.79; 95% CI = 1.11-7.04; OR = 2.41; 95% CI = 1.14-5.08, respectively) and monounsaturated fat intake (OR = 2.63; 95% CI = 1.01-6.86; OR = 5.35; 95% CI = 2.14-13.34, respectively). Patients in the highest quartile of fresh red meat intake had a higher risk of EAC (OR = 3.15; 95% CI = 1.38-7.20). Patients in the highest category of processed meat intake had a higher risk of RE (OR = 4.67; 95% CI = 1.71-12.74). No consistent associations were seen for BE with either fat or meat intakes. Further studies investigating the association between dietary fat and food sources of fat are needed to confirm these results.

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Purpose: To evaluate adherence to prescribed antiepileptic drugs (AEDs) in children with epilepsy using a combination of adherence-assessment methods.
Methods: A total of 100 children with epilepsy (=17 years old) were recruited. Medication adherence was determined via parental and child self-reporting (=9 years old), medication refill data from general practitioner (GP) prescribing records, and via AED concentrations in dried blood spot (DBS) samples obtained from children at the clinic and via self- or parental-led sampling in children's own homes. The latter were assessed using population pharmacokinetic modeling. Patients were deemed nonadherent if any of these measures were indicative of nonadherence with the prescribed treatment. In addition, beliefs about medicines, parental confidence in seizure management, and the presence of depressed mood in parents were evaluated to examine their association with nonadherence in the participating children.
Key Findings: The overall rate of nonadherence in children with epilepsy was 33%. Logistic regression analysis indicated that children with generalized epilepsy (vs. focal epilepsy) were more likely (odds ratio [OR] 4.7, 95% confidence interval [CI] 1.37-15.81) to be classified as nonadherent as were children whose parents have depressed mood (OR 3.6, 95% CI 1.16-11.41).
Significance: This is the first study to apply the novel methodology of determining adherence via AED concentrations in clinic and home DBS samples. The present findings show that the latter, with further development, could be a useful approach to adherence assessment when combined with other measures including parent and child self-reporting. Seizure type and parental depressed mood were strongly predictive of nonadherence. © 2013 International League Against Epilepsy.
Key Words: Adherence, Epilepsy, Dried blood spots, MARS, Depressed mood.