479 research outputs found
Genotypes and haplotypes of the methyl-CpG-binding domain 2 modify breast cancer risk dependent upon menopausal status
INTRODUCTION: MBD2, the gene encoding methyl-CpG-binding domain (MBD)2, is a major methylation related gene and functions as a transcriptional repressor that can specifically bind to the methylated regions of other genes. MBD2 may also mediate gene activation because of its potential DNA demethylase activity. The present case-control study investigated associations between two single nucleotide polymorphisms (SNPs) in the MBD2 gene and breast cancer risk. METHODS: DNA samples from 393 Caucasian patients with breast cancer (cases) and 436 matched control individuals, collected in a recently completed breast cancer case–control study conducted in Connecticut, were included in the study. Because no coding SNPs were found in the MBD2 gene, one SNP in the noncoding exon (rs1259938) and another in the intron 3 (rs609791) were genotyped. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to estimate cancer risk associated with the variant genotypes and the reconstructed haplotypes. RESULTS: The variant genotypes at both SNP loci were significantly associated with reduced risk among premenopausal women (OR = 0.41 for rs1259938; OR = 0.54 for rs609791). Further haplotype analyses showed that the two rare haplotypes (A-C and A-G) were significantly associated with reduced breast cancer risk (OR = 0.40, 95% CI = 0.20–0.83 for A-C; OR = 0.47, 95% CI = 0.26–0.84 for A-G) in premenopausal women. No significant associations were detected in the postmenopausal women and the whole population. CONCLUSION: Our results demonstrate a role for the MBD2 gene in breast carcinogenesis in premenopausal women. These findings suggest that genetic variations in methylation related genes may potentially serve as a biomarker in risk estimates for breast cancer
Family coordination in families who have a child with autism spectrum disorder
Little is known about the interactions of families where there is a child with autism spectrum disorder (ASD). The present study applies the Lausanne Trilogue Play (LTP) to explore both its applicability to this population as well as to assess resources and areas of deficit in these families. The sample consisted of 68 families with a child with ASD, and 43 families with a typically developing (TD) child. With respect to the global score for family coordination there were several negative correlations: the more severe the symptoms (based on the child’s ADOS score), the more family coordination was dysfunctional. This correlation was particularly high when parents had to play together with the child. In the parts in which only one of the parents played actively with the child, while the other was simply present, some families did achieve scores in the functional range, despite the child’s symptom severity. The outcomes are discussed in terms of their clinical implications both for assessment and for interventio
Value of multidetector computed tomography image segmentation for preoperative planning in general surgery
Using practical examples, this report aims to highlight the clinical value of patient-specific three-dimensional (3D) models, obtained segmenting multidetector computed tomography (MDCT) images, for preoperative planning in general surgery.In this study, segmentation and 3D model generation were performed using a semiautomatic tool developed in the authors' laboratory. Their segmentation procedure is based on the neighborhood connected region-growing algorithm that, appropriately parameterized for the anatomy of interest and combined with the optimal segmentation sequence, generates good-quality 3D images coupled with facility of use. Using a touch screen monitor, manual refining can be added to segment structures unsuitable for automatic reconstruction. Three-dimensional models of 10 candidates for major general surgery procedures were presented to the operating surgeons for evaluation. A questionnaire then was administered after surgery to assess the perceived added value of the new technology.The questionnaire results were very positive. The authors recorded the diffuse opinion that planning the procedure using a segmented data set allows the surgeon to plan critical interventions with better awareness of the specific patient anatomy and consequently facilitates choosing the best surgical approach.The benefit shown in this report supports a wider use of segmentation software in clinical practice, even taking into account the extra time and effort required to learn and use these systems
Magnetic field-temperature phase diagram of multiferroic (NH4)2FeCl5??H2O
Owing to their overall low energy scales, flexible molecular architectures, and ease of chemical substitution, molecule-based multiferroics are extraordinarily responsive to external stimuli and exhibit remarkably rich phase diagrams. Even so, the stability and microscopic properties of various magnetic states in close proximity to quantum critical points are highly under-explored in these materials. Inspired by these opportunities, we combined pulsed-field magnetization, first-principles calculations, and numerical simulations to reveal the magnetic field???temperature (B???T) phase diagram of multiferroic (NH4)2FeCl5???H2O. In this system, a network of intermolecular hydrogen and halogen bonds creates a competing set of exchange interactions that generates additional structure in the phase diagram???both in the vicinity of the spin flop and near the 30 T transition to the fully saturated state. Consequently, the phase diagrams of (NH4)2FeCl5???H2O and its deuterated analog are much more complex than those of other molecule-based multiferroics. The entire series of coupled electric and magnetic transitions can be accessed with a powered magnet, opening the door to exploration and control of properties in this and related materials
Comparison of Rx-defined morbidity groups and diagnosis- based risk adjusters for predicting healthcare costs in Taiwan
<p>Abstract</p> <p>Background</p> <p>Medication claims are commonly used to calculate the risk adjustment for measuring healthcare cost. The Rx-defined Morbidity Groups (Rx-MG) which combine the use of medication to indicate morbidity have been incorporated into the Adjusted Clinical Groups (ACG) Case Mix System, developed by the Johns Hopkins University. This study aims to verify that the Rx-MG can be used for adjusting risk and for explaining the variations in the healthcare cost in Taiwan.</p> <p>Methods</p> <p>The Longitudinal Health Insurance Database 2005 (LHID2005) was used in this study. The year 2006 was chosen as the baseline to predict healthcare cost (medication and total cost) in 2007. The final sample size amounted to 793 239 (81%) enrolees, and excluded any cases with discontinued enrolment. Two different kinds of models were built to predict cost: the concurrent model and the prospective model. The predictors used in the predictive models included age, gender, Aggregated Diagnosis Groups (ADG, diagnosis- defined morbidity groups), and Rx-defined Morbidity Groups. Multivariate OLS regression was used in the cost prediction modelling.</p> <p>Results</p> <p>The concurrent model adjusted for Rx-defined Morbidity Groups for total cost, and controlled for age and gender had a better predictive R-square = 0.618, compared to the model adjusted for ADGs (R<sup>2 </sup>= 0.411). The model combined with Rx-MGs and ADGs performed the best for concurrently predicting total cost (R<sup>2 </sup>= 0.650). For prospectively predicting total cost, the model combined Rx-MGs and ADGs (R<sup>2 </sup>= 0.382) performed better than the models adjusted by Rx-MGs (R<sup>2 </sup>= 0.360) or ADGs (R<sup>2 </sup>= 0.252) only. Similarly, the concurrent model adjusted for Rx-MGs predicting pharmacy cost had a better performance (R-square = 0.615), than the model adjusted for ADGs (R<sup>2 </sup>= 0.431). The model combined with Rx-MGs and ADGs performed the best in concurrently as well as prospectively predicting pharmacy cost (R<sup>2 </sup>= 0.638 and 0.505, respectively). The prospective models showed a remarkable improvement when adjusted by prior cost.</p> <p>Conclusions</p> <p>The medication-based Rx-Defined Morbidity Groups was useful in predicting pharmacy cost as well as total cost in Taiwan. Combining the information on medication and diagnosis as adjusters could arguably be the best method for explaining variations in healthcare cost.</p
A primary care, multi-disciplinary disease management program for opioid-treated patients with chronic non-cancer pain and a high burden of psychiatric comorbidity
BACKGROUND: Chronic non-cancer pain is a common problem that is often accompanied by psychiatric comorbidity and disability. The effectiveness of a multi-disciplinary pain management program was tested in a 3 month before and after trial. METHODS: Providers in an academic general medicine clinic referred patients with chronic non-cancer pain for participation in a program that combined the skills of internists, clinical pharmacists, and a psychiatrist. Patients were either receiving opioids or being considered for opioid therapy. The intervention consisted of structured clinical assessments, monthly follow-up, pain contracts, medication titration, and psychiatric consultation. Pain, mood, and function were assessed at baseline and 3 months using the Brief Pain Inventory (BPI), the Center for Epidemiological Studies-Depression Scale scale (CESD) and the Pain Disability Index (PDI). Patients were monitored for substance misuse. RESULTS: Eighty-five patients were enrolled. Mean age was 51 years, 60% were male, 78% were Caucasian, and 93% were receiving opioids. Baseline average pain was 6.5 on an 11 point scale. The average CESD score was 24.0, and the mean PDI score was 47.0. Sixty-three patients (73%) completed 3 month follow-up. Fifteen withdrew from the program after identification of substance misuse. Among those completing 3 month follow-up, the average pain score improved to 5.5 (p = 0.003). The mean PDI score improved to 39.3 (p < 0.001). Mean CESD score was reduced to 18.0 (p < 0.001), and the proportion of depressed patients fell from 79% to 54% (p = 0.003). Substance misuse was identified in 27 patients (32%). CONCLUSIONS: A primary care disease management program improved pain, depression, and disability scores over three months in a cohort of opioid-treated patients with chronic non-cancer pain. Substance misuse and depression were common, and many patients who had substance misuse identified left the program when they were no longer prescribed opioids. Effective care of patients with chronic pain should include rigorous assessment and treatment of these comorbid disorders and intensive efforts to insure follow up
The association between prescription change frequency, chronic disease score and hospital admissions: a case control study
A Longitudinal Study of Medicaid Coverage for Tobacco Dependence Treatments in Massachusetts and Associated Decreases in Hospitalizations for Cardiovascular Disease
Thomas Land and colleagues show that among Massachusetts Medicaid subscribers, use of a comprehensive tobacco cessation pharmacotherapy benefit was followed by a substantial decrease in claims for hospitalizations for acute myocardial infarction and acute coronary heart disease
Hypergammaglobulinemia in the pediatric population as a marker for underlying autoimmune disease: a retrospective cohort study
Validation of a method for identifying nursing home admissions using administrative claims
<p>Abstract</p> <p>Background</p> <p>Currently there is no standard algorithm to identify whether a subject is residing in a nursing home from administrative claims. Our objective was to develop and validate an algorithm that identifies nursing home admissions at the resident-month level using the MarketScan Medicare Supplemental and Coordination of Benefit (COB) database.</p> <p>Methods</p> <p>The computer algorithms for identifying nursing home admissions were created by using provider type, place of service, and procedure codes from the 2000 – 2002 MarketScan Medicare COB database. After the algorithms were reviewed and refined, they were compared with a detailed claims review by an expert reviewer. A random sample of 150 subjects from the claims was selected and used for the validity analysis of the algorithms. Contingency table analysis, comparison of mean differences, correlations, and t-test analyses were performed. Percentage agreement, sensitivity, specificity, and Kappa statistics were analyzed.</p> <p>Results</p> <p>The computer algorithm showed strong agreement with the expert review (99.9%) for identification of the first month of nursing home residence, with high sensitivity (96.7%), specificity (100%) and a Kappa statistic of 0.97. Weighted Pearson correlation coefficient between the algorithm and the expert review was 0.97 (<it>p </it>< 0.0001).</p> <p>Conclusion</p> <p>A reliable algorithm indicating evidence of nursing home admission was developed and validated from administrative claims data. Our algorithm can be a useful tool to identify patient transitions from and to nursing homes, as well as to screen and monitor for factors associated with nursing home admission and nursing home discharge.</p
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