Patient and provider characteristics associated with communication about opioids: An observational study

Objective Our objective is to examine the relationship of patient and provider characteristics and communication with chronic non-cancer pain and opioid management in primary care. Method We conducted an observational study using audio-recorded primary care appointments (up to 3/patient) and self-reported assessments of primary care providers (PCPs) and patients. We coded visit transcripts for 1) opioid and pain management talk and 2) mental health and opioid safety talk. Results Eight PCPs and 30 patients had complete data for 78 clinic visits. PCPs and patients engaged in more opioid and pain management talk when patients reported greater pain catastrophizing and PCPs reported higher psychosocial orientation. PCPs and patients engaged in talk about mental health and opioid safety when patients reported greater anxiety, higher working alliance with their PCP, and when PCPs reported higher burnout. PCPs’ negative attitudes about opioids were associated with fewer discussions about mental health and opioid safety. Conclusions Our results should facilitate design of interventions that improve communication and, ultimately, pain outcomes for patients. Practice Implications Clinicians can use our results to increase patient engagement in discussions about opioid use and pain management or mental health and safety discussions

Legal Rights and Issues Surrounding Conception, Pregnancy, and Birth

Advances in medicine are reported almost daily in the media. Medical researchers have developed and are continuing to develop new methods of creating, saving, and prolonging life. This Special Project examines the impact that rapidly advancing medical technology has on the law governing conception, pregnancy, and birth. Although medical techniques have advanced rapidly during the past decades, state and federal legislatures have responded in-adequately to the legal consequences of these new birth technologies. The resulting lag between technology and the law has forced courts to confront new situations that do not fit neatly into the statutory framework created to deal with past fact situations. For example, courts have applied statutes prohibiting child bartering to surrogate parenting cases and statutes prohibiting fetal experimentation to artificial insemination cases although it is clear that the legislators never considered such fact patterns when passing the statutes. A lag is inevitable because the law can only respond to, rather than predict, emerging medical developments. Nonetheless, legislators must respond promptly by confronting the new legal issues that result from new medical technologies. One impediment to prompt legislative response to the lag between medical technology and the law is the controversial nature of the legal problems posed. Abortion continues to be an extremely controversial issue thirteen years after the Supreme Court legalized it in the landmark decision Roe v. Wade. The Baby Doe issue of whether to force hospitals and parents of severely deformed newborns to provide medical care is another extremely controversial issue. Baby Doe has become highly politicized as the Reagan administration, Congress, right-to-life groups, disability groups, medical professionals, and other groups have taken stances. Surrogate parenting also has produced controversial situations. In one incident, a New York couple contracted with a California surrogate mother. When the surrogate mother breached the agreement, the couple brought suit. The court discovered that the couple consisted of a man and a transsexual, thus raising the issue of whether transsexuals or homosexuals should be allowed to adopt children by contracting with surrogate mothers

Consequences of a Rare Complement Factor H Variant for Age-Related Macular Degeneration in the Amish

PURPOSE. Genetic variants in the complement factor H gene (CFH) have been consistently implicated in age-related macular degeneration (AMD) risk. However, their functional effects are not fully characterized. We previously identified a rare, AMD-associated variant in CFH (P503A, rs570523689) in 19 Amish individuals, but its functional consequences were not investigated. METHODS. We performed genotyping for CFH P503A in 1326 Amish individuals to identify additional risk allele carriers. We examined differences for age at AMD diagnosis between carriers and noncarriers. In blood samples from risk allele carriers and noncarriers, we quantified (i) CFH RNA expression, (ii) CFH protein expression, and (iii) C -reactive protein (CRP) expression. Potential changes to the CFH protein structure were interrogated computationally with Phyre2 and Chimera software programs. RESULTS. We identified 39 additional carriers from Amish communities in Ohio and Indiana. On average, carriers were younger than noncarriers at AMD diagnosis, but this difference was not significant. CFH transcript and protein levels in blood samples from Amish carriers and noncarriers were also not significantly different. CRP levels were also comparable in plasma samples from carriers and noncarriers. Computational protein modeling showed slight changes in the CFH protein conformation that were predicted to alter interactions between the CFH 503 residue and other neighboring residues. CONCLUSIONS. In total, we have identified 58 risk allele carriers for CFH P503A in the Ohio and Indiana Amish. Although we did not detect significant differences in age at AMD diagnosis or expression levels of CFH in blood samples from carriers and noncarriers, we observed modest structural changes to the CFH protein through in silico modeling. Based on our functional and computational observations, we hypothesize that CFH P503A may affect CFH binding or function rather than expression, which would require additional research to confirm

Psychometric Approaches to Defining Cognitive Phenotypes in the Old Order Amish

Memory and cognitive problems are central to the diagnosis of Alzheimer's disease (AD). Psychometric approaches to defining phenotypes can aid in identify genetic variants associated with AD. However, these approaches have mostly been limited to affected individuals. Defining phenotypes of both affected and unaffected individuals may help identify genetic variants associated with both AD and healthy aging. This study compares psychometric methods for developing cognitive phenotypes that are more granular than clinical classifications. 682 older Old Order Amish individuals were included in the analysis. Adjusted Z-scores of cognitive tests were used to create four models including 1) global threshold scores or 2) memory threshold scores, and 3) global clusters and 4) memory clusters. An ordinal regression examined the coherence of the models with clinical classifications [cognitively impaired (CI), mildly impaired (MI), cognitively unimpaired (CU)], APOE-e4, sex, and age. An ANOVA examined the best model phenotypes for differences in clinical classification, APOE-e4, domain Z-scores (memory, language, executive function, and processing speed), sex, and age. The memory cluster identified four phenotypes and had the best fit (χ = 491.66). Individuals in the worse performing phenotypes were more likely to be classified as CI or MI and to have APOE-e4. Additionally, all four phenotypes performed significantly differently from one another on the domains of memory, language, and executive functioning. Memory cluster stratification identified the cognitive phenotypes that best aligned with clinical classifications, APOE-e4, and cognitive performance We predict these phenotypes will prove useful in searching for protective genetic variants. This article is protected by copyright. All rights reserved

Psychometric approaches to defining cognitive phenotypes in the Old Order Amish

Objective: Memory and cognitive problems are central to the diagnosis of Alzheimer's disease (AD). Psychometric approaches to defining phenotypes can aid in identify genetic variants associated with AD. However, these approaches have mostly been limited to affected individuals. Defining phenotypes of both affected and unaffected individuals may help identify genetic variants associated with both AD and healthy aging. This study compares psychometric methods for developing cognitive phenotypes that are more granular than clinical classifications.Methods: 682 older Old Order Amish individuals were included in the analysis. Adjusted Z-scores of cognitive tests were used to create four models including (1) global threshold scores or (2) memory threshold scores, and (3) global clusters and (4) memory clusters. An ordinal regression examined the coherence of the models with clinical classifications (cognitively impaired [CI], mildly impaired [MI], cognitively unimpaired), APOE-e4, sex, and age. An ANOVA examined the best model phenotypes for differences in clinical classification, APOE-e4, domain Z-scores (memory, language, executive function, and processing speed), sex, and age.Results: The memory cluster identified four phenotypes and had the best fit (?(2) = 491.66). Individuals in the worse performing phenotypes were more likely to be classified as CI or MI and to have APOE-e4. Additionally, all four phenotypes performed significantly differently from one another on the domains of memory, language, and executive functioning.Conclusions: Memory cluster stratification identified the cognitive phenotypes that best aligned with clinical classifications, APOE-e4, and cognitive performance We predict these phenotypes will prove useful in searching for protective genetic variants

Rare variants and loci for age-related macular degeneration in the Ohio and Indiana Amish

Age-related macular degeneration (AMD) is a leading cause of blindness in the world. While dozens of independent genomic variants are associated with AMD, about one-third of AMD heritability is still unexplained. To identify novel variants and loci for AMD, we analyzed Illumina HumanExome chip data from 87 Amish individuals with early or late AMD, 79 unaffected Amish individuals, and 15 related Amish individuals with unknown AMD affection status. We retained 37,428 polymorphic autosomal variants across 175 samples for association and linkage analyses. After correcting for multiple testing (n = 37,428), we identified four variants significantly associated with AMD: rs200437673 (LCN9, p = 1.50 × 10 ), rs151214675 (RTEL1, p = 3.18 × 10 ), rs140250387 (DLGAP1, p = 4.49 × 10 ), and rs115333865 (CGRRF1, p = 1.05 × 10 ). These variants have not been previously associated with AMD and are not in linkage disequilibrium with the 52 known AMD-associated variants reported by the International AMD Genomics Consortium based on physical distance. Genome-wide significant linkage peaks were observed on chromosomes 8q21.11-q21.13 (maximum recessive HLOD = 4.03) and 18q21.2-21.32 (maximum dominant HLOD = 3.87; maximum recessive HLOD = 4.27). These loci do not overlap with loci previously linked to AMD. Through gene ontology enrichment analysis with ClueGO in Cytoscape, we determined that several genes in the 1-HLOD support interval of the chromosome 8 locus are involved in fatty acid binding and triglyceride catabolic processes, and the 1-HLOD support interval of the linkage region on chromosome 18 is enriched in genes that participate in serine-type endopeptidase inhibitor activity and the positive regulation of epithelial to mesenchymal transition. These results nominate novel variants and loci for AMD that require further investigation

Lower Levels of Education Are Associated with Cognitive Impairment in the Old Order Amish

Background: Lower education has been reported to be associated with dementia. However, many studies have been done in settings where 12 years of formal education is the standard. Formal schooling in the Old Order Amish communities (OOA) ends at 8th grade which, along with their genetic homogeneity, makes it an interesting population to study the effect of education on cognitive impairment. Objective: The objective of this study was to examine the association of education with cognitive function in individuals from the OOA. We hypothesized that small differences in educational attainment at lower levels of formal education were associated with risk for cognitive impairment. Methods: Data of 2,426 individuals from the OOA aged 54–99 were analyzed. The Modified Mini-Mental State Examination (3MS-R) was used to classify participants as CI or normal. Individuals were classified into three education categories: 8 years of education. To measure the association of education with cognitive status, a logistic regression model was performed adding age and sex as covariates. Results: Our results showed that individuals who attained lowest levels of education (8 years (OR = 2.96 and 1.85). Conclusion: Even within a setting of low levels of formal education, small differences in educational attainment can still be associated with the risk of cognitive impairment. Given the homogeneity of the OOA, these results are less likely to be biased by differences in socioeconomic backgrounds