Changing patterns of home visiting in general practice: an analysis of electronic medical records

BACKGROUND: In most European countries and North America the number of home visits carried out by GPs has been decreasing sharply. This has been influenced by non-medical factors such as mobility and pressures on time. The objective of this study was to investigate changes in home visiting rates, looking at the level of diagnoses in1987 and in 2001. METHODS: We analysed routinely collected data on diagnoses in home visits and surgery consultations from electronic medical records by general practitioners. Data were used from 246,738 contacts among 124,791 patients in 103 practices in 1987, and 77,167 contacts among 58,345 patients in 80 practices in 2001. There were 246 diagnoses used. The main outcome measure was the proportion of home visits per diagnosis in 2001. RESULTS: Within the period studied, the proportion of home visits decreased strongly. The size of this decrease varied across diagnoses. The relation between the proportion of home visits for a diagnosis in 1987 and the same proportion in 2001 is curvilinear (J-shaped), indicating that the decrease is weaker at the extreme points and stronger in the middle. CONCLUSION: By comparison with 1987, the proportion of home visits shows a distinct decline. However, the results show that this decline is not necessarily a problem. The finding that this decline varied mainly between diagnoses for which home visits are not always urgent, shows that medical considerations still play an important role in the decision about whether or not to carry out a home visit

Non-nucleoside reverse transcriptase inhibitor-based combination antiretroviral therapy is associated with lower cell-associated hiv rna and dna levels as compared with therapy based on protease inhibitors

BACKGROUND: It remains unclear whether combination antiretroviral therapy (ART) regimens differ in their ability to fully suppress HIV replication. Here, we report the results of two crosssectional studies that compared levels of cell-associated (CA) HIV markers between individuals receiving suppressive ART containing either a non-nucleoside reverse transcriptase inhibitor (NNRTI) or a protease inhibitor (PI). METHODS: CA HIV unspliced RNA and total HIV DNA were quantified in two cohorts (n=100, n=124) of individuals treated with triple ART regimens consisting of two nucleoside reverse transcriptase inhibitors (NRTIs) plus either a NNRTI or a PI. To compare CA HIV RNA and DNA levels between the regimens, we built multivariable models adjusting for age, gender, current and nadir CD4+ count, plasma viral load zenith, duration of virological suppression, NRTI backbone composition, low-level plasma HIV RNA detectability, and electronically-measured adherence to ART. RESULTS: In both cohorts, levels of CA HIV RNA and DNA strongly correlated (rho=0.70 and rho=0.54) and both markers were lower in NNRTI-treated than in PI-treated individuals. In the multivariable analysis, CA RNA in both cohorts remained significantly reduced in NNRTI-treated individuals (padj=0.02 in both cohorts), with a similar but weaker association between the ART regimen and total HIV DNA (padj=0.048 and padj=0.10). No differences in CA HIV RNA or DNA levels were observed between individual NNRTIs or individual PIs, but CA HIV RNA was lower in individuals treated with either nevirapine or efavirenz, compared to PI-treated individuals CONCLUSIONS: All current classes of antiretroviral drugs only prevent infection of new cells but do not inhibit HIV RNA transcription in long-lived reservoir cells. Therefore, these differences in CA HIV RNA and DNA levels by treatment regimen suggest that NNRTIs are more potent in suppressing HIV residual replication than PIs, which may result in a smaller viral reservoir size

Unmappable ventricular tachycardia after an old myocardial infarction. Long-term results of substrate modification in patients with an implantable cardioverter defibrillator

Purpose The frequent occurrence of ventricular tachycardia can create a serious problem in patients with an implantable cardioverter defibrillator. We assessed the long-term efficacy of catheter-based substrate modification using the voltage mapping technique of infarct-related ventricular tachycardia and recurrent device therapy. Methods The study population consisted of 27 consecutive patients (age 68 +/- 8 years, 25 men, mean left ventricular ejection fraction 31 +/- 9%) with an old myocardial infarction and multiple and/or hemodynamically not tolerated ventricular tachycardia necessitating repeated device therapy. A total of 31 substrate modification procedures were performed using the three-dimensional electroanatomical mapping system. Patients were followed up for a median of 23.5 (interquartile range 6.5-53.2) months before and 37.8 (interquartile range 11.7-71.8) months after ablation. Antiarrhythmic drugs were not changed after the procedure, and were stopped 6 to 9 months after the procedure in patients who did not show ventricular tachycardia recurrence. Results Median ventricular tachycardias were 1.6 (interquartile range 0.7-6.7) per month before and 0.2 (interquartile range 0.00-1.3) per month after ablation (P = 0.006). Nine ventricular fibrillation episodes were registered in seven patients before and two after ablation (P = 0.025). Median antitachycardia pacing decreased from 1.6 (interquartile range 0.01-5.5) per month before to 0.18 (interquartile range 0.00-1.6) per month after ablation (P = 0.069). Median number of shocks decreased from 0.19 (interquartile range 0.04-0.81) per month before to 0.00 (interquartile range 0.00-0.09) per month after ablation (P = 0.001). One patient had a transient ischemic attack during the procedure, and another developed pericarditis. Nine patients died during follow-up, eight patients due to heart failure and one patient during valve surgery. Conclusion Catheter-based substrate modification using voltage mapping results in a long-lasting reduction of cardioverter defibrillator therapy in patients with multiple and/or hemodynamically not tolerated infarct-related ventricular tachyarrhythmia

Accurate HLA type inference using a weighted similarity graph

Abstract Background The human leukocyte antigen system (HLA) contains many highly variable genes. HLA genes play an important role in the human immune system, and HLA gene matching is crucial for the success of human organ transplantations. Numerous studies have demonstrated that variation in HLA genes is associated with many autoimmune, inflammatory and infectious diseases. However, typing HLA genes by serology or PCR is time consuming and expensive, which limits large-scale studies involving HLA genes. Since it is much easier and cheaper to obtain single nucleotide polymorphism (SNP) genotype data, accurate computational algorithms to infer HLA gene types from SNP genotype data are in need. To infer HLA types from SNP genotypes, the first step is to infer SNP haplotypes from genotypes. However, for the same SNP genotype data set, the haplotype configurations inferred by different methods are usually inconsistent, and it is often difficult to decide which one is true. Results In this paper, we design an accurate HLA gene type inference algorithm by utilizing SNP genotype data from pedigrees, known HLA gene types of some individuals and the relationship between inferred SNP haplotypes and HLA gene types. Given a set of haplotypes inferred from the genotypes of a population consisting of many pedigrees, the algorithm first constructs a weighted similarity graph based on a new haplotype similarity measure and derives constraint edges from known HLA gene types. Based on the principle that different HLA gene alleles should have different background haplotypes, the algorithm searches for an optimal labeling of all the haplotypes with unknown HLA gene types such that the total weight among the same HLA gene types is maximized. To deal with ambiguous haplotype solutions, we use a genetic algorithm to select haplotype configurations that tend to maximize the same optimization criterion. Our experiments on a previously typed subset of the HapMap data show that the algorithm is highly accurate, achieving an accuracy of 96% for gene HLA-A, 95% for HLA-B, 97% for HLA-C, 84% for HLA-DRB1, 98% for HLA-DQA1 and 97% for HLA-DQB1 in a leave-one-out test. Conclusions Our algorithm can infer HLA gene types from neighboring SNP genotype data accurately. Compared with a recent approach on the same input data, our algorithm achieved a higher accuracy. The code of our algorithm is available to the public for free upon request to the corresponding authors

Designing Genome-Wide Association Studies: Sample Size, Power, Imputation, and the Choice of Genotyping Chip

Genome-wide association studies are revolutionizing the search for the genes underlying human complex diseases. The main decisions to be made at the design stage of these studies are the choice of the commercial genotyping chip to be used and the numbers of case and control samples to be genotyped. The most common method of comparing different chips is using a measure of coverage, but this fails to properly account for the effects of sample size, the genetic model of the disease, and linkage disequilibrium between SNPs. In this paper, we argue that the statistical power to detect a causative variant should be the major criterion in study design. Because of the complicated pattern of linkage disequilibrium (LD) in the human genome, power cannot be calculated analytically and must instead be assessed by simulation. We describe in detail a method of simulating case-control samples at a set of linked SNPs that replicates the patterns of LD in human populations, and we used it to assess power for a comprehensive set of available genotyping chips. Our results allow us to compare the performance of the chips to detect variants with different effect sizes and allele frequencies, look at how power changes with sample size in different populations or when using multi-marker tags and genotype imputation approaches, and how performance compares to a hypothetical chip that contains every SNP in HapMap. A main conclusion of this study is that marked differences in genome coverage may not translate into appreciable differences in power and that, when taking budgetary considerations into account, the most powerful design may not always correspond to the chip with the highest coverage. We also show that genotype imputation can be used to boost the power of many chips up to the level obtained from a hypothetical “complete” chip containing all the SNPs in HapMap. Our results have been encapsulated into an R software package that allows users to design future association studies and our methods provide a framework with which new chip sets can be evaluated

Local Genealogies in a Linear Mixed Model for Genome-Wide Association Mapping in Complex Pedigreed Populations

INTRODUCTION: The state-of-the-art for dealing with multiple levels of relationship among the samples in genome-wide association studies (GWAS) is unified mixed model analysis (MMA). This approach is very flexible, can be applied to both family-based and population-based samples, and can be extended to incorporate other effects in a straightforward and rigorous fashion. Here, we present a complementary approach, called 'GENMIX (genealogy based mixed model)' which combines advantages from two powerful GWAS methods: genealogy-based haplotype grouping and MMA. SUBJECTS AND METHODS: We validated GENMIX using genotyping data of Danish Jersey cattle and simulated phenotype and compared to the MMA. We simulated scenarios for three levels of heritability (0.21, 0.34, and 0.64), seven levels of MAF (0.05, 0.10, 0.15, 0.20, 0.25, 0.35, and 0.45) and five levels of QTL effect (0.1, 0.2, 0.5, 0.7 and 1.0 in phenotypic standard deviation unit). Each of these 105 possible combinations (3 h(2) x 7 MAF x 5 effects) of scenarios was replicated 25 times. RESULTS: GENMIX provides a better ranking of markers close to the causative locus' location. GENMIX outperformed MMA when the QTL effect was small and the MAF at the QTL was low. In scenarios where MAF was high or the QTL affecting the trait had a large effect both GENMIX and MMA performed similarly. CONCLUSION: In discovery studies, where high-ranking markers are identified and later examined in validation studies, we therefore expect GENMIX to enrich candidates brought to follow-up studies with true positives over false positives more than the MMA would

Non-nucleoside reverse transcriptase inhibitor-based combination antiretroviral therapy is associated with lower cell-associated HIV RNA and DNA levels compared to protease inhibitor-based therapy

Background: It remains unclear whether combination antiretroviral therapy (ART) regimens differ in their ability to fully suppress human immunodeficiency virus (HIV) replication. Here, we report the results of two cross-sectional studies that compared levels of cell-associated (CA) HIV markers between individuals receiving suppressive ART containing either a non-nucleoside reverse transcriptase inhibitor (NNRTI) or a protease inhibitor (PI). Methods: CA HIV unspliced RNA and total HIV DNA were quantified in two cohorts (n = 100, n = 124) of individuals treated with triple ART regimens consisting of two nucleoside reverse transcriptase inhibitors (NRTIs) plus either an NNRTI or a PI. To compare CA HIV RNA and DNA levels between the regimens, we built multivariable models adjusting for age, gender, current and nadir CD4+ count, plasma viral load zenith, duration of virological suppression, NRTI backbone composition, low-level plasma HIV RNA detectability, and electronically measured adherence to ART. Results: In both cohorts, levels of CA HIV RNA and DNA strongly correlated (rho = 0.70 and rho = 0.54) and both markers were lower in NNRTI-treated than in PI-treated individuals. In the multivariable analysis, CA RNA in both cohorts remained significantly reduced in NNRTI-treated individuals (padj = 0.02 in both cohorts), with a similar but weaker association between the ART regimen and total HIV DNA (padj = 0.048 and padj = 0.10). No differences in CA HIV RNA or DNA levels were observed between individual NNRTIs or individual PIs, but CA HIV RNA was lower in individuals treated with either nevirapine or efavirenz, compared to PI-treated individuals. Conclusions: All current classes of antiretroviral drugs only prevent infection of new cells but do not inhibit HIV RNA transcription in long-lived reservoir cells. Therefore, these differences in CA HIV RNA and DNA levels by treatment regimen suggest that NNRTIs are more potent in suppressing HIV residual replication than PIs, which may result in a smaller viral reservoir size

Genetic risk factors for ischaemic stroke and its subtypes (the METASTROKE Collaboration): a meta-analysis of genome-wide association studies

<p>Background - Various genome-wide association studies (GWAS) have been done in ischaemic stroke, identifying a few loci associated with the disease, but sample sizes have been 3500 cases or less. We established the METASTROKE collaboration with the aim of validating associations from previous GWAS and identifying novel genetic associations through meta-analysis of GWAS datasets for ischaemic stroke and its subtypes.</p> <p>Methods - We meta-analysed data from 15 ischaemic stroke cohorts with a total of 12 389 individuals with ischaemic stroke and 62 004 controls, all of European ancestry. For the associations reaching genome-wide significance in METASTROKE, we did a further analysis, conditioning on the lead single nucleotide polymorphism in every associated region. Replication of novel suggestive signals was done in 13 347 cases and 29 083 controls.</p> <p>Findings - We verified previous associations for cardioembolic stroke near PITX2 (p=2·8×10−16) and ZFHX3 (p=2·28×10−8), and for large-vessel stroke at a 9p21 locus (p=3·32×10−5) and HDAC9 (p=2·03×10−12). Additionally, we verified that all associations were subtype specific. Conditional analysis in the three regions for which the associations reached genome-wide significance (PITX2, ZFHX3, and HDAC9) indicated that all the signal in each region could be attributed to one risk haplotype. We also identified 12 potentially novel loci at p<5×10−6. However, we were unable to replicate any of these novel associations in the replication cohort.</p> <p>Interpretation - Our results show that, although genetic variants can be detected in patients with ischaemic stroke when compared with controls, all associations we were able to confirm are specific to a stroke subtype. This finding has two implications. First, to maximise success of genetic studies in ischaemic stroke, detailed stroke subtyping is required. Second, different genetic pathophysiological mechanisms seem to be associated with different stroke subtypes.</p&gt