154 research outputs found
Striking variations in consultation rates with general practice reveal family influence
BACKGROUND: The reasons why patients decide to consult a general practitioner vary enormously. While there may be individual reasons for this variation, the family context has a significant and unique influence upon the frequency of individuals' visits. The objective of this study was to explore which family factors can explain the differences between strikingly high, and correspondingly low, family consultation rates in families with children aged up to 21. METHODS: Data were used from the second Dutch national survey of general practice. This survey extracted from the medical records of 96 practices in the Netherlands, information on all consultations with patients during 2001. We defined, through multilevel analysis, two groups of families. These had respectively, predominantly high, and low, contact frequencies due to a significant family influence upon the frequency of the individual's first contacts. Binomial logistic regression analyses were used to analyse which of the family factors, related to shared circumstances and socialisation conditions, can explain the differences in consultation rates between the two groups of families. RESULTS: In almost 3% of all families, individual consultation rates decrease significantly due to family influence. In 11% of the families, individual consultation rates significantly increase due to family influence. While taking into account the health status of family members, family factors can explain family consultation rates. These factors include circumstances such as their economic status and number of children, as well as socialisation conditions such as specific health knowledge and family beliefs. The chance of significant low frequencies of contact due to family influences increases significantly with factors such as, paid employment of parents in the health care sector, low expectations of general practitioners' care for minor ailments and a western cultural background. CONCLUSION: Family circumstances can easily be identified and will add to the understanding of the health complaints of the individual patient in the consulting room. Family circumstances related to health risks often cannot be changed but they can illuminate the reasons for a visit, and mould strategies for prevention, treatment or recovery. Health beliefs, on the other hand, may be influenced by providing specific knowledge
Towards a more efficient diabetes control in primary care: six-monthly monitoring compared with three-monthly monitoring in type 2 diabetes - The EFFIMODI trial. Design of a randomised controlled patient-preference equivalence trial in primary care
Changes in the severity and subtype of Guillain-Barré syndrome admitted to a specialist Neuromedical ICU over a 25 year period
Guillain-Barré syndrome: a century of progress
In 1916, Guillain, BarrĂ© and Strohl reported on two cases of acute flaccid paralysis with high cerebrospinal fluid protein levels and normal cell counts â novel findings that identified the disease we now know as GuillainâBarrĂ© syndrome (GBS). 100 years on, we have made great progress with the clinical and pathological characterization of GBS. Early clinicopathological and animal studies indicated that GBS was an immune-mediated demyelinating disorder, and that severe GBS could result in secondary axonal injury; the current treatments of plasma exchange and intravenous immunoglobulin, which were developed in the 1980s, are based on this premise. Subsequent work has, however, shown that primary axonal injury can be the underlying disease. The association of Campylobacter jejuni strains has led to confirmation that anti-ganglioside antibodies are pathogenic and that axonal GBS involves an antibody and complement-mediated disruption of nodes of Ranvier, neuromuscular junctions and other neuronal and glial membranes. Now, ongoing clinical trials of the complement inhibitor eculizumab are the first targeted immunotherapy in GBS
A novel approach to locate Phytophthora infestans resistance genes on the potato genetic map
Mapping resistance genes is usually accomplished by phenotyping a segregating population for the resistance trait and genotyping it using a large number of markers. Most resistance genes are of the NBS-LRR type, of which an increasing number is sequenced. These genes and their analogs (RGAs) are often organized in clusters. Clusters tend to be rather homogenous, viz. containing genes that show high sequence similarity with each other. From many of these clusters the map position is known. In this study we present and test a novel method to quickly identify to which cluster a new resistance gene belongs and to produce markers that can be used for introgression breeding. We used NBS profiling to identify markers in bulked DNA samples prepared from resistant and susceptible genotypes of small segregating populations. Markers co-segregating with resistance can be tested on individual plants and directly used for breeding. To identify the resistance gene cluster a gene belongs to, the fragments were sequenced and the sequences analyzed using bioinformatics tools. Putative map positions arising from this analysis were validated using markers mapped in the segregating population. The versatility of the approach is demonstrated with a number of populations derived from wild Solanum species segregating for P. infestans resistance. Newly identified P. infestans resistance genes originating from S. verrucosum, S. schenckii, and S. capsicibaccatum could be mapped to potato chromosomes 6, 4, and 11, respectively
Identification of a resistance gene Rpi-dlc1 to Phytophthora infestans in European accessions of Solanum dulcamara
Initial screening of 14 Solanum dulcamara accessions enabled the identification of individuals resistant and susceptible to Phytophthora infestans. Crosses between contrasting genotypes resulted in three F2âBC1 populations segregating for resistance to late blight in a laboratory assay and under field conditions. Genetic profiling of one of these populations using 128 AFLP primers generated three markers linked to the resistant phenotype. Blast analysis of the sequenced markers resulted in a plausible gene position on the distal end of the long arm of chromosome 9 that could be confirmed by CAPS markers. Thus, we describe a first resistant gene, named Rpi-dlc1, from S. dulcamara, a Solanum species native to Europe. In addition, one population was tested for broadness of resistance responses using a set of seven additional P. infestans isolates, varying in virulence. This indicated the possible presence of additional Rpi genes
Do decision support systems influence variation in prescription?
<p>Abstract</p> <p>Background</p> <p>Translating scientific evidence into daily practice is problematic. All kinds of intervention strategies, using educational and/or directive strategies, aimed at modifying behavior, have evolved, but have been found only partially successful. In this article the focus is on (computerized) decision support systems (DSSs). DSSs intervene in physicians' daily routine, as opposed to interventions that aim at influencing knowledge in order to change behavior. We examined whether general practitioners (GPs) are prescribing in accordance with the advice given by the DSS and whether there is less variation in prescription when the DSS is used.</p> <p>Methods</p> <p>Data were used from the Second Dutch National Survey of General Practice (DNSGP2), collected in 2001. A total of 82 diagnoses, 749811 contacts, 133 physicians, and 85 practices was included in the analyses. GPs using the DSS daily were compared to GPs who do not use the DSS. Multilevel analyses were used to analyse the data. Two outcome measures were chosen: whether prescription was in accordance with the advice of the DSS or not, and a measure of concentration, the Herfindahl-Hirschman Index (HHI).</p> <p>Results</p> <p>GPs who use the DSS daily prescribe more according to the advice given in the DSS than GPs who do not use the DSS. Contradictory to our expectation there was no significant difference between the HHIs for both groups: variation in prescription was comparable.</p> <p>Conclusion</p> <p>We studied the use of a DSS for drug prescribing in general practice in the Netherlands. The DSS is based on guidelines developed by the Dutch College of General Practitioners and implemented in the Electronic Medical Systems of the GPs. GPs using the DSS more often prescribe in accordance with the advice given in the DSS compared to GPs not using the DSS. This finding, however, did not mean that variation is lower; variation is the same for GPs using and for GPs not using a DSS. Implications of the study are that DSSs can be used to implement guidelines, but that it should not be expected that variation is limited.</p
Substitution and pooling in crowding
Unless we fixate directly on it, it is hard to see an object among other objects. This breakdown in object recognition, called crowding, severely limits peripheral vision. The effect is more severe when objects are more similar. When observers mistake the identity of a target among flanker objects, they often report a flanker. Many have taken these flanker reports as evidence of internal substitution of the target by a flanker. Here, we ask observers to identify a target letter presented in between one similar and one dissimilar flanker letter. Simple substitution takes in only one letter, which is often the target but, by unwitting mistake, is sometimes a flanker. The opposite of substitution is pooling, which takes in more than one letter. Having taken only one letter, the substitution process knows only its identity, not its similarity to the target. Thus, it must report similar and dissimilar flankers equally often. Contrary to this prediction, the similar flanker is reported much more often than the dissimilar flanker, showing that rampant flanker substitution cannot account for most flanker reports. Mixture modeling shows that simple substitution can account for, at most, about half the trials. Pooling and nonpooling (simple substitution) together include all possible models of crowding. When observers are asked to identify a crowded object, at least half of their reports are pooled, based on a combination of information from target and flankers, rather than being based on a single letter
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