86 research outputs found

    Presentation of Diagnostic Information to Doctors May Change Their Interpretation and Clinical Management: A Web-Based Randomised Controlled Trial

    No full text
    <div><p>Background</p><p>There is little evidence on how best to present diagnostic information to doctors and whether this makes any difference to clinical management. We undertook a randomised controlled trial to see if different data presentations altered clinicians’ decision to further investigate or treat a patient with a fictitious disorder (“Green syndrome”) and their ability to determine post-test probability.</p><p>Methods</p><p>We recruited doctors registered with the United Kingdom’s largest online network for medical doctors between 10 July and 6” November 2012. Participants were randomised to one of four arms: (a) text summary of sensitivity and specificity, (b) Fagan’s nomogram, (c) probability-modifying plot (PMP), (d) natural frequency tree (NFT). The main outcome measure was the decision whether to treat, not treat or undertake a brain biopsy on the hypothetical patient and the correct post-test probability. Secondary outcome measures included knowledge of diagnostic tests.</p><p>Results</p><p>917 participants attempted the survey and complete data were available from 874 (95.3%). Doctors randomized to the PMP and NFT arms were more likely to treat the patient than those randomized to the text-only arm. (ORs 1.49, 95% CI 1.02, 2.16) and 1.43, 95% CI 0.98, 2.08 respectively). More patients randomized to the PMP (87/218–39.9%) and NFT (73/207–35.3%) arms than the nomogram (50/194–25.8%) or text only (30/255–11.8%) arms reported the correct post-test probability (p <0.001). Younger age, postgraduate training and higher self-rated confidence all predicted better knowledge performance. Doctors with better knowledge were more likely to view an optional learning tutorial (OR per correct answer 1.18, 95% CI 1.06, 1.31).</p><p>Conclusions</p><p>Presenting diagnostic data using a probability-modifying plot or natural frequency tree influences the threshold for treatment and improves interpretation of tests results compared to text summary of sensitivity and specificity or Fagan’s nomogram.</p></div

    Different modes of data presentation to help interpret the results of the index test (A) Fagan’s nomogram (B) Probability modifying plot (C) Natural frequency tree.

    No full text
    <p>Different modes of data presentation to help interpret the results of the index test (A) Fagan’s nomogram (B) Probability modifying plot (C) Natural frequency tree.</p

    Supplemental Material - Treatment Decision-Making in Myocardial Infarction for People With Advanced Kidney Disease: Protocol for a Qualitative Study

    No full text
    Supplemental Material for Treatment Decision-Making in Myocardial Infarction for People With Advanced Kidney Disease: Protocol for a Qualitative Study by Jemima Scott, Lucy Ellen Selman, Fergus J. Caskey, Thomas Johnson, Yoav Ben-Shlomo, and Pippa Bailey in International Journal of Qualitative Methods</p

    Comparison of baseline characteristics of participants eligible for the final analysis, by gender (mean and SD, unless stated as median and IQR, or %).

    No full text
    <p>SD = Standard deviation; IQR = Interquartile Range; BMI = Body mass index.</p>1<p>Insulin Sensitivity Index whilst fasting = 104/(I0×G0).</p>2<p>Corrected Insulin Response at 30 minutes = 100×I30/(G30×(G30−70).</p>†<p>Geometric means and log SD values.</p>*<p>Difference in means by gender observed (two sample t-test), all p<0.02.</p>∧<p>N for 10 d intake = 568 (312 males, 256 females); N for 6 wk intake = 566 (309 males, 257 females); N for 3 m intake = 569 (310 males, 259 females).</p

    Multivariable regression analyses showing relative changes in outcomes at follow-up (23–27 y) in participants who consumed formula/cow's milk (FF) compared to those who were breastfed (BF) at 10 days, 6 weeks and 3 months during infancy.

    No full text
    <p>Model 1: adjusted for age at follow-up, sex, intervention group.</p><p>Model 2: as model 1 plus adjustment for z-score of birth weight, father's social class, lifetime smoking, alcohol intake and exercise.</p>1<p>Insulin Sensitivity Index whilst fasting = 10<sup>4</sup>/(I<sub>0</sub>×G<sub>0</sub>).</p>2<p>Corrected Insulin Response at 30 minutes = 100×I<sub>30</sub>/(G<sub>30</sub>×(G<sub>30</sub>−70).</p>†<p>Outcomes were natural-log transformed, and coefficients and confidence intervals represent a change in ratio of geometric means between groups.</p

    Uptake of behaviours in the Caerphilly Prospective study and in the Welsh Health Survey [18].

    No full text
    *<p>The criterion for fruit and vegetable intake had to be reduced to 3 portions a day for the Caerphilly cohort because only 15 men in the 1979 cohort consumed five portions per day.</p

    Odds ratios for individual healthy behaviours at base-line and the various outcomes during 30 years in the Caerphilly Prospective Study.

    No full text
    <p><sup></sup> All odds ratios have been adjusted for age and social class.</p><p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0081877#pone.0081877-Nelson1" target="_blank">[27]</a>.<sup></sup> Cognitive function has also been adjusted for the National Adult Reading Test </p><p><sup></sup> Vascular disease includes ischaemic heart disease and ischaemic stroke.</p><p><b>Smoking</b>  =  men not smoking, including ex-smokers.<sup></sup></p><p><b>BMI</b> (Body Mass Index)  =  18 to 25 Kg/m2.</p><p><b>Fruit and vegetable consumption</b>  =  3 or more portions per day, plus less than 30% of calories from fat. The criterion for fruit and vegetable intake had to be reduced because only 15 men consumed five portions per day).</p><p><b>Regular exercise</b>  =  walking two or more miles to work each day, or cycling ten or more miles to work each day, or ‘vigorous’ exercise described as a regular habit.</p><p><b>Alcohol intake</b>  =  three or fewer units per day, with abstinence not treated as a healthy behaviour.</p
    corecore