611 results found
Cole GD, Nowbar A, Mielewczik M, et al., 2015, Frequency of discrepancies in retracted clinical trial reports versus unretracted reports: blinded case-control study, British Medical Journal, Vol: 351, ISSN: 1468-5833
Objectives To compare the frequency of discrepancies in retracted reports of clinical trials with those in adjacent unretracted reports in the same journal.Design Blinded case-control study.Setting Journals in PubMed.Population 50 manuscripts, classified on PubMed as retracted clinical trials, paired with 50 adjacent unretracted manuscripts from the same journals. Reports were randomly selected from PubMed in December 2012, with no restriction on publication date. Controls were the preceding unretracted clinical trial published in the same journal. All traces of retraction were removed. Three scientists, blinded to the retraction status of individual reports, reviewed all 100 trial reports for discrepancies. Discrepancies were pooled and cross checked before being counted into prespecified categories. Only then was the retraction status unblinded for analysis.Main outcome measure Total number of discrepancies (defined as mathematically or logically contradictory statements) in each clinical trial report.Results Of 479 discrepancies found in the 100 trial reports, 348 were in the 50 retracted reports and 131 in the 50 unretracted reports. On average, individual retracted reports had a greater number of discrepancies than unretracted reports (median 4 (interquartile range 2-8.75) v 0 (0-5); P<0.001). Papers with a discrepancy were significantly more likely to be retracted than those without a discrepancy (odds ratio 5.7 (95% confidence interval 2.2 to 14.5); P<0.001). In particular, three types of discrepancy arose significantly more frequently in retracted than unretracted reports: factual discrepancies (P=0.002), arithmetical errors (P=0.01), and missed P values (P=0.02). Results from a retrospective analysis indicated that citations and journal impact factor were unlikely to affect the result.Conclusions Discrepancies in published trial reports should no longer be assumed to be unimportant. Scientists, blinded to retraction status and with no specialist skill
Ahmad Y, Nijjer S, Cook CM, et al., 2015, A new method of applying randomised control study data to the individual patient: A novel quantitative patient-centred approach to interpreting composite end points, INTERNATIONAL JOURNAL OF CARDIOLOGY, Vol: 195, Pages: 216-224, ISSN: 0167-5273
Dehbi H-M, Jones S, Sohaib SMA, et al., 2015, A novel curve fitting method for AV optimisation of biventricular pacemakers, PHYSIOLOGICAL MEASUREMENT, Vol: 36, Pages: 1889-1900, ISSN: 0967-3334
Cole GD, Francis DP, 2015, Trials are best, ignore the rest: safety and efficacy of digoxin., BMJ, Vol: 351
Koa-Wing M, Nakagawa H, Luther V, et al., 2015, A diagnostic algorithm to optimize data collection and interpretation of Ripple Maps in atrial tachycardias, International Journal of Cardiology, Vol: 199, Pages: 391-400, ISSN: 1874-1754
BackgroundRipple Mapping (RM) is designed to overcome the limitations of existing isochronal 3D mapping systems by representing the intracardiac electrogram as a dynamic bar on a surface bipolar voltage map that changes in height according to the electrogram voltage–time relationship, relative to a fiduciary point.ObjectiveWe tested the hypothesis that standard approaches to atrial tachycardia CARTO™ activation maps were inadequate for RM creation and interpretation. From the results, we aimed to develop an algorithm to optimize RMs for future prospective testing on a clinical RM platform.MethodsCARTO-XP™ activation maps from atrial tachycardia ablations were reviewed by two blinded assessors on an off-line RM workstation. Ripple Maps were graded according to a diagnostic confidence scale (Grade I — high confidence with clear pattern of activation through to Grade IV — non-diagnostic). The RM-based diagnoses were corroborated against the clinical diagnoses.Results43 RMs from 14 patients were classified as Grade I (5 [11.5%]); Grade II (17 [39.5%]); Grade III (9 [21%]) and Grade IV (12 [28%]). Causes of low gradings/errors included the following: insufficient chamber point density; window-of-interest < 100% of cycle length (CL); < 95% tachycardia CL mapped; variability of CL and/or unstable fiducial reference marker; and suboptimal bar height and scar settings.ConclusionsA data collection and map interpretation algorithm has been developed to optimize Ripple Maps in atrial tachycardias. This algorithm requires prospective testing on a real-time clinical platform.
Raphael CE, Finegold JA, Barron AJ, et al., 2015, The effect of duration of follow-up and presence of competing risk on lifespan-gain from implantable cardioverter defibrillator therapy: who benefits the most?, EUROPEAN HEART JOURNAL, Vol: 36, Pages: 1676-1688, ISSN: 0195-668X
Cole GD, Dhutia NM, Shun-Shin MJ, et al., 2015, Defining the real-world reproducibility of visual grading and visual estimation of left ventricular ejection fraction: impact of image quality, experience and accreditation., International Journal of Cardiovascular Imaging, Vol: 31, Pages: 1303-1314, ISSN: 1569-5794
Left ventricular function can be evaluated by qualitative grading and by eyeball estimation of ejection fraction (EF). We sought to define the reproducibility of these techniques, and how they are affected by image quality, experience and accreditation. Twenty apical four-chamber echocardiographic cine loops (Online Resource 1–20) of varying image quality and left ventricular function were anonymized and presented to 35 operators. Operators were asked to provide (1) a one-phrase grading of global systolic function (2) an “eyeball” EF estimate and (3) an image quality rating on a 0–100 visual analogue scale. Each observer viewed every loop twice unknowingly, a total of 1400 viewings. When grading LV function into five categories, an operator’s chance of agreement with another operator was 50 % and with themself on blinded re-presentation was 68 %. Blinded eyeball LVEF re-estimates by the same operator had standard deviation (SD) of difference of 7.6 EF units, with the SD across operators averaging 8.3 EF units. Image quality, defined as the average of all operators’ assessments, correlated with EF estimate variability (r = −0.616, p < 0.01) and visual grading agreement (r = 0.58, p < 0.01). However, operators’ own single quality assessments were not a useful forewarning of their estimate being an outlier, partly because individual quality assessments had poor within-operator reproducibility (SD of difference 17.8). Reproducibility of visual grading of LV function and LVEF estimation is dependent on image quality, but individuals cannot themselves identify when poor image quality is disrupting their LV function estimate. Clinicians should not assume that patients changing in grade or in visually estimated EF have had a genuine clinical change.
Cole GD, Shun-Shin MJ, Nowbar AN, et al., 2015, Difficulty in detecting discrepancies in a clinical trial report:260-reader evaluation, International Journal of Epidemiology, Vol: 44, Pages: 862-869, ISSN: 1464-3685
Background: Scientific literature can contain errors. Discrepancies, defined as two or more statements or results that cannot both be true, may be a signal of problems with a trial report. In this study, we report how many discrepancies are detected by a large panel of readers examining a trial report containing a large number of discrepancies.Methods: We approached a convenience sample of 343 journal readers in seven countries, and invited them in person to participate in a study. They were asked to examine the tables and figures of one published article for discrepancies. 260 participants agreed, ranging from medical students to professors. The discrepancies they identified were tabulated and counted. There were 39 different discrepancies identified. We evaluated the probability of discrepancy identification, and whether more time spent or greater participant experience as academic authors improved the ability to detect discrepancies.Results: Overall, 95.3% of discrepancies were missed. Most participants (62%) were unable to find any discrepancies. Only 11.5% noticed more than 10% of the discrepancies. More discrepancies were noted by participants who spent more time on the task (Spearman’s ρ = 0.22, P < 0.01), and those with more experience of publishing papers (Spearman’s ρ = 0.13 with number of publications, P = 0.04).Conclusions: Noticing discrepancies is difficult. Most readers miss most discrepancies even when asked specifically to look for them. The probability of a discrepancy evading an individual sensitized reader is 95%, making it important that, when problems are identified after publication, readers are able to communicate with each other. When made aware of discrepancies, the majority of readers support editorial action to correct the scientific record.
Barron AJ, Dhutia NM, Glaeser S, et al., 2015, Physiology of oxygen uptake kinetics: Insights from incremental cardiopulmonary exercise testing in the Study of Health in Pomerania, IJC METABOLIC & ENDOCRINE, Vol: 7, Pages: 3-9, ISSN: 2214-7624
Ahmad Y, Sen S, Shun-Shin MJ, et al., 2015, Intra-aortic Balloon Pump Therapy for Acute Myocardial Infarction AMeta-analysis, JAMA INTERNAL MEDICINE, Vol: 175, Pages: 931-939, ISSN: 2168-6106
Nijjer SS, Petraco R, van de Hoef TP, et al., 2015, Change in Coronary Blood Flow After Percutaneous Coronary Intervention in Relation to Baseline Lesion Physiology Results of the JUSTIFY-PCI Study, CIRCULATION-CARDIOVASCULAR INTERVENTIONS, Vol: 8, ISSN: 1941-7640
Sohaib SM, Kyriacou A, Jones S, et al., 2015, Evidence that conflict regarding size of haemodynamic response to interventricular delay optimization of cardiac resynchronization therapy may arise from differences in how atrioventricular delay is kept constant., Europace, Vol: 17, ISSN: 1532-2092
AIMS: Whether adjusting interventricular (VV) delay changes haemodynamic efficacy of cardiac resynchronization therapy (CRT) is controversial, with conflicting results. This study addresses whether the convention for keeping atrioventricular (AV) delay constant during VV optimization might explain these conflicts. METHOD AND RESULTS: Twenty-two patients in sinus rhythm with existing CRT underwent VV optimization using non-invasive systolic blood pressure. Interventricular optimization was performed with four methods for keeping the AV delay constant: (i) atrium and left ventricle delay kept constant, (ii) atrium and right ventricle delay kept constant, (iii) time to the first-activated ventricle kept constant, and (iv) time to the second-activated ventricle kept constant. In 11 patients this was performed with AV delay of 120 ms, and in 11 at AV optimum. At AV 120 ms, time to the first ventricular lead (left or right) was the overwhelming determinant of haemodynamics (13.75 mmHg at ±80 ms, P < 0.001) with no significant effect of time to second lead (0.47 mmHg, P = 0.50), P < 0.001 for difference. At AV optimum, time to first ventricular lead again had a larger effect (5.03 mmHg, P < 0.001) than time to second (2.92 mmHg, P = 0.001), P = 0.02 for difference. CONCLUSION: Time to first ventricular activation is the overwhelming determinant of circulatory function, regardless of whether this is the left or right ventricular lead. If this is kept constant, the effect of changing time to the second ventricle is small or nil, and is not beneficial. In practice, it may be advisable to leave VV delay at zero. Specifying how AV delay is kept fixed might make future VV delay research more enlightening.
Sohaib SMA, Finegold JA, Nijjer SS, et al., 2015, Opportunity to Increase Life Span in Narrow QRS Cardiac Resynchronization Therapy Recipients by Deactivating Ventricular Pacing Evidence From Randomized Controlled Trials, JACC-HEART FAILURE, Vol: 3, Pages: 327-336, ISSN: 2213-1779
Nijjer SS, Sen S, Petraco R, et al., 2015, The Instantaneous wave-Free Ratio (iFR) pullback: a novel innovation using baseline physiology to optimise coronary angioplasty in tandem lesions, CARDIOVASCULAR REVASCULARIZATION MEDICINE, Vol: 16, Pages: 167-171, ISSN: 1553-8389
Ploux S, Eschalier R, Whinnett ZI, et al., 2015, Electrical dyssynchrony induced by biventricular pacing: Implications for patient selection and therapy improvement, HEART RHYTHM, Vol: 12, Pages: 782-791, ISSN: 1547-5271
Jamil-Copley S, Vergara P, Carbucicchio C, et al., 2015, Application of Ripple Mapping to Visualize Slow Conduction Channels Within the Infarct-Related Left Ventricular Scar, CIRCULATION-ARRHYTHMIA AND ELECTROPHYSIOLOGY, Vol: 8, Pages: 76-U110, ISSN: 1941-3149
Finegold J, Bordachar P, Kyriacou A, et al., 2015, Atrioventricular delay optimization of cardiac resynchronisation therapy: Comparison of non-invasive blood pressure with invasive haemodynamic measures, INTERNATIONAL JOURNAL OF CARDIOLOGY, Vol: 180, Pages: 221-222, ISSN: 0167-5273
Howard JP, Francis DP, 2015, Overcoming the three biases obscuring the science of renal denervation in humans: Big-day bias, check-once-more bias and I-will-take-it-now bias, TRENDS IN CARDIOVASCULAR MEDICINE, Vol: 25, Pages: 116-118, ISSN: 1050-1738
Cole GD, Shun-Shin MJ, Finegold JA, et al., 2015, Grateful receipt of clarifications on a perioperative trial: An illustration of the duty of readers to ask questions, INTERNATIONAL JOURNAL OF CARDIOLOGY, Vol: 179, Pages: 507-509, ISSN: 0167-5273
Jabbour RJ, Shun-Shin MJ, Finegold JA, et al., 2015, Effect of Study Design on the Reported Effect of Cardiac Resynchronization Therapy (CRT) on Quantitative Physiological Measures: Stratified Meta-Analysis in Narrow-QRS Heart Failure and Implications for Planning Future Studies, JOURNAL OF THE AMERICAN HEART ASSOCIATION, Vol: 4, ISSN: 2047-9980
Panikker S, Virmani R, Sakakura K, et al., 2015, Left atrial appendage electrical isolation and concomitant device occlusion: A safety and feasibility study with histologic characterization, HEART RHYTHM, Vol: 12, Pages: 202-210, ISSN: 1547-5271
Howard JP, Shun-Shin MJ, Francis DP, 2015, Great myths of blood pressure effect size in renal denervation, Renal Denervation: A New Approach to Treatment of Resistant Hypertension, Pages: 175-180, ISBN: 9781447152224
Raphael CE, Francis DP, 2014, Response to 'A simplified method for determination of the optimal atrioventricular delay in cardiac resynchronization therapy' IJC-D-14-02689, INTERNATIONAL JOURNAL OF CARDIOLOGY, Vol: 177, Pages: 1122-1123, ISSN: 0167-5273
Jones S, Shun-Shin MJ, Cole GD, et al., 2014, Iterative method for atrioventricular optimization of cardiac resynchronization therapy: is beauty only in the eye of the beholder? Reply, EUROPACE, Vol: 16, Pages: 1866-1866, ISSN: 1099-5129
Nijjer SS, Sen S, Petraco R, et al., 2014, Pre-Angioplasty Instantaneous Wave-Free Ratio Pullback Provides Virtual Intervention and Predicts Hemodynamic Outcome for Serial Lesions and Diffuse Coronary Artery Disease, JACC-CARDIOVASCULAR INTERVENTIONS, Vol: 7, Pages: 1386-1396, ISSN: 1936-8798
Dhutia NM, Cole GD, Zolgharni M, et al., 2014, Automated speckle tracking algorithm to aid on-axis imaging in echocardiography, Journal of Medical Imaging, Vol: 1, ISSN: 2329-4310
Obtaining a "correct" view in echocardiography is a subjective process in which an operator attempts to obtain images conforming to consensus standard views. Real-time objective quantification of image alignment may assist less experienced operators, but no reliable index yet exists. We present a fully automated algorithm for detecting incorrect medial/lateral translation of an ultrasound probe by image analysis. The ability of the algorithm to distinguish optimal from sub-optimal four-chamber images was compared to that of specialists-the current "gold-standard." The orientation assessments produced by the automated algorithm correlated well with consensus visual assessments of the specialists ([Formula: see text]) and compared favourably with the correlation between individual specialists and the consensus, [Formula: see text]. Each individual specialist's assessments were within the consensus of other specialists, [Formula: see text] of the time, and the algorithm's assessments were within the consensus of specialists 85% of the time. The mean discrepancy in probe translation values between individual specialists and their consensus was [Formula: see text], and between the automated algorithm and specialists' consensus was [Formula: see text]. This technology could be incorporated into hardware to provide real-time guidance for image optimisation-a potentially valuable tool both for training and quality control.
Patel HC, Hayward C, Ozdemir BA, et al., 2014, Magnitude of Blood Pressure Reduction in the Placebo Arms of Modern Hypertension Trials Implications for Trials of Renal Denervation, Hypertension, Vol: 65, Pages: 401-406, ISSN: 1524-4563
Stewart AJ, Nijjer SS, Francis DP, 2014, Protecting the pipeline of science: Openness, scientific methods and the lessons from ticagrelor and the PLATO trial, INTERNATIONAL JOURNAL OF CARDIOLOGY, Vol: 176, Pages: 600-604, ISSN: 0167-5273
Cole GD, Patel SJ, Zaman N, et al., 2014, "Triple Therapy" of Heart Failure With Angiotensin-Converting Enzyme Inhibitor, Beta-Blocker, and Aldosterone Antagonist May Triple Survival Time Shouldn't We Tell Patients?, JACC-HEART FAILURE, Vol: 2, Pages: 545-548, ISSN: 2213-1779
Sohaib SM, Jones S, Manoharan K, et al., 2014, 55Testing the validity of electrogram based AV optimization schemes using real world patient data., Europace, Vol: 16 Suppl 3
Manufacturers have each implemented manufacturer specific methods for electrogram based optimization of AV delay in CRT devices. Agreement between manufacturer algorithms has never been formally tested. Where the algorithms are fully published and available, we tested agreement between different device based AV optimisation scheme, and compared this to the AV optimum selected using non-invasive haemodynamic optimisation.
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