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- Chesnut, G. T., et al.
(författare)
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Patient-reported pain, discomfort, and anxiety during magnetic resonance imaging-targeted prostate biopsy
- 2020
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Ingår i: Canadian Urological Association Journal. - 1920-1214. ; 14:5
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: The addition of targeted prostate biopsy to systemic biopsy impacts patient experience. We examined patient-reported pain, discomfort, anxiety, and tolerability among men undergoing magnetic resonance imaging (MRI)-targeted prostate biopsy in addition to transrectal ultrasound-guided systematic biopsy compared to those undergoing systematic biopsy alone. Methods: All patients underwent transrectal systematic 14-core biopsies. Patients with regions of interest on MRI underwent additional targeted biopsies. All patients received equivalent periprostatic nerve block. Four single-item, standard 11-point numerical rating scales evaluating pain, discomfort, anxiety, and tolerability were completed immediately after biopsy. Differences in means were compared using t-tests. Correlation between rated domains was tested using Spearman's correlation coefficient. Results: Of 273 consecutive patients, 195 (71%) underwent targeted biopsy and 188 (69%) had undergone prior biopsy. In all men, the median score for pain and tolerability was 3, while the median score for discomfort and anxiety was 4. Pain was rated at 7 or above by 15% of patients. Moderate correlation between pain, discomfort, anxiety, and tolerability of repeat biopsy was observed (Spearman's ρ between 0.48 and 0.76). Compared to patients undergoing systematic biopsy alone, men who received both targeted and systematic biopsies reported higher anxiety scores (difference 1.2; 95% confidence interval [CI] 0.4-2.0; p=0.004) and discomfort (difference 1.0; 95% CI 0.3-1.7; p<0.001). Conclusions: Patients undergoing targeted and systematic biopsies report more discomfort and anxiety than patients undergoing systematic biopsies alone. Absolute differences are small, and patients are willing to undergo repeat biopsy if advised. Interventions to reduce biopsy-related anxiety are needed. © 2020 Canadian Urological Association. All rights reserved.
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- Mann, Stefan A., et al.
(författare)
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Convergence of models of human ventricular myocyte electrophysiology after global optimization to recapitulate clinical long QT phenotypes
- 2016
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Ingår i: Journal of Molecular and Cellular Cardiology. - : Elsevier BV. - 0022-2828 .- 1095-8584. ; 100, s. 25-34
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Tidskriftsartikel (refereegranskat)abstract
- In-silico models of human cardiac electrophysiology are now being considered for prediction of cardiotoxicity as part of the preclinical assessment phase of all new drugs. We ask the question whether any of the available models are actually fit for this purpose. We tested three models of the human ventricular action potential, the O'hara-Rudy (ORD11), the Grandi-Bers (GB10) and the Ten Tusscher (TT06) models. We extracted clinical QT data for LQTS1 and LQTS2 patients with nonsense mutations that would be predicted to cause 50% loss of function in I-Ks and I-Kr respectively. We also obtained clinical QT data for LQTS3 patients. We then used a global optimization approach to improve the existing in silico models so that they reproduced all three clinical data sets more closely. We also examined the effects of adrenergic stimulation in the different LQTS subsets. All models, in their original form, produce markedly different and unrealistic predictions of QT prolongation for LQTS1, 2 and 3. After global optimization of the maximum conductances for membrane channels, all models have similar current densities during the action potential, despite differences in kinetic properties of the channels in the different models, and more closely reproduce the prolongation of repolarization seen in all LQTS subtypes. In-silico models of cardiac electrophysiology have the potential to be tremendously useful in complementing traditional preclinical drug testing studies. However, our results demonstrate they should be carefully validated and optimized to clinical data before they can be used for this purpose.
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