196,048 research outputs found
Deep learning-based insights on T:R ratio behaviour during prolonged screening for S-ICD eligibility
No full textDr. Mohamed ElRefai is receiving unrestricted grant from Boston Scientific. Dr. Benedict Wiles has received unrestricted research funding and consultancy payments from Boston Scientific. Dr. Paul Roberts receives consultancy fees from Boston Scientific and Medtronic. The other authors declare no competing interests.Peer reviewe
The use of artificial intelligence and deep learning methods in subcutaneous implantable cardioverter defibrillator screening to optimise selection in special patient populations
No full textFunding Acknowledgements: Type of funding sources: Private company. Main funding source(s): Dr.Mohamed ElRefai is receiving an unrestricted grant from Boston Scientific.Introduction: Adult congenital heart disease (ACHD) and hypertrophic cardiomyopathy (HCM) patients who require defibrillator therapy are often relatively young and may require several generator replacements in their lifetime. The increased risk of complications associated with transvenous ICDs make the subcutaneous (S-ICD) a valuable alternative. However, higher S-ICD ineligibility rates (20-40% in ACHD and 7-38% in HCM) and higher inappropriate shock rates (10.5% in ACHD and 12.5% in HCM) are observed in these populations. Unfavourable T:R ratios and dynamic changes in the R and T wave amplitudes are the primarily factors behind ineligibility and inappropriate shocks, which are most commonly caused by T wave over-sensing.Purpose: We report a novel application of deep learning methods used to autonomously screen patients for S-ICD eligibility over a longer period than conventional screening. We hypothesise that this screening approach might achieve better patient selection and optimise S-ICD vector selection in challenging patient cohorts.Methods: Adult patients with ACHD or HCM and a control group of normal subjects were fitted with a 24-hour ambulatory ECG with the leads placed to record their S-ICD vectors. T: R ratio throughout the recordings was analysed utilising phase space reconstruction matrices to convert the ECG signal into compressed pixel images. Whilst a convolutional neural network model was trained to provide an in-depth description of the T: R variation plot for each vector T: R variation was compared statistically using a one-way ANOVA test.Results: 20 patients (age 44.1 ±11.68, 60% male, 7 HCM, 6 ACHD and 7 control subjects) were enrolled. A significant difference was observed in the mean and median T: R values between the three groups (p<0.001). There was no difference observed in the standard deviation of T: R between the control subjects and HCM group. However, there was a statistically significant difference in the standard deviation of T: R between the control subjects and the ACHD group (p= 0.01). [see Figure].Conclusions: T:R ratio, a main determinant for S-ICD eligibility, is significantly higher in ACHD and HCM when compared to normal hearts and it also has more tendency to fluctuate in ACHD patients when compared to HCM and normal hearts populations. We hypothesise that our novel model could be used to select S-ICD eligible patients by better characterisation of T:R ratio reducing the risk of T wave oversensing and inappropriate shocks particularly in the ACHD patients’ cohor
Leadless pacemakers: where is the device?
No full textType of funding sources: None.Introduction: Leadless pacemakers (LPs) were designed to avoid lead-related complications associated with transvenous pacing. To minimise the risk of complications, there is preference towards implanting LPs into the septal aspect of the right ventricle rather than the apex or free wall. The Transcatheter Pacing Study (TPS) and the international post-approval registry demonstrated the safety and reliability of the LP systems in real-world settings. The registry demonstrated that more than half of the LPs were implanted into the septum and most required <2 attempts at deployment. We report a radiological method of defining LP position.Methods: We reviewed the first 100 LPs implanted at our centre. Two independent observers who didn’t implant LPs reviewed the patients’ post-implant fluoroscopy images and/or post-implant CXRs when available. The reviewers assessed the devices’ positions in postero-anterior (PA) and/or right anterior oblique (RAO) views based on conventional fluoroscopic criteria for lead position. We used the proposed criteria interchangeably on fluoroscopic images and post implant CXRs (Figure). Differences in classification of device position were resolved by consensus.Results: Three experienced operators implanted 100 LPs at our centre. Patients (61% male) 56.6 ± 22.2 years had normal hearts (74%), ischaemic cardiomyopathies (12%), congenital heart diseases (6%), valvular pathologies (5%) and dilated cardiomyopathies (3%). Indications for pacing were symptomatic sinus node dysfunction (36%), followed by high grade atrio-ventricular block (33%), bradyarrhythmia associated with atrial tachyarrhythmias (27%) and other indications for pacing (4%). We had a 100% successful implant rate, 88% required ≤2 attempts and 70% required one attempt. There were no major complications.We were able to classify the site of the LPs implants in a total of 90 patients who had fluoroscopic projections or chest x-rays that would allow us to classify the implant sites. A total of 32 implants were in the apex (35.6%). 28 were in mid-septum (31.1 %), 15 in the apical septum (16.7%), 14 on the septal aspect of the right ventricular inflow (15.5%) and 1 implant (1.1%) in the septum of the RV outflow tract.Conclusion: Our proposed method of defining LP position demonstrated that the rate of implants into the true apex at our centre was highly comparable to that of the international registry. It also showed that we had lower rates of implants into the mid-septum in favour of apical septum. There were no pericardial effusions or cardiac perforations resulting from our implant procedures regardless of the site of the implant. We utilised widely used fluoroscopic and chest x-ray criteria for categorisation of the LPs implantation sites. However, a recognised limitation to our analysis is that our findings were not validated using other imaging modalities such as echocardiogram or cardiac computerised tomography (CT)
Leadless pacemakers: does location matter?
No full textFunding AcknowledgementsType of funding sources: None.Introduction: Leadless pacemakers (LPs) provide a viable alternative for patients who have an indication for pacing where transvenous pacing is not desirable or possible. Registries have demonstrated stable performance associated with LPs. There is preference towards implanting LPs into the trabeculated septum rather than the apex or free wall. We report our experience with the impact of the implantation site on acute and long-term electrical performance of LPs.Methods: We ran a retrospective analysis on the first 100 LPS implanted at our centre. Two independent observers reviewed the fluoroscopic images and post-implant chest x-rays to classify the LPs’ positions. We obtained the recorded pacing threshold , R-wave amplitude and impedance of the devices at the time of implant and at the latest available routine device follow-up. We used one-way ANOVA testing to compare the acute and long-term electrical performance of the LPs between different implantation sites.Results: We were able to classify the site of the LPs implants in a total of 90 patient. 84 Patients (60% male) 57.3± 22.16 years were included .23.8% of the patients presented with syncope. Indications for pacing were symptomatic sinus node dysfunction (33.3%), high grade AV block (34.5%), bradyarrhythmia associated with atrial tachyarrhythmias (28.6%) and other indications (3.6%). We had a 100% successful implant rate, 85.7% required ≤2 attempts and 71.4% required one attempt. A total of 32 implants were in the apex (38.1%), 26 in mid-septum (30.9 %), 13 in the apical septum (15.5%), 12 on the septal aspect of the right ventricular inflow (14.3%) and 1 implant (1.2%) in the septum of the RV outflow tract.The follow up period of the 84 patients was 3.09 ± 1.97 years. 100% of the LPs had the pacing thresholds <2.0 V @0.24 ms at the time of implant. Pacing threshold, R-wave amplitude, and impedance averaged at 0.67 ± 0.41 V, 10.86 ± 5.41 mV, and 775 ± 193.28 Ohms respectively at the time of implantation and 0.66 ± 0.39 V, 14.08 ± 6.14 mV, and 564.29 ± 96.76 Ohms at the last device check. There was no statistically significant difference in either the pacing thresholds or the impedance between implant sites. Post hocTukey’s analysis (excluding the outflow tract case) demonstrated significant statistical difference in the R-wave amplitudes between implants at the apex and the mid-septum both at the time of implantation (12.9 ± 6.1 mV and 8.53 ± 2.84 mV; p = 0.0196) and at follow up (15.97 ± 5.35 mV and 11.52 ± 5.01 mV; p = 0.0415). There were no differences between other sitesConclusions: Our analysis demonstrated that aside from the difference between the sensed R wave amplitudes between LPs implanted at the apex and those implanted at mid-septum , there was no statistically significant difference in the acute or the long term electrical performance of implanted LPs regardless of the implantation site. A limitation to our analysis is the relatively low number of LP implants included in our analysi
Eligibility for subcutaneous implantable cardiac defibrillator utilising artificial intelligence and deep learning methods for prolonged screening: where is the cut-off?
No full textFunding acknowledgements: type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Main author is receiving an unrestricted grant by Boston ScientificBackground: S-ICD eligibility is determined by a single surface ECG analysis in which the suitability of an individual’s ECG vector morphology is assessed. A major predictor of eligibility is the T:R ratio. Current screening tools proposes T: R of 1:3 as a cut-off for eligibility. Inappropriate shocks due to T-wave oversensing (TWO) remains an issue despite screening. EFFORTLESS and PRAETORIAN trials reported inappropriate shock rates of 11.4% and 9.7% respectively, most frequently caused by cardiac oversensing.Purpose: the cut-off T: R of 1:3 currently used incorporates a safety margin to accommodate for ECG signal amplitudes fluctuations without affecting S-ICD sensing. Prolonged screening using our tool accurately measures the T: R fluctuations. However, utilising a T: R of 1:3 for prolonged screening can unnecessarily exclude appropriate S-ICD candidates. The purpose of our study is to provide groundwork for future trials to find the optimal ratio that identifies patients at risk of TWO and inappropriate shocks while not excluding true S-ICD candidates after prolonged screening.Methods: patients were fitted with 24-hour Holter monitors with leads placed to correspond to the vectors of an S-ICD. We used our tool to assess T: R over the recordings utilising Phase Space Reconstruction matrices - to convert the ECG signal into compressed pixel images. A Convolutional Neural Network (CNN) model was trained to accurately predict the T: R from these images resulting in a T: R variation plot for each vector. We then applied multiple T:R ratio cut-offs on the recordings to identify patients at risk of inappropriate shocks due to TWO at each proposed value. A vector with a T: R above the cut-off for 20 consecutive seconds was deemed to have failed screening, the time determined by the current detection, charge, and redetection time of the current S-ICD system. A patient has to have at least one suitable vector to pass the screening at the selected threshold.Results: 37 patients (mean age 54.5 years,64.8% male) were included. 14 had Heart failure, 7 Hypertrophic cardiomyopathy, 7 normal hearts, 6 Adult congenital heart disease and 3 patients who received inappropriate S-ICD shocks due to TWO. Overall, 20 (54%) of patients passed prolonged screening using a 1:3 ratio. All of the patients passed screening with a T: R of 1:1. The only subgroup to wholly pass the screening for all the proposed ratios are the normal hearts group.Conclusion: we propose adopting prolonged screening to select S-ICD eligible patients with low probability of TWO and inappropriate shocks. However, utilising T: R of 1:3 can unnecessarily exclude otherwise S-ICD eligible patients. The appropriate ratio likely lies between 1:3 - 1:1. Further studies are needed to identify the optimal screening thresholds, particularly in patients that have had inappropriate shocks due to TWO
Dr. Duane M. Jackson, Morehouse College, July 2011
No full textThis video is a conversation with Dr. Duane M. Jackson. Dr. Jackson talks about his paper, "Recall and the Serial Position Effect: The Role of Primacy and Recency on Accounting Students' Performance." Jackie Daniel, AUC Woodruff Library, is the interviewer
"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States" By M. Carey.
No full text"Reflections on the subject of Emigration from Europe with a view to Settlement in the United States: containing bried sketches of the moral and political character of those states.
By M. Carey, member of the American philosophical, and of the American Antiquarian Society, and author of The Olive Branch, Cindiciae Hibernicae, essays on banking, on political economy, and on internal improvement.
To which are now added the English editor's comments on the subject; together with Important Advice to Emigrants, and Cautions Against Impositions Practiced in the Outports
Deep learning methods for screening patients' S-ICD implantation eligibility
No full textSubcutaneous Implantable Cardioverter-Defibrillators (S-ICDs) are used for prevention of sudden cardiac death triggered by ventricular arrhythmias. T Wave Over Sensing (TWOS) is an inherent risk with S-ICDs which can lead to inappropriate shocks. A major predictor of TWOS is a high T:R ratio (the ratio between the amplitudes of the T and R waves). Currently, patients' Electrocardiograms (ECGs) are screened over 10 s to measure the T:R ratio to determine the patients' eligibility for S-ICD implantation. Due to temporal variations in the T:R ratio, 10 s is not a long enough window to reliably determine the normal values of a patient's T:R ratio. In this paper, we develop a convolutional neural network (CNN) based model utilising phase space reconstruction matrices to predict T:R ratios from 10-second ECG segments without explicitly locating the R or T waves, thus avoiding the issue of TWOS. This tool can be used to automatically screen patients over a much longer period and provide an in-depth description of the behavior of the T:R ratio over that period. The tool can also enable much more reliable and descriptive screenings to better assess patients' eligibility for S-ICD implantation.</p
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Dr. Glendon Swarthout
No full textHosted by Roger M. Busfield, MSU Assistant Professor of Speech and Theater, Meet the Author is designed to introduce a general audience to a contemporary author and their work through in-depth interviews. This episode features a conversation between Dr. Glendon Swarthout, prolific author and English professor at MSU, and assistant professors Sam S. Baskett and Theodore B. Strandness
- …
