QT dispersion as an attribute of T-loop morphology

BACKGROUND: The suggestion that increased QT dispersion (QTD) is due to increased differences in local action potential durations within the myocardium is wanting. An alternative explanation was sought by relating QTD to vectorcardiographic T-loop morphology. METHODS AND RESULTS: The T loop is characterized by its amplitude and width (defined as the spatial angle between the mean vectors of the first and second halves of the loop). We reasoned that small, wide ("pathological") T loops produce larger QTD than large, narrow ("normal") loops. To quantify the relationship between QTD and T-loop morphology, we used a program for automated analysis of ECGs and a database of 1220 standard simultaneous 12-lead ECGs. For each ECG, QT durations, QTD, and T-loop parameters were computed. T-loop amplitude and width were dichotomized, with 250 microV (small versus large amplitudes) and 30 degrees (narrow versus wide loops) taken as thresholds. Over all 1220 ECGs, QTDs were smallest for large, narrow T loops (54.2+/-27.1 ms) and largest for small, wide loops (69. 5+/-33.5 ms; P<0.001). CONCLUSIONS: QTD is an attribute of T-loop morphology, as expressed by T-loop amplitude and width

Expert knowledge for computerized ECG interpretation

In this study, two main questions are addressed: (1) Can the time consuming and cumbersome development and refinement of (heuristic) ECG classifiers be alleviated, and (2) Is it possible to increase diagnostic performance of ECG computer programs by combining knowledge from multiple sources? Chapters 2 and 3 are of an introductory character. In Chapter 2, the measurement part of MEANS is described and evaluated. This research largely depends on the earlier work of Talman [11]. In Chapter 3, different methods of diagnostic ECG classification are described and their pros and cons discussed. The issue is raised whether or not the ECG should be classified using as much prior information as possible, and our position is made clear. The first question~ how to ease the transfer of cardiological knowledge into computer algorithms, is addressed in Chapters 4 and 5. The development and refinement of heuristic ECG classifiers is impeded by two problems: (1) It generally requires a computer expert to translate the cardiologist's reasoning into computer language without the average cardiologist being able to verify whether his diagnostic intentions were properly realized, and (2) The classifiers are often so complex as to obscure insight into their doings when a particular case is processed by the classification program. To circumvent these problems. we developed a dedicated language. DTL (Decision Tree Language), and an interpreter and compiler of that language. In Chapter 4, a comprehensive description of the DTL environment is given. In Chapter 5, the use of the environment to optimize MEANS, following a procedure of stepwise refmement, is described The second question, whether it is feasible to combine knowledge from multiple sources in order to increase diagnostic performance of an ECG computer program, is explored from several perspectives in Chapters 6 tlrrough

Minimum bandwidth requirements for recording of pediatric electrocardiograms

BACKGROUND: Previous studies that determined the frequency content of the pediatric ECG had their limitations: the study population was small or the sampling frequency used by the recording system was low. Therefore, current bandwidth recommendations for recording pediatric ECGs are not well founded. We wanted to establish minimum bandwidth requirements using a large set of pediatric ECGs recorded at a high sampling rate. METHODS AND RESULTS: For 2169 children aged 1 day to 16 years, a 12-lead ECG was recorded at a sampling rate of 1200 Hz. The averaged beats of each ECG were passed through digital filters with different cut off points (50 to 300 Hz in 25-Hz steps). We measured the absolute errors in maximum QRS amplitude for each simulated bandwidth and determined the percentage of records with an error >25 microV. We found that in any lead, a bandwidth of 250 Hz yields amplitude errors 95% of the children <1 year. For older children, a gradual decrease in ECG frequency content was demonstrated. CONCLUSIONS: We recommend a minimum bandwidth of 250 Hz to record pediatric ECGs. This bandwidth is considerably higher than the previous recommendation of 150 Hz from the American Heart Association

Training text chunkers on a silver standard corpus: Can silver replace gold?

Background: To train chunkers in recognizing noun phrases and verb phrases in biomedical text, an annotated corpus is required. The creation of gold standard corpora (GSCs), however, is expensive and time-consuming. GSCs therefore tend to be small and to focus on specific subdomains, which limits their usefulness. We investigated the use of a silver standard corpus (SSC) that is automatically generated by combining the outputs of multiple chunking systems. We explored two use scenarios: one in which chunkers are trained on an SSC in a new domain for which a GSC is not available, and one in which chunkers are trained on an available, although small GSC but supplemented with an SSC.Results: We have tested the two scenarios using three chunkers, Lingpipe, OpenNLP, and Yamcha, and two different corpora, GENIA and PennBioIE. For the first scenario, we showed that the systems trained for noun-phrase recognition on the SSC in one domain performed 2.7-3.1 percenta

The meaning of chakin placed on koita, as the evidence that temae has changed

textabstractIntroduction: There is growing interest in whether social media can capture patient-generated information relevant for medicines safety surveillance that cannot be found in traditional sources. Objective: The aim of this study was to evaluate the potential contribution of mining social media networks for medicines safety surveillance using the following associations as case studies: (1) rosiglitazone and cardiovascular events (i.e. stroke and myocardial infarction); and (2) human papilloma virus (HPV) vaccine and infertility. Methods: We collected publicly accessible, English-language posts on Facebook, Google+, and Twitter until September 2014. Data were queried for co-occurrence of keywords related to the drug/vaccine and event of interest within a post. Messages were analysed with respect to geographical distribution, context, linking to other web content, and author’s assertion regarding the supposed association. Results: A total of 2537 posts related to rosiglitazone/cardiovascular events and 2236 posts related to HPV vaccine/infertility were retrieved, with the majority of posts representing data from Twitter (98 and 85 %, respectively) and originating from users in the US. Approximately 21 % of rosiglitazone-related posts and 84 % of HPV vaccine-related posts referenced other web pages, mostly news items, law firms’ websites, or blogs. Assertion analysis predominantly showed affirmation of the association of rosiglitazone/cardiovascular events (72 %; n = 1821) and of HPV vaccine/infertility (79 %; n = 1758). Only ten posts described personal accounts of rosiglitazone/cardiovascular adverse event experiences, and nine posts described HPV vaccine problems related to infertility. Conclusions: Publicly available data from the considered social media networks were sparse and largely untrackable for the purpose of providing early clues of safety concerns regarding the prespecified case studies. Further research investigating other case studies and exploring other social media platforms are necessary to further characterise the usefulness of social media for safety surveillance

The Normal College News, February 22, 1918

BACKGROUND: Knowledge graphs can represent the contents of biomedical literature and databases as subject-predicate-object triples, thereby enabling comprehensive analyses that identify e.g. relationships between diseases. Some diseases are often diagnosed in patients in specific temporal sequences, which are referred to as disease trajectories. Here, we determine whether a sequence of two diseases forms a trajectory by leveraging the predicate information from paths between (disease) proteins in a knowledge graph. Furthermore, we determine the added value of directional information of predicates for this task. To do so, we create four feature sets, based on two methods for representing indirect paths, and both with and without directional information of predicates (i.e., which protein is considered subject and which object). The added value of the directional information of predicates is quantified by comparing the classification performance of the feature sets that include or exclude it. RESULTS: Our method achieved a maximum area under the ROC curve of 89.8% and 74.5% when evaluated with two different reference sets. Use of directional information of predicates significantly improved performance by 6.5 and 2.0 percentage points respectively. CONCLUSIONS: Our work demonstrates that predicates between proteins can be used to identify disease trajectories. U