A simplified study of trans-mitral Doppler patterns

<p>Abstract</p> <p>Background</p> <p>Trans-mitral Doppler produces complex patterns with a great deal of variability. There are several confusing numerical measures and indices to study these patterns. However trans-mitral Doppler produces readymade data visualization by pattern generation which could be interpreted by pattern analysis. By following a systematic approach we could create an order and use this tool to study cardiac function.</p> <p>Presentation of the hypothesis</p> <p>In this new approach we eliminate the variables and apply pattern recognition as the main criterion of study. Proper terminologies are also devised to avoid confusion. In this way we can get some meaningful information.</p> <p>Testing the hypothesis</p> <p>Trans-mitral Doppler should be seen as patterns rather than the amplitude. The hypothesis can be proven by logical deduction, extrapolation and elimination of variables. Trans-mitral flow is also analyzed <it>vis-à-vis </it>the Starling's Law applied to the left atrium.</p> <p>Implications of the hypothesis</p> <p>Trans-mitral Doppler patterns are not just useful for evaluating diastolic function. They are also useful to evaluate systolic function. By following this schema we could get useful diagnostic information and therapeutic options using simple pattern recognition with minimal measurements. This simplified but practical approach will be useful in day to day clinical practice and help in understanding cardiac function better. This will also standardize research and improve communication.</p

Identification of Single- and Multiple-Class Specific Signature Genes from Gene Expression Profiles by Group Marker Index

Informative genes from microarray data can be used to construct prediction model and investigate biological mechanisms. Differentially expressed genes, the main targets of most gene selection methods, can be classified as single- and multiple-class specific signature genes. Here, we present a novel gene selection algorithm based on a Group Marker Index (GMI), which is intuitive, of low-computational complexity, and efficient in identification of both types of genes. Most gene selection methods identify only single-class specific signature genes and cannot identify multiple-class specific signature genes easily. Our algorithm can detect de novo certain conditions of multiple-class specificity of a gene and makes use of a novel non-parametric indicator to assess the discrimination ability between classes. Our method is effective even when the sample size is small as well as when the class sizes are significantly different. To compare the effectiveness and robustness we formulate an intuitive template-based method and use four well-known datasets. We demonstrate that our algorithm outperforms the template-based method in difficult cases with unbalanced distribution. Moreover, the multiple-class specific genes are good biomarkers and play important roles in biological pathways. Our literature survey supports that the proposed method identifies unique multiple-class specific marker genes (not reported earlier to be related to cancer) in the Central Nervous System data. It also discovers unique biomarkers indicating the intrinsic difference between subtypes of lung cancer. We also associate the pathway information with the multiple-class specific signature genes and cross-reference to published studies. We find that the identified genes participate in the pathways directly involved in cancer development in leukemia data. Our method gives a promising way to find genes that can involve in pathways of multiple diseases and hence opens up the possibility of using an existing drug on other diseases as well as designing a single drug for multiple diseases

Defining left ventricular remodeling following acute ST-segment elevation myocardial infarction using cardiovascular magnetic resonance.

The assessment of post-myocardial infarction (MI) left ventricular (LV) remodeling by cardiovascular magnetic resonance (CMR) currently uses criteria defined by echocardiography. Our aim was to provide CMR criteria for assessing LV remodeling following acute MI.This article is freely available via Open Access. Click on the Additional Link above to access the full-text via the publisher's site

Atrial tachyarrythmias and atrioventricular delay optimization: the MATE study

The aim of MATE study is to demonstrate that the total number of atrial arrhythmia episodes is significantly reduced when combining an optimal atrioventricular delay with HRV mode switching algorithm in comparison with standrd pacing and nominal atrioventricular delay

Relationship between infarct size and severity measured by gated SPECT and long-term left ventricular remodelling after acute myocardial infarction

Purpose: After acute myocardial infarction (AMI), left ventricular (LV) remodelling may occur despite successful reperfusion. This study aimed to investigate by gated single photon emission computed tomography (SPECT) the long-term evolution of myocardial perfusion and LV function after AMI and to identify the predictors of LV remodelling. Methods: Sixty-eight AMI patients successfully treated by primary percutaneous coronary intervention underwent 99mTc-sestamibi gated SPECT at 1 month (baseline) and over 6-month follow-up after the acute event. LV remodelling was defined as 20% increase in LV end-diastolic volume at follow-up. Results: At baseline, patients with remodelling (n=14) showed larger (infarct size 29.3±7.8%) and more transmural (infarct severity 0.28±0.10) infarctions, and reduced LV ejection fraction (35.4±5.6%), but similar LV volume indexes, compared to patients without remodelling (n=54) (infarct size 20.8±14.4%, p<0.05, infarct severity 0.40±0.11, p<0.001, ejection fraction 44.5±9.2, p<0.001). At stepwise multivariate regression analysis, infarct severity showed the best predictive value for predicting LV remodelling (F=5.54, p<0.05). Using the thresholds identified by receiver-operating characteristic curve analysis, infarct size and severity detected patients with remodelling with 75% accuracy and 95% negative predictive value. Infarct resorption (defined as the defect size difference between follow-up and baseline) was comparable between patients with (-4.4±8.4%) and without remodelling (-6.8±9.4%) (p=NS). Conclusion: Perfusion parameters assessed by gated SPECT in the subacute phase after successfully treated AMI correlate with changes in functional parameters at long-term follow-up. Infarct severity is more effective than infarct size, but both are helpful for predicting LV remodelling