Tanveer Ahmed Bhuiyan

The T-peak–T-end Interval as a Marker of Repolarization Abnormality: A Comparison with the QT Interval for Five Different Drugs

Background and ObjectiveThe T-peak to T-end (TpTe) interval has been suggested as an index of transmural dispersion and as a marker of drug-induced abnormal repolarization. In this study, we investigate the relation between TpTe and the QT interval.MethodsElectrocardiograms (ECGs) from five different drugs (sotalol, sertindole, moxifloxacin, nalmefene, and Lu 38-135) and from a placebo group were analyzed. Semi-automatic measurements of T-peak, T-end, and QRS onset were obtained. The TpTe/QT ratio was calculated to investigate the proportional relationship of QT and TpTe.ResultsAlthough a significant increase of both TpTe and QT from baseline is apparent with QT-prolonging drugs, the TpTe/QT ratio remained the same at baseline and after drug administration, thus indicating that prolongation of TpTe is just a fractional part of total QT prolongation. In the presence of notched or flattened T-waves, the uncertainty associated with measurement of the TpTe interval increases. The errors in TpTe for individual subjects may be substantial, thus complicating the use of TpTe for follow-up of individuals.ConclusionsThe duration of the QT interval and TpTe are closely related. Drugs appear to prolong the TpTe interval as a predictable fraction of the total QT prolongation.

A belief rule-based expert system to assess mental disorder under uncertainty

Mental disorder is a change of mental or behavioral pattern that causes sufferings and impairs the ability to function in ordinary life. In psychopathology, the assessment methods of mental disorder contain various types of uncertainties associated with signs and symptoms. This study identifies a method that addresses the issue of uncertainty in assessing mental disorder. The fuzzy logic knowledge representation schema can address uncertainty associated with linguistic terms including ambiguity, imprecision, and vagueness. However, fuzzy logic is incapable of addressing uncertainty due to ignorance, incompleteness, and randomness. So, a belief rule-based expert system (BRBES) has been designed and developed with the capability of handling the uncertainties mentioned. Evidential reasoning works as the inference engine and the belief rule base as the knowledge representation schema in this BRBES. The study shows that the results generated by BRBES are more reliable than that of Fuzzy Rule-based expert system and from a human expert.

A History of Drug-Induced Torsades de Pointes Is Associated With T-wave Morphological Abnormalities

The hypothesis of the study is that Torsades de pointes (TdP) history can be better identified using T-wave morphology compared to Fridericia-corrected QT interval (QTcF) at baseline. ECGs were recorded at baseline and during sotalol challenge in 20 patients with a history of TdP (+TdP) and 16 patients without previous TdP (-TdP). The QTcF and T-wave morphology combination score (MCS) were calculated. At baseline, there was no significant difference in QTcF between the groups (+TdP: QTcF = 446 ± 9 ms; -TdP: QTcF = 431 ± 9 ms, P = 0.27). In contrast, MCS was significantly different between the groups at baseline (+TdP: MCS = 1.07 ± 0.095; -TdP: MCS = 0.74 ± 0.07, P = 0.012). Both QTcF and MCS could be used to discriminate between +TdP and -TdP after sotalol but only MCS reached statistical significance at baseline. Combining QTcF with MCS provided a significantly larger difference between groups than QTcF alone.

A Belief Rule-Based Expert System to Assess Bronchiolitis Suspicion from Signs and Symptoms Under Uncertainty

Bronchiolitis is an acute viral infection of the bronchioles—a common disease that affects millions of children around the world. Clinically, the disease is suspected by observing the signs and symptoms. The signs and symptoms are difficult to measure with 100% certainty, which make suspecting Bronchiolitis inaccurate while suspecting severity level as well. So, the paper aims at designing and developing a Belief Rule-Based Expert System (BRBES), which can suspect Bronchiolitis under uncertainty and increase accuracy. Belief rule based inference methodology has been considered to develop the inference engine of the expert system while the belief rule base has been used to develop the knowledge-base. The reliability of the BRBES has been tested by using real patient data and compared with the expert opinion.