The Measurement of the QT Interval

The evaluation of every electrocardiogram should also include an effort to interpret the QT interval to assess the risk of malignant arrhythmias and sudden death associated with an aberrant QT interval. The QT interval is measured from the beginning of the QRS complex to the end of the T-wave, and should be corrected for heart rate to enable comparison with reference values. However, the correct determination of the QT interval, and its value, appears to be a daunting task. Although computerized analysis and interpretation of the QT interval are widely available, these might well over- or underestimate the QT interval and may thus either result in unnecessary treatment or preclude appropriate measures to be taken. This is particularly evident with difficult T-wave morphologies and technically suboptimal ECGs. Similarly, also accurate manual assessment of the QT interval appears to be difficult for many physicians worldwide. In this review we delineate the history of the measurement of the QT interval, its underlying pathophysiological mechanisms and the current standards of the measurement of the QT interval, we provide a glimpse into the future and we discuss several issues troubling accurate measurement of the QT interval. These issues include the lead choice, U-waves, determination of the end of the T-wave, different heart rate correction formulas, arrhythmias and the definition of normal and aberrant QT intervals. Furthermore, we provide recommendations that may serve as guidance to address these complexities and which support accurate assessment of the QT interval and its interpretation.     

Ten‐Year Retrospective Follow‐Up Study of the TiOblast™ Dental Implant

Purpose: Long‐term results in the clinical outcome of different implant systems, including high patient numbers and a long follow‐up time, are rare. This retrospective study evaluated the cumulative survival rate of a self‐tapping, cylindrical implant system with a conical implant‐abutment connection after 10 years of prosthetic loading. Materials and Methods: A total of 516 TiOblast? implants (Astra Tech AB, Mölndal, Sweden) were placed in 108 patients. The patients were treated in the Department of Oral and Maxillofacial Surgery, Johannes Gutenberg University, Mainz, Germany, between September 1994 and May 2005. The main indications for implantation were the treatment of edentulous mandibles (74%) and partial edentulism (15%). Twenty‐three implants were placed postradiation, and a further 64 implants were irradiated after insertion. In 153 implants, a bony augmentation was conducted prior to implantation. Results: The in situ rate was 89.7% after an average implantation time of 108 months. Eighty‐three patients with 403 implants were available for investigation. Seventeen patients with 76 implants have died since 1994. Absence of osseointegration (n = 22), peri‐implantitis (n = 18), fracture of the implants (n = 9), failing of primary stability (n = 2), and implants next to tumors (n = 2) were the reasons of explantation in 26 patients. Under analysis with different implant success‐assessment criteria, the success rate showed results from 76 to 89%. Conclusion: With respect to the critical patient selection including a high number of patients with minor and major augmentations, the 10‐year clinical use of the studied implant system showed acceptable results.     

MicroRNAs can effectively induce formation of insulin‐producing cells from mesenchymal stem cells

MicroRNAs regulate insulin secretion, pancreatic development and beta cell differentiation. However, the function of microRNAs in the formation of insulin‐producing cells (IPCs) from adult stem cells is poorly understood. We examine the microRNA expression profile in nestin‐positive umbilical cord‐derived mesenchymal stem cells (N‐UCMSCs) and nestin‐positive pancreatic mesenchymal stem cells using a deep sequencing approach. We also selected specific microRNAs for overexpression in N‐UCMSCs and found that miR‐375 and miR‐26a induced IPCs differentiation from N‐UCMSCs by downregulating target genes including mtpn, sox6, bhlhe22 and ccnd1. Small interfering RNAs were also used to knock down these genes in N‐UCMSCs to induce the formation of IPCs. These results suggest that endogenous microRNAs involved in the formation of IPCs from adult stem cells show promise for advancing the development of an effective cell transplant therapy for diabetes. Copyright © 2017 John Wiley & Sons, Ltd.