A titration model for evaluating calcium hydroxide removal techniques

Objective Calcium hydroxide (Ca(OH)2) has been used in endodontics as an intracanal medicament due to its antimicrobial effects and its ability to inactivate bacterial endotoxin. The inability to totally remove this intracanal medicament from the root canal system, however, may interfere with the setting of eugenol-based sealers or inhibit bonding of resin to dentin, thus presenting clinical challenges with endodontic treatment. This study used a chemical titration method to measure residual Ca(OH)2 left after different endodontic irrigation methods. Material and Methods Eighty-six human canine roots were prepared for obturation. Thirty teeth were filled with known but different amounts of Ca(OH)2 for 7 days, which were dissolved out and titrated to quantitate the residual Ca(OH)2 recovered from each root to produce a standard curve. Forty-eight of the remaining teeth were filled with equal amounts of Ca(OH)2 followed by gross Ca(OH)2 removal using hand files and randomized treatment of either: 1) Syringe irrigation; 2) Syringe irrigation with use of an apical file; 3) Syringe irrigation with added 30 s of passive ultrasonic irrigation (PUI), or 4) Syringe irrigation with apical file and PUI (n=12/group). Residual Ca(OH)2 was dissolved with glycerin and titrated to measure residual Ca(OH)2 left in the root. Results No method completely removed all residual Ca(OH)2. The addition of 30 s PUI with or without apical file use removed Ca(OH)2 significantly better than irrigation alone. Conclusions This technique allowed quantification of residual Ca(OH)2. The use of PUI (with or without apical file) resulted in significantly lower Ca(OH)2 residue compared to irrigation alone

The GEnetic Syntax Score: a genetic risk assessment implementation tool grading the complexity of coronary artery disease—rationale and design of the GESS study

Abstract Background Coronary artery disease (CAD) remains one of the leading causes of mortality worldwide and is associated with multiple inherited and environmental risk factors. This study is designed to identify, design, and develop a panel of genetic markers that combined with clinical and angiographic information, will facilitate the creation of a personalized risk prediction algorithm (GEnetic Syntax Score—GESS). GESS score could be a reliable tool for predicting cardiovascular risk for future adverse events and for guiding therapeutic strategies. Methods GESS (ClinicalTrials.gov Identifier: NCT03150680) is a prospective, non-interventional clinical study designed to enroll 1080 consecutive patients with no prior history of coronary revascularization procedure, who undergo scheduled or emergency coronary angiography in AHEPA, University General Hospital of Thessaloniki. Next generation sequencing (NGS) technology will be used to genotype specific single-nucleotide polymorphisms (SNPs) across the genome of study participants, which were identified as clinically relevant to CAD after extensive bioinformatic analysis of literature-based SNPs. Enrichment analyses of Gene Ontology-Molecular Function, Reactome Pathways and Disease Ontology terms were also performed to identify the top 15 statistically significant terms and pathways. Furthermore, the SYNTAX score will be calculated for the assessment of CAD severity of all patients based on their angiographic findings. All patients will be followed-up for one-year, in order to record any major adverse cardiovascular events. Discussion A group of 228 SNPs was identified through bioinformatic and pharmacogenomic analysis to be involved in CAD through a wide range of pathways and was correlated with various laboratory and clinical parameters, along with the patients' response to clopidogrel and statin therapy. The annotation of these SNPs revealed 127 genes being affected by the presence of one or more SNPs. The first patient was enrolled in the study in February 2019 and enrollment is expected to be completed until June 2021. Hence, GESS is the first trial to date aspiring to develop a novel risk prediction algorithm, the GEnetic Syntax Score, able to identify patients at high risk for complex CAD based on their molecular signature profile and ultimately promote pharmacogenomics and precision medicine in routine clinical settings. Trial registration GESS trial registration: ClinicalTrials.gov Number: NCT03150680. Registered 12 May 2017- Prospectively registered, https://clinicaltrials.gov/ct2/show/NCT03150680