MATERIALS AND METHODS: The research question was created based on the PICO strategy. Two reviewers independently performed a comprehensive literature search in electronic databases. Following application of inclusion and exclusion criteria to the selected articles, a systematic data extraction sheet was constructed. The selected articles were assessed using methodological quality scoring protocol. The risk of bias in selected studies was critically assessed by two reviewers.
RESULTS: A total of 15 articles were included for the systematic review. The included studies were heterogeneous in study design; hence, meta-analysis was not performed. The overall risk of bias for the selected studies was moderate. Overall, UAI showed superior reduction of microbial counts, resulting in better disinfection compared to other irrigation systems chosen for comparison in this review.
CONCLUSION: The use of UAI can bring about superior microbial reduction within the root canal system compared to other irrigant activation techniques.
CLINICAL RELEVANCE: Activation of irrigants with ultrasonic brings about significant bacterial reduction from the root canal systems compared to other methods of irrigant activation and conventional syringe irrigation. This might help in improving the outcome of root canal treatment.
METHODS: A gender-matched case-control study was conducted in the largest public sector cardiac hospital of Pakistan, and the data of 460 subjects were collected. The dataset comprised of eight nonclinical features. Four supervised ML algorithms were used to train and test the models to predict the CVDs status by considering traditional logistic regression (LR) as the baseline model. The models were validated through the train-test split (70:30) and tenfold cross-validation approaches.
RESULTS: Random forest (RF), a nonlinear ML algorithm, performed better than other ML algorithms and LR. The area under the curve (AUC) of RF was 0.851 and 0.853 in the train-test split and tenfold cross-validation approach, respectively. The nonclinical features yielded an admissible accuracy (minimum 71%) through the LR and ML models, exhibiting its predictive capability in risk estimation.
CONCLUSION: The satisfactory performance of nonclinical features reveals that these features and flexible computational methodologies can reinforce the existing risk prediction models for better healthcare services.
Materials and Methods: The minimum inhibitory concentration (MIC) was obtained using serial dilution method. The agar diffusion method was then used to determine the zones of inhibition for each irrigant. Lastly, forty 6-mm dentin blocks were prepared from human mandibular premolars and inoculated with S. epidermidis. Samples were randomly divided into 4 groups of 10 blocks and irrigated for 3 minutes with saline (control), 2% CHX, 3% NaOCl, or 0.1% OCT. Dentin samples were then collected immediately for microbial analysis, including an analysis of colony-forming units (CFUs).
Results: The MICs of each tested irrigant were 0.05% for CHX, 0.25% for NaOCl, and 0.0125% for OCT. All tested irrigants showed concentration-dependent increase in zones of inhibition, and 3% NaOCl showed the largest zone of inhibition amongst all tested irrigants (p < 0.05). There were no significant differences among the CFU measurements of 2% CHX, 3% NaOCl, and 0.1% OCT showing complete elimination of S. epidermidis in all samples.
Conclusions: This study showed that OCT was comparable to or even more effective than CHX and NaOCl, demonstrating antimicrobial activity at low concentrations against S. epidermidis.