Nickel-titanium (NiTi) orthodontic archwires are crucial in the initial stages of orthodontic therapy when the movement of teeth and deflection of the archwire are the largest. Their great mechanical properties come with their main disadvantage—the leakage of nickel. Various in vitro studies measured nickel leakage from archwires that were only immersed in the medium with little or minimal simulation of all stress and deflection forces that affect them. This study aims to overcome that by simulating deflection forces that those archwires are exposed to inside the mouth of a patient. NiTi orthodontic archwires were immersed in CACO2-2 cell culture medium and then immediately loaded while using a simulator of multiaxial stress for 24 h. After the experiment, the surface of the NiTi orthodontic archwires were analysed while using scanning electron microscopy (SEM) and auger electron spectroscopy (AES). The observations showed significant microstructural and compositional changes within the first 51 nm thickness of the archwire surface. Furthermore, the released nickel and titanium concentrations in the CACO2-2 cell culture medium were measured while using Inductively Coupled Plasma Mass Spectroscopy (ICP-MS). It was found out that the level of released nickel ions was 1.310 µg/L, which can be assigned as statistically significant results. These data represent the first mention of the already detectable release of Ni ions after 24 h during the simulation of mechanical loading in the CACO2-2 cell culture medium, which is important for clinical orthodontic praxis.

During orthodontic treatment, pain is a subjective experience influenced by several factors. Orthodontic patients consume analgesics at different rates to alleviate this pain. Correlations between orthodontic pain and analgesic consumption were analyzed. Predictive factors to analgesics consumption were not statistically analyzed. This study was conducted to identify the predictive factors for analgesic consumption after initiation of orthodontic treatment with fixed appliances. Two hundred and eighty-six patients involved in this study kept a seven-day diary in which they recorded pain intensity (using a 0–10 numerical rating scale), analgesic consumption, localization of pain, pain triggers, and pain characteristics. Univariable analyses identified potential predictive factors: age, gender, pain intensity, pain localization, pain while chewing, pain at rest, night pain, headache, pulsating pain, sharp pain, dull pain, and tingling. Logistic regression was conducted to create a model that could predict analgesic consumption. Multivariate analyses demonstrated that analgesic consumption was increased by increased age, increased intensity of pain, and presence of a headache. Overall, the model explained 33% of analgesic requirement variability. Age, intensity of pain, and headache proved to be predictors of analgesic consumption. Knowledge of such factors may help clinicians identify orthodontic patients who will consume analgesics on their own.