Orthodontists' use of remote monitoring platforms pre-, amid, and post-COVID-19: a survey study.

BACKGROUND: Did the COVID-19 pandemic affect orthodontists' use of remote monitoring platforms? The goal of this research was to examine orthodontists' experiences implementing remote monitoring platforms before, during, and after the initial COVID-19 lockdown. METHODS: In this descriptive cross-sectional survey study, an electronic, anonymous questionnaire consisting of a series of 31 short-answer and multiple-choice questions was administered to an international sampling of practicing orthodontists. The target population in the study included currently practicing orthodontists who were graduates of an accredited orthodontic residency program. Participants were recruited in 2021 through collaboration with the American Association of Orthodontists (AAO) Partners in Research Program and the Harvard School of Dental Medicine Orthodontic Alumni Association. Descriptive analysis was conducted, reporting frequency (N and %) distributions for each question. The questionnaire aimed to describe whether orthodontists incorporated remote monitoring platforms into their practices, their experiences doing so, and if the COVID-19 pandemic influenced their use of these resources. RESULTS: Orthodontists' use of remote monitoring platforms was negligible prior to the pandemic; however, a quarter of surveyed orthodontists began using a remote monitoring platform during COVID-19 and nearly all respondents plan to continue using remote monitoring for the foreseeable future. Approximately half of orthodontists believe most patients' treatment progress can be monitored to the standard of care between in-person orthodontic appointments using remote monitoring platforms. Half of the orthodontists who do not currently use a remote monitoring platform in their practice are interested in learning more about how to implement one. CONCLUSIONS: The COVID-19 pandemic led to an increase in the interest and adoption of remote monitoring platforms in orthodontic practices. Most orthodontists had not incorporated remote monitoring platforms into their practices prior to the COVID-19 pandemic. However, this study revealed that a subset of orthodontists utilized the pandemic as motivation to incorporate remote monitoring into their practices and an additional group of orthodontists were interested in incorporating one in the future. Remote monitoring platforms garnered interest and importance with the arrival of the COVID-19 pandemic and may only have an increasing role in the field in years to come.

Evaluation of Dental Root Development Regarding Maxillary Canine Eruption Status after Secondary Alveolar Bone Grafting in Patients with Cleft Lip and Palate.

In children born with cleft lip and palate, the timing of the secondary alveolar bone graft (SABG) is crucial to its success; this involves estimating the eruption of the permanent maxillary canine. Altered dental eruption in this patient group gives impetus to the identification of dental developmental factors concerning maxillary canine eruption, which may steer the clinical decision of SABG timing. Records of over nine hundred patients who received SABG with pre- and post-operative cone beam computed tomography (CBCT) scans were analyzed for inclusion and divided into two groups (erupting or non-erupting canine after SABG). Roots of the maxillary canines and premolars were segmented from the cementoenamel junction then linear and volumetric measurements were performed. The pre- and post-operative root length and volume differences were calculated and compared statistically using independent sample tests and paired t-tests. No statistically significant differences were found in the volume change (%), or reciprocal of mean root length in the erupted and unerupted groups in the canine, first premolar, or second premolar roots except for an association between the post-operative dental root length of the canine and the maxillary canine eruption status. Therefore, assessment of root development from pre-treatment CBCT scans was not deemed worthy from a diagnostic perspective.

Assessment of artificial intelligence-based remote monitoring of clear aligner therapy: A prospective study.

INTRODUCTION: Artificial intelligence remote monitoring of clear aligner therapy has recently gained popularity. It uses deep learning algorithms on a patient's mobile smartphone to determine readiness to progress to the next aligner (ie, GO vs NO-GO) and identify areas in which the teeth are not tracking with the clear aligners. This study aimed to assess the repeatability of the Go or No-Go instructions provided by the application and to determine the 3-dimensional discrepancies that constitute an unseat. METHODS: Thirty patients in treatment with clear aligners at an academic clinic were scanned twice using a remote monitoring application on a smartphone, and the results were compared. Gauge repeatability and reproducibility analysis were performed. Intraoral and remote monitoring scans were obtained on the same day from 24 additional clear aligner patients that completed treatment using their final aligners. The intraoral scan after using the final aligner and the stereolithography file of the planned position at the final aligner was compared with measure the maximum discrepancies between the actual and planned position of the teeth. RESULTS: Gauge compatibility of 44.7% was noted. In total 83.3% of patient instructions agreed between Scan 1 and 2, but 0% agreed completely on which and/or how many teeth had tracking issues. Patients who received GO instruction had mean greatest discrepancies of 1.997 mm, 1.901 mm, 0.530 mm, 8.911°, 7.827°, and 7.049° in mesiodistal, buccolingual, occlusogingival, tip, torque, and rotational dimensions, respectively. These discrepancies were not significantly different from patients receiving NO-GO instruction (1.771 mm, 1.808 mm, 0.606 mm, 8.673°, 8.134°, and 6.719° for the corresponding categories). CONCLUSIONS: Despite the study's limitations, these findings suggest concerns with the consistency of remote monitoring instructions because of gauge compatibility over the industry standard. Similarly, large discrepancies in tooth position for patients receiving GO and NO-GO instruction suggest that artificial intelligence decisions were inconsistent with quantitative findings.