Increasing occlusal vertical dimension can be critical in the management of severely worn dentition, yet this approach remains controversial due to potential adverse effects. This article presents a comprehensive, digitally driven workflow that integrates aligner therapy to optimize both function and esthetics in an Angle class I patient with severe erosive wear. By leveraging orthodontic pre-alignment, minimally invasive restorative protocols, and advanced visualization tools, a predictable outcome was achieved in a complex full-mouth rehabilitation case.
Because dental implant post-surgical pain is mainly driven by inflammation, nonsteroidal anti-inflammatory drugs (NSAIDs) such as ibuprofen (eg, Advil\'ae, Motrin\'ae IB) or naproxen sodium (Aleve\'ae) are logical choices to address it. These drugs are highly efficacious, non-addicting, and generally well tolerated. Dental implant patients, however, are generally older than those having their impacted third molars removed and are, therefore, likely to present with more comorbidities and drug intake, leading to potentially more adverse effects and serious adverse drug interactions. Fortunately, pain following dental implant surgery is generally milder than that of impacted third molar surgery and is amenable to low over-the-counter (OTC) dosing regimens. Administering NSAIDs immediately after surgery before the local anesthesia has worn off and then around the clock for 2 to 3 days appears to be an effective strategy at not only preventing the onset of postoperative pain, but also diminishing breakthrough pain, which is typically seen with as-needed (PRN) dosing. Implant surgeons must be able to identify those patients in whom a short course of NSAIDs can be used safely and employ dosing strategies that provide optimal analgesic efficacy while limiting untoward events. This article discusses current recommendations for postoperative pain management in dental implant patients, emphasizing the role of NSAIDs while addressing patient-specific safety considerations.
Peri-implantitis represents a biologically complex, biofilm-mediated inflammatory condition characterized by progressive loss of supporting bone and soft tissue around dental implants, with a reported prevalence approaching 22%. The pathogenesis of peri-implantitis is multifactorial, involving dysregulated host immune responses, altered peri-implant tissue biology, and persistent microbial biofilm, which collectively hinder the predictability of conventional periodontal therapies. This article provides a comprehensive overview of currently available treatment modalities with an emphasis on implant surface decontamination as a critical determinant of clinical success. Both chemical and mechanical detoxification strategies are reviewed, including saline, citric acid, chlorhexidine, hydrogen peroxide, and hypochlorous acid, as well as air abrasion, implantoplasty, and emerging electrolytic cleaning technologies. While many of these approaches demonstrate the ability to reduce microbial load and clinical inflammation, no single modality has demonstrated consistent superiority, and true re-osseointegration remains difficult to achieve. Electrolytic cleaning has shown promising early evidence for facilitating re-osseointegration in preclinical and limited clinical studies, representing a potential advancement in peri-implantitis management. Clinically, effective treatment requires complete disruption of the biofilm and detoxification of the implant surface, often necessitating surgical intervention when osseous defects are present. This review highlights the advantages, limitations, and biologic implications of each modality, underscoring the need for a multifaceted, case-specific approach. Future research should focus on long-term human outcomes and optimization of combined therapeutic protocols to improve predictability and implant survival.
INTRODUCTION:A 61-year-old woman with lifelong Goldenhar syndrome was treated with a combination of zygomatic, pterygoid, and conventional dental implants using the PATZi protocol algorithm. All implants were immediately loaded and the patient received final restorations after 7 months of healing. Since that time, the patient has received yearly maintenance. RESULTS:The patient healed uneventfully and has functioned for close to 5 years from the date of surgery. DISCUSSION:Craniofacial structures affected by Goldenhar syndrome typically result in several dental complications, including malocclusion, increased potential for decay, and challenging environments for the placement of dental implants. While a few publications have reviewed treatment of children and adolescents afflicted with Goldenhar syndrome, none have documented treatment of adults. Asymmetric mandibular hypoplasia and secondary underdevelopment of associated maxillary and malar structures make prosthetic restoration of these patients difficult. These craniofacial deficits may be addressed using remote anchorage fixtures including zygomatic and pterygoid dental implants. CONCLUSION:With nearly 5 years of successful outcome, treatment of the patient in this case report indicates that remote anchorage implants may be a potential solution to address prosthetic needs of persons affected by Goldenhar syndrome.
Artificial intelligence (AI) is moving rapidly from research into everyday dental practice. Tools capable of analyzing imaging and assisting with clinical decisions are now commercially available. Systematic reviews and meta-analyses published between 2021 and 2025 demonstrate that deep learning algorithms achieve pooled diagnostic sensitivity of 0.94 for approximal caries detection on bitewing radiographs, 0.93 for periapical radiolucent lesion detection with high GRADE certainty of evidence, and 0.88 for periodontal bone loss assessment. As of late 2025, more than 44 AI-enabled dental devices had received US Food and Drug Administration 510(k) clearance as Class II Software as a Medical Device, and robotic-assisted implant surgery systems demonstrated mean angular deviations below 1.5 degrees in clinical series exceeding 270 placements. These developments raise a question the profession must now answer: at what point does the availability of validated AI tools cross from a competitive option into the standard of care? Early empirical liability research suggests that juror perceptions may increasingly favor clinicians who incorporate validated AI decision-support tools, although dental-specific legal precedent remains limited. This article reviews the clinical evidence across dental disciplines, traces the historical pattern by which technologies have reshaped practice expectations, analyzes the medicolegal framework for professional accountability, and proposes guidelines for responsible integration alongside a discussion of limitations, including automation bias, algorithmic fairness, and the gap between regulatory clearance and independent scientific validation.
