Clinical dentistry’s next question: does it help patients?

Explore the clinical research trends shaping dental care, from vital pulp therapy and implant maintenance to AI, biomarkers, and patient outcomes.

Research

By Dr. Mahmoud H. Al-Johani

Some of the most interesting questions in dental research today go beyond "Can we make this work?" They ask whether an approach can preserve teeth, prevent disease and make a meaningful difference to patients in everyday care.

That's a shift in emphasis, not an overnight revolution. We can see it most clearly in tissue-preserving care and long-term implant maintenance. Artificial intelligence (AI) is moving quickly, but proof of clinical benefit is still catching up. Salivary biomarkers are intriguing, too, although they are not yet ready to guide routine treatment decisions.

Preserving the pulp: progress, with important caveats

When deep decay reaches close to a tooth's pulp, vital pulp therapy (VPT) offers a way to try to keep that tissue alive instead of moving straight to root canal treatment. This is no longer just an appealing idea: it is reflected in current clinical guidance. A 2025 evidence-based guideline recommends selective caries removal for deep caries when the pulp is normal or reversibly inflamed. In appropriate cases, it also supports pulp capping and partial or full pulpotomy.¹

What about a tooth that hurts spontaneously, lingers after a stimulus or wakes someone at night? The clinician may need to expose and assess the pulp. If it is still vital and the bleeding can be controlled, pulpotomy may be considered. As always, the recommendation depends on careful diagnosis, asepsis, material choice and a durable restoration—not simply on choosing the most conservative-sounding treatment.¹

The message is not that "pulpotomy replaces root canal treatment." The evidence is more reassuring for some presentations than others, and comparisons between procedures can have short follow-up or low certainty. The next useful step is well-designed, multicentre research with consistent diagnostic criteria and longer follow-up. Alongside clinical and radiographic success, studies should report whether the tooth survives, whether pain returns, how the restoration performs, whether further treatment is needed and how patients feel about the result.

Implants need a plan for the long term

An implant may be restored and functioning well, but care does not end there. The focus is increasingly on preventing problems before implant placement and providing supportive care over time. A systematic review found that regular supportive care was associated with a lower risk of peri-implant disease. The European Federation of Periodontology guideline also recommends ongoing care to prevent disease and manage recurrence.²˒³

There is an important caveat: much of the evidence is observational. It supports regular maintenance, but it does not prove that one recall interval is best for every patient. The 2025 AO/AAP consensus also recommends tailoring maintenance to each patient's risk profile. It notes, though, that no systematic review was conducted for its maintenance question; its suggested intervals are expert consensus, not the result of trials comparing schedules.⁴

So what does that mean in practice? A history of periodontitis, plaque control, smoking and glycaemic control are among the factors worth considering. The aim is to match follow-up to the person's needs rather than treat one timetable as settled science.

For researchers, the challenge is to follow patients and implants long enough to measure disease recurrence and implant survival, while also asking about function, symptoms, treatment burden and patients' own assessment of their care. Shared outcome definitions would make studies easier to compare across centres and countries.

AI: impressive scores are only part of the story

Dental AI can help with image interpretation and treatment planning. But a high accuracy score, on its own, cannot tell us whether patients receive better care.

A 2025 systematic review found that 21 of its 23 included studies focused on diagnostic accuracy. Nearly four in five were retrospective, and prospective or external validation was limited.⁵ A randomized study in which dentists assessed panoramic radiographs found a modest improvement in accuracy with AI assistance and fewer false-positive diagnoses. AI also shifted decisions toward more conservative options. That is an encouraging sign that AI can influence clinical reasoning. It does not yet tell us whether real patients had fewer unnecessary procedures, better long-term outcomes or a better experience.⁶

The next wave of AI research should look beyond how well a system reads an image. Does it change decisions, and are those changes appropriate? What happens to patients—including missed disease, overtreatment, chair time and costs? And does the system work just as well in clinics and patient groups beyond those used to develop it? These are the questions that will show whether a promising tool is ready to become a useful part of care.

Salivary biomarkers: promising, but not ready to call the shots

Saliva may one day help clinicians monitor disease activity or tailor prevention. For now, the research is ahead of routine clinical use. A scoping review of 57 human studies found wide variation in the biomarkers and methods used, with no single accepted clinical approach.⁷

Consider one example: a 2024 meta-analysis of a salivary point-of-care test for active MMP-8, a marker associated with periodontal tissue breakdown. It included six studies and reported pooled sensitivity of 0.63 and specificity of 0.84. The authors concluded that more research was needed to establish clinical utility and implementation.⁸ These findings are a reason to keep studying the test—not proof that biomarker-guided care improves treatment choices or patient outcomes compared with a clinical examination.

A sensible path forward has a few steps: standardize how samples are collected and tested; check performance prospectively in independent, diverse populations; and then test whether using the result actually improves care. Decision-impact trials will be most useful once the test is reliable enough to justify them.

Four research priorities that could make a difference

Over the next few years, the most practical opportunities are studies that help promising evidence translate into dependable care:

  1. Vital pulp therapy: multicentre comparisons using shared diagnostic criteria, longer follow-up and outcomes that matter to patients.
  2. Dental AI: prospective clinical-impact trials that track real decisions, treatments, harms, benefits, workflow and costs—not accuracy alone.
  3. Implant maintenance: long-term studies comparing risk-based strategies and reporting both implant-level and patient-reported outcomes.
  4. Salivary biomarkers: standardized tests and external validation first, followed by trials asking whether biomarker-guided decisions improve care.

There is one more question to ask across all four areas: who can access the intervention, and who benefits from it? Dissemination and implementation research in oral health is still developing, while inequities in access and outcomes remain important concerns. These are valuable considerations when designing studies, but they do not mean implementation science is already a mature clinical trend.⁹

The next step is not simply to produce more promising tools. It is to find out which approaches protect health over time, work in everyday practice and make a real difference to the patients and communities they are meant to serve.

References

  1. Coll JA, et al. Guideline for Use of Vital Pulp Therapy in Permanent Teeth. Pediatric Dentistry. 2025;47(5):299–311. PubMed 41121563
  2. Carra MC, et al. Primordial and primary prevention of peri-implant diseases: A systematic review and meta-analysis. Journal of Clinical Periodontology. 2023;50(Suppl 26):77–112. doi:10.1111/jcpe.13790
  3. Herrera D, et al. Prevention and treatment of peri-implant diseases—The EFP S3 level clinical practice guideline. Journal of Clinical Periodontology. 2023;50(Suppl 26):4–76. doi:10.1111/jcpe.13823
  4. Wang HL, et al. AO/AAP consensus on prevention and management of peri-implant diseases and conditions: Summary report. Journal of Periodontology. 2025;96(6):519–541. doi:10.1002/JPER.25-0270
  5. Araidy S, Batshon G, Mirochnik R. Artificial Intelligence Applications in Dentistry: A Systematic Review. Oral. 2025;5(4):90. doi:10.3390/oral5040090
  6. Pul U, et al. Impact of artificial intelligence assistance on diagnosing periapical radiolucencies: A randomized controlled trial. Journal of Dentistry. 2025;160:105868. doi:10.1016/j.jdent.2025.105868
  7. Paqué PN, et al. Salivary biomarkers as key to monitor personalized oral healthcare and precision dentistry: A scoping review. Frontiers in Oral Health. 2022;3:1003679. doi:10.3389/froh.2022.1003679
  8. Wei S, et al. Diagnostic accuracy of salivary active matrix metalloproteinase (aMMP)-8 point-of-care test for detecting periodontitis in adults: A systematic review and meta-analysis. Journal of Clinical Periodontology. 2024;51(8):1093–1108. doi:10.1111/jcpe.14000
  9. Randall CL. Dissemination and implementation research for oral and craniofacial health: Background, a review of literature and future directions. Community Dentistry and Oral Epidemiology. 2023;51(1):119–132. doi:10.1111/cdoe.12841

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