Case Selection: Who Should (and Shouldn’t) Get Implants?

Dental implants have become the gold standard for tooth replacement. 

Dental implants showcase survival rates of 90% over 20 years and 80% in 20 years^1,2. It is indeed a remarkable achievement in restorative dentistry. 

Yet, the difference between long-term success and early failure often comes down to one factor: case selection.

Poor case selection remains one of the leading causes of early failure and complications.

So when should we place implants, and when is it better to hold back? Let’s look at what the latest evidence tells us.

The Hidden Predictors of Implant Outcomes

Implant availability is more or less known to be dominated by bone availability. Now, clinicians understand that quality matters as much as quantity. 

Here are key considerations:

• Bone density & vascularity – Adequate cortical strength and blood supply are essential for predictable osseointegration. Research highlights bone density as a key factor in stress distribution and long-term success³.
• Systemic factors – Systematic reviews demonstrate that poorly controlled diabetes, osteoporosis, and immunocompromised states can significantly impair healing and implant success⁴.
• 3D diagnostics – CBCT scans provide detailed mapping of both anatomy and density, with AI models that highlight the potential to identify edentulous areas and provide bone measurements as part of dental implant planning.

Even with sufficient bone volume, ignoring systemic and biologic factors can lead to negative outcomes.

Red Flags: High-Risk Profiles to Watch

Certain patient groups carry a significantly higher risk for implant complications:

Smokers

Recent literature shows that for 1420 dental implants in 826 patients, smoking was associated with the highest proportion of dental implant failures compared to other medical risk factors⁵. 

Meta-analysis data show the risk of implant failure increases with the number of cigarettes smoked per day. It also highlighted higher mean marginal bone loss than implants in non-smokers.

Periodontal issues

Research shows that patients with a history of gum disease, poor oral hygiene, or who skip regular maintenance after implant treatment are at a much higher risk of developing peri-implantitis⁶.

Bruxers

Excessive occlusal forces can cause microfractures in bone and prosthetic components, thereby increasing biomechanical risks. 

Non-compliant patients

Special attention should be given to continuous periodontal supportive programs, as regular maintenance was found to be strongly related to implant survival in 10-year studies. Irregular follow-up and poor oral hygiene tend to negatively impact long-term survival.

How Technology is Shaping Decisions?

Digital flows are now more helpful than only surgical planning, as they play a crucial role in guiding the decision-making process for implant placement.

AI-driven radiographic analysis

AI models have the potential to identify edentulous areas and provide measurements of bone as part of dental implant planning using CBCT images. 

Additional well-conducted research is needed to enhance the accuracy and applicability of these AI-based approaches⁷.

Advanced Planning Integration

AI-driven implant planning can be more time-efficient than traditional methods, and automated 

AI-based registration of CBCT data and model scan data can be as accurate as conventional superimposition methods when imaging artifacts are absent^8,9.

3D-printed surgical guides

The combined use of AI and augmented reality may change the perspectives of modern guided implant surgery. 

These technologies deliver better outcomes for challenging cases by enhancing accuracy and minimising chairside guesswork.

When Saying No is the Right Call

Implant dentistry is not just about replacing teeth. It is also about restoring function, esthetics, and long-term health. 

A "yes" should only come after evaluating:

• Biologic feasibility – Is the bone and soft tissue environment healthy?
• Functional demands – Can the implant withstand occlusal forces?
• Patient factors – Is the patient motivated, compliant, and aware of the commitment required?

Long-term data clearly emphasizes the need for continuous follow-up care. It is essential to be aware of the risks and avoid overestimating treatment success.

Sometimes, a high-quality removable or fixed prosthesis remains the safer and more ethical choice.

Final Takeaway

The future of implant success is not completely about the surgical skill but also about choosing the right patient, at the right time, with the right plan. 

Integrating clinical red flags, systemic health considerations, and digital workflows can help dentists reduce failures and boost long-term predictability.
References

1. Howe MS, Keys W, Richards D. Long-term (10-year) dental implant survival: A systematic review and sensitivity meta-analysis. J Dent. 2019;84:9-21.
2. Kupka JR, König J, Al-Nawas B, Sagheb K, Schiegnitz E. How far can we go? A 20-year meta-analysis of dental implant survival rates. Clin Oral Investig. 2024 Sep;28(10):541.
3. Ceddia M, Romasco T, De Bortoli N Jr, Mello BF, Piattelli A, Mijiritsky E, Di Pietro N, Trentadue B. Biomechanical finite element analysis of two types of short-angled implants across various bone classifications. Materials (Basel). 2024 Nov 21;17(23):5680.
4. Mosaddad SA, Talebi S, Keyhan SO. Dental implant considerations in patients with systemic diseases: An updated comprehensive review. J Oral Rehabil. 2024;51(5):475-489.
5. Naseri R, Yaghini J, Feizi A. Levels of smoking and dental implant failure: a systematic review and meta-analysis. J Clin Periodontol. 2020;47(4):518–28. 
6. Schwarz F, Derks J, Monje A, Wang HL. Peri-implantitis. J Clin Periodontol. 2018;45 Suppl 20:S246–66.
7. Alqutaibi AY, Algabri R, Ibrahim WI, Alhajj MN, Elawady D. Dental implant planning using artificial intelligence: a systematic review and meta-analysis. J Prosthet Dent. 2024 Apr 22:S0022-3913(24)00227-0.
8. Mangano FG, Admakin O, Lerner H, Mangano C. Artificial intelligence and augmented reality for guided implant surgery planning: a proof of concept. J Dent. 2023;133:104485.
9. Elgarba BM, Fontenele RC, Mangano F, Jacobs R. Novel AI-based automated virtual implant placement: artificial versus human intelligence. J Dent. 2024;147:105146. doi:10.1016/j.jdent.2024.105146. PMID: 38914182.