Is It Possible to Predict Tooth Loss?

Tooth loss is a serious dental problem that affects many people around the world. However, new research suggests that by using machine-learning tools, that it will be possible for us to predict future tooth loss, which can help to delay, or even prevent, eventual tooth loss.

Most people view tooth loss as an inevitable part of life – something that as we grow older, becomes unavoidable.

But this isn’t necessarily the case, and recent research has showed that in the future, technological advancements mean that it is possible that we could predict tooth loss, and therefore act quickly to delay or even prevent tooth loss. This interesting research could improve the oral health of people all around the world.

Tooth loss

Tooth loss is a very difficult process to go through. Tooth loss is very common, with various studies estimating that over 175 million Americans are missing at least one tooth, with tooth loss worsening as we grow older [1].

Tooth loss is usually caused by gum disease (also known as periodontal disease), which is an incredibly common condition – with research suggesting that approximately 90% of the world’s population has some form of gum disease [2].

Gum disease can be linked to several areas, most commonly poor oral hygiene, such as not brushing teeth properly. A high-sugar diet, untreated cavities, smoking and conditions like diabetes or arthritis are other risk factors.

Tooth loss has both physical and psychological consequences. Losing teeth can affect a person’s overall wellbeing, diet and quality of life [3]. It also has the psychological impact of affecting confidence and self-esteem [4].

Given all of these issues, the recent findings of the research is an exciting development, which could have a highly-positive effect on society.

The Study

The research was carried out by the Harvard School of Dental Medicine, before being published in PLOS One [5]. The study was based around how machine learning tools fared when it came to the identification of those at risk of tooth loss.

The study compared 5 different algorithms, which included different combinations of variables, with each of the algorithms then used to screen for risk of tooth loss, including complete and incremental tooth loss [5].

As mentioned, different variables were used in the different algorithms. These variables included medical characteristics, education, race and general health conditions like diabetes.

The study used data from the National Health and Nutrition Examination Survey – specifically using the data of 12,000 adults from 2011 to 2014. The data was used to design and then test the five machine-learning algorithms – and subsequently compare their findings to the results of a dental examination.

The results showed that the algorithms produced more accurate results than a routine dental examination. As mentioned above, these algorithms differed based on certain characteristics and variables.

The patient’s history of attending a dentist and age were, as expected, important factors. But the algorithms were able to teach us more. A patient’s education level, employment status and income were all very relevant for predicting tooth loss.

Those from low-income and marginalized populations were already known to have high levels of tooth loss, with previous research confirming this [6]. Lack of access to dental care continues to be a significant problem for these demographics.

What does this mean for dentistry?

The results suggest that in the long-term, machine learning could help to predict tooth loss, which would protect millions from the difficulties and consequences of losing teeth.

The idea is that by predicting tooth loss early, eventual tooth loss can help to delay, or even prevent, cases of tooth loss.

Lead researcher Hawazin Elani, an Assistant Professor at Harvard School of Dental Medicine, praised the findings, stating that the analysis proved that machine-learning models could be effective at predicting risk. Elani went on to state that machine-learning “could help to screen people all over the world”.

But these results also underline the importance of early intervention. Unfortunately, many people who need dental treatment avoid going to the dentist until they are in excruciating pain, by which time it is often too late to save their tooth, leading to removal.

This shows how vital it is to attend regular dental check-ups, as any problems can be identified and acted on quickly. Machine-learning certainly has a place in dentistry, but a regular check-up, twice a year, can help immeasurably.

What we offer at Savanna Dental

At Savanna Dental, we offer our patients a range of services. We are located in a convenient location in Calgary, Alberta, Canada, and ensure that we provide our patients with a caring and comfortable experience.

The research above has shown how crucial it is to detect dental problems early. The best thing to do therefore is to attend regular dental check-ups. We recommend that our patients come to see us twice a year for a check-up.

When further treatment is required following a regular check-up, we provide many different services to fit the patient’s circumstances. These include cavity fillings, root canals, and dentures among other treatments.

Many people are put off of visiting the dentist due to the costs involved. However, our Calgary-based dental clinic Savanna Dental follows the Alberta Dental Fee Guide, which provides our patients with transparent and affordable costs.

As always, we recommend brushing your teeth at least twice a day, flossing regularly, and avoiding sugary foods and drinks, alcohol and smoking wherever possible. Good oral hygiene is very important, and has numerous benefits, including slowing down cognitive decline(click to know more).

We also provide some cosmetic dentistry treatments at our Calgary dental clinic, including teeth whitening.

Summary

Machine-learning definitely has the impact to positively affect the dental industry. The ability to predict tooth loss offers many benefits. Early intervention continues to be crucial in preventing tooth loss and other oral problems.

We hope that you consider visiting our Calgary-based dental clinic Savanna Dental, you can find out about us and the various services we offer by visiting our website https://savannadentalclinic.ca, we hope to see you soon!

• [1] American College of Prosthodontists. (2015). Missing Teeth. Available: https://www.prosthodontics.org/assets/1/7/ACP_Talking_points_for_Missing_Teeth_1-12-15.pdf. Last accessed: 24 July 2021
• [2] Pihlstrom, B. L., Michalowicz, B. S., & Johnson, N. W. (2005). Periodontal diseases. Lancet. 366 (9499), p1809-1820.
• [3] Saintrain, M. V .d .L. & de Souza, E. H. A. (2012), Impact of tooth loss on the quality of life. Gerodontology, 29(2), pe632-e636.
• [4] Kaur, P., Singh, S., Mathur, A., Makkar, D. K., Aggarwal, V. P., Batra, M., Sharma, A., & Goyal, N. (2017). Impact of Dental Disorders and its Influence on Self Esteem Levels among Adolescents. Journal of clinical and diagnostic research: 11(4), pZC05–ZC08.
• [5] Elani, H. W., Batista, A. F. M.M Thomson, W. M., Kawachi, I., & Filho, A. D. P. C. (2021). Predictors of tooth loss: A machine learning approach. PLOS One. 16(6): e0252873. https://doi.org/10.1371/journal.pone.0252873.
• [6] Elani, H. W., Harper, S., & Thomson, W. M., Espinoza, I. L., Mejia, G. C., Ju, X., Jamieson, L. M., Kawachi, I., & Kaufman, J. S.. (2017). Social inequalities in tooth loss: A multinational comparison. Community Dentistry and Oral Epidemiology. 45(3), p266– 274.