Impact of periodontal treatment on diabetes management

Background + Aims

• Diabetes mellitus (DM) is a chronic condition where the body fails to produce or effectively use insulin, resulting in elevated blood glucose. Poor glycaemic control in DM patients can lead to severe complications like cardiovascular disease and kidney failure. The glycosylated haemoglobin assay (HbA1c) is a reliable measure of long-term blood sugar control and is linked to the risk of diabetic complications.
• Periodontitis, a chronic gum disease causing tissue and bone damage, is more common and severe in people with DM. Research suggests a bidirectional relationship between periodontitis and glycaemic levels: DM can worsen periodontitis, and periodontitis may elevate systemic inflammation, affecting glycaemic control. Managing periodontitis through regular deep cleaning and oral hygiene reduces inflammation and may benefit blood glucose control in patients with diabetes. If effective, integrating dental care into DM management could lead to cost savings by reducing the need for advanced treatment in both diabetes and periodontitis, making a case for policy support for preventive periodontal care in DM patients.
• The aim is to examine how periodontal treatment influences glycaemic control in individuals with both diabetes mellitus and periodontitis.

Materials + Methods

• This systematic review includes only randomised controlled trials (RCTs) with a minimum follow-up period of 90 days. Participants had type 1 or type 2 diabetes and were at least 16 years old. Studies involving more than 10% of participants with gestational diabetes or metabolic syndrome were excluded.
• The review analysed the effect of professionally administered periodontal interventions, including subgingival instrumentation (deep cleaning), surgical treatment, and antimicrobial therapies, amongst others.
• Systematic searches were conducted across multiple databases, including Cochrane and MEDLINE, without restrictions on language or publication status. Additional sources included trial registries, conference proceedings, and reference lists to ensure comprehensive study inclusion.
• The outcomes assessed were:
  • Primary outcome: HbA1c levels.
  • Secondary outcomes: clinical attachment level (CAL), probing pocket depth (PPD), bleeding on probing (BOP), gingival indices (GI), plaque indices (PI), any adverse effects of treatment, quality of life (QoL – e.g. OHIP‐14 questionnaire), diabetic complications, cost implications.
• Two authors independently screened, selected, and extracted data from RCTs on periodontal treatment for participants with diabetes, using a structured template to record study characteristics, population, interventions, and outcomes.
• Data synthesis involved meta-analysis, risk of bias assessment, and sensitivity analyses. A brief economic commentary assessed cost-effectiveness.

Results

This updated systematic review included 35 RCTs involving 3,249 participants with diabetes and periodontitis. The main findings were:

• HbA1c reduction: Periodontal treatment led to significant reductions in HbA1c levels at different time-intervals after the treatment
  • At 3-4 months – a 0.43% reduction.
  • At 6-months – 0.30% reduction.
  • At 12-months – 0.50% reduction.
• Treatment resulted in significant improvements in periodontal conditions as demonstrated by clinical parameters at all intervals.
• Some studies reported adverse effects, mostly minor. Serious adverse events were rare and likely related to underlying health conditions rather than periodontal treatment.
• Three studies assessed QoL, with limited evidence suggesting improvements in oral health-related quality of life following periodontal treatment.
• None of the studies reported data on diabetic complications.
• None of the studies reported on cost-effectiveness. Economic evaluations were undertaken separately, indicating potential healthcare cost savings associated with periodontal treatment for diabetes patients due to reduced HbA1c and lowered risk of complications. However, uncertainty remains around cost-effectiveness due to limited high-quality economic data.

Limitations