# Analysis of Risk Factors Affecting Postoperative Success Rate and Postoperative Pain After Orthodontic Microimplant Nail Implantation and Improvement of Treatment Strategy

## TL;DR

This study identifies factors affecting the success and pain of orthodontic microimplants and suggests personalized strategies to improve outcomes.

## Contribution

The study proposes personalized treatment strategies based on risk factors influencing microimplant success and pain.

## Key findings

- 90.8% of microimplants remained stable over 6 months, with higher failure rates in older adults, smokers, and those with lower cortical bone thickness.
- High insertion torque increased postoperative discomfort, while operator experience reduced failure and pain.
- Bone density, insertion torque, and smoking were top predictors of microimplant outcomes.

## Abstract

This study aimed to investigate a range of patient- and procedure-related factors influencing the success rate and postoperative pain of orthodontic microimplants, and propose potential personalised management strategies based on a large, single-centre dataset.

A total of 853 participants (1,277 microimplants) were included in this single-centre, retrospective investigation. Clinical and demographic information were collected. The primary outcome was implant-level failure within 6 months (yes/no), with success defined as stable retention and function for ≥6 months without severe inflammation or reinsertion. Postoperative pain was assessed at 6 h, 24 h, and 7 days using the visual analogue scale (VAS). Analgesic usage and soft-tissue inflammation were recorded as secondary outcomes. Microimplant success was defined by stable retention over at least 6 months, absence of severe inflammation, and no requirement for reinsertion. Multivariable logistic regression and Cox proportional hazards models were used to identify independent predictors of microimplant failure over time. In addition, a random forest model was employed to rank risk-factor importance.

Overall, 1,089 microimplants (90.8%) remained stable throughout the follow-up period, with a higher failure rate observed among older adults, smokers, and patients with lower cortical bone thickness (P <0.05). High insertion torque (>15 Ncm) significantly increased the odds of postoperative discomfort (OR = 1.85, 95% CI 1.30–2.65). Operator experience also correlated with lower failure and pain scores (P <0.01). The random forest analysis highlighted bone density, insertion torque, and smoking as the top three predictors.

Incorporating individualised strategies can improve clinical outcomes. Controlling insertion torque, accounting for cortical thickness, counselling smokers, and allocating senior operators are actionable steps to improve stability and patient comfort.