Clinical Trial Details
— Status: Not yet recruiting
Administrative data
NCT number |
NCT06378502 |
Other study ID # |
antibiotic-resistence |
Secondary ID |
|
Status |
Not yet recruiting |
Phase |
Phase 4
|
First received |
|
Last updated |
|
Start date |
May 3, 2024 |
Est. completion date |
June 30, 2026 |
Study information
Verified date |
April 2024 |
Source |
Universita degli Studi di Genova |
Contact |
Maria Menini |
Phone |
3396598789? |
Email |
maria.menini[@]unige.it |
Is FDA regulated |
No |
Health authority |
|
Study type |
Interventional
|
Clinical Trial Summary
The aim of the present project (non-inferiority trial) is to evaluate the effect of different
antibiotic strategies (long-span vs. short-span) for implant surgery on peri-implant tissue
health, oral microbiome (included resistome) and salivary MiRNomics in healthy patients.
Description:
A total of 80 patients will be included and randomly divided in two groups:
1. Long-span prescription: 1 g Amoxicillin every 8 h starting 1 day before surgery and for
5 days after surgery
2. Short-span prescription: 2 g Amoxicillin 1 h before surgery Before surgery, patients
will undergo an antibiotic sensitivity test (AST), and non-invasive samples will be
taken to analyse oral microbiome including resistome. Saliva samples will be also taken
for miRNomics analysis. Patients will be rehabilitated with single implants or partial
implant-supported fixed prostheses. The day of surgery, samples of peripheral blood will
be taken and peripheral blood mononuclear cells (PBMCs) isolated from the first 30
patients in order to implement a micro-fluidic bioreactor replicating the bone healing
process of each patient. 3D bone models will be developed that are suitable for drug
screening.
At 2 and 6 months post-treatment, AST test and oral microbiome and resistome analysis will be
performed again. 2 months after treatment, a new saliva sample of the patients will be also
taken, analysed and compared using MiRnomics technology with the preoperative one with the
further aim of identifying reliable biomarkers of mucositis and perimplantitis. During the
12-month follow-up implant survival rate, marginal bone loss (MBL), biologic and technical
complication rate and peri-implant health parameters (including plaque index, probing depth
and bleeding on probing) will be evaluated.
Parametric or non-parametric comparative tests, as appropriate, will be performed to detect
differences between the groups in the various outcome variables. The effect of
patient-related and implant-related predictive factors on the various outcomes will be
evaluated using multilevel logistic regression analysis. Metadata will be analyzed also with
4th generation Artificial Neural Networks (ANNs) (machine learning) using unsupervised and
supervised systems.
Expected results: The present project is expected to clarify if the short-span antibiotic
therapy is not inferior to the long-span one in healthy patients undergoing implant surgery.
The outcomes will contribute to the development of effective clinical guidelines that will
help to tackle the issue of antimicrobial resistance. In addition, the development and
validation of a 3D bone model to be used for drug screening is expected, that might overcome
limitations of currently available 2D bone models and animal studies. A further expected
result is the identification of biomarkers for diagnosis and prognosis in implant dentistry,
through salivary miRNomics that might lead to the development of a non-invasive liquid
biopsy.