Cases That Need Extraction of Teeth in OrthodonticsNCT05348109
Assessment of Decision Support System Software in Extraction and Anchorage Planning Among Adult Patients Using Computer Algorithm
An observational study of Cases That Need Extraction of Teeth in Orthodontics and Anchorage Planning, run by Cairo University at 1 site in Egypt.
Trial summary
It was introduced in dentistry to be used in innovative research and development in addition to facilitating the decision in complicated cases and ensure high patient care quality. Read more about this study
- Who is it for?
- Ages 15 to 35 years
- Conditions the study is for
- Cases That Need Extraction of Teeth in Orthodontics, Anchorage Planning
- What is being tested?
- Well finished cases
- How many people
- 80 participants
- Where
- 1 siteEgypt
- Study dates
- 22 Aug 2022to Apr 2023
- How long will I take part?
- 1 Year
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 15 to 35 years
- All sexes
- Child, Adult
Study population: Recruiting well finished cases having history of crowding from Kasr el Ainy with no severe skeletal discrepancy, cases should be well documented. The precise and complete documentation of the patients in terms of the presence of: 1. Preoperative and postoperative x-rays. 2. Good quality preoperative and postoperative photographs. 3. Preoperative and postoperative study models. 4. Detailed documentation of the treatment sequence and mechanics. If there were incomplete data provided in the patient's file; the patient will then be excluded from the study.
Who may be able to join
- Cases with well finished orthodontic treatment.
- Cases with history of crowding more than 10 mm and requiring extraction.
- Cases with no severe skeletal discrepancy.
- Well documented cases with both pre-operative and post-operative records.
- Patients with a full set of permanent teeth erupted
Who cannot join
- Improperly finished orthodontic cases.
- Cases with mild crowding managed by treatment options other than extraction.
- Growing patients or showing any residual growth remaining in cephalometric analysis
- Cases with severe skeletal discrepancy.
- Poorly documented cases.
- Patients not sticking to anchorage plan
Trial locations and contacts
1 site in 1 country.
Egypt1 site, 1 recruiting
- Recruiting
Walaa Mohamed Hassan Gadallah
Cairo
walaa mohamed Gadallah, Bachelor, 01021340189, walaa.hassan@dentistry.cu.edu.eg
About this study
It was introduced in dentistry to be used in innovative research and development in addition to facilitating the decision in complicated cases and ensure high patient care quality. In the field of Orthodontics in specific, many studies previously mentioned the idea of artificial intelligence showing very promising results and high degree of reliability. It was used in different domains in orthodontics like diagnosis, treatment planning, evaluation of treatment outcome
Read the detailed description
In this study, the aim is to access the efficiency of the new decision support system in determining whether the decision is extraction or non-extraction and the anchorage plan required for each case. This was performed in the past in many countries and those studies are published
- Being tested
- Well finished cases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Well finished casesOther
Also called extraction and non-extraction in well finished cases
To decide whether extraction or non-extraction decision will be made for each case
| Study group | Role | What they receive |
|---|---|---|
| well fininshed cases | Not described Receives: Other: Well finished cases |
What is being measured
The primary outcome is the main question the study is designed to answer.
To study the efficiency of the program decisions in terms of extraction/non-extraction and Anchorage planning decisions
The concordance correlation coefficient would be used to measure the agreement between the 2 methods on the basis of the values (%) assigned for each treatment option by the 2 methods (quantitative data).
Measured: 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Apr 2022
- Study start22 Aug 2022 (estimated)
- Primary completionNov 2022 (estimated)
- Study completionApr 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (38)Papers the sponsor has linked to this study.
- Other trials for Cases That Need Extraction of Teeth in OrthodonticsStudies of the same condition, open and under way.
- More trials run by Cairo UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Other
- Enrolment
- 80 participants (estimated)
- Target duration
- 1 Year
Sponsor and investigators
- Lead sponsor
- Cairo University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Walaa Mohamed Hassan Gadallah, Cairo University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05348109
- Sponsor's protocol ID
- 94030405
- Status last verified
- Jul 2022
- First submitted
- 21 Dec 2021
- Last updated
- 20 Jul 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Publications
Mandava, P., Ganugapanta, V. R. and Pradesh, A. (2016) 'Review article Annals and Essences of Dentistry ANCHORAGE IN ORTHODONTICS : A LITERATURE REVIEW Review article', Annals and Essences of Dentistry, VIII(2).
Muraev AA, Tsai P, Kibardin I, Oborotistov N, Shirayeva T, Ivanov S, Ivanov S, Guseynov N, Aleshina O, Bosykh Y, Safyanova E, Andreischev A, Rudoman S, Dolgalev A, Matyuta M, Karagodsky V, Tuturov N. Frontal cephalometric landmarking: humans vs artificial neural networks. Int J Comput Dent. 2020;23(2):139-148.
PubMed 32555767Aksakalli S, Demir A, Selek M, Tasdemir S. Temperature increase during orthodontic bonding with different curing units using an infrared camera. Acta Odontol Scand. 2014 Jan;72(1):36-41. doi: 10.3109/00016357.2013.794954. Epub 2013 May 3.
PubMed 23638766Auconi P, Scazzocchio M, Cozza P, McNamara JA Jr, Franchi L. Prediction of Class III treatment outcomes through orthodontic data mining. Eur J Orthod. 2015 Jun;37(3):257-67. doi: 10.1093/ejo/cju038. Epub 2014 Sep 4.
PubMed 25190642Bichu YM, Hansa I, Bichu AY, Premjani P, Flores-Mir C, Vaid NR. Applications of artificial intelligence and machine learning in orthodontics: a scoping review. Prog Orthod. 2021 Jul 5;22(1):18. doi: 10.1186/s40510-021-00361-9.
PubMed 34219198Briganti G, Le Moine O. Artificial Intelligence in Medicine: Today and Tomorrow. Front Med (Lausanne). 2020 Feb 5;7:27. doi: 10.3389/fmed.2020.00027. eCollection 2020.
PubMed 32118012Chen S, Wang L, Li G, Wu TH, Diachina S, Tejera B, Kwon JJ, Lin FC, Lee YT, Xu T, Shen D, Ko CC. Machine learning in orthodontics: Introducing a 3D auto-segmentation and auto-landmark finder of CBCT images to assess maxillary constriction in unilateral impacted canine patients. Angle Orthod. 2020 Jan;90(1):77-84. doi: 10.2319/012919-59.1. Epub 2019 Aug 12.
PubMed 31403836Chen YW, Stanley K, Att W. Artificial intelligence in dentistry: current applications and future perspectives. Quintessence Int. 2020;51(3):248-257. doi: 10.3290/j.qi.a43952.
PubMed 32020135Choi HI, Jung SK, Baek SH, Lim WH, Ahn SJ, Yang IH, Kim TW. Artificial Intelligent Model With Neural Network Machine Learning for the Diagnosis of Orthognathic Surgery. J Craniofac Surg. 2019 Oct;30(7):1986-1989. doi: 10.1097/SCS.0000000000005650.
PubMed 31205280Dorsey ER, Glidden AM, Holloway MR, Birbeck GL, Schwamm LH. Teleneurology and mobile technologies: the future of neurological care. Nat Rev Neurol. 2018 May;14(5):285-297. doi: 10.1038/nrneurol.2018.31. Epub 2018 Apr 6.
PubMed 29623949Felfoul O, Mohammadi M, Taherkhani S, de Lanauze D, Zhong Xu Y, Loghin D, Essa S, Jancik S, Houle D, Lafleur M, Gaboury L, Tabrizian M, Kaou N, Atkin M, Vuong T, Batist G, Beauchemin N, Radzioch D, Martel S. Magneto-aerotactic bacteria deliver drug-containing nanoliposomes to tumour hypoxic regions. Nat Nanotechnol. 2016 Nov;11(11):941-947. doi: 10.1038/nnano.2016.137. Epub 2016 Aug 15.
PubMed 27525475Feres M, Louzoun Y, Haber S, Faveri M, Figueiredo LC, Levin L. Support vector machine-based differentiation between aggressive and chronic periodontitis using microbial profiles. Int Dent J. 2018 Feb;68(1):39-46. doi: 10.1111/idj.12326. Epub 2017 Aug 2.
PubMed 28771699Goto S, Kimura M, Katsumata Y, Goto S, Kamatani T, Ichihara G, Ko S, Sasaki J, Fukuda K, Sano M. Artificial intelligence to predict needs for urgent revascularization from 12-leads electrocardiography in emergency patients. PLoS One. 2019 Jan 9;14(1):e0210103. doi: 10.1371/journal.pone.0210103. eCollection 2019.
PubMed 30625197Hamet P, Tremblay J. Artificial intelligence in medicine. Metabolism. 2017 Apr;69S:S36-S40. doi: 10.1016/j.metabol.2017.01.011. Epub 2017 Jan 11.
PubMed 28126242Hwang JJ, Lee JH, Han SS, Kim YH, Jeong HG, Choi YJ, Park W. Strut analysis for osteoporosis detection model using dental panoramic radiography. Dentomaxillofac Radiol. 2017 Oct;46(7):20170006. doi: 10.1259/dmfr.20170006. Epub 2017 Jul 14.
PubMed 28707523
Study at a glance
From the registry record, last updated by the sponsor on 20 Jul 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Assessment of Decision Support System Software in Extraction and Anchorage Planning Among Adult Patients Using Computer Algorithm
- ClinicalTrials.gov ID
- NCT05348109
- Acronym / sponsor ID
- 94030405
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 80 participants (estimated)
- Lead sponsor
- Cairo UniversityUniversity, hospital or other
- Study start
- 22 Aug 2022 (estimated)
- Primary completion
- Nov 2022 (estimated)
- Study completion
- Apr 2023 (estimated)
- First posted
- 27 Apr 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
It was introduced in dentistry to be used in innovative research and development in addition to facilitating the decision in complicated cases and ensure high patient care quality. In the field of Orthodontics in specific, many studies previously mentioned the idea of artificial intelligence showing very promising results and high degree of reliability. It was used in different domains in orthodontics like diagnosis, treatment planning, evaluation of treatment outcome
Detailed description
In this study, the aim is to access the efficiency of the new decision support system in determining whether the decision is extraction or non-extraction and the anchorage plan required for each case. This was performed in the past in many countries and those studies are published
Study design
- Observational model
- Cohort
- Time perspective
- Other
- Target follow-up
- 1 Year
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| well fininshed cases | – | Other: Well finished cases |
Who may qualify
- Ages
- 15 to 35 years
- Sex
- All
- Age groups
- Child, Adult
- Study population
- Recruiting well finished cases having history of crowding from Kasr el Ainy with no severe skeletal discrepancy, cases should be well documented. The precise and complete documentation of the patients in terms of the presence of: 1. Preoperative and postoperative x-rays. 2. Good quality preoperative and postoperative photographs. 3. Preoperative and postoperative study models. 4. Detailed documentation of the treatment sequence and mechanics. If there were incomplete data provided in the patient's file; the patient will then be excluded from the study.
Key inclusion criteria (5 listed)
- Cases with well finished orthodontic treatment.
- Cases with history of crowding more than 10 mm and requiring extraction.
- Cases with no severe skeletal discrepancy.
- Well documented cases with both pre-operative and post-operative records.
- Patients with a full set of permanent teeth erupted
Key exclusion criteria (6 listed)
- Improperly finished orthodontic cases.
- Cases with mild crowding managed by treatment options other than extraction.
- Growing patients or showing any residual growth remaining in cephalometric analysis
- Cases with severe skeletal discrepancy.
- Poorly documented cases.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Well finished casesAlso: extraction and non-extraction in well finished casesTo decide whether extraction or non-extraction decision will be made for each case | Other | well fininshed cases |
Primary outcome
To study the efficiency of the program decisions in terms of extraction/non-extraction and Anchorage planning decisions
Time frame: 1 year
The concordance correlation coefficient would be used to measure the agreement between the 2 methods on the basis of the values (%) assigned for each treatment option by the 2 methods (quantitative data).
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 20 Jul 2022.
- BackgroundMandava, P., Ganugapanta, V. R. and Pradesh, A. (2016) 'Review article Annals and Essences of Dentistry ANCHORAGE IN ORTHODONTICS : A LITERATURE REVIEW Review article', Annals and Essences of Dentistry, VIII(2).
- Background: PubMed 32555767Muraev AA, Tsai P, Kibardin I, Oborotistov N, Shirayeva T, Ivanov S, Ivanov S, Guseynov N, Aleshina O, Bosykh Y, Safyanova E, Andreischev A, Rudoman S, Dolgalev A, Matyuta M, Karagodsky V, Tuturov N. Frontal cephalometric landmarking: humans vs artificial neural networks. Int J Comput Dent. 2020;23(2):139-148.
- Results publication: PubMed 23638766Aksakalli S, Demir A, Selek M, Tasdemir S. Temperature increase during orthodontic bonding with different curing units using an infrared camera. Acta Odontol Scand. 2014 Jan;72(1):36-41. doi: 10.3109/00016357.2013.794954. Epub 2013 May 3.
- Results publication: PubMed 25190642Auconi P, Scazzocchio M, Cozza P, McNamara JA Jr, Franchi L. Prediction of Class III treatment outcomes through orthodontic data mining. Eur J Orthod. 2015 Jun;37(3):257-67. doi: 10.1093/ejo/cju038. Epub 2014 Sep 4.
- Results publication: PubMed 34219198Bichu YM, Hansa I, Bichu AY, Premjani P, Flores-Mir C, Vaid NR. Applications of artificial intelligence and machine learning in orthodontics: a scoping review. Prog Orthod. 2021 Jul 5;22(1):18. doi: 10.1186/s40510-021-00361-9.
- Results publication: PubMed 32118012Briganti G, Le Moine O. Artificial Intelligence in Medicine: Today and Tomorrow. Front Med (Lausanne). 2020 Feb 5;7:27. doi: 10.3389/fmed.2020.00027. eCollection 2020.
- Results publication: PubMed 31403836Chen S, Wang L, Li G, Wu TH, Diachina S, Tejera B, Kwon JJ, Lin FC, Lee YT, Xu T, Shen D, Ko CC. Machine learning in orthodontics: Introducing a 3D auto-segmentation and auto-landmark finder of CBCT images to assess maxillary constriction in unilateral impacted canine patients. Angle Orthod. 2020 Jan;90(1):77-84. doi: 10.2319/012919-59.1. Epub 2019 Aug 12.
- Results publication: PubMed 32020135Chen YW, Stanley K, Att W. Artificial intelligence in dentistry: current applications and future perspectives. Quintessence Int. 2020;51(3):248-257. doi: 10.3290/j.qi.a43952.
- Results publication: PubMed 31205280Choi HI, Jung SK, Baek SH, Lim WH, Ahn SJ, Yang IH, Kim TW. Artificial Intelligent Model With Neural Network Machine Learning for the Diagnosis of Orthognathic Surgery. J Craniofac Surg. 2019 Oct;30(7):1986-1989. doi: 10.1097/SCS.0000000000005650.
- Results publication: PubMed 29623949Dorsey ER, Glidden AM, Holloway MR, Birbeck GL, Schwamm LH. Teleneurology and mobile technologies: the future of neurological care. Nat Rev Neurol. 2018 May;14(5):285-297. doi: 10.1038/nrneurol.2018.31. Epub 2018 Apr 6.
- Results publication: PubMed 27525475Felfoul O, Mohammadi M, Taherkhani S, de Lanauze D, Zhong Xu Y, Loghin D, Essa S, Jancik S, Houle D, Lafleur M, Gaboury L, Tabrizian M, Kaou N, Atkin M, Vuong T, Batist G, Beauchemin N, Radzioch D, Martel S. Magneto-aerotactic bacteria deliver drug-containing nanoliposomes to tumour hypoxic regions. Nat Nanotechnol. 2016 Nov;11(11):941-947. doi: 10.1038/nnano.2016.137. Epub 2016 Aug 15.
- Results publication: PubMed 28771699Feres M, Louzoun Y, Haber S, Faveri M, Figueiredo LC, Levin L. Support vector machine-based differentiation between aggressive and chronic periodontitis using microbial profiles. Int Dent J. 2018 Feb;68(1):39-46. doi: 10.1111/idj.12326. Epub 2017 Aug 2.
- Related InfoLink provided by the sponsor.
- Individual participant dataSharing planned: Undecided
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Cases That Need Extraction of Teeth in Orthodontics and Anchorage Planning, run by Cairo University at 1 site in Egypt.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 20 Jul 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Egypt. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Walaa Mohamed Gadallah, Bachelor degree (01021340189, walaa.hassan@dentistry.cu.edu.eg), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
To study the efficiency of the program decisions in terms of extraction/non-extraction and Anchorage planning decisions (time frame: 1 year). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05348109, which also lists 38 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 20 Jul 2022.