MétaCan
Menu
Back to cohort
Record W4400042504 · doi:10.3390/dj12070196

CBCT in Dental Implantology: A Key Tool for Preventing Peri-Implantitis and Enhancing Patient Outcomes

2024· article· en· W4400042504 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDentistry Journal · 2024
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsDalhousie UniversityPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsPeri-implantitisMedicineDentistryKey (lock)ImplantSurgeryComputer science

Abstract

fetched live from OpenAlex

(1) Introduction: Trust is a cornerstone of the patient-physician relationships. Unforeseen complications in the health care system could jeopardize patients' trust in their physicians. (2) Aim: This article presents a quantitative figure regarding foreseeing the necessity of a three-dimensional quantitative visualization of bone structure and concurrently preparing for an ancillary procedure by a dentist to successfully perform the surgery that could minimize unforeseen complications; (3) Materials and method: This retrospective study has been derived based on an analysis of 1134 patients who had received 4800 dental implants from January 2001 to August 2020, out of which 200 cases were randomly selected for this study. Each procedure during implant treatment was categorized as OPG (Orthopantomography) or OPG with CBCT as per all the procedures which included and were coded as follows, 1: Surgery & Restoration, 2: GBR (Guided Bone Regeneration), 3: GTR (Guided Tissue Regeneration), 4: Block Bone Graft, 5: Spreading, 6: Splitting, 7: Internal Sinus, 8: External Sinus, 9: PRF (Platelet Rich Fibrin). Any of the 200 cases in which implant placement could not have been performed for reasons related to a lack of CBCT were selected for this study. The surgery was aborted halfway through without implant placement in these cases due to a lack of bone quantity and/or lack of primary stability. These cases were registered for re-evaluation and statistical analysis; (4) Results: 7% of the cases that used OPG alone led the surgeon to unexpectedly abort in the middle of the surgery without implant placement. All (100%) of the patients who had CBCT during treatment planning were able to receive implants during the surgery. None of the patients left the surgery without receiving implants if CBCT was used (0%); (5) Discussion: Radiographic image quality is defined as the amount of information within the image that allows the radiologist to make a diagnostic decision with a particular level of certainty (Martin et al., 1999) and hence the importance of CBCT. The unexpected 7% of devastating situations for patients who started surgery but did not have implant placement led to [A] aborting the surgery, [B] procedural difficulties requiring an alternative treatment plan, [C] a negative impact on the patient's behavior, and [D] wanting to change doctor due to a lack of trust; (6) Conclusion: This study indicates that in implant dentistry patients' mistrust could be avoided by 7% if CBCT is obtained. It also shows the significance of cone-beam computed tomography as an adjunct to panoramic radiography during the diagnosis and treatment planning phase. The use of panoramic radiography alone can lead to a 7% likelihood of misdiagnosis. A lack of CBCT during treatment planning negatively affects the outcome of surgical procedures.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.319
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it