MétaCan
Menu
Back to cohort
Record W2902582248 · doi:10.1097/scs.0000000000004958

Comparison of the Clinical Outcomes of Buccal Advancement Flap Versus Platelet-Rich Fibrin Application for the Immediate Closure of Acute Oroantral Communications

2018· article· en· W2902582248 on OpenAlexfundno aff
Kani Bilginaylar

Bibliographic record

VenueJournal of Craniofacial Surgery · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCleft Lip and Palate Research
Canadian institutionsnot available
FundersFaculty of Medicine and Dentistry, University of Alberta
KeywordsMedicinePlatelet-rich fibrinBuccal administrationAnalgesicFibrinSurgeryDentistryAnesthesia

Abstract

fetched live from OpenAlex

The aim of this study was to compare the clinical outcomes of buccal advancement flap surgery to platelet-rich fibrin (PRF) application for the closure of acute oroantral communications (AOACs). In 36 patients, following the extractions of posterior maxillary teeth, AOACs which were larger than 3 mm diameter were detected. In group A, PRF clots were used in 21 patients and group B, classic buccal advancement flap was used in 15 patients. Baseline variables such as pain, the analgesic doses are taken, and swelling was assessed preoperatively. These were also examined on postoperative days 1, 2, 3, and 7, and patients were seen again in the 3rd week. In group A, statistically significant reduction was examined (P < 0.05) in pain and the analgesic doses are taken (sum of 1st, 2nd, 3rd, and 7th days on days 1 and 2) (PRF). The swelling was also significantly less in group A (P < 0.05). The mean duration did not differ between the groups (P > 0.05). In conclusion, both methods were successful for the immediate closure of AOACs. However, a lesser amount of pain and no swelling observed with the use of PRF clots for the immediate closure of AOACs compared to buccal advancement flap surgery.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.217

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.083
GPT teacher head0.433
Teacher spread0.350 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations21
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Craniofacial SurgerySame topicCleft Lip and Palate ResearchFrench-language works237,207