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Record W4319293862 · doi:10.1111/edt.12827

Dental patient‐reported outcomes following traumatic dental injuries and treatment: A narrative review

2023· review· en· W4319293862 on OpenAlexaff
Venkateshbabu Nagendrababu, Thilla Sekar Vinothkumar, Giampiero Rossi‐Fedele, Esma J. Doğramacı, Henry F. Duncan, Paul V. Abbott, Liran Levin, Shaul Lin, P. M. H. Dummer

Bibliographic record

VenueDental Traumatology · 2023
Typereview
Languageen
FieldHealth Professions
TopicDental Trauma and Treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineTraumatologyQuality of life (healthcare)Patient satisfactionAnxietyHealth carePsychiatryNursingOrthopedic surgery

Abstract

fetched live from OpenAlex

Dental patient-reported outcomes (dPROs) are self-reported descriptions of a patient's oral health status that are not modified or interpreted by a healthcare professional. Dental patient-reported outcome measures (dPROMs) are objective or subjective measurements used to assess dPROs. In oral healthcare settings, the emphasis on assessing treatment outcomes from the patient's perspective has increased and this is particularly important after traumatic dental injuries (TDIs), as this group of injuries represent the fifth most prevalent disease or condition worldwide. The purpose of this review is to summarize the current use of dPROs and dPROMs in the field of dental traumatology. Oral Health-Related Quality of Life, pain, swelling, aesthetics, function, adverse effects, patient satisfaction, number of clinical visits and trauma-related dental anxiety are the key dPROs following TDIs. Clinicians and researchers should consider the well-being of patients as their top priority and conduct routine evaluations of dPROs using measures that are appropriate, accurate and reflect what is important to the patient. After a TDI, dPROs can assist clinicians and patients to choose the best management option(s) for each individual patient and potentially improve the methodology, design and relevance of clinical studies.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.593
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.002
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.003

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 head0.191
GPT teacher head0.497
Teacher spread0.306 · 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; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreReview

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

Citations18
Published2023
Admission routes1
Has abstractyes

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