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Record W1971919229 · doi:10.1155/2014/393571

Psychosocial and Quality of Life Outcomes of Prosthetic Auricular Rehabilitation with CAD/CAM Technology

2014· article· en· W1971919229 on OpenAlexfundno aff
Chi Keung Tam, Colman McGrath, Samuel M. Y. Ho, Ehn Pow, Henry W.K. Luk, Lim Kwong Cheung

Bibliographic record

VenueInternational Journal of Dentistry · 2014
Typearticle
Languageen
FieldMedicine
TopicEar Surgery and Otitis Media
Canadian institutionsnot available
FundersFaculty of Dentistry, University of TorontoUniversity of Hong KongUniversity of Toronto
KeywordsPsychosocialMedicineQuality of life (healthcare)RehabilitationMoodPhysical therapyCohortCADImplantProsthesisClinical psychologyPsychiatrySurgeryInternal medicineNursing

Abstract

fetched live from OpenAlex

Introduction. The psychosocial and quality of life (QoL) of patients with deformed or missing ears are frequently compromised. The aim of this study is to develop innovative techniques using CAD/CAM technology in prosthetic auricular rehabilitation and provide improvement in the treatment outcomes, including their psychology and QoL. Methods. This is a preliminary clinical cohort study. Six patients requesting for auricular reconstruction were recruited and rehabilitated with implant-supported prosthesis using CAD/CAM technology. Different treatment outcomes including QoL and psychological changes were assessed at different time points. Results. A significant reduction in severity of depressive symptoms (P = 0.038) and an improving trend of satisfaction with life were found at 1 year postoperatively when compared with the preoperative findings. The domain scores in ''Body image", ''Family/friends/strangers", and ''Mood" were also significantly higher (P < 0.05) at 1 year postoperatively than 1 week postoperatively. However, only 50% of the patients wear their auricular prosthesis regularly. Conclusion. This preliminary study has confirmed that implant-supported auricular prosthesis could induce improvement in the psychology and QoL with statistically significant differences in the domains of the body image, social interaction, and mood. Our present findings can inform research design and hypotheses generation of future 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)0.001
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 score0.004
Threshold uncertainty score0.168

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.012
GPT teacher head0.317
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; 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

Citations29
Published2014
Admission routes1
Has abstractyes

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