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Record W4393233470 · doi:10.1002/ccr3.8720

Successful treatment of body integrity dysphoria with amputation: A case report

2024· article· en· W4393233470 on OpenAlexaff
N Nadeau

Bibliographic record

VenueClinical Case Reports · 2024
Typearticle
Languageen
FieldPsychology
TopicBody Image and Dysmorphia Studies
Canadian institutionsUniversité LavalCentre Intégré de Santé et de Services Sociaux du Bas-Saint-Laurent
Fundersnot available
KeywordsAmputationDistressMedicineDysphoriaPsychiatryPsychologyClinical psychologyAnxiety

Abstract

fetched live from OpenAlex

Key Clinical Message: In select cases of body integrity identity disorder or body integrity dysphoria where noninvasive treatments prove ineffective and the patient's distress is substantial, elective amputation may serve as a viable and highly satisfying intervention, aligning the individual's physical self with their perceived identity. Abstract: This case report presents an illustration of body integrity identity disorder (BIID), wherein a 20 years old ambidextrous male experiencing profound distress over his left hand's fourth and fifth fingers sought elective amputation after noninvasive treatments proved unsuccessful. Despite ethical concerns and limited literature on BIID, the decision to proceed with elective surgery was based on the patient's sustained desire, potential risks of self-harm, and the distinct presentation involving two fingers rather than a complete limb. Following amputation, the patient experienced immediate relief, with nightmares ceasing, emotional distress subsiding, and improved functionality. This case highlights the potential efficacy and patient satisfaction associated with elective amputation in specific BIID presentations, shedding light on the unique challenges faced by affected individuals and emphasizing the importance of understanding, support, and inclusive healthcare practices.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.082
GPT teacher head0.447
Teacher spread0.365 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations6
Published2024
Admission routes1
Has abstractyes

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