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Record W2053584707 · doi:10.15273/dmj.vol36no2.3912

Assessment and management of amputations distal to the wrist

2009· article· en· W2053584707 on OpenAlexaffvenueabout
Natalie Parks, Stephen F. Morris

Bibliographic record

VenueDalhousie Medical Journal · 2009
Typearticle
Languageen
FieldMedicine
TopicReconstructive Surgery and Microvascular Techniques
Canadian institutionsDalhousie University
Fundersnot available
KeywordsReplantationAmputationMedicineNumerical digitThumbSurgeryMicrosurgeryWristHand surgeryRange of motion

Abstract

fetched live from OpenAlex

Hand amputation is a devastating injury which may result in permanent quality-of-life impairment. The goal of treatment is to anatomically restore the amputated limb in order to optimize sensation and range of motion of the injured structures. All cases should be emergently referred to a hand surgeon trained in microsurgery for assessment and management. Generally accepted indications for replantation include amputation at the level of the wrist or mid-palm, thumb or multiple digit amputation and single digit amputation when distal to flexor digitorum superficialis insertion. In addition, replantation should always be attempted for children. Appropriate primary care which includes wrapping the amputated part in saline-soaked gauze, sealing in a plastic bag, and immersing in an ice bath increases the viability of amputated tissue and facilitates replantation. This review explores hand amputation classification, indications for replantation, primary care of the amputated part, surgical replantation techniques, post-operative care, and complications following replantation surgery. Three cases, treated at the Halifax Infirmary, were identified to illustrate the clinical presentation and outcome of patients presenting with multiple digit, thumb, or mid-palm amputation.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.011
GPT teacher head0.320
Teacher spread0.309 · 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 designNot applicable
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

Citations0
Published2009
Admission routes3
Has abstractyes

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