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Record W2161233805 · doi:10.1136/jramc-2013-000032

Medical lessons learnt from the US and Canadian experience of treating combat casualties from Afghanistan and Iraq

2013· article· en· W2161233805 on OpenAlexaboutno aff
Shreshth Dharm-Datta, J McLenaghan

Bibliographic record

VenueJournal of the Royal Army Medical Corps · 2013
Typearticle
Languageen
FieldMedicine
TopicHeterotopic Ossification and Related Conditions
Canadian institutionsnot available
FundersWinston Churchill Memorial Trust
KeywordsMedicineAmputationHeterotopic ossificationRehabilitationSoft tissueSurgeryPhysical medicine and rehabilitationPhysical therapy

Abstract

fetched live from OpenAlex

The Winston Churchill Memorial Trust, established in 1965, funds Travelling Fellowships and both authors visited hospitals in Germany, Canada and the USA regarded as centres of excellence with expertise in the early care, reconstruction and rehabilitation of the combat casualties of our NATO Allies, as recipients of these Fellowships. This article presents some of the lessons learnt in the field of musculoskeletal trauma and rehabilitation from the Canadian and US military medical systems. In trauma, there were significant differences in wound debridement policy, use of external fixators for fractures, primary use of circular frames for open tibial fractures and a far more liberal use of bone morphogenetic protein in fracture treatment. Differences in soft tissue reconstruction policy regarding flaps for soft tissue cover over exposed bone, near-universal usage of topical negative pressure dressings and use of Allgöwer-Donati suture pattern to close all wounds were noted. Ertl amputation osteoplasty, a modified form of transtibial amputation, had also been reintroduced. In rehabilitation, the management of heterotopic ossification, in particular with imaging techniques and excision surgery, was identified. For the upper limb, we observed the patient training required to use a myoelectric hand and the future possibility of targeted muscle re-innervation to make controlling these myoelectric prostheses more natural using innate motor patterns. For the lower limb, we found we used identical above knee prostheses. For patients who have had limb reconstruction and have poor function, an energy-storing orthosis was demonstrated to compensate for the loss of range of motion and muscle power.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.998

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.280
Teacher spread0.260 · 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.

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

Citations14
Published2013
Admission routes1
Has abstractyes

Explore more

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