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Record W2524903965

MULTINATIONAL INTEGRATED MEDICAL UNIT BOSNIA – OPERATING THEATRE ACTIVITY ANALYSIS

2005· article· en· W2524903965 on OpenAlexaboutno aff
Wg Cdr Satish Venkatachalam

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSurgeryGeneral surgeryPopulationMultinational corporationMedical emergency
DOInot available

Abstract

fetched live from OpenAlex

Introduction An analysis was carried out of the operating theatre activity at the Role Three Multinational Integrated Medical Unit, located at Sipovo in Bosnia. The overall number of operative procedures, over a two-year period from January 2001 - December 2002, were studied. A total of 409 patients were treated and 443 operations were carried out. The patients ranged in age from 2 – 83 years. Results 202 operations were performed in 2001 and 241 operations in 2002. Of the total operations, 349 (79%) were performed by the General Surgeon and 91 (21%) performed by the Orthopaedic Surgeon. The majority of patients treated were local civilians, who outnumbered military personnel, by a ratio of 3:1. 347 operations (78%) were of a non-emergency nature and 96 carried out as emergencies (22%). Of the 111 military patients operated on, 63 were from the UK, 25 were Dutch, 16 Canadian and the rest from other countries. The vast majority of orthopaedic procedures performed were of a minor nature, such as incision and drainage, wound debridement and tendon repair. The general surgical procedures consisted largely of elective surgery in the local civilian population. During my deployment of three months, from November 2002 - January 2003, I carried out 11 operative procedures on 9 patients, 6 of these patients were civilian and 3 military. During the same period, 23 general surgical procedures were performed. Conclusion My personal experience over 3 months and, a wider analysis over 2 years highlights, the gross under-utilisation of scarce and valuable resource. I feel that the deployment of a General Surgeon with trauma experience could very adequately provide combined surgical cover for the two specialities.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.001

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 head0.015
GPT teacher head0.310
Teacher spread0.295 · 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 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

Citations0
Published2005
Admission routes1
Has abstractyes

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