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Record W2959313009 · doi:10.1002/ehf2.12489

Perioperative Mortality Secondary to a Pulmonary Embolism During a Surgical Implantation of the Endo-Exo-Prosthesis: A Case Report

2019· article· en· W2959313009 on OpenAlexaff
Marcus Örgel, Horst‐Heinrich Aschoff, Christian Krettek, Tilman Graulich, Mohamed Omar, Afif Harb, Sulaiman Alazzawi

Bibliographic record

VenueESC Heart Failure · 2019
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsUniversity of British Columbia Hospital
Fundersnot available
KeywordsMedicinePerioperativeProsthesisSurgeryPulmonary embolismComplicationAmputationOrthopedic surgeryFemur

Abstract

fetched live from OpenAlex

We report on a 53-year-old female patient who suffered a perioperative death secondary to a pulmonary embolism (PE) during an implantation of Endo-Exo-Prosthesis. This is a retrospective review of medical case for a patient who had a previous above-the-knee amputation secondary to a failed previous arthroplasty surgery. Our planned surgery was a stage 1 implantation of an Endo-Exo-Prosthesis, and it was performed under general anaesthesia. After 25 min from starting the surgical procedure, the patient sustained a cardiac arrest, and despite an active cardiopulmonary resuscitation for 50 min, the patient did not recover, the ventilator machine was stopped later on, and the patient was declared deceased at that stage. Fatal intraoperative PE is a rare but significant complication during orthopaedic procedures. There are few reports of similar events but include mainly trauma patients with fractured neck of femur. Endo-Exo-Prosthesis is a relatively newly evolved procedure in a unique group of patients. To our knowledge, this is the first case report of such complication during Endo-Exo-Prosthesis implantation. Patient and surgeon should be aware of it, and additional preventive measures like preoperative scoring systems and in special cases using inferior vena cava filter should be considered in patients with high risk of developing venous thromboembolism.

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)0.000
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 score0.271
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.010
GPT teacher head0.271
Teacher spread0.261 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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