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Record W4306833615

[SURGICAL "NEVER EVENTS" IN THE ANTERIOR CERVICAL APPROACH].

2022· article· en· W4306833615 on OpenAlexaff
Avi Abraham Baruch Rubinstein, Michal Rubinstein, Irena Dolinger, Shmuel Yakirevitch

Bibliographic record

VenuePubMed · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective Tissue Growth Factor Research
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsMedicineComplicationMalpracticeDamagesIntensive care medicineComprehensionMedical literatureMedical malpracticeMedical emergencySurgeryGeneral surgery
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION: This article deals with incidents which involved damages that could have been prevented. This includes patients who have been suffocated and have suffered irreversible damage, unfortunately, as far as we know, due to the powerlessness of the medical staff who did not act suitably. The disasters have happened as a result of upper respiratory airway obstruction by a blood clot (retropharyngeal hematoma) that developed as a complication after an anterior cervical surgery (spine/carotid artery) or after a sharp cervical injury. The main question that derives from the following cases is whether it was possible to prevent the unnecessary death and/or the severe ongoing disability of the patients by choosing a different form of medical treatment. We are dealing with common practical knowledge, while referring to the importance of the immediate concern about the airway of patients after an anterior cervical surgery both by the nursing and the treating medical staff and also, by the risk managers. Malpractice events are very important educational material for the medical and nursing staff in order to avoid such preventable cases. Right before our eyes, a real revolution is happening in terms of digital medicine. This revolution may change the current comprehension among physicians about medical decisions, diagnosis and treatment selection. All of the above is being done by the rare resource that we possess which is the human resource. However, the problem is that in many medical cases, for instance the ones mentioned in the article, the medical treatment method for the patient will not benefit from digital medicine, moreso, in those cases we depend on the human resource. The purpose of this work is mainly to make an intellectual-behavioral change among medical staff, nurses and physicians, in terms of complaints such as dysphagia or respiratory difficulties after anterior cervical surgery. Time has a crucial role in those emergency cases, therefore complete seriousness, caution and a rapid airway opening are demanded in the described circumstances.

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)0.001
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 score0.277
Threshold uncertainty score0.260

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.027
GPT teacher head0.262
Teacher spread0.235 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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