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Record W2096335309 · doi:10.1097/aco.0b013e328011390b

Management of the patient with a large anterior mediastinal mass: recurring myths

2007· editorial· en· W2096335309 on OpenAlexaff
Peter Slinger, Cengiz Karsli

Bibliographic record

VenueCurrent Opinion in Anaesthesiology · 2007
Typeeditorial
Languageen
FieldMedicine
TopicMyasthenia Gravis and Thymoma
Canadian institutionsHospital for Sick ChildrenToronto General Hospital
Fundersnot available
KeywordsMedicineMediastinal massCardiopulmonary bypassAnestheticAnesthesiaSurgeryIntensive care medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: This editorial review summarizes the current anesthetic management of patients with anterior mediastinal masses. RECENT FINDINGS: With increased appreciation of the correct intraoperative management of these cases severe intraoperative respiratory or cardiovascular collapse is less likely to occur during general anesthesia. Maintenance of spontaneous ventilation is the anesthetic goal whenever possible. Major life-threatening complications now occur more frequently postoperatively. SUMMARY: General anesthesia is not safe in patients with severe positional symptoms from an anterior mediastinal mass. With modern imaging techniques, general anesthesia is rarely needed for diagnostic procedures in these patients. Preoperative flow-volume loops are not useful in the management of these patients and the concept of cardiopulmonary bypass on 'standby' is not appropriate during induction of anesthesia.

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)0.006
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0030.003

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 head0.018
GPT teacher head0.316
Teacher spread0.298 · 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
GenreEditorial

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

Citations197
Published2007
Admission routes1
Has abstractyes

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