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Record W2546978028 · doi:10.14740/jmc.v7i11.2673

Spinal Anesthesia for Urologic Surgery in an Infant With Palliated Single Ventricle Physiology

2016· article· en· W2546978028 on OpenAlexvenueno aff
Alexander B. Froyshteter, Emmett E. Whitaker, Jason Bryant, Christina B. Ching, Joseph D. Tobias

Bibliographic record

VenueJournal of Medical Cases · 2016
Typearticle
Languageen
FieldNeuroscience
TopicAnesthesia and Neurotoxicity Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAnestheticAnesthesiaSpinal anesthesiaSurgeryHeart diseaseNeurocognitiveCardiology

Abstract

fetched live from OpenAlex

Although commonly practiced in the adult population, spinal anesthesia has seen sporadic use in the pediatric population, being employed historically as a means of avoiding apnea following general anesthesia with halothane. With the emergence of evidence that specific anesthetic agents may affect future neurocognitive outcomes, there has been an increased focus on alternatives to general anesthesia, including spinal anesthesia.  However, spinal anesthesia may also have applications in patients with co-morbid conditions that increase the risk of general anesthesia. We present the use of spinal anesthesia during urologic surgery in a 19-month-old boy with hypoplastic left heart syndrome who had undergone surgical palliation. The use of spinal anesthesia in patients with congenital heart disease is reviewed, potential hemodynamic consequences are presented, and the use of spinal anesthesia as an alternative to general anesthesia is discussed. J Med Cases. 2016;7(11):493-497 doi: http://dx.doi.org/10.14740/jmc2673w

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)0.000
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.124
GPT teacher head0.352
Teacher spread0.229 · 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 designCase report
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
Published2016
Admission routes1
Has abstractyes

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