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Record W3092254410 · doi:10.1016/j.bjan.2020.07.002

Bloqueio do gânglio esfenopalatino autoaplicado para cefaleia pós‐punção dural: relato de quatro casos

2020· article· pt· W3092254410 on OpenAlexaff
Andrés Rocha‐Romero, Priodarshi Roychoudhury, Rodrigo Benavides Cordero, Maynor Lopez Mendoza

Bibliographic record

VenueBrazilian Journal of Anesthesiology · 2020
Typearticle
Languagept
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsMedicineNasal cavityAnesthesiaNerve blockSurgery

Abstract

fetched live from OpenAlex

O Bloqueio do Gânglio Esfenopalatino (BGEP) é opção de tratamento efetivo associado a baixo risco para Cefaleia Pós‐Punção Dural (CPPD) refratária às medidas conservadoras. Este relato apresenta quatro pacientes com alta complexidade que apresentaram cefaleia relacionada à baixa pressão do líquido cefaloraquidiano. Três pacientes foram tratados com sucesso pela instilação de gotas de anestésico local tópico na cavidade nasal. A nova abordagem descrita neste relato apresenta riscos mínimos de desconforto ou lesão à mucosa nasal. A aplicação é rápida e pode ser administrada pelo próprio paciente. The Sphenopalatine Ganglion Block (SGB) is an effective, low‐risk treatment option for Postdural Puncture Headache (PDPH) refractory to conservative management. This report presents four complex cases of patients with headache related to low cerebrospinal fluid pressure. Three of them were successfully treated with the application of local anesthetic topical drops through the nasal cavity. The novel approach described in this report has minimal risks of discomfort or injury to the nasal mucosa. It is quick to apply and can be administered by the patient himself.

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)0.001
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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0020.001
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 head0.028
GPT teacher head0.278
Teacher spread0.250 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

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Same venueBrazilian Journal of AnesthesiologySame topicAnesthesia and Pain ManagementFrench-language works237,207