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The Epidural Test Dose: A Review

2006· review· en· W2015337928 on OpenAlexaff
Joanne Guay

Bibliographic record

VenueAnesthesia & Analgesia · 2006
Typereview
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsHôpital Maisonneuve-RosemontUniversité de Montréal
Fundersnot available
KeywordsMedicineFentanylEpinephrineCatheterSedationAnesthesiaIntrathecalBlood pressureSurgeryInternal medicine

Abstract

fetched live from OpenAlex

In Brief This review systematically examines the literature on the ability of the classical epidural test dose and other strategies to detect intravascular, intrathecal, or subdural epidural needle/catheter misplacement. For detection of simulated intravascular misplacements, a sensitivity (S) and a positive predictive value (PPV) ≥80 demonstrated by at least two randomized controlled trials coming from two different centers were determined for the following tests and patient populations: Nonpregnant adult patients = increase in systolic blood pressure (SBP) ≥15 mm Hg (S = 80–100 and 93–100; PPV = 80–100 and 83–100) or either an increase in SBP ≥15 mm Hg or an increase in heart rate ≥10 bpm after the injection of 10 (S = 100; PPV = 83–100) or 15 μg of epinephrine (S = 100; PPV = 83–100); pregnant patients = sedation, drowsiness, or dizziness within 5 min after the injection of 100 μg of fentanyl (S = 92–100; PPV = 91–95); and children = increase in SBP ≥15 mm Hg after the injection of 0.5 μg/kg of epinephrine (S = 81–100; PPV = 100). Conversely, more studies are required to determine the best strategies to detect intrathecal and subdural epidural needle/catheter misplacements in these three patient populations. IMPLICATIONS: The epinephrine test dose for intravascular epidural needle/catheter misplacement can only be recommended for nonpregnant adult patients and children. More studies are required to determine the best strategies to detect intrathecal and subdural needle/catheter misplacement for adult nonpregnant patients, pregnant women, and children.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.651
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.035
GPT teacher head0.328
Teacher spread0.294 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations132
Published2006
Admission routes1
Has abstractyes

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