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Double-blind randomized study of tramadol vs. paracetamol in analgesia after day-case tonsillectomy in children

2000· article· en· W2143420245 on OpenAlexaboutno aff
Philippe Pendeville, Serge Von Montigny, Junio Dort, Francis Veyckemans

Bibliographic record

VenueEuropean Journal of Anaesthesiology · 2000
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTramadolAnesthesiaTonsillectomyAcetaminophenAnalgesicIbuprofenAdverse effectKetoprofenDiclofenacVisual analogue scaleRandomized controlled trialPain scaleLoading doseSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Fifty children (2-9 years) scheduled for tonsillectomy were enrolled in a double-blind randomized prospective study to compare postoperative analgesia provided with propacetamol/paracetamol (acetaminophen) or tramadol. A standard anaesthetic technique was used; each patient received sufentanil 0.25 microg kg(-1) intravenously followed with either i.v. propacetamol 30 mg kg(-1) or tramadol 3 mg kg(-1) before surgical incision. For postoperative analgesia, each child received either tramadol drops (2.5 mg kg(-1)) or paracetamol (acetaminophen) suppositories (15 mg kg(-1)), 6 and 12 h after surgery the first day and three times a day during postoperative days 2 and 3. This dosage of paracetamol is lower than the current recommended dosage, which is 40 mg kg(-1) loading dose followed by 20 mg kg(-1) 8 h(-1). Rescue medication consisted of i.v. diclofenac (1 mg kg(-1)) during the first six postoperative hours and oral ibuprofen (6-9 mg kg(-1)) afterwards. Postoperative pain scores (Children's Hospital of Eastern Ontario Pain Scale) in recovery, numerical pain scale in the ward and at home, and rescue analgesic use were significantly lower in the tramadol group. No serious adverse effects were observed.

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.002
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.017
GPT teacher head0.265
Teacher spread0.249 · 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 designRandomized trial
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

Citations55
Published2000
Admission routes1
Has abstractyes

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