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Record W1982425042 · doi:10.1053/rapm.2001.25914

Analgesic effects of low-dose ropivacaine for interscalene brachial plexus block for outpatient shoulder surgery—A dose-finding study

2001· article· en· W1982425042 on OpenAlexaff
S. Krone

Bibliographic record

VenueRegional Anesthesia & Pain Medicine · 2001
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsToronto Western HospitalUniversity Health Network
Fundersnot available
KeywordsMedicineRopivacaineAnalgesicAnesthesiaShoulder surgeryBrachial plexus blockBrachial plexusSurgery

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Interscalene brachial plexus block (ISB) with low-dose bupivacaine provides effective postoperative shoulder analgesia in outpatients. The analgesic effect of low-dose ropivacaine for ISB is unknown. METHODS: In this double-blind study, 66 outpatients scheduled to undergo arthroscopic shoulder surgery were randomly assigned to receive an ISB with 10 mL of 0.125%, 0.25%, or 0.5% ropivacaine before surgery. Postoperative verbal pain rating score, analgesic consumption, and the extent of motor and sensory block was assessed for 120 minutes after surgery. RESULTS: The degree of shoulder analgesia was dose dependent. Postoperative pain scores were lowest with 0.5% ropivacaine, and analgesic was not required in the hospital in 70% of the patients who received 0.25% and 0.5% ropivacaine, compared to 30% with 0.125% ropivacaine (P < .03). In the patients who required no analgesic in the hospital, the time to first oral analgesic at home was approximately 10 hours irrespective of ropivacaine concentration. Motor and sensory block distal to the elbow was detected in 25% of the patients in the 0.5% group but none in the 0.125% group. CONCLUSIONS: Interscalene brachial plexus block with low-dose ropivacaine, 10 mL of 0.25% and 0.5%, provides effective long-lasting shoulder analgesia in a majority of patients after arthroscopic surgery.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.041
GPT teacher head0.302
Teacher spread0.261 · 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 designObservational
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

Citations58
Published2001
Admission routes1
Has abstractyes

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