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Record W3045358465 · doi:10.1080/01616412.2020.1796383

Prospective randomized appraisal of the best pain relief option after L4/L5 discectomy

2020· article· en· W3045358465 on OpenAlexaboutno aff
Tomislav Sajko, Krešimir Rotim, Biljana Kurtović, Cecilija Rotim, Ante Rotim

Bibliographic record

VenueNeurological Research · 2020
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMcGill Pain QuestionnaireAnesthesiaAnalgesicRandomized controlled trialDiscectomyTramadolSurgeryProspective cohort studyLumbarVisual analogue scale

Abstract

fetched live from OpenAlex

Objectives To determine the efficacy of paracetamol and tramadol analgesia via patient controlled pump and intermittent administration using the Short-Form McGill Pain Questionnaire after L4/L5 discectomy in neurosurgical patients.Methods Fourteen months prospective quantitative study with 200 neurosurgical patients’ participation who underwent elective discectomy of the L4/L5 intervertebral disc extrusion. The study was conducted due to a patient-controlled analgesia pump and intermittent analgesia application. Pain was assessed using the Short-Form McGill Pain Questionnaire in the Croatian language during the zero, first, and second postoperative day.Results Perception of pain was reduced in patient controlled analgesia pump groups after the second measurement during the first postoperative day [95% CI: −3.89, −0.76], regardless of administered analgesic (p< 0.001). After the final measurement, at 7 PM on the second postoperative day, the differences were not significant (p= 0.070). This study results are registered and allocated in the Australian New Zealand Clinical Trials Registry (ANZCTR).Discussion Analgesia administration via patient-controlled pump contributes to the alleviation of postoperative pain after L4/L5 disc extrusion surgery regardless of administered analgesic.

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)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.474
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.081
GPT teacher head0.399
Teacher spread0.318 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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