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Treatment of Chronic Low Back Pain With Successive Injections of Botulinum Toxin A Over 6 Months

2006· article· en· W1978721577 on OpenAlexfundno aff
John P. Ney, Marc DiFazio, Afsoun Sichani, William Monacci, L. John R. Foster, Bahman Jabbari

Bibliographic record

VenueClinical Journal of Pain · 2006
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsnot available
FundersMcGill University
KeywordsMedicineLow back painVisual analogue scaleBotulinum toxinAnesthesiaChronic painmyalgiaRadicular painProspective cohort studyBack painRefractory (planetary science)SurgeryPhysical therapyInternal medicineLumbar

Abstract

fetched live from OpenAlex

OBJECTIVES: The aim of this study was to evaluate the effects of two successive neurotoxin treatments for chronic low back pain using multiple pain rating scales in an open-label, prospective study. METHODS: Adult patients with chronic low back pain received multiple paraspinal muscle injections with a maximum dosing of 500 units of botulinum A toxin per session. Those with a beneficial clinical response received a second treatment at 4 months. Pain was assessed by visual analog scale (VAS), modified low back pain questionnaire (OLBPQ), and a clinical low back pain questionnaire (CLBPQ) at baseline, 3 weeks, 2 months, 4 months, and 6 months after the first treatment. RESULTS: Eighteen women and 42 men, ages 21 to 79 years (mean 46.6 years), with low back pain of a mean duration of 9.1 years were included. Significant improvement in back and radicular pain occurred at 3 weeks in 60% and at 2 months in 58% of the cohort. Beneficial clinical response to the first injection predicted response to reinjection in 94%. A significant minority of patients had a sustained beneficial effect from the first injection at 4 (16.6%) and 6 months (8.3%). Two patients had a transient flu-like reaction after the initial treatment. CONCLUSIONS: Botulinum toxin A improves refractory chronic low back pain with a low incidence of side effects. The beneficial clinical response is sustained with a second treatment.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score0.436

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
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 head0.019
GPT teacher head0.315
Teacher spread0.296 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations36
Published2006
Admission routes1
Has abstractyes

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