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Record W1585309213 · doi:10.3390/medicina45020015

The measurements of health-related quality-of-life and pain assessment in the preoperative patients with low back pain

2009· article· en· W1585309213 on OpenAlexaboutno aff
Kotryna Vereščiagina, Kazys Vytautas Ambrozaitis, Bronius Špakauskas

Bibliographic record

VenueMedicina · 2009
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePhysical therapyMcGill Pain QuestionnaireOswestry Disability IndexLow back painBack painVisual analogue scaleQuality of life (healthcare)Observational studyLumbarPain assessmentPopulationSurgeryPain managementAlternative medicineInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: This prospective observational study of the Short-Form Health Survey (SF-36), Oswestry Disability Index, Lithuanian version of the McGill Pain Questionnaire, and Visual Analogue Scale (VAS) for pain was performed to evaluate their effectiveness in the additional preoperative screening of patients with disc herniation disease. PATIENTS AND METHODS: In the present study, we investigated a cohort of 100 patients with lumbar disc herniation causing low back pain and the second one of 100 patients with nonspecific low back pain by applying physical activity, pain scales and Short-Form 36 General Health Questionnaire. RESULTS: The quantitative analysis of SF-36 domain scores showed the substantial differences in both examined (herniated and control) groups. In the present study, we estimated moderate but statistically significant (P<0.05) correlations between the bodily pain domain scores and assessment of back and leg pain on the VAS, as well as between the physical function and walking/standing ability (Oswestry). According to appropriate pain assessment instruments (Lithuanian version of the McGill Pain Questionnaire), qualitative and quantitative analysis of the preoperative patients was performed. CONCLUSION: The provided methodology could be used in population-based studies or in clinical samples that focus on specific impairments and seek to control the pain frequency and intensity, for example, follow-up assessments testing the effectiveness of surgical procedures performed, and to elicit the pathways leading to other impairments.

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)0.007
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 score0.036
Threshold uncertainty score0.248

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.055
GPT teacher head0.347
Teacher spread0.292 · 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

Citations17
Published2009
Admission routes1
Has abstractyes

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