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Record W2484324309 · doi:10.1097/bsd.0000000000000414

Lumbar Discectomy

2017· article· en· W2484324309 on OpenAlexaboutno aff
Errikos A. Koen, Petros Antonarakos, Labrini T. Katranitsa, Kostas E. Poulis, Thomas M. Apostolou, Evangelos Christodoulou, Anastasios Christodoulou

Bibliographic record

VenueClinical Spine Surgery A Spine Publication · 2017
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialMedicineMcGill Pain QuestionnairePhysical therapyLogistic regressionObservational studyDiscectomyLumbarDepression (economics)Quality of life (healthcare)SurgeryInternal medicineVisual analogue scalePsychiatry

Abstract

fetched live from OpenAlex

STUDY DESIGN: We followed a longitudinal observational design with 2 assessment points, presurgery and postsurgery, in 83 consecutive patients undergoing single-level lumbar discectomy. OBJECTIVE: Prognostic data can be gathered from commonly used generic outcome measures to identify patients at risk of persistent leg pain-associated chronicity, following lumbar discectomy SUMMARY OF BACKGROUND DATA:: Suboptimal results observed, following open lumbar discectomy, have been connected to the interplay among presurgery pain characteristics, functional and psychosocial adaptations like persistent pain, disability, and depression. Outcome predictive qualities have been recently attributed to well-known outcome measures. However, most studies on prognostic indicators use multiple tools designs, inhibiting clinical application. Here we elaborate on predictive indications identified in 2 generic patient-rated questionnaires, Short Form-36 (SF-36) and McGill Pain, as many of their domains can evaluate factors related to unfavorable outcomes. METHODS: For the prognostic value calculations, multivariate logistic [Short-Form McGill Pain Questionnaire (SF-MPQ)] and linear regression models (SF-36) were fitted to investigate the association between presurgery and postsurgery scores. In all models, the presurgical score at question was assigned as the dependent variable while age, sex and presurgery score at question were the independent variables. RESULTS: Overall, a statistically significant amelioration in both SF-MPQ and SF-36 scores was observed postsurgically. For the SF-MPQ leg cramping, gnawing, burning, and aching pain symptoms, when present presurgically, were the least responsive to treatment. For the SF-36, mental scores overall were less responsive than physical equivalents postoperatively, while general health perception improved only marginally. Differences in pain level scores did not correlate with an equivalent reduction in postsurgery anxiety and depression indices. CONCLUSIONS: SF-MPQ and SF-36 can assist in treatment decision, as they can readily identify patients at risk of unfavorable outcomes even in primary/clinical settings. The above findings additionally suggest a wider scope of clinical use for the above questionnaires allowing parallel processing and interpretation of the same patient data. LEVELS OF EVIDENCE: Level I.

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)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.123
GPT teacher head0.430
Teacher spread0.308 · 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; both teacher heads agree on what is shown here.

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
Published2017
Admission routes1
Has abstractyes

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