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Record W4313237044 · doi:10.1159/000527257

Establishing Minimal Clinically Important Difference in Sleep Outcomes after Spinal Cord Stimulation in Patients with Chronic Pain Disorders

2022· article· en· W4313237044 on OpenAlexaboutno aff
Phillip M Johansen, Frank Trujillo, Vivian Hagerty, Tessa Harland, Gregory Davis, Julie G. Pilitsis

Bibliographic record

VenueStereotactic and Functional Neurosurgery · 2022
Typearticle
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and StrokeNational Cancer Institute
KeywordsMinimal clinically important differenceOswestry Disability IndexPhysical therapyBeck Depression InventoryMedicineChronic painEpworth Sleepiness ScaleDepression (economics)AnxietyPhysical medicine and rehabilitationPain catastrophizingMcGill Pain QuestionnaireHospital Anxiety and Depression ScaleBrief Pain InventoryActigraphyDeep brain stimulationInsomniaLow back painAnesthesiaVisual analogue scaleRandomized controlled trialPsychiatrySurgeryPolysomnographyInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: As one of the most common medical conditions for which patients seek medical care, chronic pain can be debilitating. The relationship between chronic pain and sleep is thought to be bidirectional, suggesting that treatment of one can be beneficial to the other. There is mounting evidence that spinal cord stimulation (SCS) improves aspects of sleep. How meaningful that is to patients' lives has not been ascertained. OBJECTIVE: The aim of the current study was to further elucidate the effect of SCS on sleep by examining the relationship between pain outcome measures with the insomnia severity index (ISI) and to establish the minimally clinical important difference (MCID), which is defined as the smallest noticeable change that an individual perceives as clinically significant. MATERIALS AND METHODS: We prospectively collected ISI, Epworth sleepiness scale (ESS), Numerical Rating Scale, McGill Pain Questionnaire-Short Form, Oswestry Disability Index, Beck Depression Inventory, and Pain Catastrophizing Scale data both pre- and postoperatively for chronic pain patients who underwent SCS placement and had long-term outcomes. The ISI is a well-studied questionnaire used to assess an individual's level of insomnia. RESULTS: We correlated the ESS and ISI with pain outcome measures in sixty-four patients at a mean follow-up of 9.8 ± 2.9 months. The ISI showed correlations with disability as measured through the Oswestry Disability Index (p = 0.014) and depression as measured through the Beck Depression Inventory (p = 0.024). MCID values for the ISI were calculated using both anchor- and distribution-based methods. The minimal detectable change method resulted in an MCID of 2.4 points, standard error of measurement resulted in an MCID of 2.6 points, and the change difference resulted in an MCID of 2.45. The receiver operating characteristic method yielded an MCID of 0.5-point change with an area under the curve of 0.61. CONCLUSION: This study successfully established MCID ranges for the ISI outcome measure to help gauge improvement in insomnia after SCS. The ISI has ample evidence of its validity in assessment of insomnia, and MCID values of 2.4-2.6 correlate with improvement in disability and depression in our patients.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.247
Teacher spread0.231 · 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 source (direct Gemma or distilled Codex), 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

Citations10
Published2022
Admission routes1
Has abstractyes

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