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Record W4417252321 · doi:10.1097/aln.0000000000005876

Evaluating the Statistical Robustness of Randomized Controlled Trials of Spinal Cord Stimulation for Pain through the Use of Fragility Index

2025· article· en· W4417252321 on OpenAlexaff
Nasir Hussain, Richard Brull, Raghav Shah, Jordan Bozer, Ryan S. D’Souza, Jay Karri, Tristan Weaver, Larry J. Prokop, Faraj W. Abdallah

Bibliographic record

VenueAnesthesiology · 2025
Typearticle
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsOttawa HospitalUniversity of OttawaSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsFragilityRandomized controlled trialRobustness (evolution)Spinal cord stimulationClinical trialMEDLINE

Abstract

fetched live from OpenAlex

BACKGROUND: The use of spinal cord stimulation (SCS) for managing severe refractory chronic pain has expanded considerably due to positive statistical evidence regarding its use; however, the statistical robustness of the underlying randomized controlled trials (RCTs) requires further scrutiny. One such tool that can be used for this purpose is the fragility index, which quantifies how many individual outcome events must be altered for an outcome to lose statistical significance. Thus the index can be used quantitatively to assess the stability and robustness of an RCT's conclusions, with higher values indicating increased trial stability. This study assesses the fragility of pain outcomes across RCTs investigating SCS for chronic pain to better understand the quality and robustness of evidence. METHODS: A systematic search was conducted for RCTs assessing SCS for any chronic pain indication. The primary outcome was an evaluation of the trial-specific fragility index for the prespecified pain primary outcomes of RCTs. Secondary outcomes included an evaluation of fragility for (1) specified indications for SCS therapy, (2) reported pain outcomes appearing in three or more RCTs, (3) the presence/absence of a conflict of interest, and (4) comparisons of SCS to conservative management or different SCS waveform modalities. RESULTS: A total of 30 RCTs were included. The median (interquartile range [IQR]) fragility index across the primary outcome of all trials was 5.45 (3.00 to 11.45). There was no statistical difference between the (1) types of outcomes (dichotomous vs. continuous; P = 0.710), (2) primary versus secondary pain outcomes ( P = 0.771), or (3) presence versus absence of trial conflict of interest ( P = 0.753). Indications with a median (IQR) fragility score greater than three included persistent spinal pain syndrome type 2 with a score of 8.00 (2.80 to 12.60), painful diabetic neuropathy with a score of 6.00 (3.00 to 11.80), complex regional pain syndrome with a score of 7.20 (4.62 to 81.50), mixed etiologies with a score of 9.00 (3.00 to 38.00), and other etiologies with a score of 3.00 (1.00 to 8.55). CONCLUSIONS: This study suggests that the majority of RCTs investigating primary pain outcomes after SCS therapy are robust with relatively high fragility scores. Reporting the fragility of outcomes in trials can provide a more comprehensive assessment of trial robustness and can further aid clinicians in interpreting trial results and making informed treatment decisions.

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)0.485
metaresearch head score (Gemma)0.776
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.997
Threshold uncertainty score0.635

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4850.776
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0150.033
Bibliometrics0.0210.019
Science and technology studies0.0020.008
Scholarly communication0.0070.008
Open science0.0050.007
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0080.001

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 head0.192
GPT teacher head0.447
Teacher spread0.255 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designMeta-analysis
DomainMethods
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

Citations0
Published2025
Admission routes1
Has abstractyes

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