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Record W2921581587 · doi:10.1097/md.0000000000014812

Effectiveness of neuromuscular electrical stimulation and ibuprofen for pain caused by necrosis of the femoral head

2019· article· en· W2921581587 on OpenAlexaboutno aff
Qing-hui Ji, Xiao‐Feng Qiao, Shoufeng Wang, Peng Zhao, Shichen Liu, Yu Xue, Jian-Min Qiao, Yanbao Li

Bibliographic record

VenueMedicine · 2019
Typearticle
Languageen
FieldMedicine
TopicBone and Joint Diseases
Canadian institutionsnot available
FundersJiamusi University
KeywordsMedicineWOMACIbuprofenVisual analogue scaleOsteoarthritisAdverse effectAnesthesiaFemoral headSurgeryInternal medicine

Abstract

fetched live from OpenAlex

This retrospective study analyzed the effectiveness of neuromuscular electrical stimulation (NMES) for pain relief caused by necrosis of femoral head (NFH).Totally, 80 cases of patients with NFH were analyzed and then were assigned to a treatment group or a control group in this study. Of these, 40 cases in the treatment group received ibuprofen and NMES therapy. The other 40 cases in the control group received ibuprofen alone. Cases in both groups were treated for a total of 6 weeks. The primary outcome of pain intensity was measured by a visual analog scale (VAS). The secondary outcome was assessed by Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). In addition, adverse events (AEs) were also recorded in each case. All outcomes were evaluated before and after the treatment.After treatment, patients in the treatment group showed more effectiveness in pain relief, as measured by VAS (P < .01) and WOMAC sub-pain scale (P < .01), except stiffness, as evaluated by WOMAC sub-stiffness scale (P = .07), and function, as assessed by WOMAC sub-function scale (P = .09), than patients in the control group. Additionally, no significant differences in AEs were detected between 2 groups.This study found that NMES may be helpful for pain relief in patients with NFH.

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 score0.383
Threshold uncertainty score0.193

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.014
GPT teacher head0.285
Teacher spread0.271 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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