MétaCan
Menu
Back to cohort
Record W3147468613 · doi:10.1093/neuros/nyx193

In Reply: Decompressive Surgery for Diabetic Neuropathy: Waiting for Incontrovertible Proof

2017· letter· en· W3147468613 on OpenAlexaff
Martijn R. Tannemaat, Mirjam Datema, J. Gert van Dijk, Rajiv Midha, Martijn J. A. Malessy

Bibliographic record

VenueNeurosurgery · 2017
Typeletter
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineAldose reductaseDiabetic neuropathySurgeryDiabetes mellitusObservational studyPerioperativeIntensive care medicineInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

To the Editor: We thank Dr Liao for his response1 to our review.2 We agree that the practice advisory published by the American Academy of Neurology stated that decompressive surgery for diabetic peripheral neuropathy (DPN) is unproven,3 but appear to differ on the implications of this assessment. When the risk of an intervention is clear but its benefit is not, the fundamental principle of “primum non nocere” should prevail, especially in patients with diabetes, in whom the incidence of perioperative complications is increased4 and wound healing is impaired.5 Dr Liao suggests that observational studies showing the involvement of aldose reductase pathways, oxidative stress, and advanced glycation end products in diabetic neuropathy provide evidence for the utility of decompressive surgery, but to our knowledge there is no evidence that surgery affects any of these processes. In fact, historical experience with aldose reductase inhibitors admonishes against inferring clinical efficacy from basic scientific research: the clinical effects of aldose reductase inhibitors have been disappointing and they are not used for treatment today.6 Importantly, the inclusion criteria for decompressive surgery remain unclear: proponents state that it should only be considered in patients with DPN and superimposed focal nerve entrapment. Dr Liao states that confirmation with electrophysiological testing is required for a diagnosis of superimposed nerve entrapment, although his paper on decompressive surgery did not mention abnormal nerve conduction studies as an inclusion criterion.7 As in other studies on decompressive surgery, the authors relied solely on a combination of clinical findings and the presence of a Tinel sign at sites of potential entrapment for a diagnosis of nerve compression. However, a positive Tinel sign has no diagnostic value for nerve compression in the legs.8 While we sympathize with the notion “where there is compression, there should be decompression,” we feel that this requires proof of compression as well as proof that patients benefit clinically from decompression. In our view, surgical decompression in patients with diabetes should be restricted to focal nerve entrapment based on solid diagnostic criteria. Finally, it worries us that many surgeons subject thousands of patients to an unproven procedure when clear proof of its efficacy could be obtained with a small clinical trial on as few as 22 patients.2 Fortunately, a randomized sham-controlled clinical trial is now underway at the University of Texas. The results are eagerly anticipated. If this trial provides solid evidence that decompressive surgery causes a significant, long-term reduction in pain compared to the placebo control (the sham-operated leg), we will revise our position. Until then, we prefer to do no harm. Disclosure The authors have no personal, financial, or institutional interest in any of the drugs, materials, or devices described in this article.

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)0.007
metaresearch head score (Gemma)0.065
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.021
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.065
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0020.003
Scholarly communication0.0040.008
Open science0.0040.002
Research integrity0.0210.031
Insufficient payload (model declined to judge)0.0080.006

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 head0.042
GPT teacher head0.296
Teacher spread0.254 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueNeurosurgerySame topicPain Mechanisms and TreatmentsFrench-language works237,207