Surgical Management of Abdominal Anterior Cutaneous Nerve Entrapment Syndrome: Case Report, Surgical Technique, and Literature Review
Bibliographic record
Abstract
Abdominal anterior cutaneous nerve entrapment syndrome (ACNES) is an emerging diagnosis, with estimated incidence of 13%-30% of the adult population. It is a syndrome characterized by chronic abdominal pain caused by entrapment of cutaneous branches of thoracoabdominal nerves at the lateral border of the rectus abdominis muscle. If conservative treatment with pain medication, botulinum toxin, or lidocaine injections is inadequate, surgical management is indicated. METHODS: We present a case of a 40-year-old woman presenting with a 1-year history of daily right anterior abdominal wall pain, consistent with a diagnosis of ACNES. We describe our approach for an anterior neurectomy of the intercostal nerve with closure of its fascial foramen. RESULTS: Three months after surgery, she remained pain free and was back to work full time. At a 13-month follow-up, the patient reported that her pain had resolved completely following surgery. CONCLUSIONS: Results are encouraging following anterior neurectomy for ACNES. Surgical descriptions in the literature are brief, with limited pictorial account. Our detailed surgical approach is provided along with a review of the existing literature on the management of ACNES.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".