Comparison of the Clinical Efficacy, Safety, and Postoperative Outcomes Between Peroral Esophageal Myotomy and Laparoscopic Heller's Myotomy With Fundoplication: A Systematic Review
Bibliographic record
Abstract
Achalasia, a neurodegenerative disease caused by the progressive destruction of ganglion cells in the myenteric plexus, is accompanied by incomplete relaxation of the lower esophageal sphincter. Laparoscopic Heller's myotomy (LHM) coupled with fundoplication has been the gold standard procedure for achalasia. Peroral esophageal myotomy (POEM) has recently gained popularity as it is minimally invasive, has fewer adverse events, and has excellent short-term outcomes. So, we aimed to compare the clinical efficacy, safety, and postoperative outcomes between LHM and POEM. We did a systematic review by following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines for 2020 and exploring research databases such as PUBMED and PMC Central, Google Scholar, and Research Gate. After appropriate screenings, articles relevant to the review were scrutinized based on the eligibility criteria. Quality assessment tools such as the Newcastle-Ottawa Scale (NOS) and the assessment of multiple systematic reviews (AMSTAR) were used to finalize the articles. A total of 11 articles (seven observational studies, two RCTs, and two systematic reviews) were included in the review after a quality check. The study included 2127 patients, classified into 981 for POEM and 1146 for LHM, who had undergone treatment for achalasia. Most of the studies had a follow-up of ≤ two years. Comparing efficacy, POEM had similar results to LHM in terms of Eckardt scores. However, abnormal DeMeester scores were found in POEM. Adverse events were significantly higher in LHM when compared to POEM in terms of safety. Peroral esophageal myotomy also stood out as having a shorter procedure time, a shorter hospital stay, and lesser odds of being a clinical failure. As for postoperative outcomes, despite treatment with proton pump inhibitors, LHM was more effective in preventing the development of esophagitis compared to POEM due to partial fundoplication. Postoperative reflux and the development of esophagitis remain certain with POEM and need to be followed up with more studies with longer follow-ups. However, POEM still stands as a better choice compared to LHM in terms of efficacy and safety.
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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 | 0.010 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.016 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".