Motion – Laparoscopic Nissen Fundoplication Is More Cost-Effective than Oral PPI Administration: Arguments against the Motion
Bibliographic record
Abstract
Discussion of the cost effectiveness of medical and surgical treatments of gastroesophageal reflux disease (GERD) is plagued by a number of logical fallacies. Several of these defects in reasoning are reviewed. For example, it is inappropriate to compare the costs of therapies unless they are equally effective. The relative cost effectiveness of various treatment options is difficult to determine because monetary expenditures and gains in health status cannot easily be measured in commensurate units. Not everything can be translated into incremental cost effectiveness ratios. Two decision analyses from European investigators seemed to show that Nissen fundoplication was more cost effective than long term acid-suppression therapy, but they failed to consider the costs of surgical complications and failures. The most comprehensive decision analysis, employing a Markov chain model, found that the two treatment options were roughly equivalent, at least during the first seven years of follow-up. Decision analyses often do not reflect actual practice patterns and cannot provide solutions to problems that cannot be solved by appropriate medical reasoning. Moreover, results that are reported by specialized surgical centres probably cannot be duplicated by less experienced surgeons. The increasing incidence of esophageal adenocarcinoma has been erroneously attributed to the use of potent acid-suppressant medications, but the actual cause has been shown to be the decreased prevalence of Helicobacter pylori. There are no significant differences in the incidence of this tumour after medical or surgical therapy of GERD. It is unlikely, however, that arguments will convince proponents of one treatment or another to change their opinions.
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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 | 0.038 | 0.127 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".