Reply: Insurance should cover vancomycin for primary sclerosing cholangitis
Bibliographic record
Abstract
Ali and colleagues raise issues of insurance coverage for oral vancomycin (OV) for the treatment of primary sclerosing cholangitis (PSC); however, the purpose of AASLD guidance statements is to help clinicians understand and implement the most recent evidence (https://www.aasld.org/practice-guidelines). The writing group, Practice Guidance Committee, and AASLD Governing Board and supported the final statement that there is insufficient evidence to recommend the use of OV which is consistent with the 2022 European Association for the Study of the Liver guidelines.1 The meta-analysis referred to included only 2 randomized controlled trials of OV.2. The largest study randomized 29 patients to OV or placebo for 12 weeks and reported an improvement in Mayo Risk Score, though total bilirubin did not change. The other randomized controlled trials was not placebo-controlled and included 8 and 9 patients who received low or high doses of OV, respectively, for 12 weeks. Compared with baseline, alkaline phosphatase decreased in both groups, and Mayo Risk Score decreased only in the low-dose group, but without change in total bilirubin. A third study was open-labeled and reported on 30 enrolled subjects and 29 patients treated outside protocol, 25 (42%) of whom had small duct PSC, and several previously treated with OV.3 The methods used to support the claims of imprvements in histology and cholangiograms were not reported. In contrast, a retrospective study of 264 patients found that neither OV nor ursodiol were associated with clinical improvements compared with observation in pediatric patients with PSC.4 Thus, the data supporting the use of OV in PSC is not “robust” and the statements Ali an colleagues made about OV are not supported by current evidence. More concerning is the suggestion that OV might be a substitute for biologics for treating inflammatory bowel disease. Management of PSC-associated inflammatory bowel disease was outside the scope of the Guidance, but multiple society guidelines do not recommend vancomycin for acute severe ulcerative colitis. All stakeholders desire a safe and effective treatment for PSC. Ali and colleagues believe that OV is that treatment, but current evidence does not support this belief.
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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 | 0.005 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.037 | 0.036 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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".