Bibliographic record
Abstract
To the Editor—From a cost-effectiveness point of view, Rajasingham et al conclude that the preferred regimen for treatment of Clostridiodes difficile infection (CDI) is fidaxomicin for nonsevere CDI, vancomycin for severe CDI, fidaxomicin for first recurrences, and fecal microbiota transplant for subsequent recurrences [1]. This is based on the premise that individuals and payers are willing to pay $31 751 dollars per quality-adjusted life-year (QALY), the incremental cost of this regimen over using metronidazole for nonsevere CDI and vancomycin for severe CDI and for all recurrences. The methodology of this study appears to be sound. However, the authors assume that any intervention that costs less than $100 000 per QALY is cost-effective. They do not provide an explanation for this cutoff, which is at the upper end of the amounts typically chosen for such analyses [2]. When the cost per QALY that individuals and payers would be willing to pay was first derived in the early 1990s, there were limited ultraexpensive drugs and technologies. The number of ultraexpensive drugs and technologies that clinicians can recommend is rapidly increasing. If we choose to adopt any that meet this broad definition of “cost-effective,” there will be limited incentive for manufacturers to decrease prices and the cost of healthcare will increase beyond what even the wealthiest of nations can afford.
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 | 0.005 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.008 | 0.015 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".