2023 Annual Conference Conférence Annuelle
Bibliographic record
Abstract
OBJECTIVES: The use of flourine-18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in the evaluation of patients with Staphylococcus aureus bacteremia (SAB) is associated with decreased mortality in observational studies.However, uptake is limited by cost and availability.We aimed to evaluate the cost-utility of PET/CT among adults hospitalized with SAB in Ontario.METHODS: A cost-utility analysis was conducted using a probabilistic Markov cohort model assessing three diagnostic strategies: (1) PET/CT in all patients, (2) PET/CT in high-risk patients only, and (3) standard workup (without PET/CT) for all patients.The analysis was from the Ontario healthcare payer perspective using a lifetime horizon, with costs and utilities discounted at 1.5%/year.Primary outcomes were quality-adjusted life years (QALYs), costs, and an incremental cost-effectiveness ratio (ICER).Deterministic and probabilistic sensitivity analyses were conducted to evaluate parameter uncertainty.RESULTS: Current standard of care resulted in an average of 17.09 QALYs at a cost of $209,510 per patient.This was dominated by PET/CT in high-risk patients with average 17.34 QALYs and cost of $199,561.Compared to PET/CT in high-risk patients only, PET/CT for all patients had an ICER of $72,794; however, there was a high degree of uncertainty comparing these two strategies with the existing data inputs.Results were most sensitive to the specificity of standard low-risk workup and PET/CT for detecting metastatic foci.At a willingness-to-pay threshold of $50,000/ QALY, PET/CT in high-risk patients was the most cost-effective strategy in 56.9% of simulations (vs 40.2% for PET/ CT in all patients).CONCLUSIONS: Our findings suggest that a strategy of using PET/CT in high-risk patients is more cost-effective than the current standard of care of no PET/CT.Randomized controlled trials should be conducted to compare the use of PET/CT in all patients versus high-risk patients only.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.548 | 0.471 |
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".