The cost-effectiveness of elective Cesarean delivery for HIV-infected women with detectable HIV RNA during pregnancy
Bibliographic record
Abstract
OBJECTIVES: To determine the net health consequences, costs, and cost-effectiveness of alternative delivery strategies for HIV-infected pregnant women with detectable HIV RNA in the USA. DESIGN: Cost-effectiveness analysis using a probabilistic decision model. METHODS: The model compared two strategies: elective Cesarean section and vaginal delivery. Data for HIV transmission rate, maternal death rate, health-related quality of life and costs were obtained from the literature, national databases, and a tertiary hospital's cost accounting system. Model outcomes included total lifetime costs, quality-adjusted life expectancy, maternal death rate, HIV transmission rate, and incremental cost-effectiveness ratios. RESULTS: Elective Cesarean section resulted in a vertical HIV transmission rate of 34.9 per 1000 births compared with 62.3 per 1000 births for vaginal delivery. Elective Cesarean section was more effective (38.7 quality adjusted life years per mother and child pair) and less costly ($10600 per delivery) than trial of labor (38.2 combined quality adjusted life years at a cost of $14500 per delivery). However, elective Cesarean section increased maternal mortality by 2.4 deaths per 100000 deliveries. The results were consistent over a wide range of the variables, but were sensitive to the risk of HIV transmission with vaginal delivery and the relative risk of HIV transmission with elective Cesarean section. CONCLUSIONS: In pregnant HIV-infected women with detectable HIV RNA, elective Cesarean section would reduce total costs and increase overall quality-adjusted life expectancy for the mother-child pair, albeit at a slight loss of quality adjusted life expectancy to the mother.
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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".