Bibliographic record
Abstract
The objectives of this review include the conceptualization of the health-related quality of life effects of prenatal diagnosis and a brief summary of evidence on the short- and long-term effects of prenatal diagnosis on the health-related quality of life effects associated with chorionic villi sampling and genetic amniocentesis and the identification of important unresolved issues. Although this is not a systematic review, it is an update of published research on the utility approach to assessing the health-related quality of life in prenatal diagnosis. It is based on a search of publications by investigators known to be active in the area and a hand search of selected specialized journals. Important health states associated with prenatal diagnosis include both process (undergoing testing) and outcome. Empirical studies providing preference scores for health states associated with prenatal diagnosis highlight the importance of long-term outcomes relative to process. On average with respect to process, chorionic villi sampling is less burdensome than genetic amniocentesis. On average with respect to infrequent but potentially important outcomes as health states associated with diagnostic inaccuracy, genetic amniocentesis is less burdensome than chorionic villi sampling. Almost all of the existing evidence on the health-related quality of life effects of prenatal diagnosis reports on the experience of the women undergoing prenatal diagnosis. The preferences of partners have not been assessed. Furthermore, few studies have investigated subsequent reproductive behavior. Finally, there is considerable scope for the use of preference elicitation techniques in helping couples to decide on whether or not to undergo prenatal diagnosis and if they do, help them to choose the modality that best suites their preferences.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".