A retrospective study of the added value of parallel titers compared with serial titers
Bibliographic record
Abstract
BACKGROUND: Prenatal antibody titers for alloimmunized patients are subject to multiple sources of variation. A parallel titer on the previous sample at the same time as the current sample is recommended. The purpose of this study was to determine the added value of parallel titers. STUDY DESIGN AND METHODS: This is a retrospective study of samples from consecutive prenatal patients with at least two prenatal antibody titers performed in the same pregnancy at a single institution between October 2010 and March 2017. Prenatal titers were performed using gel technology. Data were collected to determine the sensitivity and specificity of a clinically significant increase (twofold or greater) in serial titers compared with the gold standard of using parallel titers. RESULTS: There were 155 serial prenatal titers performed in 59 alloimmunized pregnant women. Nineteen samples (12%) had a serial titer increase of twofold or greater with eight false positive samples (increase less than twofold when using parallel titers). Thirty-six samples (23%) had a serial titer increase of onefold with two false negative samples (increase of twofold or greater using parallel titers). One hundred samples (65%) had no increase (or a decrease) in serial titer with none having an increase of twofold or greater using parallel titers. The sensitivity of a twofold or greater increase in serial titers was 84.6% (95% CI 55-98%) and the specificity was 94.4% (95% CI 89-98%) when compared with parallel titers. CONCLUSION: This study questions the value of parallel titers on every prenatal titer performed. When no increase in serial titers was observed, parallel titers added no new information.
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 | 0.006 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".