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Record W4394393785 · doi:10.6084/m9.figshare.19650841

Delivery prediction by quantitative analysis of four steroid metabolites with liquid chromatography tandem mass spectrometry in asymptomatic pregnant women

2022· dataset· en· W4394393785 on OpenAlexaff
Lanlan Meng, Shaofei Su, Lin Li, Shengmin Liu, Youran Li, Ying Liu, Yifan Lu, Zhengwen Xu, Lin Liu, Qixin He, Yuanyuan Zheng, Xiaowei Liu, Yuting Cong, Yanhong Zhai, Zhen Zhao, Zheng Cao

Bibliographic record

VenueFigshare · 2022
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsChromatographyLiquid chromatography–mass spectrometryTandem mass spectrometryAsymptomaticMass spectrometrySteroidChemistryMedicineInternal medicineBiochemistryHormone

Abstract

fetched live from OpenAlex

Prediction of delivery is important for assessing due dates, providing adequate prenatal care, and suggesting appropriate interventions in preterm and post-term pregnancies. Recent metabolomic findings suggested that the temporal abundance information of metabolome can be used to predict delivery timing with high accuracy in a cohort of healthy women. However, a targeted and quantitative assay is required to further validate the clinical performance and utility of this group of metabolomic candidates in delivery prediction with a larger and independent cohort. LC-MS/MS quantitative assays were applied to determine the plasma concentrations of four steroid metabolites, including oestriol-16-glucuronide (E3-16-Gluc), 17-alpha-hydroxyprogesterone (17-OHP), tetrahydrodeoxycorticosterone (THDOC), and androstane-3,17-diol (A-3,17-Diol) in asymptomatic women of singleton pregnancies (≥30th gestational weeks). Subsequent statistical analysis was conducted to assess the performance of the above candidates in delivery prediction. Using LC-MS/MS, four steroids were separated and quantified in 5.5 min. The coefficients of variation (CVs) of the four analytes at the lower limit of quantification ranged from 7.9% to 14.6%, with the R2 values greater than 0.990 in the calibration curves. Of the 585 recruited pregnant women who ended up with spontaneous delivery, 17.1% and 82.9% of the subjects delivered within and after 7 days since plasma collection, respectively. In the receiver operator curve analysis, the gestational age-adjusted area under the curve of the combined measurements of E3-16-Gluc and 17-OHP was 0.69 (95% CI: 0.60–0.76), with the sensitivity of 87.0% (95% CI: 78.8%–92.9%) and specificity of 60.2% (95% CI: 55.7%–64.6%). Moreover, the positive and the negative predictive values were 28.3%–34.0% and 93.1%–97.4% respectively for this combined panel. We performed analytical and clinical validation of a quantitation LC-MS/MS panel for the four steroids in the plasma of pregnant women. The steroid metabolites panel of E3-16-Gluc and 17-OHP was potentially useful for predicting delivery within one week in asymptomatic women of singleton pregnancies. Key messagesA quantitative LC-MS/MS assay for determining the plasma levels of 17-OHP, THDOC, A-3,17-Diol and E3-16-Gluc was developed and validated, in order to evaluate their predictive performance in asymptomatic delivery of singleton pregnancy. The levels of E3-16-Gluc and 17-OHP were found to be significantly elevated at the time of sampling in women that delivered within one week and their combinational testing may be potentially useful in delivery prediction. A quantitative LC-MS/MS assay for determining the plasma levels of 17-OHP, THDOC, A-3,17-Diol and E3-16-Gluc was developed and validated, in order to evaluate their predictive performance in asymptomatic delivery of singleton pregnancy. The levels of E3-16-Gluc and 17-OHP were found to be significantly elevated at the time of sampling in women that delivered within one week and their combinational testing may be potentially useful in delivery prediction.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.237
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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