Classifying neonatal growth outcomes: use of birth weight, placental evaluation and individualized growth assessment
Bibliographic record
Abstract
OBJECTIVE: To compare neonatal growth outcomes determined by birth weight (BW), placental assessment (Plac Assess) and individualized growth assessment (IGA). METHODS: This retrospective analysis was carried out in 45 selected pregnancies at risk for fetal growth restriction. Serial fetal biometry was carried out in the 2nd and 3rd trimester. First and second trimester placental biomarkers, 2nd trimester uterine artery (Ut A) velocimetry and postnatal placental pathology were evaluated as indicators of placental insufficiency. At delivery, weight (WT), head circumference (HC) and crown-heel length (CHL) were measured. BWs were categorized as large-for-gestational-age (LGA), appropriate-for-gestational-age (AGA) and small-for-gestational age (SGA) (<10th, 10th-90th and >90th percentiles). In these categories, neonatal growth outcomes were classified as growth restricted (GR), normal (NORMAL) or macrosomic (MACRO) based on BW plus Plac Assess (Ut A velocimetry, biomarkers, pathology) or IGA [growth potential realization index profile (WT, HC and CHL)]. RESULTS: There were 6 LGA, 14 AGA and 25 SGA neonates in this sample. All 14 AGA neonates were considered NORMAL by both IGA and BW + Plac Assess. All six LGA neonates were classified as MACRO by BW + Plac Assess but only four by IGA (the remaining two were NORMAL and high NORMAL). The 25 SGA cases could be divided into five subgroups based on IGA and BW + Plac Assess. The largest subgroup (56%) was GR and the next largest (24%) was NORMAL by both classification methods. In the remaining 20%, there was some evidence of GR but IGA and BW + Plac Assess were not in complete agreement. CONCLUSIONS: Agreement was good for all three methods in the LGA and AGA groups. The SGA group was heterogeneous but agreement between IGA and BW + Plac Assess was 89%. These results, using more sophisticated growth assessment methods, confirm placental insufficiency as a primary cause of growth restriction. Most normal and GR SGA neonates can be identified with conventional anatomical measurements if IGA is used.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".