Low Birth Weight Is a Risk Factor for Severe Retinopathy of Prematurity Depending on Gestational Age
Bibliographic record
Abstract
OBJECTIVE: To evaluate the impact of low birth weight as a risk factor for retinopathy of prematurity (ROP) that will require treatment in correlation with gestational age at birth (GA). STUDY DESIGN: In total, 2941 infants born <32 weeks GA were eligible from five cohorts of preterm infants previously collected for analysis in WINROP (Weight IGF-I Neonatal ROP) from the following locations: Sweden (EXPRESS) (n = 426), North America (n = 1772), Boston (n = 338), Lund (n = 52), and Gothenburg (n = 353). Data regarding GA at birth, birth weight (BW), gender, and need for ROP treatment were retrieved. Birth weight standard deviation scores (BWSDS) were calculated with Swedish as well as Canadian reference models. Small for gestational age (SGA) was defined as BWSDS less than -2.0 SDS using the Swedish reference and as BW below the 10th percentile using the Canadian reference charts. RESULTS: Univariate analysis showed that low GA (p<0.001), low BW (p<0.001), male gender (p<0.05), low BWSDSCanada (p<0.001), and SGACanada (p<0.01) were risk factors for ROP that will require treatment. In multivariable logistic regression analysis, low GA (p<0.0001), male gender (p<0.01 and p<0.05), and an interaction term of BWSDS*GA group (p<0.001), regardless of reference chart, were risk factors. Low BWSDS was less important as a risk factor in infants born at GA <26 weeks compared with infants born at GA ≥26 weeks calculated with both reference charts (BWSDSSweden, OR = 0.80 vs 0.56; and BWSDSCanada, OR = 0.72 vs 0.41). CONCLUSIONS: Low BWSDS as a risk factor for vision-threatening ROP is dependent on the infant's degree of immaturity. In more mature infants (GA ≥26 weeks), low BWSDS becomes a major risk factor for developing ROP that will require treatment. These results persist even when calculating BW deficit with different well-established approaches.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".