Changes in retinal flow density during and after pregnancy—an optical coherence tomography angiography study
Bibliographic record
Abstract
OBJECTIVE: Employing optical coherence tomography angiography (OCTA), recent research has uncovered retinal vascular changes in pregnant women compared to nonpregnant controls. Yet, longitudinal data on retinal OCTA metrics until childbirth are lacking in the current literature, and an understanding of a possible reversibility of these changes remains limited. This prospective study aims to quantify retinal capillary metrics in healthy pregnant women prenatally and postnatally, describing the natural evolution of OCTA metrics during and after pregnancy. METHODS: OCTA measurements were performed repeatedly on 52 eyes of 26 healthy, pregnant women, assessing the superficial (SCP), deep (DCP), choriocapillary (CC), and radial peripapillary (RPC) capillary plexus at various intervals during pregnancy and after childbirth. Flow density (FD) within these layers and parameters of the foveal avascular zone (FAZ) were compared throughout pregnancy and in the postpartum period using linear mixed models. RESULTS: 52 eyes of 26 pregnant women were included in the study. Although layer-specific variations in FD throughout the prepartum phase were noted, these changes were statistically insignificant for all investigated capillary plexus and the FAZ (p > 0.05). FD of the DCP, CC and RPC capillary plexus was significantly lower after childbirth in comparison to the prepartum phase (p ≤ 0.04). CONCLUSIONS: The microvascular structure remains stable throughout healthy pregnancies; however, postpartum changes hint toward late vasculo-structural adaptations after childbirth. OCTA can be used to noninvasively to assess microvascular changes associated with pregnancy.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".