Resolution patterns and duration of retinal haemorrhages measured by two-dimensional retinal area pixel counts from sequential retinal imaging in childhood encephalopathies: a morphometric study
Bibliographic record
Abstract
OBJECTIVE: To determine the time to resolution of different-layered retinal haemorrhages (RHs), and to describe the main patterns of their resolution in a group of children with encephalopathies. METHODS AND ANALYSIS: From a prospective study of 114 children with traumatic and non-traumatic encephalopathies, 429 selected individual RHs (iRHs) from 18 children were serially imaged from admission using a RetCam. Photoshop and Scion Imaging software allowed calculation of RH area in pixels. RESULTS: Two patterns of the resolution were recognised on the basis of area measurements: a progressive decrease (pattern A, 60% of iRHs), and a form of asymmetrical decay in which iRHs first increased in size before then progressively decreasing (pattern B, 35% of iRHs). Within the pattern A group, the Kaplan-Meier median survival time (MST) (95% CI) was 10 (9.3 to 10.7) days for intra-RHs (IRHs) and 38 (10.8 to 65.2) days for pre-RHs (PRHs), log rank (Mantel-Cox) p=0.001. The mean percentage reduction in area per day was 12.5% for all iRHs, 14.5% for IRHs and 6.3% for PRHs. CONCLUSION: Serial area measurements of iRHs revealed that 35% haemorrhages became temporarily larger before decreasing to resolution. Serially imaged selected RHs showed a longer MST for PRHs than for IRHs.
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 | 0.002 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".