Ethnicity is a risk factor for permanent brachial plexus birth injury: A population study in Southern Finland
Bibliographic record
Abstract
Objective: To calculate the incidence and assess risk factors leading to permanent brachial plexus birth injury (BPBI) in Southern Finland Design: Retrospective population-based study Setting: Helsinki University Women’s Hospital and Helsinki University New Children’s Hospital, Finland Sample: All children born from 2006 to 2022 in Southern Finland with a permanent BPBI and their mothers Methods: Birth information of all mothers and their children born from 2006 to 2022 in Southern Finland were gathered from the national database and compared to prospectively collected data from mothers and their children with a permanent BPBI delivered within the same period. Permanent injury was defined as limited active or passive range of motion or decreased strength in the affected limb detected at one year of age. The severity of the injury was assessed using the 3-month Toronto test score. Main outcome measures: Permanent brachial plexus birth injury Results: Altogether, 298 428 children were born within the study period, of which 100 acquired a permanent BPBI. The incidence of a permanent BPBI was 0.4 per 1000 vaginal live births (0.34 all births), with a declining trend. Children born to immigrant mothers and women of Black ethnicity had a higher incidence of permanent injury (0.85 and 1.52 per 1000). Non-white background and immigrant status correlated with a more severe injury (β=-1.12 range, -2.17 to -0.07, p=0.004), with children to Black mothers having the least favorable outcome (β= -1.64 range, -2.79 to -0.49, p=0.005). Conclusion: The overall incidence of permanent BPBI is declining. Immigrant status and Black ethnicity increase the risk of a permanent BPBI.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".