Maternal and Neonatal Outcomes in 89 Patients with Takayasu Arteritis (TA): Comparison Before and After the TA Diagnosis
Bibliographic record
Abstract
OBJECTIVE: To evaluate maternal and neonatal outcomes in patients before and after a diagnosis of Takayasu arteritis (TA). METHODS: Patients diagnosed with TA according to the American College of Rheumatology criteria were selected from the Vasculitis Outpatient Clinic of the Rheumatology Division. Healthy female staff members of this hospital of similar age and educational level were selected as the controls. The disease data were obtained from an ongoing electronic database protocol. A standardized questionnaire, emphasizing gestational history, was applied to both groups. The prevalence of fetomaternal complications and disease variables were evaluated between the groups and a statistical analysis was performed. RESULTS: A total of 89 patients with TA (156 pregnancies) and 89 healthy controls (181 pregnancies) were evaluated. There were 75.6% pregnancies that occurred before the TA diagnosis (pre-TA group) and 24.3% after (post-TA group). In the pre-TA group, higher rates of hypertension (HTN; 27.1% vs 3.9%, p < 0.001), low birth weight (16.8% vs 6.5%, p = 0.012), and perinatal mortality (7.9% vs 0.7%, p = 0.003) were observed compared with healthy controls. The frequency of abortions and the average number of children were similar in both groups (p > 0.05). Further comparison of the pre- and post-TA groups revealed similar rates of HTN, abortion, and low birth weight, and higher rates of Cesarean delivery (p = 0.002), prematurity (p < 0.001), and infection (p = 0.045) in the latter group. CONCLUSION: Our study identified that patients with TA, even before the disease diagnosis, have a worse fetal outcome that is most likely associated with high rates of HTN. TA was identified as an additional differential diagnosis for HTN in pregnancy.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".