Consequences of brucellosis infection during pregnancy: A systematic review of the literature
Bibliographic record
Abstract
BACKGROUND: The aim was to establish the incidence of adverse outcomes with brucellosis infection during pregnancy. METHODS: Ovid Medline (1946-), Ovid Embase (1974-), and Web of Science (Clarivate Analytics) (1900-), the World Health Organization website and Google were searched September 27, 2017 for (i) outcomes with brucellosis diagnosed during pregnancy and (ii) studies with retrospective diagnosis of maternal brucellosis following adverse pregnancy outcomes. RESULTS: Sixty studies met inclusion criteria. In 65 pregnancies from 28 case reports and 9 small case series (<10 women), there were 20 spontaneous abortions (SAs) (31%), 2 intra-uterine fetal deaths (IUFDs) (3%) and 11 cases of congenital brucellosis (17%). In 14 larger case series there were 181 SAs in 679 pregnancies (27%), 19 IUFDs in 458 pregnancies (4%), and 44 preterm infants (12%) plus 6 infants with congenital brucellosis (2%) in 362 pregnancies. SA, IUFD and preterm delivery incidence were increased with meta-analysis of the 5 case series with controls. Nine studies described brucellosis seroprevalence with adverse pregnancy outcomes with no increased seroprevalence in the two studies with controls. CONCLUSIONS: Brucellosis almost certainly causes SA with increasing evidence that it also leads to IUFD and prematurity. Congenital brucellosis occurs in approximately 2% of infants exposed in-utero.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".