The role of infection in miscarriage
Bibliographic record
Abstract
BACKGROUND: Miscarriage is the spontaneous loss of a pregnancy before 12 weeks (early miscarriage) or from 12 to 24 weeks (late miscarriage) of gestation. Miscarriage occurs in one in five pregnancies and can have considerable physiological and psychological implications for the patient. It is also associated with significant health care costs. There is evidence that potentially preventable infections may account for up to 15% of early miscarriages and up to 66% of late miscarriages. However, the provision of associated screening and management algorithms is inconsistent for newly pregnant women. Here, we review recent population-based studies on infections that have been shown to be associated with miscarriage. METHODS: Our aim was to examine where the current scientific focus lies with regards to the role of infection in miscarriage. Papers dating from June 2009 with key words 'miscarriage' and 'infection' or 'infections' were identified in PubMed (292 and 327 papers, respectively, on 2 June 2014). Relevant human studies (meta-analyses, case-control studies, cohort studies or case series) were included. Single case reports were excluded. The studies were scored based on the Newcastle - Ottawa Quality Assessment Scale. RESULTS: The association of systemic infections with malaria, brucellosis, cytomegalovirus and human immunodeficiency virus, dengue fever, influenza virus and of vaginal infection with bacterial vaginosis, with increased risk of miscarriage has been demonstrated. Q fever, adeno-associated virus, Bocavirus, Hepatitis C and Mycoplasma genitalium infections do not appear to affect pregnancy outcome. The effects of Chlamydia trachomatis, Toxoplasma gondii, human papillomavirus, herpes simplex virus, parvovirus B19, Hepatitis B and polyomavirus BK infections remain controversial, as some studies indicate increased miscarriage risk and others show no increased risk. The latest data on rubella and syphilis indicate increased antenatal screening worldwide and a decrease in the frequency of their reported associations with pregnancy failure. Though various pathogens have been associated with miscarriage, the mechanism(s) of infection-induced miscarriage are not yet fully elucidated. CONCLUSIONS: Further research is required to clarify whether certain infections do increase miscarriage risk and whether screening of newly pregnant women for treatable infections would improve reproductive outcomes.
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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 | 0.009 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".