Evaluation and Management of Congenital Cytomegalovirus Infection
Bibliographic record
Abstract
The purpose of this review is to serve as an update on congenital cytomegalovirus (CMV) evaluation and management for obstetrician-gynecologists and to provide a framework for counseling birthing people at risk for or diagnosed with a primary CMV infection or reactivation or reinfection during pregnancy. A DNA virus, CMV is the most common congenital viral infection and the most common cause of nongenetic childhood hearing loss in the United States. The risk of congenital CMV infection from transplacental viral transfer depends on the gestational age at the time of maternal infection and whether the infection is primary or nonprimary. Although the risk of congenital CMV infection is lower with infection at earlier gestational ages, clinical sequelae are more severe with maternal infections earlier in gestation. At present, routine screening for maternal CMV infection is not recommended by U.S. guidelines. When maternal primary infection is confirmed in early pregnancy, emerging data support consideration of maternal antiviral therapy to prevent congenital CMV infection. When congenital CMV infection is confirmed, typically after an abnormal prenatal ultrasound result, there are more limited data on the utility of maternal antiviral therapy. Universal newborn screening for congenital CMV infection is not mandatory in most U.S. states at present. Newborns diagnosed with congenital CMV infection undergo an extensive evaluation to determine whether neurologic symptoms are present, which guides postnatal evaluation and management. In this review, we discuss the diagnosis and management of maternal CMV infection, the risk and diagnosis of congenital CMV infection, prevention and potential treatment of congenital CMV infection in utero, and neonatal congenital CMV infection diagnosis and management.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".