Predictive accuracy of prenatal ultrasound findings for lower urinary tract obstruction: A systematic review and Bayesian meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Lower urinary tract obstruction (LUTO) is a rare but critical fetal diagnosis. Different ultrasound markers have been reported with varying sensitivity and specificity. AIMS: The objective of this systematic review and meta-analysis was to identify the diagnostic accuracy of ultrasound markers for LUTO. MATERIALS AND METHODS: We performed a systematic literature review of studies reporting on fetuses with hydronephrosis or a prenatally suspected and/or postnatally confirmed diagnosis of LUTO. Bayesian bivariate random effects meta-analytic models were fitted, and we calculated posterior means and 95% credible intervals for the pooled diagnostic odds ratio (DOR). RESULTS: A total of 36,189 studies were identified; 636 studies were available for full text review and a total of 42 studies were included in the Bayesian meta-analysis. Among the ultrasound signs assessed, megacystis (DOR 49.15, [15.28, 177.44]), bilateral hydroureteronephrosis (DOR 41.33, [13.36,164.83]), bladder thickening (DOR 13.73, [1.23, 115.20]), bilateral hydronephrosis (DOR 8.36 [3.17, 21.91]), male sex (DOR 8.08 [3.05, 22.82]), oligo- or anhydramnios (DOR 7.75 [4.23, 14.46]), and urinoma (DOR 7.47 [1.14, 33.18]) were found to be predictive of LUTO (Table 1). The predictive sensitivities and specificities however are low and wide study heterogeneity existed. DISCUSSION: Classically, LUTO is suspected in the presence of prenatally detected megacystis with a dilated posterior urethra (i.e., the keyhole sign), and bilateral hydroureteronephrosis. However, keyhole sign has been found to have modest diagnostic performance in predicting the presence of LUTO in the literature which we confirmed in our analysis. The surprisingly low specificity may be influenced by several factors, including the degree of obstruction, and the diligence of the sonographer at searching for and documenting it during the scan. As a result, providers should consider this when establishing the differential for a fetus with hydronephrosis as the presence or absence of keyhole sign does not reliably rule in or rule out LUTO. CONCLUSIONS: Megacystis, bilateral hydroureteronephrosis and bladder wall thickening are the most accurate predictors of LUTO. Given the significant consequences of a missed LUTO diagnosis, clinicians providing counselling for prenatal hydronephrosis should maintain a low threshold for considering LUTO as part of the differential diagnosis.
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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 | 0.021 | 0.068 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.041 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".