VP45.12: A cross‐sectional evaluation of fetal ultrasound utilisation and acuity during the COVID‐19 pandemic
Bibliographic record
Abstract
To evaluate the impact of the COVID-19 pandemic on fetal assessment utilisation and acuity of cases seen. This is a cross-sectional study comparing temporal trends in fetal assessment unit volumes and acuity at a single, tertiary-care centre. All fetal assessment scans performed during the first ‘wave’ of the pandemic (March to May 2020) were compared to scans from the same time last year (March to May 2019). Clinic lists and stored ultrasound reports were reviewed to collate maternal demographics and medical history, referral patterns, number of scans, ultrasound findings, and level of acuity, in order to compare outcomes between time periods. There were 5811 scans performed during the study period, and an overall reduction in the number of fetal assessment scans performed during the first wave of the COVID pandemic compared to last year. The most dramatic decline was seen in the number of scans performed for first-trimester complications (0.9% vs 0.2%; p < 0.001) and genetic ultrasounds including amniocentesis (2.5% vs 1.7%; p < 0.05). Interestingly, there was in increase in the relative proportion of nuchal translucency scans performed between the 2 periods (10.8% vs 13.7%; p < 0.001). The causes of these changes in volumes and acuity were attributable to changes in referral practices (including modified prenatal visit schedules), changes to timing of follow-up scans, and patient preferences. There was also a significant increase in the acuity of cases seen during the pandemic, with several referrals requiring emergency delivery or urgent hospital admission due to fetal and/or maternal complications (p < 0.05). There was a decrease in fetal assessment utilisation during the first wave of the pandemic combined with an overall increase in the level of acuity of cases seen, which appears multi-factorial in nature. An enhanced awareness of changes in fetal ultrasound volumes and the relationship with adverse outcomes will be essential in planning obstetrical care for the next wave of the pandemic.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".