Intrauterine Pregnancy Detection and Gestational Age Assessment During Early Pregnancy by a Handheld Point-Of-Care Ultrasound Device Compared to a High-End Ultrasound System. An Accuracy and Reliability Study
Bibliographic record
Abstract
Objective: The main objective of this study is the evaluation of the accuracy and reliability of a handheld point of care ultrasound device (POCUS-hd) for intrauterine pregnancy (IUP) detection compared to comprehensive reference transabdominal ultrasound (TU). The secondary objectives were to evaluate POCUS-hd for intrauterine pregnancy (IUP) detection compared to transabdominal and transvaginal ultrasound (TUTV), evaluate the inter-device agreement and inter-rater reliability of gestational age during early pregnancy. Methods: It is an observational transverse study with consecutive patient recruitment. Two blinded operators systematically used POCUS-hd and reference transabdominal ultrasound for IUP diagnosis. The accuracy of POCUS-hd for IUP diagnosis was expressed as sensitivity, specificity, negative predictive value (NPV) and positive predictive value (PPV). The gestational age (GA) was assessed based on the crown-rump length. The reliability and agreement of gestational age evaluation were assessed by Bland-Altman plots, kappa statistic, and intraclass correlation coefficients (ICC). Results: POCUS-hd compared to TU had a sensitivity of 95-100%, a specifcity of 90-100%, PPV of 95-100% and NPV of 90-100%. Inter-rater agreement for IUP detection using POCUS-hd was very good, kappa=1.0; CI95% [0.9-1.0]. The inter-device agreement limits (mean difference ± 2SD) for GA were: -3 to +2.3 days by Operator 1, -3.4 to +3.3 days by Operator 2 for POCUS-hd vs. TU and -3.1 to +2.3 days for POCUS-hd versus TUTV. Conclusion: This handheld POCUS device is an accurate and reliable diagnostic tool that can be used for IUP positive findings and GA assessment during early pregnancy by clinicians in family planning settings or general practice.
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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 | 0.010 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".