Estimation of Spleen Size With Hand‐Carried Ultrasound
Bibliographic record
Abstract
OBJECTIVES: Physical examination can identify palpable splenomegaly easily, but evaluating lesser degrees of splenomegaly is problematic. Hand-carried ultrasound allows rapid bedside assessment of patients. We conducted this study to determine whether hand-carried ultrasound can reliably assess spleen size. METHODS: Patients with varying degrees of splenomegaly were studied. Two sonographers blindly measured spleen size in each patient using either a hand-carried or conventional ultrasound device in random order. Sonographers completed a data sheet indicating the adequacy of the image, clinical measurements of enlargement, and confidence in their observations. RESULTS: Sixteen patients (10 male and 6 female; mean age ± SEM, 60 ± 4 years) were recruited. Image quality was adequate or better in all scans with conventional ultrasound and in 15 of 16 scans with hand-carried ultrasound. The greatest longitudinal measurement recorded was statistically equivalent across ultrasound techniques, with mean values of 16.4 cm (95% confidence interval, 14.8-18.0 cm) for conventional ultrasound and 15.8 cm (95% confidence interval, 14.1-17.4 cm) for hand-carried ultrasound. The correlation between measurement techniques was r = 0.89 (P < .0001). Sonographers were somewhat or very confident in the outcomes of all scans with conventional ultrasound and in 15 of 16 cases with hand-carried ultrasound. In general, it took longer for sonographers to obtain images with hand-carried ultrasound. CONCLUSIONS: We have shown that hand-carried ultrasound can be used at the point of care by trained individuals to diagnose splenomegaly. However, hand-carried ultrasound images were less likely to be judged excellent, were accompanied by less diagnostic certainty, and took longer to obtain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".