Accuracy of Spleen Measurement by Medical Residents Using Hand‐Carried Ultrasound
Bibliographic record
Abstract
OBJECTIVES: Easily palpable splenomegaly can be identified on physical examination, but it is difficult to detect lesser degrees of splenomegaly. Rapid bedside assessment can be conducted with hand-carried ultrasound. We performed this study to determine whether medical residents could reliably assess spleen size using hand-carried ultrasound after a brief educational intervention. METHODS: Postgraduate year 1 internal medicine residents were shown a brief (45-minute) presentation on ultrasound basics, the use of hand-carried ultrasound, and principles of splenic ultrasound imaging. They practiced on each other, using hand-carried ultrasound to assess spleen size, for 1 hour in the presence of an instructor. Patients with varying degrees of splenomegaly and hospital staff were recruited at Vancouver General Hospital. A sonographer measured spleen size in each participant using conventional ultrasound. Subsequently, the trained residents scanned the participants using hand-carried ultrasound, blinded to the sonographer's measurements and the participants' diagnoses. The instructor was not present during scanning. RESULTS: Twelve first-year residents (8 male and 4 female; mean age ± SEM, 28 ± 1 years; all with limited prior ultrasound training) and 19 patients and staff members (10 male and 9 female; mean age, 60 ± 4 years; body mass index, 24 ± 2 kg/m(2)) were recruited. The greatest longitudinal measurements were 14.0 ± 0.7 cm with conventional ultrasound administered by the sonographer and 13.2 ± 0.9 cm with hand-carried ultrasound administered by the residents (P > .05, not significant). The correlation between conventional and hand-carried ultrasound was r = 0.81 (P < .001). CONCLUSIONS: Internal medicine residents can reliably assess spleen size at the point of care using hand-carried ultrasound with minimal training. Our findings, if replicated in other centers and in different clinical scenarios, may change the way that clinicians examine the spleen.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".