MP08-03 PREDICTING URETERIC STONE EXPULSION WITH PATIENT REPORTED OUTCOMES: A PROSPECTIVE OBSERVATIONAL STUDY
Bibliographic record
Abstract
These results are consistent with EAU guidelines that US should be the first imaging modality for nephrolithiasis.We sought to determine the potential reduction in radiation exposure for an US-first approach using population-based diagnostic imaging patterns in the ED.METHODS: We performed a cross-sectional study of adults who presented to 70 emergency departments in South Carolina between 1996 and 2017 using all payer hospital claims data.All ED encounters within a 6 month "episode" following the initial ED visit were identified, along with ultrasound and CT ordered at the visits.Patterns of US and CT during the first two consecutive ER visits were determined at the patient-and hospital-level.Imaging patterns in which only a CT was performed were classified as an "opportunity for reduction in CT 00 .RESULTS: From 1996 to 2017, 180,845 patients had 233,242 unique stone episodes involving at least 1 ED visit and 282,845 ED encounters.A CT was obtained in 72.8% of all ED encounters as compared to 3.5% with US.The median number of CTs obtained within a 6 month episode after the initial ED visit was 1 (IQR 0,1; range 1-13).The highest cumulative number of CTs was 80 for a single patient over the 18 year period.CT was obtained without US in 94.8% of all episodes during which an US and/or CT was obtained.Of those episodes that involved at least two consecutive ED visits, 79.1% represented an opportunity for reduction in CT use [Figure 1].Twenty-eight percent of patients presented to different EDs for the initial and subsequent visits; CT utilization patterns between those who presented to the same ED and different EDs were similar (90% vs. 93.9%).There was an inverse relationship between hospital volume and CT utilization, which was clinically unimportant.CONCLUSIONS: The vast majority of ED encounters include CT alone.CT utilization was similar for repeat ED visits at the same and different hospitals.A US-first approach offers substantial potential for radiation reduction during ED visits for nephrolithiasis.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".