A44 IS BLOOD UREA NITROGEN AN INDEPENDENT PREDICTOR OF POSITIVE ENDOSCOPIC FINDINGS IN PRESUMED UPPER GI BLEEDING?
Bibliographic record
Abstract
Several prognostic scales have been developed for use in upper gastrointestinal bleeding (UGIB), including the Glasgow-Blatchford score, which uses blood urea nitrogen (BUN) as one of eight prognostic variables. However, the test characteristics of BUN in the identification of UGIB or high-risk endoscopic lesions have not been clearly determined. This study aimed to evaluate if BUN independently predicts the presence of positive endoscopic findings in cases of presumed UGIB and determine a threshold urea level above which it is more likely to identify a source of UGIB on endoscopy. A crude odds ratio was calculated for odds of bleeding being identified on upper endoscopy based on thresholds of urea>=5, 7.5, 10, 12.5 and 15, compared to values lower than these. Adjusted odds ratios were then calculated using logistic regression to account for the factors that were determined a priori. Covariates included in the model were age, sex, hemoglobin, presence of melena, presence of hematemesis, admission in ICU, and use of ASA, warfarin, clopidogrel, or NSAIDS. The odds of identifying UGIB at endoscopy for patients with a urea >=10 was 3.73 (95% CI: 1.90–7.31) times higher than for patients with urea < 10. Variables that were significantly associated with identifying source of bleeding at upper GI endoscopy included male gender and symptoms of melena or hematemesis, after adjusting for the impact of other covariates. BUN >20 is predictive of UGIB in the following settings: normal renal function (spec 98%, PPV 0.86), melena (spec 81%, PPV 0.8), NSAID+anticoagulation/ASA use (spec 85%, PPV 0.8), and cirrhotic patients (spec 100%, PPV 1.0). BUN >20 is also predictive of positive EGD findings (spec 87%, PPV 0.8) and high risk lesions (spec 81%, NPP 0.83). A BUN level >20 had 82% specificity for high risk endoscopic lesion requiring intervention, but lower BUN levels were not able to predict EGD intervention. BUN >15 is predictive of UGIB in hematemesis (spec 95%, PPV 0.95) or NSAID users (spec 100%, PPV 1.0). BUN levels >20 had a specificity of 87% for UGIB but poor sensitivity (23%), in contrast to the Glasgow-Blatchford score which is highly sensitive (>90%) but poorly specific (<20%). Overall, the results of this study provide new clinically relevant information regarding the operating characteristics of BUN for UGIB. In males, patients with normal renal function, cirrhosis, NSAID/ASA/AC users, or symptoms of melena and hematemesis, a high BUN level is predictive of positive endoscopic findings in presumed UGIB. A BUN level >20 predicts the need for endoscopic intervention but levels below 20 do not correlate well with the need for endoscopic intervention. BUN level alone is more specific for UGIB when compared to the Glasgow-Blatchford score, which has a higher sensitivity. None
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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 | 0.010 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".