Factors Associated With Emergency Department Discharge, Outcomes and Follow-Up Rates of Stable Patients With Lower Gastrointestinal Bleeding
Bibliographic record
Abstract
BACKGROUND: Lower gastrointestinal bleeding (LGIB) is a common reason for hospitalization. However, recent data suggest low-risk patients may be safely evaluated as an outpatient. Here, we compare stable LGIB patients discharged from the emergency department (ED) with those admitted, determine factors associated with discharge and 30-day outcomes, and evaluate follow-up rates amongst the discharged cohort. METHODS: A retrospective study of stable LGIB patients (heart rate < 100 beats/min, systolic blood pressure > 100 mm Hg and blood on rectal exam) who presented to the ED was conducted. Factors associated with discharge and rates of outpatient follow-up were determined in the discharged cohort. Therapeutic interventions and 30-day outcomes (including re-bleeding, re-admission and mortality rates) were compared between the admitted and discharged groups. RESULTS: Ninety-seven stable LGIB patients were reviewed, of whom 38% were discharged and characteristics associated with discharge included age (P < 0.001), lack of aspirin (P < 0.002) and anticoagulant (P < 0.004) use, higher index hemoglobin (P < 0.001) and albumin (P < 0.001), lower blood urea nitrogen (P < 0.001) and creatinine (P = 0.008), lower Oakland score (P < 0.001), lower Charlson Comorbidity Index (P < 0.001) and lack of transfusion requirements (P < 0.001). There was no statistical difference in 30-day re-bleeding, re-admission or mortality rates between admitted and discharged patients. Discharged patients had a 46% outpatient follow-up rate. CONCLUSIONS: While early discharge in low-risk LGIB patients appears to be safe and associated with a decrease in length of stay, further studies are needed to guide timely and appropriate outpatient evaluation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".