Intravenous Albumin in Patients With Cirrhosis: Evaluation of Practice Patterns and Secular Trends of Usage in Ontario 2000 to 2017
Bibliographic record
Abstract
BACKGROUND: Intravenous (IV) albumin has evidence-based indications in cirrhosis that are limited in most guidelines to spontaneous bacterial peritonitis (SBP), type 1 hepatorenal syndrome (HRS) and large volume paracentesis (LVP).This study aimed to describe the trends of IV albumin usage in patients with cirrhosis at the population level and evaluate indications for IV albumin in the hospital setting. METHODS: A retrospective study identified albumin infusions in health care data from Ontario, Canada between 2000 and 2017 in those with and without cirrhosis. Annual rates of IV albumin by cirrhosis status were calculated per 10,000 person-years (PY) and described using Poisson regression and rate ratios. Secondly, patients with cirrhosis receiving IV albumin while hospitalized at Kingston Health Sciences Centre (KHSC) in 2017 were identified and underwent detailed chart abstraction to determine the reason for IV albumin administration. RESULTS: <0.001). The majority of albumin was used during hospitalization (88%) and 22% was used in patients with cirrhosis. At KHSC, there were134 admissions where a patient with cirrhosis received IV albumin. Of these, 49% of prescriptions were for evidence-based indications (LVP 30%, type 1 HRS 10%, SBP 10%), whereas other indications included non-HRS renal failure, hypovolemia and sepsis. CONCLUSION: IV albumin use has doubled over two decades and is frequently used in hospitalized patients with cirrhosis with only 50% being prescribed for evidence-based indications. These results highlight the impact of cirrhosis on albumin use and highlight potential quality improvement opportunities.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".