Frusemide Administration in Critically Ill Patients by Continuous Compared to Bolus Therapy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Frusemide is frequently administered to critically ill patients in the intensive care unit (ICU). We investigated whether continuous frusemide infusion therapy was more effective than regular intermittent bolus doses at causing diuresis. METHODS: 59 adult patients with fluid overload admitted to two tertiary multidisciplinary ICUs were randomised to either a continuous frusemide infusion or regular intermittent intravenous boluses of frusemide according to pre-defined algorithms aiming for a minimum hourly urine output. RESULTS: There was no significant difference in diuretic response between the two groups during the first 24 h (5.3 liters in the bolus group vs. 5.4 liters in the infusion group). In the bolus group a significantly higher dose of frusemide was needed to achieve target diuresis (24.1 vs. 9.2 mg/h in the infusion group, p = 0.0002). Mean urine output per dose of frusemide was significantly higher in the infusion group (31.6 vs. 18 ml/mg in the bolus group, p = 0.014). At the end of the study, there were no differences in hospital mortality, number of patients requiring ventilatory support, change in serum creatinine or change in estimated glomerular filtration rate. CONCLUSIONS: Both intermittent boluses and continuous infusion of frusemide were successful in achieving algorithm-driven diuresis. However, continuous infusion therapy was more effective than intermittent boluses since the dose of frusemide required was significantly less.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.080 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it