Bibliographic record
Abstract
Fluid therapy is perhaps the most common intervention received by acutely ill hospitalized patients; however, a number of critical questions on the efficacy and safety of the type and dose remain. In this review, recent insights derived from randomized trials in terms of fluid type, dose and toxicity are discussed. We contend that the prescription of fluid therapy is context-specific and that any fluid can be harmful if administered inappropriately. When contrasting ''crystalloid vs colloid'', differences in efficacy are modest but differences in safety are significant. Differences in chloride load and strong ion difference across solutions appear to be clinically important. Phases of fluid therapy in acutely ill patients are recognized, including acute resuscitation, maintaining homeostasis, and recovery phases. Quantitative toxicity (fluid overload) is associated with adverse outcomes and can be mitigated when fluid therapy based on functional hemodynamic parameters that predict volume responsiveness and minimization of non-essential fluid. Qualitative toxicity (fluid type), in particular for iatrogenic acute kidney injury and metabolic acidosis, remain a concern for synthetic colloids and isotonic saline, respectively. Physiologically balanced crystalloids may be the ''default'' fluid for acutely ill patients and the role for colloids, in particular hydroxyethyl starch, is increasingly unclear. We contend the prescription of fluid therapy is analogous to the prescription of any drug used in critically ill patients.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".