A Prospective Study on the Implications of a Base Deficit During Fluid Resuscitation
Bibliographic record
Abstract
An excessive base deficit (BD) and elevated serum lactate are increasingly recognized as important markers of a malperfusion state during the resuscitation of thermally injured patients. In a previous retrospective study, we found that patients with a BD less than -6 mmol/l during fluid resuscitation developed more severe systemic inflammatory response syndrome (SIRS), more frequent acute respiratory distress syndrome (ARDS), and more severe multiple organ dysfunction syndrome (MODS). The object of this study was to reexamine prospectively the relationship between the BD during fluid resuscitation and the subsequent development of SIRS, ARDS, and MODS by undertaking a prospective observational study of a cohort of consecutive burn patients. Analysis was completed on 38 patients with a mean age of 39 +/- 17 years and a mean %TBSA burn of 36 +/- 15%. The mean BD in the first 24 hours was less than -6 mmol/l in five patients (BD24 < -6 group), and was greater than -6 mmol/L in 33 patients (BD24 > -6 group). Patients in both groups were resuscitated to nearly identical endpoints of urinary output (1.2 ml/kg/hr in the BD24 < -6 group vs 1.3 ml/kg/hr in the BD24 > -6 group). Patients in the BD24 < -6 group had a trend toward a greater number of SIRS signs on the first postburn day, had a significantly higher incidence of ARDS (P =.02), and had significantly more severe MODS (P <.001) than patients in the BD24 > -6 group. The results concur with those of our previous retrospective study. Despite resuscitation to an acceptable urinary output, some burn patients develop a more extreme BD and go on to experience more severe organ dysfunction than do patients who do not generate a BD. The effect of specific correction of the BD during fluid resuscitation is not known at this time.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".