UTILITY OF PRE-HOSPITAL LACTATE MEASUREMENT FOR TRAUMA PATIENTS: A SYSTEMATIC REVIEW
Bibliographic record
Abstract
Background Serum lactate serves as a surrogate marker for tissue hypoxia following traumatic injury, and may be used to guide resuscitation. The portable, lightweight nature of handheld point-of-care monitoring devices enables lactate values to be readily available in the pre-hospital environment, whether in land or air based evacuation modalities. The current review evaluates the utility of pre-hospital lactate measurement in the management of trauma patients. Methods The published literature up to 06 August 2015 was searched using Medline and EMBASE using pre-defined criteria (English language, pre-hospital lactate measurement, trauma patients; excluding non-trauma/mixed patient groups). The Newcastle-Ottawa Scale was used to assess risk of bias of individual studies. Results Of 857 non-duplicate articles of interest, 5 articles met the inclusion criteria, and included four cohort studies and one cross-sectional study. There were 2049 patients included in all studies. Key findings ▸ Pre-hospital lactate may be an independent prognostic marker of in-hospital mortality, multiple organ dysfunction, and requirement for transfusion or surgical intervention in trauma patients, particularly in blunt trauma. ▸ Pre-hospital lactate measurement may be more sensitive than systolic blood pressure in determining need for resuscitative care. ▸ Early lactate measurement may be particularly useful in the detection of occult hypotension, with elevated levels detectable within 30 minutes of injury. ▸ All current studies that investigate pre-hospital lactate were assessed as being at risk of bias. Conclusions There is a paucity of evidence relating to pre-hospital lactate-guided management in trauma. From the limited literature, it seems that pre-hospital lactate may be a useful early tool in guiding the management of trauma patient resuscitation. Further prospective studies are required to elucidate the sensitivity and specificity of abnormal pre-hospital lactate values.
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How this classification was reachedexpand
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| 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) | 0.010 | 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 teacher head, 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".