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Record W2124857923 · doi:10.1097/ta.0000000000000549

A comparison of prehospital lactate and systolic blood pressure for predicting the need for resuscitative care in trauma transported by ground

2015· article· en· W2124857923 on OpenAlexfundno aff
Francis X. Guyette, Eric N. Meier, Craig D. Newgard, Barbara McKnight, Mohamud Daya, Eileen M. Bulger, Judy Powell, Karen J. Brasel, Jeffery D. Kerby, Debra Egan, Michael J. Sise, Raúl Coimbra, Timothy C. Fabian, David B. Hoyt

Bibliographic record

VenueThe Journal of Trauma: Injury, Infection, and Critical Care · 2015
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchInstitute of Circulatory and Respiratory HealthUniversity of California, San DiegoNational Institutes of HealthUniversity of PittsburghUniversity of WashingtonAmerican Heart Association
KeywordsMedicineTrauma centerBlood pressureTriageEmergency medicineResuscitationMcNemar's testEmergency departmentEmergency medical servicesAnesthesiaSurgeryInternal medicineRetrospective cohort study

Abstract

fetched live from OpenAlex

BACKGROUND: Reliance on prehospital trauma triage guidelines misses patients with serious injury. Lactate is a biomarker capable of identifying high-risk trauma patients. Our objective was to compare prehospital point-of-care lactate (P-LAC) with systolic blood pressure (SBP) for predicting the need for resuscitative care (RC) in trauma patients transported by ground emergency medical services. METHODS: This is a prospective observational study at nine sites within the Resuscitation Outcomes Consortium conducted from March 2011 to August 2012. Lactate was measured on patients with a prehospital SBP of 100 mm Hg or less who were transported by emergency medical services to a Level I or II trauma center. Patients were followed up for the need for RC, defined as any of the following within 6 hours of emergency department arrival: blood transfusion of 5 U or greater; intervention for hemorrhage including thoracotomy, laparotomy, pelvic fixation, or interventional radiology embolization; or death. RESULTS: A total of 387 patients had a lactate value and presented with SBP between 71 mm Hg and 100 mm Hg, and 70 (18%) required RC. With the use of a P-LAC decision rule (≥2.5 mmol/L) that yielded the same specificity as that of SBP of 90 mm Hg or less (48%), the observed sensitivities for RC were 93% (95% confidence interval [CI], 84-98%) for P-LAC of 2.5 mmol/L or greater and 67% (95% CI, 55-78%) for SBP of 90 mm Hg or less (McNemar's test, p < 0.001). P-LAC has an estimated area under the curve of 0.78 (95% CI, 0.73-0.83), which is statistically superior to that of SBP (0.59; 95% CI, 0.53-0.66) and shock index (heart rate / SBP) (0.66; 95% CI, 0.60-0.74). CONCLUSION: P-LAC obtained at the scene is associated with the need for RC. P-LAC is superior to other early surrogates for hypoperfusion (SBP and shock index) in predicting the need for RC in trauma patients with 70 mm Hg < SBP ≤ 100 mm Hg. LEVEL OF EVIDENCE: Prognostic study, level II.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.037
GPT teacher head0.364
Teacher spread0.327 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations78
Published2015
Admission routes1
Has abstractyes

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