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Abstract 13835: Accuracy of Prehospital Documentation of Hypoxia Compared to Continuous Non-Invasive Monitor Data Tracking in Major Traumatic Brain Injury

2016· article· en· W2890251960 on OpenAlexaff
Octavio Perez, Daniel W. Spaite, Eric Helfenbein, Bruce Barnhart, Saeed Babaeizadeh, Chengcheng Hu, Vatsal Chikani, Joshua B. Gaither, Kurt R. Denninghoff, Samuel M. Keim, Chad Viscusi, Duane L. Sherrill, Bentley J. Bobrow

Bibliographic record

VenueCirculation · 2016
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsBentley (Canada)
Fundersnot available
KeywordsMedicineHypoxia (environmental)Traumatic brain injuryDocumentationIntensive care medicineEmergency medicineMedical emergencyPsychiatry

Abstract

fetched live from OpenAlex

Background: It is well established that prehospital hypoxia dramatically increases mortality in Traumatic Brain Injury (TBI). Thus, in EMS TBI research, case ascertainment and risk-adjustment are highly dependent upon documentation of in-field O 2 saturation. Objective: To compare the rate of hypoxia identified by EMS personnel and documented in EMS patient care records (PCR) vs the actual rate of hypoxia recorded by continuous, non-invasive monitor in TBI. Methods: A subset of major TBI cases (moderate/severe) in the EPIC EMS TBI Study (NIH 1R01NS071049) were evaluated (3/30/13-6/26/15). Cases from 4 EMS agencies that report continuous monitor data (Philips MRx™) as part of EPIC were included. All monitor data available for post-hoc review were displayed and accessible to the providers during EMS care. We compared PCR documentation of hypoxia (O 2 sat <90%) to actual recorded monitor data on each patient (Fisher’s Exact Test; α=0.05). Results: 77 cases were included [median age: 52; 65% male]. The monitors displayed and recorded 16 hypoxic cases (20.8%), but only 6 (37.5%) were documented. Thus, while the rate of actual hypoxia was 20.8%, the case ascertainment was only 7.8% (6/77) when PCR documentation alone was used (p=0.036). Conclusion: Among patients with major TBI, monitor-identified hypoxia occurred much more frequently (20.8%) than was documented (7.8%). Only 37.5% of cases with actual hypoxia were recorded in the PCRs. This may be explained, in part, by the fact that pulse oximetry occurs continuously. Thus, ongoing care responsibilities and scene distractions may cause providers to miss low readings as they fluctuate moment-by-moment. This has significant clinical implications as a potential hidden contributor to poor outcomes if hypoxia goes unrecognized (and untreated) rather than simply not being documented. Furthermore, these findings have important implications for case ascertainment, confounding, and risk-adjustment in EMS TBI studies. Whenever possible, quality improvement and research projects should utilize continuous non-invasive monitor data to identify and evaluate hypoxic patients in the setting of TBI. These findings may also have implications for identifying hypoxia in EMS patients with other critical conditions.

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)0.007
metaresearch head score (Gemma)0.042
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 score0.007
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.042
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.049
GPT teacher head0.334
Teacher spread0.284 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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