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Record W2775117242 · doi:10.1089/neu.2017.5472

Critical Thresholds of Intracranial Pressure-Derived Continuous Cerebrovascular Reactivity Indices for Outcome Prediction in Noncraniectomized Patients with Traumatic Brain Injury

2017· article· en· W2775117242 on OpenAlexaff
Frederick A. Zeiler, Joseph E. Donnelly, Peter Smielewski, David K. Menon, Peter J. Hutchinson, Marek Czosnyka

Bibliographic record

VenueJournal of Neurotrauma · 2017
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsUniversity of Manitoba
FundersNational Institute for Health and Care Research
KeywordsTraumatic brain injuryMedicineLogistic regressionIntracranial pressureUnivariate analysisCerebral perfusion pressureReceiver operating characteristicGlasgow Outcome ScaleInternal medicineAnesthesiaCardiologyGlasgow Coma ScalePerfusionMultivariate analysis

Abstract

fetched live from OpenAlex

The aim of the study was to compare intracranial pressure (ICP)-derived cerebrovascular reactivity indices in their ability to predict six-month outcome, and to determine/compare critical thresholds related to outcome for each index in adult noncraniectomized traumatic brain injury (TBI). Using a retrospective cohort of nondecompressive craniectomy (non-DC) patients with TBI, we performed univariate and multi-variate binary logistic regression outcome analysis of: pressure reactivity index (PRx), pulse amplitude index (PAx), and a newly described index (RAC) calculated as the regression coefficient between ICP waveform amplitude and cerebral perfusion pressure (CPP). Finally, we performed sequential chi-square threshold analysis for each index as it related to six-month binary outcomes. Outcome was assessed via dichotomized Glasgow Outcome Scores (GOS): (A) favorable (GOS 4 or 5) versus unfavorable (GOS 3 or less), (B) alive versus dead. There were 358 non-DC patients with TBI included in all aspects of the analysis. In an analysis of the entire recording period for all patients using univariate binary logistic regression, the areas under the curves (AUCs) for favorable versus unfavorable outcome were: PRx (0.573, p < 0.0001), PAx (0.606, p < 0.0001), and RAC (0.655, p < 0.0001). Similarly, the AUCs for alive versus dead outcome were: PRx (0.651, p < 0.0001), PAx (0.705, p < 0.0001), and RAC (0.722, p < 0.0001). RAC displayed superior AUC statistics compared with PRx and PAx, using both univariate and multi-variate regression. RAC displayed more stable critical thresholds related to six-month outcomes. Thresholds for both favorable versus unfavorable and alive versus dead outcomes for PRx, PAx, and RAC across the entire recording period were: +0.35 and +0.35, 0 and +0.25, -0.10 and -0.05, respectively. In non-DC patients with TBI, RAC appears to be superior to PRx and PAx in six-month outcome prediction, using both univariate and multi-variate logistic regression. Further, RAC displayed more stable critical thresholds associated with binary outcomes at six months. Further analysis of RAC in TBI is required.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.032
Threshold uncertainty score0.868

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.046
GPT teacher head0.334
Teacher spread0.288 · 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 teacher head, 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

Citations112
Published2017
Admission routes1
Has abstractyes

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