MétaCan
Menu
Back to cohort
Record W2861861479 · doi:10.1089/neu.2017.5603

Validation of Pressure Reactivity and Pulse Amplitude Indices against the Lower Limit of Autoregulation, Part I: Experimental Intracranial Hypertension

2018· article· en· W2861861479 on OpenAlexafffund
Frederick A. Zeiler, Joseph E. Donnelly, Leanne Calviello, Jennifer K. Lee, Peter Smielewski, Ken M. Brady, Dong‐Joo Kim, Marek Czosnyka

Bibliographic record

VenueJournal of Neurotrauma · 2018
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsUniversity of Manitoba
FundersNational Institute of Neurological Disorders and StrokeCambridge Commonwealth TrustKorea Health Industry Development InstituteUniversity of Manitoba
KeywordsAutoregulationCerebral autoregulationCerebral blood flowCerebral perfusion pressureTranscranial DopplerIntracranial pressureCardiologyInternal medicineMedicineMean arterial pressureLaser Doppler velocimetryCorrelationHemodynamicsAnesthesiaBlood pressureBlood flowMathematicsHeart rate

Abstract

fetched live from OpenAlex

The purpose of this study was to provide validation of intracranial pressure (ICP) derived continuous indices of cerebrovascular reactivity against the lower limit of autoregulation (LLA). Utilizing an intracranial hypertension model within white New Zealand rabbits, ICP, transcranial Doppler (TCD), laser Doppler flowmetry (LDF), and arterial blood pressure were recorded. Data were retrospectively analyzed in a cohort of 12 rabbits with adequate signals for interrogating the LLA. We derived continuous indices of cerebrovascular reactivity: PRx (correlation between ICP and mean arterial pressure [MAP]), PAx (correlation between pulse amplitude of ICP [AMP] and MAP), and Lx (correlation between LDF-based cerebral blood flow [CBF] and cerebral perfusion pressure [CPP]). LLA was derived via piecewise linear regression of CPP versus LDF or CPP versus systolic flow velocity (FVs) plots. We then produced error bar plots for PRx, PAx, and Lx against 2.5 mm Hg bins of CPP, to display the relationship between these indices and the LLA. We compared the CPP values at clinically relevant thresholds of PRx and PAx, to the CPP defined at the LLA. Receiver operating curve (ROC) analysis was performed for each index across the LLA using 2.5 mm Hg bins for CPP. The mean LLA was 51.5 ± 8.2 mm Hg. PRx and PAx error bar plots demonstrate that each index correlates with the LLA, becoming progressively more positive below the LLA. Similarly, CPP values at clinically relevant thresholds of PRx and PAx were not statistically different from the CPP derived at the LLA. Finally, ROC analysis indicated that PRx and PAx predicted the LAA, with areas under the curve (AUCs) of 0.795 (95% confidence interval [CI]: 0.731-0.857, p < 0.0001) and 0.703 (95% CI: 0.631-0.775, p < 0.0001), respectively. Both PRx and PAx generally agree with LLA within this experimental model of intracranial hypertension. Further analysis of clinically used indices of autoregulation across the LLA within pure arterial hypotension models 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 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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.053
GPT teacher head0.297
Teacher spread0.244 · 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 designBench or experimental
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

Citations69
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueJournal of NeurotraumaSame topicTraumatic Brain Injury and Neurovascular DisturbancesFrench-language works237,207