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Record W4225656439 · doi:10.1186/s13054-022-03978-2

Transcranial Doppler as a screening test to exclude intracranial hypertension in brain-injured patients: the IMPRESSIT-2 prospective multicenter international study

2022· article· en· W4225656439 on OpenAlexaff
Frank Rasulo, Stefano Calza, Chiara Robba, Fabio Silvio Taccone, Daniele Guerino Biasucci, Rafael Badenes, Simone Piva, Davide Savo, Giuseppe Citerio, Jamil Dibu, Francesco Lo Curto, Martina Merciadri, Paolo Gritti, Paola Fassini, Soojin Park, Massimo Lamperti, Pierre Bouzat, P Malacarne, Arturo Chieregato, Rita Bertuetti, Raffaele Aspide, A Cantoni, Victoria McCredie, Lucrezia Guadrini, Nicola Latronico

Bibliographic record

VenueCritical Care · 2022
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsToronto Western HospitalUniversity Health Network
FundersUniversity of Texas Southwestern Medical Center
KeywordsMedicineTranscranial DopplerReceiver operating characteristicSubarachnoid hemorrhageGold standard (test)Prospective cohort studyTraumatic brain injuryIntracerebral hemorrhageIntracranial pressureNeurointensive careInternal medicineAnesthesia

Abstract

fetched live from OpenAlex

BACKGROUND: Alternative noninvasive methods capable of excluding intracranial hypertension through use of transcranial Doppler (ICPtcd) in situations where invasive methods cannot be used or are not available would be useful during the management of acutely brain-injured patients. The objective of this study was to determine whether ICPtcd can be considered a reliable screening test compared to the reference standard method, invasive ICP monitoring (ICPi), in excluding the presence of intracranial hypertension. METHODS: This was a prospective, international, multicenter, unblinded, diagnostic accuracy study comparing the index test (ICPtcd) with a reference standard (ICPi), defined as the best available method for establishing the presence or absence of the condition of interest (i.e., intracranial hypertension). Acute brain-injured patients pertaining to one of four categories: traumatic brain injury (TBI), subarachnoid hemorrhage (SAH), intracerebral hemorrhage (ICH) or ischemic stroke (IS) requiring ICPi monitoring, were enrolled in 16 international intensive care units. ICPi measurements (reference test) were compared to simultaneous ICPtcd measurements (index test) at three different timepoints: before, immediately after and 2 to 3 h following ICPi catheter insertion. Sensitivity, specificity, positive (PPV) and negative predictive values (NPV) were calculated at three different ICPi thresholds (> 20, > 22 and > 25 mmHg) to assess ICPtcd as a bedside real-practice screening method. A receiver operating characteristic (ROC) curve analysis with the area under the curve (AUC) was used to evaluate the discriminative accuracy and predictive capability of ICPtcd. RESULTS: Two hundred and sixty-two patients were recruited for final analysis. Intracranial hypertension (> 22 mmHg) occurred in 87 patients (33.2%). The total number of paired comparisons between ICPtcd and ICPi was 687. The NPV was elevated (ICP > 20 mmHg = 91.3%, > 22 mmHg = 95.6%, > 25 mmHg = 98.6%), indicating high discriminant accuracy of ICPtcd in excluding intracranial hypertension. Concordance correlation between ICPtcd and ICPi was 33.3% (95% CI 25.6-40.5%), and Bland-Altman showed a mean bias of -3.3 mmHg. The optimal ICPtcd threshold for ruling out intracranial hypertension was 20.5 mmHg, corresponding to a sensitivity of 70% (95% CI 40.7-92.6%) and a specificity of 72% (95% CI 51.9-94.0%) with an AUC of 76% (95% CI 65.6-85.5%). CONCLUSIONS AND RELEVANCE: ICPtcd has a high NPV in ruling out intracranial hypertension and may be useful to clinicians in situations where invasive methods cannot be used or not available. TRIAL REGISTRATION: NCT02322970 .

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)0.000
metaresearch head score (Gemma)0.002
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 score0.120
Threshold uncertainty score0.560

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.020
GPT teacher head0.308
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

Citations107
Published2022
Admission routes1
Has abstractyes

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