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Record W3109358919 · doi:10.1155/2020/8874605

Transcranial Doppler for Early Prediction of Cognitive Impairment after Aneurysmal Subarachnoid Hemorrhage and the Associated Clinical Biomarkers

2020· article· en· W3109358919 on OpenAlexaboutno aff
Ahmed Esmael, Tamer Belal, Khaled Eltoukhy

Bibliographic record

VenueStroke Research and Treatment · 2020
Typearticle
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTranscranial DopplerSubarachnoid hemorrhageGlasgow Coma ScaleMontreal Cognitive AssessmentInternal medicineCognitionCardiologyBlood pressureCognitive impairmentAnesthesiaPsychiatry

Abstract

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Background and Aim. Cognitive impairment after aneurysmal subarachnoid hemorrhage (aSAH) stays under investigation. This study is aimed at predicting the cognitive impairment by transcranial Doppler (TCD) and detecting the associated clinical biomarkers of impaired cognition after aSAH after 3 months from the onset. Methods. Prospective study included 40 cases with acute aSAH. Initial evaluation by Glasgow Coma Scale (GCS) and the severity of aSAH was detected by both the clinical Hunt and Hess and radiological Fisher’s grading scales. TCD was done for all patients five times within 10 days measuring the mean flow velocities (MFVs) of cerebral arteries. At the 3-month follow-up, patients were classified into two groups according to Montreal Cognitive Assessment (MoCA) scale: the first group was 31 cases (77.5%) with intact cognitive functions and the other group was 9 cases (22.5%) with impaired cognition. Results. Patients with impaired cognitive functions showed significantly lower mean GCS ( <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <mi>p</mi> <mo>=</mo> <mn>0.03</mn> </math> ), significantly higher mean Hunt and Hess scale grades ( <math xmlns="http://www.w3.org/1998/Math/MathML" id="M2"> <mi>p</mi> <mo>=</mo> <mn>0.04</mn> </math> ), significantly higher mean diabetes mellitus (DM) ( <math xmlns="http://www.w3.org/1998/Math/MathML" id="M3"> <mi>p</mi> <mo>=</mo> <mn>0.03</mn> </math> ), significantly higher mean systolic blood pressure (SBP) and diastolic blood pressure (DBP) ( <math xmlns="http://www.w3.org/1998/Math/MathML" id="M4"> <mi>p</mi> <mo>=</mo> <mn>0.02</mn> </math> and <math xmlns="http://www.w3.org/1998/Math/MathML" id="M5"> <mi>p</mi> <mo>=</mo> <mn>0.005</mn> </math> , respectively), and significantly higher MFVs measured within the first 10 days. The patients with cognitive impairment were accompanied by a higher incidence of hydrocephalus ( <math xmlns="http://www.w3.org/1998/Math/MathML" id="M6"> <mi>p</mi> <mo>=</mo> <mn>0.01</mn> </math> ) and a higher incidence of delayed cerebral ischemia (DCI) ( <math xmlns="http://www.w3.org/1998/Math/MathML" id="M7"> <mi>p</mi> <mo>&lt;</mo> <mn>0.001</mn> </math> ). Logistic regression analysis detected that <math xmlns="http://www.w3.org/1998/Math/MathML" id="M8"> <mtext>MFV</mtext> <mo>≥</mo> <mn>86</mn> <mo> </mo> <mo> </mo> <mtext>cm</mtext> <mo>/</mo> <mtext>s</mtext> </math> in the middle cerebral artery (MCA), <math xmlns="http://www.w3.org/1998/Math/MathML" id="M9"> <mtext>MFV</mtext> <mo>≥</mo> <mn>68</mn> <mo> </mo> <mo> </mo> <mtext>cm</mtext> <mo>/</mo> <mtext>s</mtext> </math> in the anterior cerebral artery (ACA), and <math xmlns="http://www.w3.org/1998/Math/MathML" id="M10"> <mtext>MFV</mtext> <mo>≥</mo> <mn>45</mn> <mo> </mo> <mo> </mo> <mtext>cm</mtext> <mo>/</mo> <mtext>s</mtext> </math> in the posterior cerebral artery (PCA) were significantly associated with increased risk of cognitive impairment. Conclusion. Cognitive impairment after the 3-month follow-up phase in aSAH patients was 22.5%. Acute hydrocephalus and DCI are highly associated with poor cognitive function in aSAH. Increased MFV is a strong predictor for poor cognitive function in aSAH. This trial is registered with NCT04329208.

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)0.000
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 score0.131
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.067
GPT teacher head0.345
Teacher spread0.278 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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