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Record W4399897067 · doi:10.25259/sni_1003_2023

Neurocognitive outcome post cranioplasty: The role of cerebral hemodynamics and cerebrospinal fluid dynamics

2024· article· en· W4399897067 on OpenAlexaboutno aff
Manish Agrawal, Keshav Mishra

Bibliographic record

VenueSurgical Neurology International · 2024
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsnot available
Fundersnot available
KeywordsCranioplastyMedicineNeurocognitiveCerebrospinal fluidHemodynamicsOutcome (game theory)SurgeryInternal medicineSkullPsychiatryCognition

Abstract

fetched live from OpenAlex

Background: Cranioplasty has been useful in treating the symptoms associated with the "Sunken skin flap syndrome" post decompressive craniectomy, for which various mechanisms have been proposed. In this study, we aim to assess the changes in the cerebral blood flow and intracranial cerebrospinal fluid (CSF) dynamics post cranioplasty and correlate with the improvement in the neurocognitive status. Methods: Computed tomography perfusion and cine magnetic resonance imaging studies were done to study the changes in cerebral perfusion and CSF flow dynamics postcranioplasty. The cognitive status was assessed using Montreal cognitive assessment, mini-mental state examination, and frontal assessment battery scores in the preoperative period and at 1 and 6 months follow-up. Results: There was a significant change in cognitive status postcranioplasty, both at 1 and 6 months follow-up, which was associated with a significant improvement in cerebral blood flow, decreased mean transit time, and improvement in the mean and peak CSF flow velocities at the foramen of Magendie and aqueduct of Sylvius. Conclusion: Cranioplasty leads to a marked improvement in cerebral hemodynamics, which is more significant on the ipsilateral side. It also leads to increased CSF turnover and improved CSF circulation. Improved cerebral perfusion and, more importantly, CSF dynamics may be responsible for the demonstrable improvement in the neurocognition in the postcranioplasty period.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.460
Threshold uncertainty score0.455

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 studies0.0000.000
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 head0.008
GPT teacher head0.261
Teacher spread0.254 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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