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Record W2129998383 · doi:10.1186/s12987-015-0004-z

MRI assessment of the effects of acetazolamide and external lumbar drainage in idiopathic Normal Pressure Hydrocephalus

2015· article· en· W2129998383 on OpenAlexfundno aff
Miloš Ivković, M Reiss-Zimmermann, Heather Katzen, Matthias Preuß, İlhami Kovanlıkaya, Linda Heier, Noam Alperin, Karl‐Titus Hoffmann, Norman Relkin

Bibliographic record

VenueFluids and Barriers of the CNS · 2015
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsnot available
FundersNational Institute on AgingNational Institute of Biomedical Imaging and BioengineeringCanadian Institutes of Health ResearchNational Institutes of HealthGenentechNational Institute of Neurological Disorders and StrokeIXICOServierEisaiNorthern California Institute for Research and EducationUniversity of California, San DiegoPfizerBiogenBioClinicaF. Hoffmann-La RocheFoundation for the National Institutes of HealthLeon Levy FoundationSynarcUniversity of Southern CaliforniaMedpaceNovartis Pharmaceuticals CorporationU.S. Department of DefenseEli Lilly and CompanyBristol-Myers SquibbAlzheimer's AssociationAlzheimer's Disease Neuroimaging InitiativeMeso Scale Diagnostics
KeywordsAcetazolamideMedicineHydrocephalusLumbarMagnetic resonance imagingNeurologyDiffusion MRINormal pressure hydrocephalusRadiologyCerebral blood flowNuclear medicineAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The objective was to identify changes in quantitative MRI measures in patients with idiopathic normal pressure hydrocephalus (iNPH) occurring in common after oral acetazolamide (ACZ) and external lumbar drainage (ELD) interventions. METHODS: A total of 25 iNPH patients from two clinical sites underwent serial MRIs and clinical assessments. Eight received ACZ (125-375 mg/day) over 3 months and 12 underwent ELD for up to 72 hours. Five clinically-stable iNPH patients who were scanned serially without interventions served as controls for the MRI component of the study. Subjects were divided into responders and non-responders to the intervention based on gait and cognition assessments made by clinicians blinded to MRI results. The MRI modalities analyzed included T1-weighted images, diffusion tensor Imaging (DTI) and arterial spin labelling (ASL) perfusion studies. Automated threshold techniques were used to define regions of T1 hypo-intensities. RESULTS: Decreased volume of T1-hypointensities and decreased mean diffusivity (MD) within remaining hypointensities was observed after ACZ and ELD but not in controls. Patients responding positively to these interventions had more extensive decreases in T1-hypointensites than non-responders: ACZ-responders (4,651 ± 2,909 mm(3)), ELD responders (2,338 ± 1,140 mm(3)), ELD non-responders (44 ± 1,188 mm(3)). Changes in DTI MD within T1-hypointensities were greater in ACZ-responders (7.9% ± 2%) and ELD-responders (8.2% ± 3.1%) compared to ELD non-responders (2.1% ± 3%). All the acetazolamide-responders showed increases in whole-brain-average cerebral blood flow (wbCBF) estimated by ASL (18.8% ± 8.7%). The only observed decrease in wbCBF (9.6%) occurred in an acetazolamide-non-responder. A possible association between cerebral atrophy and response was observed, with subjects having the least cortical atrophy (as indicated by a positive z-score on cortical thickness measurements) showing greater clinical improvement after ACZ and ELD. CONCLUSIONS: T1-hypointensity volume and DTI MD measures decreased in the brains of iNPH patients following oral ACZ and ELD. The magnitude of the decrease was greater in treatment responders than non-responders. Despite having different mechanisms of action, both ELD and ACZ may decrease interstitial brain water and increase cerebral blood flow in patients with iNPH. Quantitative MRI measurements appear useful for objectively monitoring response to acetazolamide, ELD and potentially other therapeutic interventions in patients with iNPH.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.244
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.008
GPT teacher head0.244
Teacher spread0.235 · 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 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

Citations35
Published2015
Admission routes1
Has abstractyes

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