MétaCan
Menu
Back to cohort
Record W2263256000 · doi:10.1186/s12987-016-0025-2

Nonsurgical therapy for hydrocephalus: a comprehensive and critical review

2015· review· en· W2263256000 on OpenAlexafffund
Marc R. Del Bigio, Domenico L. Di Curzio

Bibliographic record

VenueFluids and Barriers of the CNS · 2015
Typereview
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsDiagnostic Services ManitobaChildren's Hospital Research Institute of ManitobaUniversity of Manitoba
FundersCanadian Institutes of Health ResearchResearch Manitoba
KeywordsMedicineHydrocephalusNeuroprotectionCerebral blood flowNeurologySubarachnoid hemorrhageHypervolemiaShuntingIntensive care medicineCerebrospinal fluidAnesthesiaPharmacologySurgeryPathologyBlood volume

Abstract

fetched live from OpenAlex

Pharmacological interventions have been tested experimentally and clinically to prevent hydrocephalus and avoid the need for shunting beginning in the 1950s. Clinical trials of varied quality have not demonstrated lasting and convincing protective effects through manipulation of cerebrospinal fluid production, diuresis, blood clot fibrinolysis, or manipulation of fibrosis in the subarachnoid compartment, although there remains some promise in the latter areas. Acetazolamide bolus seems to be useful for predicting shunt response in adults with hydrocephalus. Neuroprotection in the situation of established hydrocephalus has been tested experimentally beginning more recently. Therapies designed to modify blood flow or pulsation, reduce inflammation, reduce oxidative damage, or protect neurons are so far of limited success; more experimental work is needed in these areas. As has been recommended for preclinical studies in stroke and brain trauma, stringent conditions should be met for preclinical studies in hydrocephalus.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.091
GPT teacher head0.365
Teacher spread0.274 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations140
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueFluids and Barriers of the CNSSame topicCerebrospinal fluid and hydrocephalusFrench-language works237,207