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Record W4292542323 · doi:10.1080/02699052.2022.2109750

Atorvastatin treatment in a patient with post-traumatic hydrocephalus: a case report

2022· article· en· W4292542323 on OpenAlexaboutno aff
Jiaqi Zhu, Yuewen Ma

Bibliographic record

VenueBrain Injury · 2022
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHydrocephalusAtorvastatinTraumatic brain injuryCerebrospinal fluidCommunicating hydrocephalusVentricleThird ventricleAnesthesiaSurgeryCardiologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: Clinical treatment of post-traumatic hydrocephalus (PTH) is limited to cerebrospinal fluid (CSF) extracranial shunting, and research on noninvasive treatment is still lacking. In a follow-up study of a patient with PTH, atorvastatin treatment was beneficial in controlling hydrocephalus and promoting neurological recovery. METHOD: A 29-year-old male patient with traumatic brain injury (TBI) was found to have progressive hydrocephalus and presented with symptoms of decreased spontaneous speech and delayed functional recovery. We added oral treatment with 20 mg/day atorvastatin and followed up hydrocephalus with head CT every two months. RESULTS: The span of the third ventricle decreased by 21%, Evan's index fell by 16%, and the Fugl-Meyer motor score was up from 17/100 to 56/100. The Montreal Cognitive Assessment score was modified from 15/30 to 23/30. CONCLUSION: The use of atorvastatin in the patient may improve the imaging results and benefit the patient functionally.

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)0.000
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.021
GPT teacher head0.276
Teacher spread0.255 · 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 designCase report
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
Published2022
Admission routes1
Has abstractyes

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