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Record W4394745159 · doi:10.1136/jnis-2023-020979

Long-term neuropsychiatric complications of aneurysmal subarachnoid hemorrhage: a narrative review

2024· review· en· W4394745159 on OpenAlexaff
Jose Danilo Bengzon Diestro, Manav V. Vyas, Youngkyung Jung, Teruko Kishibe, Carl Froilan D. Leochico, Adrian I. Espiritu, Maria Kristina Dorotan, Nico Dimal, Abdelsimar T. Omar, April Sienes, Gustavo Saposnik, Thomas R. Marotta, Atif Zafar, Vítor Mendes Pereira, Julian Spears

Bibliographic record

VenueJournal of NeuroInterventional Surgery · 2024
Typereview
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsOntario Shores Centre for Mental Health SciencesMcMaster UniversityUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineHeadachesSubarachnoid hemorrhageAnxietyDepression (economics)Intensive care medicineNarrative reviewAneurysmPediatricsPsychiatrySurgery

Abstract

fetched live from OpenAlex

This review focuses on the often-neglected long-term neuropsychiatric consequences of aneurysmal subarachnoid hemorrhage (aSAH), beyond traditional randomized trial outcomes of mortality and retreatment. While current guidelines recommend screening for these sequalae, it may not be routinely practiced. This review will underscore the prevalence and management of common neuropsychiatric sequalae, including anxiety, depression, cognitive dysfunction, headaches, seizures, and sexual dysfunction, all of which can significantly impact the quality of life of survivors of aSAH. We emphasize the critical role neurointerventionalists can play by going beyond the customary practice of radiological monitoring for treated aneurysms by screening for and helping guide management of these common neuropsychiatric complications.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.378
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.006
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.064
GPT teacher head0.358
Teacher spread0.294 · 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.

Study designSystematic review
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

Citations6
Published2024
Admission routes1
Has abstractyes

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