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Record W7161941729 · doi:10.82308/28476

Predictors of Ventriculoperitoneal Shunt Placement in Adult Patients with Aneurysmal Subarachnoid Haemorrhage: understanding the pathophysiology of Cerebrospinal fluid changes after aneurysmal subarachnoid hemorrhage

2024· dissertation· en· W7161941729 on OpenAlexaboutno aff
Qais Alrashidi

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsnot available
Fundersnot available
KeywordsSubarachnoid hemorrhageHydrocephalusLogistic regressionRetrospective cohort studyMedical recordExternal ventricular drainUnivariate analysisShunt (medical)Cohort

Abstract

fetched live from OpenAlex

Abstracts Introduction and aim of the study:Aneurysmal subarachnoid hemorrhage (aSAH) presents a formidable neurological challenge affecting 80% of non-traumatic SAH cases. Hydrocephalus develops in 20-30% of aSAH patients, resulting in further neurological cognitive impairment. Management involves temporary external ventricular drain (EVD) placement to alleviate elevated intracranial pressure. Some patients become EVD-dependent, necessitating permanent ventriculoperitoneal shunt (VPS) insertion. Predictors for VPS insertion in adult aSAH patients remain unclear, so the primary objective of this study is to identify those predictors, so as to afford better clinical decision-making and to improve patient outcomes.Methodology: This retrospective cohort study includes adult patients diagnosed with aSAH admitted to the Montreal Neurological Hospital from January 2015 to December 2020. Regarding the potential predictors of VPS, variables were first elucidated and better defined through a recent literature review. The data variables were then collected from medical records encompassing demographic details (age, sex), clinically relevant medical history (hypertension, diabetes, smoking, alcohol use), radiological findings (Evan’s Index, Modified Fisher Score, Graeb score), and treatment methods (surgical clipping, endovascular treatment). The primary study outcome was VPS placement during hospital admission. The secondary outcome measure was the length of hospital stay. Descriptive statistics were summarized on demographic and clinical characteristics. Univariate analysis, using a chi-square test for categorical variables, and a t-test, or Wilcoxon rank-sum test for continuous variables, was employed to identify factors associated with VPS placement. Unconditional multivariable logistic regression was employed on all predictors of VPS insertion to determine predictors of VPS placement.Results: In our study of 143 patients, 29% required VP shunt insertion. Comparing shunted versus non-shunted groups there were no significant differences found in several variables. However, those needing shunts had a slightly longer hospital stay. Hypertension was higher in the non-shunted group, and larger aneurysms were more prevalent. A higher Hunt and Hess score, a higher modified Fisher’s scale score, and a higher modified Graeb score were each associated with an increased shunt placement likelihood.Conclusion: In patients with aneurysmal subarachnoid hemorrhage, higher Hunt and Hess, modified Fisher, and a modified Graeb score were each linked to an increased likelihood of needing a shunt. Hypertension and harbouring a smaller aneurysm were each associated with an increased likelihood of having a shunt placed. Recognizing these risks is crucial when considering shunt placement for improved patient care. Further research is needed to fully validate these findings

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.229
Teacher spread0.220 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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