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Record W3215198781 · doi:10.1177/19458924211060918

Diagnosis and Localization of Cerebrospinal Fluid Rhinorrhea: A Systematic Review

2021· review· en· W3215198781 on OpenAlexaff
Michael Xie, Kelvin Zhou, Shamez Kachra, Tobial McHugh, Doron D. Sommer

Bibliographic record

VenueAmerican Journal of Rhinology and Allergy · 2021
Typereview
Languageen
FieldMedicine
TopicHead and Neck Surgical Oncology
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicinerhinorrheaMagnetic resonance imagingCerebrospinal Fluid RhinorrheaCerebrospinal fluidRadiologyMeta-analysisCohortNuclear medicineSurgeryPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Cerebrospinal fluid (CSF) rhinorrhea results from abnormal communications between the subarachnoid and sinonasal spaces. Accurate preoperative diagnosis and localization are vital for positive clinical outcomes. However, the diagnosis and localization of CSF rhinorrhea remain suboptimal due to a lack of accurate understanding of test characteristics. OBJECTIVE: This systematic review aims to assess the diagnostic accuracy of various tests and imaging modalities for diagnosing and localizing CSF rhinorrhea. METHODS: A systematic review of the MEDLINE and EMBASE databases was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. RESULTS: Our search identified 4039 articles-53 cohort studies and 24 case series describing 1622 patients were included. The studies were heterogeneous and had a wide range of sensitivities and specificities. Many specificities were incalculable due to a lack of true negative and false positive results, thus precluding a meta-analysis. Median sensitivities and specificities were calculated for cohort studies of the following investigations: high-resolution computed tomography (HRCT) 0.93/0.50 (sensitivity/specificity), magnetic resonance cisternography (MRC) 0.94/0.77, computed tomography cisternography (CTC) 0.95/1.00, radionuclide cisternography (RNC) 0.90/0.50, and contrast-enhanced magnetic resonance cisternography (CEMRC) 0.99/1.00, endoscopy 0.58/1.00, topical intranasal fluorescein (TIF) 1.00/incalculable, intrathecal fluorescein (ITF) 0.96/1.00. Case series were reviewed separately. Etiology and site-specific data were also analyzed. CONCLUSION: MR cisternography is more accurate than high-resolution CT at diagnosing and localizing CSF rhinorrhea. CT cisternography, contrast-enhanced MR cisternography, and radionuclide cisternography have good diagnostic characteristics but are invasive. Intrathecal fluorescein shows promising data but has not been widely adopted for purely diagnostic use. Office endoscopy has limited data but does not sufficiently diagnose CSF rhinorrhea independently. These findings confirm with current guidelines and evidence.

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)0.008
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.039
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0090.010
Bibliometrics0.0090.009
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.343
Teacher spread0.315 · 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 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

Citations38
Published2021
Admission routes1
Has abstractyes

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