Usefulness of topical intranasal fluorescein for localization of anterior skull base fluid fistulas: a systematic review
Bibliographic record
Abstract
Abstract OBJECTIVE. This study evaluates the available evidence on the usefulness of topical intranasal fluorescein in diagnosing and localizing nasal cerebrospinal fluid (CSF) leakage. MATERIAL AND METHODS. A systematic review of the literature was conducted to investigate the usefulness and safety of intranasal topical fluorescein for locating nasal cerebrospinal fluid fistulas, following PRISMA guidelines. Articles were searched in databases including Scopus, PubMed, and ScienceDirect, (“Intranasal Fluorescein” AND “Cerebrospinal Fluid Fistula”) OR (“Intranasal Fluorescein” AND “CSF Fistula”) in the publications with no time restriction, in the English language. The chosen articles were evaluated with the Newcastle-Ottawa Scale. A table was used to summarize the results. RESULTS. The 6 included studies on topical intranasal fluorescein to locate CSF fistulas show high effectiveness and safety, with success rates close to 100%. However, limitations include small samples, lack of control groups, and the need for more comparative studies. The methodological quality of the studies is mostly moderate. CONCLUSION. Intranasal topical fluorescein is an effective and safe method to locate intranasal cerebrospinal fluid leaks, with high diagnostic accuracy. It is a less invasive and more economical option compared to techniques such as intrathecal fluorescein. More controlled research is needed to confirm its effectiveness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".