Inappropriate Indexing of Case Reports to the “Papilledema” Subject Heading: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Papilledema must be managed distinctly from other causes of optic disc edema (ODE) due to its basis in raised intracranial pressure (ICP). However, evidence indicates that the term "papilledema" is widely misused across specialties to describe ODE without raised ICP. Sources of this misconception remain undiscerned. Because all physicians consult medical databases, our objective was to evaluate whether nonspecific "papilledema" subject heading definitions misleadingly associate articles on other conditions with papilledema proper. METHODS: Systematic review of case reports, prospectively registered on PROSPERO (CRD42022363651). MEDLINE and Embase were searched to July 2022 for any full-length case report indexed to the "papilledema" subject heading. Studies were graded for incorrect indexing, defined as cases lacking evidence for raised ICP. Nonpapilledema diagnoses were assigned to a predefined set of diseases and pathophysiological mechanisms for subsequent comparison. RESULTS: Incorrect indexing occurred in 40.67% of 949 included reports. Embase-derived studies were misindexed significantly less than MEDLINE-derived studies ( P < 0.01). There was also significant heterogeneity in incorrect indexing among specific diseases ( P = 0.0015) and mechanisms ( P = 0.0003). The most commonly misindexed diseases were uveitis (21.24% of errors), optic neuritis (13.47%), and instances with no mention of ODE (13.99%). The most commonly misindexed mechanisms were inflammation (34.97%), other mechanism (e.g., genetic; 25.91%), and ischemia (20.47%). CONCLUSIONS: Database subject headings, especially from MEDLINE, do not adequately distinguish between true papilledema and other causes of ODE. Inflammatory diseases were most often incorrectly indexed among other diseases and mechanisms. Current "papilledema" subject headings should be revised to reduce the probability of misinformation.
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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 | 0.051 | 0.262 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.031 | 0.030 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".