Lymphatic Drainage Patterns of the Human Eyelid: Assessed by Lymphoscintigraphy
Bibliographic record
Abstract
PURPOSE: To describe the lymphatic drainage patterns of the human eyelids. METHODS: Twenty-eight consenting patients who underwent unilateral eyelid surgery at McMaster University between March 2001 and July 2003 had their contralateral eyelids injected with 0.2 ml (0.250 mCi) of Tc 99 m sulphur colloid. The patients were divided into 1 of 5 injection sites of the eyelid, namely upper lateral, upper medial, medial canthus, lower medial, and lower lateral. Lymphoscintigraphy was performed between 2 and 6 hours later with a conventional planar gamma camera. Nodes in the head and neck were identified. In 15 patients, the right eye was injected, and in 13 patients, the left eye was injected. RESULTS: Three patients had no nodes that were identifiable. The remaining 25 patients had at least one node identified. In 11 patients, more than one node was identified. In 18 patients, the preauricular node was most intense and recognized first. Regardless of location on the eyelid, the sentinel node was most commonly the preauricular node. CONCLUSIONS: These results conflict with previously described classic drainage patterns of the eyelid lymphatics. In 72% (18/25) of cases, the first-order sentinel node was the preauricular node, regardless of location of the injection site on the eyelid. Many individuals did not fit the classic drainage patterns.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".