Potential Complications of Intralesional Laser Photocoagulation for Extensive Vascular Malformations
Bibliographic record
Abstract
Vascular anomalies remain a challenge for both patients and plastic surgeons. Recently, promising results have been reported using intralesional photocoagulation (ILP) to treat extensive vascular lesions. At the authors' center, they have treated more than 300 patients with vascular anomalies in different parts of the body between 1996 and 1999. They describe their operative techniques of ILP. Laser pulses of a 1,064-nm wavelength from the Nd:YAG laser were delivered to the target tissues with a 600-microm optical fiber. They report 2 patients who developed complications after a single session of ILP therapy for their extensive vascular malformations. The first patient had Klippel-Trenaunay syndrome (capillary-lymphaticovenous malformations) with widespread involvement of her buttocks and left lower limb. She had severe leukocytosis, thrombocytosis, and hyperkalemia that resolved with intravenous hydration, antibiotics, and sodium bicarbonate. In their second patient, the entire left upper limb was affected. Her total red cell count diminished by a quarter and her hemoglobin concentration dropped by more than 3 g%. This was corrected gradually with supplemental oral hematinics. Although these complications resolved uneventfully in their patients, they hope that their possible development will caution anyone who may wish to attempt this new method of therapy.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".