Comprehensive Management of Cocaine-Induced Midline Destructive Lesions: A Young-IfOS Consensus
Bibliographic record
Abstract
Background: Recreational nasal cocaine use (RNCU) presents a significant challenge for rhinologists due to cocaine-induced midline destructive lesions (CIMDLs). This clinical consensus statement (CCS) offers guidelines for diagnosing, assessing, and managing both proven and suspected cases of CIMDL (including those without a prior RNCU history). It aims to support clinicians in addressing these complex cases effectively. Methods: An international, multidisciplinary panel of 18 specialists employed a three-round modified Delphi-method survey to evaluate statements covering CIMDL management issues such as definition, clinical evaluation and diagnosis, initial management approaches, and surgical management of complications and reconstructions. This study primarily targets otorhinolaryngologists. Results: Out of 44 evaluated statements, 20 achieved strong consensus, 20 reached consensus, 3 approached near-consensus, and 1 failed to achieve consensus. Consensus-covered areas included the definition of CIMDL, clinical evaluations, first-line management, and management of complications. However, reconstructive techniques remained a contentious topic. Conclusions: In the absence of extensive data, this CCS establishes a management framework for CIMDL, significantly bridging a knowledge gap. It highlights the need for standardized assessments, multidisciplinary cooperation, and customized follow-up care for patients with CIMDL. Considering the widespread use of cocaine, physicians should consistently consider the possibility of RNCU when encountering chronic inflammatory lesions in the sinonasal tract.
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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 | 0.032 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".