Bibliographic record
Abstract
INTRODUCTION: The diagnosis of perilymphatic fistula (PLF) is difficult since no single clinical situation gives the diagnosis for sure. The goal of this study is to clarify the clinical situations where you must suspect a PLF. METHODS: Retrospective study of 20 patients that had an exploratory tympanotomy with a PLF confirmed peroperatively. An analysis of the symptoms, signs and complementary exams was done. The surgical findings and the postoperative evolution were noted. RESULTS: 100% of patients reported a hearing loss, 80% vertigo, 70% a tinnitus and 35% equilibrium problems. Every patient had an etiological event to explain the PLF (trauma 85%), stapedotomy (10%), other ear surgeries. Five patients had a positive fistula or Vasalva test. All patients except one had an hearing loss on the audiogram (sensorineural, mixte or conductive). 50% had a CT scan, 70% of which were abnormal. A VNG was done on 3 patients. The sites of the PLF were as follows: 90% oval window, 5% round window and 5% both windows. The hearing got better or was stabilised in 95% of patients after the operation. 64% saw an improvement of their tinnitus and 87% of their vertigo. CONCLUSION: The diagnosis of PLF is difficult and a high index of suspicion is mandatory. One must look for an etiologic situation to explain the PLF. The audiogram is almost always modified, a mixte hearing loss being common due to the high incidence of ossicular trauma associated with PLF. The clinical clinical situations where you must suspect a PLF were identified as follows: An old trauma, a recent trauma, a history of otologic surgery particularly on the stapes and a preexisting hearing loss that aggravates. A diagnosis scale to evaluate the risk of PLF, based on clinical situations, physical exam and complementary exams was done to help the clinician in the evaluation of PLF.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.011 |
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".