Outcome of inferior oblique recession with or without vertical rectus recession for unilateral superior oblique paresis.
Bibliographic record
Abstract
PURPOSE: To determine the effectiveness of a standard fixed 10 mm inferior oblique (IO) recession with or without vertical rectus recession in visually mature patients with unilateral superior oblique paresis (SOP) and mild to moderate IO overaction. METHODS: The records of 24 patients over 12 years of age who had 10 mm IO recession for SOP, for IO overaction of +1 to +3 (out of maximum +4), with 6+ months of followup were reviewed. Criteria required for a "successful" outcome included: 1. hyperdeviation of 5delta or less in primary position; 2. elimination of any compensatory abnormal head posture; and 3. elimination of diplopia in the central 30 degrees of the binocular visual field. RESULTS: In 16 cases of IO recession alone, 88% were "successful" and in 8 cases who had in addition either contralateral inferior rectus recession or ipsilateral superior rectus recession, 75% were "successful". IO 10 mm recession alone led to an average reduction of 9.1 PD of hypertropia in primary position. CONCLUSION: A standard ungraded 10 mm recession of the IO alone or in combination with vertical rectus muscle recession is an effective weakening procedure with a high success rate for patients with unilateral SOP with mild to moderate IO overaction. In occasional cases of undercorrection, a subsequent IO myectomy is very feasible and effective.
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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".