Worldwide Argus II implantation: recommendations to optimize patient outcomes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: A position paper based on the collective experiences of Argus II Retinal Prosthesis System investigators to review strategies to optimize outcomes in patients with retinitis pigmentosa undergoing retinal prosthesis implantation. METHODS: Retinal surgeons, device programmers, and rehabilitation specialists from Europe, Canada, Middle East, and the United States were convened to the first international Argus II Investigator Meeting held in Ann Arbor, MI in March 2015. The recommendations from the collective experiences were collected. Factors associated with successful outcomes were determined. RESULTS: Factors leading to successful outcomes begin with appropriate patient selection, expectation counseling, and preoperative retinal assessment. Challenges to surgical implantation include presence of staphyloma and inadequate Tenon's capsule or conjunctiva. Modified surgical technique may reduce risks of complications such as hypotony and conjunctival erosion. Rehabilitation efforts and correlation with validated outcome measures following implantation are critical. CONCLUSIONS: Bringing together Argus II investigators allowed the identification of strategies to optimize patient outcomes. Establishing an on-line collaborative network will foster coordinated research efforts to advance outcome assessment and rehabilitation strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it