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Retinal Displacement Following Pneumatic Retinopexy vs Pars Plana Vitrectomy for Rhegmatogenous Retinal Detachment

2020· article· en· W3020216141 on OpenAlexaffabout
Koby Brosh, Carolina L. M. Francisconi, Jenny Qian, Francesco Sabatino, Verena R. Juncal, Roxane J. Hillier, Varun Chaudhary, Alan R. Berger, Louis R. Giavedoni, David T. Wong, Filiberto Altomare, Mustafa R. Kadhim, Richard Newsom, Samara B. Marafon, Rajeev H. Muni

Bibliographic record

VenueJAMA Ophthalmology · 2020
Typearticle
Languageen
FieldMedicine
TopicRetinal and Macular Surgery
Canadian institutionsKensington HealthSt. Joseph’s Healthcare HamiltonSt. Michael's HospitalMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsMedicineVitrectomyPars planaOphthalmologyRetinal detachmentRetinalFundus (uterus)Interquartile rangeAutofluorescenceVisual acuitySurgeryOptics

Abstract

fetched live from OpenAlex

Importance: Retinal displacement following rhegmatogenous retinal detachment repair may have consequences for visual function. It is important to know whether surgical technique is associated with risk of displacement. Objective: To compare retinal displacement following rhegmatogenous retinal detachment repair with pneumatic retinopexy (PR) vs pars plana vitrectomy (PPV). Interventions or Exposures: Fundus autofluorescence images were assessed by graders masked to surgical technique. Design, Setting, and Participants: A multicenter retrospective consecutive case series in Canada and the UK. A total of 238 patients (238 eyes) with rhegmatogenous retinal detachments treated with PR or PPV who underwent fundus autofluorescence imaging from November 11, 2017, to March 22, 2019, were included. Main Outcomes and Measures: Proportion of patients with retinal displacement detected by retinal vessel printings on fundus autofluorescence imaging in PR vs PPV. Results: Of the 238 patients included in the study, 144 were men (60.5%) and 94 were women (39.5%); mean (SD) age was 62.0 (11.0) years. Of the 238 eyes included in this study, 114 underwent PR (47.9%) and 124 underwent PPV (52.1%) as the final procedure to achieve reattachment. Median time from surgical procedure to fundus autofluorescence imaging was 3 months (interquartile range, 1-5 months). Baseline characteristics in both groups were similar. The proportion of eyes with retinal vessel printing on fundus autofluorescence was 7.0% for PR (8 of 114) and 44.4% for PPV (55 of 124) (37.4% difference; 95% CI, 27.4%-47.3%; P < .001). Analysis based on the initial procedure found that 42.4% (42 of 99) of the eyes in the PPV group vs 15.1% (21 of 139) of the eyes in the PR group (including 13 PR failures with subsequent PPV) had displacement (27.3% difference; 95% CI, 15.9%-38.7%; P < .001). Among eyes with displacement in the macula, the mean (SD) displacement was 0.137 (0.086) mm (n = 6) for PR vs 0.297 (0.283) mm (n = 52) for PPV (0.160-mm difference; 95% CI, 0.057-0.263 mm; P = .006). Mean postoperative logMAR visual acuity was 0.31 (0.32) (n = 134) (Snellen equivalent 20/40) in eyes that initially underwent PR and 0.56 (0.42) (n = 84) (Snellen equivalent 20/72) in eyes that had PPV (-0.25 difference; 95% CI, -0.14 to -0.35; P < .001). Among eyes with displacement, mean postoperative logMAR visual acuity was 0.42 (0.42) (n = 20) (Snellen equivalent 20/52) in those that initially underwent PR and 0.66 (0.47) (n = 33) (Snellen equivalent 20/91) in those that initially underwent PPV (-0.24 difference; 95% CI, -0.48 to 0.01; P = .07). Conclusions and Relevance: These findings suggest that retinal displacement occurs more frequently and is more severe with PPV vs PR when considering the initial and final procedure used to achieve retinal reattachment. Recognizing the importance of anatomic integrity by assessing retinal displacement following reattachment may lead to refinements in vitreoretinal surgery techniques.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.040
GPT teacher head0.308
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations97
Published2020
Admission routes2
Has abstractyes

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