Impact of submacular fluid volume on visual outcome in macula-off rhegmatogenous retinal detachment using automated optical coherence tomography volumetric quantification.


Journal

Clinical & experimental ophthalmology
ISSN: 1442-9071
Titre abrégé: Clin Exp Ophthalmol
Pays: Australia
ID NLM: 100896531

Informations de publication

Date de publication:
Jul 2021
Historique:
revised: 19 03 2021
received: 11 01 2021
accepted: 13 04 2021
pubmed: 18 4 2021
medline: 1 9 2021
entrez: 17 4 2021
Statut: ppublish

Résumé

We investigated effects of submacular fluid volume (SMFV) on visual outcomes following surgery for macula-off primary rhegmatogenous retinal detachment (RRD) using automated fluid volumetric quantification with optical coherence tomography (OCT). We analysed 127 eyes that were surgically treated for macula-off RRDs. We obtained preoperative images following the spectral domain (SD)-OCT dense volume protocol, applied automated retinal segmentation and used an automated algorithm to quantify each eye's SMFV. We used multivariate models to identify various risk factors for impaired visual outcome. Linear regression showed that preoperative SMFV (ß = 0.013; P = .005) was significantly associated with a reduced visual outcome 12 months after the treatment of macula-off RRDs. SMFV was negatively correlated with 12-month postoperative (r = .311; P = .001) visual acuity (VA). The group with low preoperative SMFV (≤9.0 mm SMFV was negatively correlated with visual outcomes after the surgical treatment of macula-off RRDs. Patients with SMFV <9.0 mm

Sections du résumé

BACKGROUND BACKGROUND
We investigated effects of submacular fluid volume (SMFV) on visual outcomes following surgery for macula-off primary rhegmatogenous retinal detachment (RRD) using automated fluid volumetric quantification with optical coherence tomography (OCT).
METHODS METHODS
We analysed 127 eyes that were surgically treated for macula-off RRDs. We obtained preoperative images following the spectral domain (SD)-OCT dense volume protocol, applied automated retinal segmentation and used an automated algorithm to quantify each eye's SMFV. We used multivariate models to identify various risk factors for impaired visual outcome.
RESULTS RESULTS
Linear regression showed that preoperative SMFV (ß = 0.013; P = .005) was significantly associated with a reduced visual outcome 12 months after the treatment of macula-off RRDs. SMFV was negatively correlated with 12-month postoperative (r = .311; P = .001) visual acuity (VA). The group with low preoperative SMFV (≤9.0 mm
CONCLUSIONS CONCLUSIONS
SMFV was negatively correlated with visual outcomes after the surgical treatment of macula-off RRDs. Patients with SMFV <9.0 mm

Identifiants

pubmed: 33864341
doi: 10.1111/ceo.13929
pmc: PMC8360107
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

439-447

Commentaires et corrections

Type : CommentIn

Informations de copyright

© 2021 The Authors. Clinical & Experimental Ophthalmology published by John Wiley & Sons Australia, Ltd on behalf of Royal Australian and New Zealand College of Ophthalmologists.

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Auteurs

Reinhard Angermann (R)

Department of Ophthalmology, Medical University Innsbruck, Innsbruck, Austria.
Department of Ophthalmology, Paracelsus Medical University Salzburg, Salzburg, Austria.

Stefan Mosböck (S)

Department of Ophthalmology, Medical University Innsbruck, Innsbruck, Austria.

Christoph Palme (C)

Department of Ophthalmology, Medical University Innsbruck, Innsbruck, Austria.

Hanno Ulmer (H)

Department of Medical Statistics, Informatics and Health Economics, Medical University Innsbruck, Innsbruck, Austria.

Teresa Rauchegger (T)

Department of Ophthalmology, Medical University Innsbruck, Innsbruck, Austria.

Yvonne Nowosielski (Y)

Department of Ophthalmology, Medical University Innsbruck, Innsbruck, Austria.

Nikolaos E Bechrakis (NE)

Department of Ophthalmology, University Hospital Essen, Essen, Germany.

Claus Zehetner (C)

Department of Ophthalmology, Medical University Innsbruck, Innsbruck, Austria.

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Classifications MeSH