Implementation of the Ebola Virus Persistence in Ocular Tissues and Fluids (EVICT) study: Lessons learned for vision health systems strengthening in Sierra Leone
Notice bibliographique
Résumé
BACKGROUND: Following the West African Ebola virus disease (EVD) outbreak of 2013-2016 and more recent EVD outbreaks in the Democratic Republic of Congo, thousands of EVD survivors are at-risk for sequelae including uveitis, which can lead to unremitting inflammation and vision loss from cataract. Because of the known risk of Ebola virus persistence in ocular fluid and the need to provide vision-restorative, safe cataract surgery, the Ebola Virus Persistence in Ocular Tissues and Fluids (EVICT) Study was implemented in Sierra Leone. During implementation of this multi-national study, challenges included regulatory approvals, mobilization, community engagement, infection prevention and control, and collaboration between multiple disciplines. In this report, we address the multifacted approach to address these challenges and the impact of implementation science research to address an urgent clinical subspecialty need in an outbreak setting. METHODOLOGY/PRINCIPAL FINDINGS: Given the patient care need to develop a protocol to evaluate ocular fluid for Ebola virus RNA persistence prior to cataract surgery, as well as protocols to provide reassurance to ophthalmologists caring for EVD survivors with cataracts, the EVICT study was designed and implemented through the work of the Ministry of Health, Sierra Leone National Eye Programme, and international partnerships. The EVICT study showed that all 50 patients who underwent ocular fluid sampling at 19 and 34 months, respectively, tested negative for Ebola virus RNA. Thirty-four patients underwent successful cataract surgery with visual acuity improvement. Here we describe the methodology for study implementation, challenges encountered, and key issues that impacted EVD vision care in the immediate aftermath of the EVD outbreak. Key aspects of the EVICT study included defining the pertinent questions and clinical need, partnership alignment with key stakeholders, community engagement with EVD survivor associations, in-country and international regulatory approvals, study site design for infection prevention and control, and thorough plans for EVD survivor follow-up care and monitoring. Challenges encountered included patient mobilization owing to transportation routes and distance of patients in rural districts. Strong in-country partnerships and multiple international organizations overcame these challenges so that lessons learned could be applied for future EVD outbreaks in West and Central Africa including EVD outbreaks that are ongoing in Guinea and Democratic Republic of Congo. CONCLUSIONS/SIGNIFICANCE: The EVICT Study showed that cataract surgery with a protocol-driven approach was safe and vision-restorative for EVD survivors, which provided guidance for EVD ophthalmic surgical care. Ophthalmologic care remains a key aspect of the public health response for EVD outbreaks but requires a meticulous, yet partnered approach with international and local in-country partners. Future efforts may build on this framework for clinical care and to improve our understanding of ophthalmic sequelae, develop treatment paradigms for EVD survivors, and strengthen vision health systems in resource-limited settings.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,048 | 0,040 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,003 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,009 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».