Symptom-based stratification algorithm for heterogeneous symptoms of dry eye disease: a feasibility study.
Journal
Eye (London, England)
ISSN: 1476-5454
Titre abrégé: Eye (Lond)
Pays: England
ID NLM: 8703986
Informations de publication
Date de publication:
Nov 2023
Nov 2023
Historique:
received:
10
01
2023
accepted:
06
04
2023
revised:
31
03
2023
pmc-release:
01
11
2024
medline:
9
11
2023
pubmed:
16
4
2023
entrez:
15
4
2023
Statut:
ppublish
Résumé
To test the feasibility of a dry eye disease (DED) symptom stratification algorithm previously established for the general population among patients visiting ophthalmologists. This retrospective cross-sectional study was conducted between December 2015 and October 2021 at a university hospital in Japan; participants who underwent a comprehensive DED examination and completed the Japanese version of the Ocular Surface Disease Index (J-OSDI) were included. Patients diagnosed with DED were stratified into seven clusters using a previously established symptom-based stratification algorithm for DED. Characteristics of the patients in stratified clusters were compared. In total, 426 participants were included (median age [interquartile range]; 63 [48-72] years; 357 (83.8%) women). Among them, 291 (68.3%) participants were diagnosed with DED and successfully stratified into seven clusters. The J-OSDI total score was highest in cluster 1 (61.4 [52.2-75.0]), followed by cluster 5 (44.1 [38.8-47.9]). The tear film breakup time was the shortest in cluster 1 (1.5 [1.1-2.1]), followed by cluster 3 (1.6 [1.0-2.5]). The J-OSDI total scores from the stratified clusters in this study and those from the clusters identified in the previous study showed a significant correlation (r = 0.991, P < 0.001). The patients with DED who visited ophthalmologists were successfully stratified by the previously established algorithm for the general population, uncovering patterns for their seemingly heterogeneous and variable clinical characteristics of DED. The results have important implications for promoting treatment interventions tailored to individual patients and implementing smartphone-based clinical data collection in the future.
Sections du résumé
BACKGROUND/OBJECTIVE
OBJECTIVE
To test the feasibility of a dry eye disease (DED) symptom stratification algorithm previously established for the general population among patients visiting ophthalmologists.
SUBJECT/METHODS
METHODS
This retrospective cross-sectional study was conducted between December 2015 and October 2021 at a university hospital in Japan; participants who underwent a comprehensive DED examination and completed the Japanese version of the Ocular Surface Disease Index (J-OSDI) were included. Patients diagnosed with DED were stratified into seven clusters using a previously established symptom-based stratification algorithm for DED. Characteristics of the patients in stratified clusters were compared.
RESULTS
RESULTS
In total, 426 participants were included (median age [interquartile range]; 63 [48-72] years; 357 (83.8%) women). Among them, 291 (68.3%) participants were diagnosed with DED and successfully stratified into seven clusters. The J-OSDI total score was highest in cluster 1 (61.4 [52.2-75.0]), followed by cluster 5 (44.1 [38.8-47.9]). The tear film breakup time was the shortest in cluster 1 (1.5 [1.1-2.1]), followed by cluster 3 (1.6 [1.0-2.5]). The J-OSDI total scores from the stratified clusters in this study and those from the clusters identified in the previous study showed a significant correlation (r = 0.991, P < 0.001).
CONCLUSIONS
CONCLUSIONS
The patients with DED who visited ophthalmologists were successfully stratified by the previously established algorithm for the general population, uncovering patterns for their seemingly heterogeneous and variable clinical characteristics of DED. The results have important implications for promoting treatment interventions tailored to individual patients and implementing smartphone-based clinical data collection in the future.
Identifiants
pubmed: 37061620
doi: 10.1038/s41433-023-02538-4
pii: 10.1038/s41433-023-02538-4
pmc: PMC10630441
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
3484-3491Subventions
Organisme : MEXT | Japan Society for the Promotion of Science (JSPS)
ID : 20KK0207
Organisme : MEXT | Japan Society for the Promotion of Science (JSPS)
ID : 21K17311
Organisme : MEXT | Japan Society for the Promotion of Science (JSPS)
ID : 21K20998
Informations de copyright
© 2023. The Author(s), under exclusive licence to The Royal College of Ophthalmologists.
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