PMID- 37203049
OWN - NLM
STAT- MEDLINE
DCOM- 20230522
LR  - 20230803
IS  - 1998-3689 (Electronic)
IS  - 0301-4738 (Print)
IS  - 0301-4738 (Linking)
VI  - 71
IP  - 5
DP  - 2023 May
TI  - Artificial intelligence-based stratification of demographic, ocular surface 
      high-risk factors in progression of keratoconus.
PG  - 1882-1888
LID - 10.4103/IJO.IJO_2651_22 [doi]
AB  - PURPOSE: The purpose of this study was to identify and analyze the clinical and 
      ocular surface risk factors influencing the progression of keratoconus (KC) using 
      an artificial intelligence (AI) model. METHODS: This was a prospective analysis 
      in which 450 KC patients were included. We used the random forest (RF) classifier 
      model from our previous study (which evaluated longitudinal changes in 
      tomographic parameters to predict "progression" and "no progression") to classify 
      these patients. Clinical and ocular surface risk factors were determined through 
      a questionnaire, which included presence of eye rubbing, duration of indoor 
      activity, usage of lubricants and immunomodulator topical medications, duration 
      of computer use, hormonal disturbances, use of hand sanitizers, immunoglobulin E 
      (IgE), and vitamins D and B12 from blood investigations. An AI model was then 
      built to assess whether these risk factors were linked to the future progression 
      versus no progression of KC. The area under the curve (AUC) and other metrics 
      were evaluated. RESULTS: The tomographic AI model classified 322 eyes as 
      progression and 128 eyes as no progression. Also, 76% of the cases that were 
      classified as progression (from tomographic changes) were correctly predicted as 
      progression and 67% of cases that were classified as no progression were 
      predicted as no progression based on clinical risk factors at the first visit. 
      IgE had the highest information gain, followed by presence of systemic allergies, 
      vitamin D, and eye rubbing. The clinical risk factors AI model achieved an AUC of 
      0.812. CONCLUSION: This study demonstrated the importance of using AI for risk 
      stratification and profiling of patients based on clinical risk factors, which 
      could impact the progression in KC eyes and help manage them better.
FAU - Kundu, Gairik
AU  - Kundu G
AD  - Department of Cornea and Refractive Surgery, Narayana Nethralaya, Bengaluru, 
      Karnataka, India.
FAU - Shetty, Naren
AU  - Shetty N
AD  - Department of Cataract and Refractive Surgery, Narayana Nethralaya, Bengaluru, 
      Karnataka, India.
FAU - Shetty, Rohit
AU  - Shetty R
AD  - Department of Cornea and Refractive Surgery, Narayana Nethralaya, Bengaluru, 
      Karnataka, India.
FAU - Khamar, Pooja
AU  - Khamar P
AD  - Department of Cataract and Refractive Surgery, Narayana Nethralaya, Bengaluru, 
      Karnataka, India.
FAU - D'Souza, Sharon
AU  - D'Souza S
AD  - Department of Cornea and Refractive Surgery, Narayana Nethralaya, Bengaluru, 
      Karnataka, India.
FAU - Meda, Tulasi R
AU  - Meda TR
AD  - Department of Cataract and Refractive Surgery, Narayana Nethralaya, Bengaluru, 
      Karnataka, India.
FAU - Nuijts, Rudy M M A
AU  - Nuijts RMMA
AD  - Department of Ophthalmology, Maastricht University Medical Center, Maastricht, 
      The Netherlands.
FAU - Narasimhan, Raghav
AU  - Narasimhan R
AD  - Imaging, Biomechanics and Mathematical Modeling Solutions, Narayana Nethralaya 
      Foundation, Bengaluru, Karnataka, India.
FAU - Roy, Abhijit Sinha
AU  - Roy AS
AD  - Imaging, Biomechanics and Mathematical Modeling Solutions, Narayana Nethralaya 
      Foundation, Bengaluru, Karnataka, India.
LA  - eng
PT  - Journal Article
PL  - India
TA  - Indian J Ophthalmol
JT  - Indian journal of ophthalmology
JID - 0405376
RN  - 37341-29-0 (Immunoglobulin E)
SB  - IM
MH  - Humans
MH  - *Keratoconus/diagnosis/epidemiology
MH  - Cornea
MH  - Corneal Topography/methods
MH  - Artificial Intelligence
MH  - Risk Factors
MH  - Immunoglobulin E
MH  - Demography
PMC - PMC10391495
OTO - NOTNLM
OT  - Artificial intelligence
OT  - demographics
OT  - keratoconus
OT  - progression
OT  - tomography
COIS- None
EDAT- 2023/05/19 06:42
MHDA- 2023/05/22 06:42
PMCR- 2023/05/01
CRDT- 2023/05/19 01:49
PHST- 2023/05/22 06:42 [medline]
PHST- 2023/05/19 06:42 [pubmed]
PHST- 2023/05/19 01:49 [entrez]
PHST- 2023/05/01 00:00 [pmc-release]
AID - IndianJOphthalmol_2023_71_5_1882_377010 [pii]
AID - IJO-71-1882 [pii]
AID - 10.4103/IJO.IJO_2651_22 [doi]
PST - ppublish
SO  - Indian J Ophthalmol. 2023 May;71(5):1882-1888. doi: 10.4103/IJO.IJO_2651_22.