|
 
 |
| INNOVATIONS |
|
| Year : 2020 | Volume
: 32
| Issue : 3 | Page : 305-310 |
|
Eye grader-smartphone app for clinical grading scales in ophthalmology
John Davis Akkara1, Anju Kuriakose2
1 Department of Ophthalmology, Sri Ramachandra Institute of Higher Education and Research, Chennai, Tamil Nadu; Department of Glaucoma, Westend Eye Hospital, Cochin; Department of Glaucoma, Little Flower Hospital, Angamaly, Kerala, India
2 Department of Ophthalmology; Department of Retina, Aravind Eye Hospital, Chennai, Tamil Nadu, India
| Date of Submission | 02-Nov-2020 |
| Date of Acceptance | 03-Nov-2020 |
| Date of Web Publication | 23-Dec-2020 |
Correspondence Address:
Dr. John Davis Akkara
Department of Glaucoma, Westend Eye Hospital, Chitoor Road, Kacheripady, Cochin - 682 018, Kerala
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/kjo.kjo_176_20
Clinical grading scales help us to objectively document clinical findings. Even though there are several good clinical grading scales, it is not feasible to memorize all of them. It would be very convenient to have all this information at your fingertips. Noting the absence of any existing app, the authors programmed a smartphone app with all the necessary grading systems. This app should be useful for all ophthalmic clinicians to quickly lookup these grading systems and helps in objective documentation.
Keywords: Clinical grading, clinical scales, eye grader, ophthalmic app, smartphone app
How to cite this article:
Akkara JD, Kuriakose A. Eye grader-smartphone app for clinical grading scales in ophthalmology. Kerala J Ophthalmol 2020;32:305-10 |
| Introduction | |  |
Clinical grades and scales help in the standardization of documentation and have several advantages.[1] They are essential in measuring, recording, and monitoring changes in clinical signs. These help in objective documentation of the magnitude or severity of clinical findings. Most of them are numeric grades or scales and have four or five-step scales of severity. Bailey et al. discussed how qualitative and quantitative grading systems can be improved with finer scaling to enhance the ability to detect smaller degrees of change.[1]
There are several clinical signs in ophthalmology and several grading systems for each of them. It is practically impossible to memorize all the grading systems, and this difficulty leads to the poor utility of these otherwise useful clinical instruments. Often, grading scales are ignored, or approximate measures are used, and sometimes, they are misremembered or wrongly interpreted. This leads to confusion in the documentation, and a lot of valuable clinical information is lost, especially when communicating between multiple clinicians.
Smartphones are now ubiquitous and have been driving innovation in several fields, including ophthalmology.[2] We had previously discussed several innovative apps for ophthalmologists[3] and for visually impaired persons.[4] We decided to make a smartphone app, “Eye Grader”[5] which provides and offline, searchable database of clinical grading scales which can be readily accessed by a busy ophthalmologist, optometrist or eye care personnel so that objective documentation of the clinical findings can be easily done and quickly interpreted.
| Clinical Grading Scale Systems | | |
Proper use of grading scales improves the standard of record-keeping which results in improved medicolegal evidence. It helps in standardization, which leads to reduced inter- and intraobserver variability. This is especially relevant when patient care is by multiple clinicians. It helps in precise monitoring and earlier detection of disease progression and the effectiveness of interventions. Last but not least, it helps in better doctor-patient communication of the disease status.
Several studies have looked at clinical grading scales and their reliability. Chong et al. evaluated Verbal Descriptor Scales, Photographic Matching Scale, and Continuous Matching Scale for anterior segment findings such as conjunctival staining and bulbar redness and found good reliability.[6] Schulze et al. noted that perceived redness is based on chromaticity and vessel-based components.[7] Later, they investigated the effect of reference anchors in arranging images of bulbar redness.[8] They also investigated cross-calibrated reference scales for bulbar redness.[9] Efron proposed grading scales for the severity of eight common complications of contact lens wear.[10] Efron et al. also validated scales for contact lens complications.[11] Murphy et al. investigated interobserver agreement of Cornea and Contact Lens Research Unit grading scale for bulbar conjunctival hyperemia.[12] MacKinven et al. studied a modified scale with decimal increments for palpebral conjunctiva redness and roughness with good results on the agreement.[13] Park et al. established that image analysis with the Contrast-Limited Adaptive Histogram Equalization algorithm was useful for objectively grading conjunctival redness compared to three other methods they tested.[14] Wolffsohn used computer image analysis on printed grading scales of the anterior segment and identified that increments followed a quadratic than a linear function and that image analysis was up to 35 times more repeatable that subjective grading.[15] Rahman et al. published their work on training field graders for trachoma using conjunctival photographs.[16]
Huang et al. validated a new pterygium grading scale with five parameters for research and clinical trials.[17] Bonini et al. proposed a clinical grading system for vernal keratoconjunctivitis based on the severity of disease.[18] Zhong et al. proposed a grading system for limbal dermoid with postoperative prognostic value.[19] Ong et al. validated a semi-quantitative tool for clinical assessment of cicatrizing conjunctivitis.[20]
Sook Chun and Park studied the reliability of four grading systems for corneal staining and noted that the National Eye Institute system had the best reliability and repeatability.[21] Dundas et al. used a photographic grading scale for corneal staining and noted low interobserver variability and suggested that decimal increments can be used.[22]
Bell et al. evaluated the grading of Relative Afferent Pupillary Defect (RAPD) by swinging flashlight test and compared with neutral density filters and found good correlation.[23] Yotharak and Aui-Aree also found good correlation between the similar clinical plus scale for RAPD (used in Thailand) with neutral density filters.[24] They suggest that the swinging flashlight grading can be converted into log units if necessary.
Taylor and West proposed a system for slit lamp grading of lens opacities with standard photographs.[25] Gali et al. published a comprehensive summary of cataract grading systems[26], including the use of deep learning and artificial intelligence.[27]
Hornbeak et al. evaluated a new 9-step scale for vitreous haze compared to the existing 6-step scale.[28] Xu et al. proposed and validated a clinical grading system for the experimental autoimmune uveitis animal model for laboratories.[29] Seddon et al. validated a 5-level clinical classification system for age-related maculopathy (ARM) known as the clinical ARM staging system.[30] Sliesoraityte et al. proposed a grading system for optical coherence tomography scans for cystic macular lesions in usher syndrome patients.[31] Ohno-Matsui et al. proposed a classification for myopic Maculopathy.[32] Bhardwaj et al. proposed a grading system for retinal hemorrhages in abusive head trauma.[33] Lee et al. proposed a grading system for Sunset Glow Fundus in Vogt-Koyanagi-Harada disease.[34] Gangaputra et al. from the Fundus Photograph Reading Center at University of Wisconsin compared standardized clinical classification with fundus photograph reading for diabetic retinopathy and diabetic macular edema.[35]
Wells et al. evaluated the Moorfields bleb grading system and the Indiana bleb appearance grading scale and noted good clinical reproducibility and minor deficiencies, which could be improved.[36] Bouremel et al. mathematically modeled blebs using bleb height, area, and pressure measured in rabbit eyes and other in vitro methods.[37]
Barrio-Barrio et al. compared vision, inflammation, strabismus, and appearance (VISA), and the European Group of Graves' Orbitopathy classifications for Graves' Ophthalmopathy.[38] Peter Dolman reviewed the methods of grading severity of thyroid eye disease focusing on VISA.[39]
| Making of “Eye Grader” App | | |
With the help of ophthalmology postgraduate residents preparing for their examinations, the authors collected several clinical grading scales most relevant to practicing ophthalmologists and formatted the data for uniformity and accuracy. Using the app-building tool PhoneGap, the authors compiled the collected information into an Android-based smartphone App “Eye Grader”[5] and uploaded it on the Google Play store. The iPhone version was delayed due to the higher cost involved. As of October 2020, the app had around 3000 downloads from around 80 countries, with the maximum users being from India, the USA, Mexico, Egypt, and Jordan. Any suggestions for improving the app can be sent to the author, preferably at [email protected]
| Using “Eye Grader” App | | |
The “Eye Grader” App can be searched for and downloaded from the Google Play store [Figure 1]. (https://play.google.com/store/apps/details?id = com.fundazone.eyegrader). When opening the app, it opens to a page with sections for Cataract, Glaucoma, Retina, Cornea, Oculoplasty, Neuro-ophthalmology, Squint, and Others [Figure 2]. These sections have the corresponding grading systems related to the sub-specialty [Figure 3] and [Figure 4]. In addition, there is a search box where you can type and search for any word in the name of the grading scale [Figure 5]. On opening a particular grading scale, it shows the grading system along with any images where needed [Figure 6] and [Figure 7]. | Figure 2: Page showing the grading systems grouped according to sub-specialties
Click here to view |
| Conclusion | | |
The eye grader app is a free tool for ophthalmologists to help in objective documentation of clinical signs using standardized clinical grading scales. Validation of the usefulness and widespread use of this app would allow better communication between ophthalmic personnel of patient's clinical condition.
Acknowledgment
The author would like thank to Dr Jyothi Rajasekhar and other ophthalmology postgraduate students at little flower hospital and research centre, Angamaly, Kerala, for collecting the grading scale information that was used for creating the eye grader app and for expressing the need for such an app.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
| References | | |
| 1. | Bailey IL, Bullimore MA, Raasch TW, Taylor HR. Clinical grading and the effects of scaling. Invest Ophthalmol Vis Sci 1991;32:422-32.  |
| 2. | Akkara JD. Commentary: Dawn of smartphones in frugal ophthalmic innovation. Indian J Ophthalmol 2018;66:1619. [ PUBMED] [Full text] |
| 3. | Akkara J, Kuriakose A. Innovative smartphone apps for ophthalmologists. Kerala J Ophthalmol 2018;30:138-44. [Full text] |
| 4. | Akkara J, Kuriakose A. Smartphone apps for visually impaired persons. Kerala J Ophthalmol 2019;31:242-8. [Full text] |
| 5. | |
| 6. | Chong T, Simpson T, Fonn D. The repeatability of discrete and continuous anterior segment grading scales. Optom Vis Sci 2000;77:244-51. |
| 7. | Schulze MM, Hutchings N, Simpson TL. The perceived bulbar redness of clinical grading scales. Optom Vis Sci 2009;86:E1250-8. |
| 8. | Schulze MM, Hutchings N, Simpson TL. The conversion of bulbar redness grades using psychophysical scaling. Optom Vis Sci 2010;87:159-67. |
| 9. | Schulze MM, Hutchings N, Simpson TL. Grading bulbar redness using cross-calibrated clinical grading scales. Invest Ophthalmol Vis Sci 2011;52:5812-7. |
| 10. | Efron N. Grading scales for contact lens complications. Ophthalmic Physiol Opt 1998;18:182-6. |
| 11. | Efron N, Morgan PB, Katsara SS. Validation of grading scales for contact lens complications. Ophthalmic Physiol Opt 2001;21:17-29. |
| 12. | Murphy PJ, Lau JS, Sim MM, Woods RL. How red is a white eye? Clinical grading of normal conjunctival hyperaemia. Eye (Lond) 2007;21:633-8. |
| 13. | MacKinven J, McGuinness CL, Pascal E, Woods RL. Clinical grading of the upper palpebral conjunctiva of non-contact lens wearers. Optom Vis Sci 2001;78:13-8. |
| 14. | Park IK, Chun YS, Kim KG, Yang HK, Hwang JM. New clinical grading scales and objective measurement for conjunctival injection. Invest Ophthalmol Vis Sci 2013;54:5249-57. |
| 15. | Wolffsohn JS. Incremental nature of anterior eye grading scales determined by objective image analysis. Br J Ophthalmol 2004;88:1434-8. |
| 16. | Rahman SA, Yu SN, Amza A, Gebreselassie S, Kadri B, Baido N, et al. Reliability of trachoma clinical grading Assessing grading of marginal cases. PLoS Negl Trop Dis 2014;8:e2840. |
| 17. | Huang P, Huang J, Tepelus T, Maram J, Sadda S, Lee OL. Validity of a new comprehensive pterygia grading scale for use in clinical research and clinical trial. Int Ophthalmol 2018;38:2303-11. |
| 18. | Bonini S, Sacchetti M, Mantelli F, Lambiase A. Clinical grading of vernal keratoconjunctivitis. Curr Opin Allergy Clin Immunol 2007;7:436-41. |
| 19. | Zhong J, Deng Y, Zhang P, Li S, Huang H, Wang B, et al. New grading system for limbal dermoid: A retrospective analysis of 261 cases over a 10-year period. Cornea 2018;37:66-71. |
| 20. | Ong HS, Minassian D, Rauz S, Mehta JS, Dart JK. Validation of a clinical assessment tool for cicatrising conjunctivitis. Ocul Surf 2020;18:121-9. |
| 21. | Sook Chun Y, Park IK. Reliability of 4 clinical grading systems for corneal staining. Am J Ophthalmol 2014;157:1097-102. |
| 22. | Dundas M, Walker A, Woods RL. Clinical grading of corneal staining of non-contact lens wearers. Ophthalmic Physiol Opt 2001;21:30-5. |
| 23. | Bell RA, Waggoner PM, Boyd WM, Akers RE, Yee CE. Clinical grading of relative afferent pupillary defects. Arch Ophthalmol 1993;111:938-42. |
| 24. | Yotharak P, Aui-Aree N. Correlation between clinical grading and quantification by neutral density filter of relative afferent pupillary defect (RAPD). J Med Assoc Thail Chotmaihet Thangphaet 2012;95 Suppl 4:S92-5. |
| 25. | Taylor HR, West SK. The clinical grading of lens opacities. Aust N Z J Ophthalmol 1989;17:81-6. |
| 26. | Gali HE, Sella R, Afshari NA. Cataract grading systems: A review of past and present. Curr Opin Ophthalmol 2019;30:13-8. |
| 27. | Akkara JD, Kuriakose A. Role of artificial intelligence and machine learning in ophthalmology. Kerala J Ophthalmol 2019;31:150. [Full text] |
| 28. | Hornbeak DM, Payal A, Pistilli M, Biswas J, Ganesh SK, Gupta V, et al. Interobserver agreement in clinical grading of vitreous haze using alternative grading scales. Ophthalmology 2014;121:1643-8. |
| 29. | Xu H, Koch P, Chen M, Lau A, Reid DM, Forrester JV. A clinical grading system for retinal inflammation in the chronic model of experimental autoimmune uveoretinitis using digital fundus images. Exp Eye Res 2008;87:319-26. |
| 30. | Seddon JM, Sharma S, Adelman RA. Evaluation of the clinical age-related maculopathy staging system. Ophthalmology 2006;113:260-6. |
| 31. | Sliesoraityte I, Peto T, Mohand-Said S, Sahel JA. Novel grading system for quantification of cystic macular lesions in Usher syndrome. Orphanet J Rare Dis 2015;10:157. |
| 32. | Ohno-Matsui K, Kawasaki R, Jonas JB, Cheung CM, Saw SM, Verhoeven VJ, et al. International photographic classification and grading system for myopic maculopathy. Am J Ophthalmol 2015;159:877-83.e7. |
| 33. | Bhardwaj G, Jacobs MB, Martin FJ, Donaldson C, Moran KT, Vollmer-Conna U, et al. Grading system for retinal hemorrhages in abusive head trauma: Clinical description and reliability study. J AAPOS 2014;18:523-8. |
| 34. | Lee EK, Lee SY, Yu HG. A clinical grading system based on ultra-wide field retinal imaging for sunset glow fundus in Vogt-Koyanagi-Harada disease. Graefes Arch Clin Exp Ophthalmol 2015;253:359-68. |
| 35. | Gangaputra S, Lovato JF, Hubbard L, Davis MD, Esser BA, Ambrosius WT, et al. Comparison of standardized clinical classification with fundus photograph grading for the assessment of diabetic retinopathy and diabetic macular edema severity. Retina 2013;33:1393-9. |
| 36. | Wells AP, Ashraff NN, Hall RC, Purdie G. Comparison of two clinical Bleb grading systems. Ophthalmology 2006;113:77-83. |
| 37. | Bouremel Y, Lee RMH, Eames I, Brocchini S, Khaw PT. Novel approaches to model effects of subconjunctival blebs on flow pressure to improve clinical grading systems after glaucoma drainage surgery. PLoS One 2019;14:e0221715. |
| 38. | Barrio-Barrio J, Sabater AL, Bonet-Farriol E, Velázquez-Villoria Á, Galofré JC. Graves' Ophthalmopathy: VISA versus EUGOGO classification, assessment, and management. J Ophthalmol 2015;2015:249125. |
| 39. | Dolman PJ. Grading severity and activity in thyroid eye disease. Ophthal Plast Reconstr Surg 2018;34 4S Suppl 1:S34-40. |
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7]
|
Search Pubmed for