Diagnostic test accuracy using digital retinal imaging in the detection of any diabetic retinopathy by graders in Vietnam, against a reference standard from the UK

BACKGROUND Diabetic retinopathy (DR), a common complication of diabetes mellitus, is the leading cause of impaired vision in adults worldwide. Smartphone ophthalmoscopy involves using a smartphone camera for digital retinal imaging. Utilizing smartphones to detect DR is potentially more affordable, accessible, and easier to use than conventional methods. OBJECTIVE This study aimed to determine the diagnostic accuracy of various smartphone ophthalmoscopy approaches for detecting DR in diabetic patients. METHODS We performed an electronic search on the Medical Literature Analysis and Retrieval System Online (MEDLINE), EMBASE, and Cochrane Library for literature published from January 2000 to November 2018. We included studies involving diabetic patients, which compared the diagnostic accuracy of smartphone ophthalmoscopy for detecting DR to an accurate or commonly employed reference standard, such as indirect ophthalmoscopy, slit-lamp biomicroscopy, and tabletop fundus photography. Two reviewers independently screened studies against the inclusion criteria, extracted data, and assessed the quality of included studies using the Quality Assessment of Diagnostic Accuracy Studies–2 tool, with disagreements resolved via consensus. Sensitivity and specificity were pooled using the random effects model. A summary receiver operating characteristic (SROC) curve was constructed. This review is reported in line with the Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies guidelines. RESULTS In all, nine studies involving 1430 participants were included. Most studies were of high quality, except one study with limited applicability because of its reference standard. The pooled sensitivity and specificity for detecting any DR was 87% (95% CI 74%-94%) and 94% (95% CI 81%-98%); mild nonproliferative DR (NPDR) was 39% (95% CI 10%-79%) and 95% (95% CI 91%-98%); moderate NPDR was 71% (95% CI 57%-81%) and 95% (95% CI 88%-98%); severe NPDR was 80% (95% CI 49%-94%) and 97% (95% CI 88%-99%); proliferative DR (PDR) was 92% (95% CI 79%-97%) and 99% (95% CI 96%-99%); diabetic macular edema was 79% (95% CI 63%-89%) and 93% (95% CI 82%-97%); and referral-warranted DR was 91% (95% CI 86%-94%) and 89% (95% CI 56%-98%). The area under SROC curve ranged from 0.879 to 0.979. The diagnostic odds ratio ranged from 11.3 to 1225. CONCLUSIONS We found heterogeneous evidence showing that smartphone ophthalmoscopy performs well in detecting DR. The diagnostic accuracy for PDR was highest. Future studies should standardize reference criteria and classification criteria and evaluate other available forms of smartphone ophthalmoscopy in primary care settings.

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Use of Smartphones to Detect Diabetic Retinopathy: Scoping Review and Meta-Analysis of Diagnostic Test Accuracy Studies

Journal of Medical Internet Research ◽

10.2196/16658 ◽

2020 ◽

Vol 22 (5) ◽

pp. e16658

Author(s):

Choon Han Tan ◽

Bhone Myint Kyaw ◽

Helen Smith ◽

Colin S Tan ◽

Lorainne Tudor Car

Keyword(s):

Diabetic Retinopathy ◽

Diagnostic Accuracy ◽

Diagnostic Test ◽

Sensitivity And Specificity ◽

Meta Analysis ◽

Diagnostic Test Accuracy ◽

Fundus Photography ◽

Diabetic Patients ◽

Test Accuracy ◽

Reference Standard

Background Diabetic retinopathy (DR), a common complication of diabetes mellitus, is the leading cause of impaired vision in adults worldwide. Smartphone ophthalmoscopy involves using a smartphone camera for digital retinal imaging. Utilizing smartphones to detect DR is potentially more affordable, accessible, and easier to use than conventional methods. Objective This study aimed to determine the diagnostic accuracy of various smartphone ophthalmoscopy approaches for detecting DR in diabetic patients. Methods We performed an electronic search on the Medical Literature Analysis and Retrieval System Online (MEDLINE), EMBASE, and Cochrane Library for literature published from January 2000 to November 2018. We included studies involving diabetic patients, which compared the diagnostic accuracy of smartphone ophthalmoscopy for detecting DR to an accurate or commonly employed reference standard, such as indirect ophthalmoscopy, slit-lamp biomicroscopy, and tabletop fundus photography. Two reviewers independently screened studies against the inclusion criteria, extracted data, and assessed the quality of included studies using the Quality Assessment of Diagnostic Accuracy Studies–2 tool, with disagreements resolved via consensus. Sensitivity and specificity were pooled using the random effects model. A summary receiver operating characteristic (SROC) curve was constructed. This review is reported in line with the Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies guidelines. Results In all, nine studies involving 1430 participants were included. Most studies were of high quality, except one study with limited applicability because of its reference standard. The pooled sensitivity and specificity for detecting any DR was 87% (95% CI 74%-94%) and 94% (95% CI 81%-98%); mild nonproliferative DR (NPDR) was 39% (95% CI 10%-79%) and 95% (95% CI 91%-98%); moderate NPDR was 71% (95% CI 57%-81%) and 95% (95% CI 88%-98%); severe NPDR was 80% (95% CI 49%-94%) and 97% (95% CI 88%-99%); proliferative DR (PDR) was 92% (95% CI 79%-97%) and 99% (95% CI 96%-99%); diabetic macular edema was 79% (95% CI 63%-89%) and 93% (95% CI 82%-97%); and referral-warranted DR was 91% (95% CI 86%-94%) and 89% (95% CI 56%-98%). The area under SROC curve ranged from 0.879 to 0.979. The diagnostic odds ratio ranged from 11.3 to 1225. Conclusions We found heterogeneous evidence showing that smartphone ophthalmoscopy performs well in detecting DR. The diagnostic accuracy for PDR was highest. Future studies should standardize reference criteria and classification criteria and evaluate other available forms of smartphone ophthalmoscopy in primary care settings.

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Observed Differences in Diagnostic Test Accuracy between Patient Subgroups: Is It Real or Due to Reference Standard Misclassification?

Clinical Chemistry ◽

10.1373/clinchem.2007.087403 ◽

2007 ◽

Vol 53 (10) ◽

pp. 1725-1729 ◽

Cited By ~ 15

Author(s):

Corné Biesheuvel ◽

Les Irwig ◽

Patrick Bossuyt

Keyword(s):

Clinical Practice ◽

Diagnostic Test ◽

Sensitivity And Specificity ◽

Diagnostic Test Accuracy ◽

Test Accuracy ◽

Reference Standard ◽

Target Condition ◽

Test Sensitivity ◽

The Past ◽

Patient Subgroups

Abstract Before a new test is introduced in clinical practice, its accuracy should be assessed. In the past decade, researchers have put an increased emphasis on exploring differences in test sensitivity and specificity between patient subgroups. If the reference standard is imperfect and the prevalence of the target condition differs among subgroups, apparent differences in test sensitivity and specificity between subgroups may be caused by reference standard misclassification. We provide guidance on how to determine whether observed differences may be explained by reference standard misclassification. Such misclassification may be ascertained by examining how the apparent sensitivity and specificity change with the prevalence of the target condition in the subgroups.

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Diagnostic Test Accuracy of Diabetic Retinopathy Screening by Physician Graders Using a Hand-held Non-Mydriatic Retinal Camera at a Tertiary Level Medical Clinic

10.21203/rs.2.77/v3 ◽

2019 ◽

Author(s):

Mapa Mudiyanselage Prabhath Nishantha Piyasena ◽

Jennifer L.Y. Yip ◽

David MacLeod ◽

Min Kim ◽

Venkata S. Murthy Gudlavalleti

Keyword(s):

Diabetic Retinopathy ◽

Diagnostic Test ◽

Predictive Value ◽

Digital Camera ◽

Diagnostic Test Accuracy ◽

Test Accuracy ◽

Medical Clinic ◽

Middle Income ◽

Diabetic Retinopathy Screening ◽

Before And After

Abstract Background The evidence on diagnostic test accuracy (DTA) of diabetic retinopathy (DR) screening utilising photographic studies by non-ophthalmologist personnel in low and middle-income country (LMIC) settings is scarce. We aimed to assess DTA of DR screening using a nonmydriatic hand-held digital camera by trained general physicians in a non-ophthalmic setting. Methods This study is a validation of a screening intervention. We selected 700 people with diabetes (PwDM) > 18 years of age, not previously screened or treated for DR, presenting at a tertiary medical clinic in Sri Lanka. Two-field retinal imaging was used to capture fundus images before and after pupil dilatation, using a hand-held non-mydriatic (Visuscout 100®-Germany) digital retinal camera. The images were captured and graded by two trained, masked independent physician graders. The DTA of different levels of DR was assessed comparing physician’s grading with a retinologist’s clinical examination by mydriatic bio-microscopy, according to a locally adopted guideline. Results Seven hundred eligible PwDM were screened by physician graders. The mean age of participants was 60.8 years (SD ±10.08) and mean duration of DM was 9.9 years (SD ±8.09). Ungradable image proportion in non-mydriatic imaging was 43.4% (either eye-31.3%, both eyes 12.1%). This decreased to 12.8% (either eye-11.6%, both eyes-1.2%) following pupil dilatation. In comparison to detection of any level of DR, a referable level DR (moderate non-proliferative DR and levels above) showed a higher level of DTA. The sensitivity of the defined referable DR was 88.7% (95% CI 81.7-93.8%) for grader 1 (positive predictive value [PPV] 59.1%) and 92.5% (95% CI 86.4-96.5%) for grader 2 (PPV 68%), using mydriatic imaging, after including ungradable images as screen positives. The specificity was 94.9% (95% CI 93.6-96.0%) for grader 1 (negative predictive value [NPV] 99%) and 96.4% (95% CI 95.3-97.3%) for grader 2 (NPV 99.4%). Conclusions The Physicians grading of images from a digital hand-held non-mydriatic camera at a medical clinic, with dilatation of pupil of those who have ungradable images, provides a valid modality to identify referable level of DR. This could be a feasible alternative modality to the existing opportunistic screening to improve the access and coverage.

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Diagnostic test accuracy of diabetic retinopathy screening by physician graders using a hand-held non-mydriatic retinal camera at a tertiary level medical clinic

BMC Ophthalmology ◽

10.1186/s12886-019-1092-3 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 6

Author(s):

Mapa Mudiyanselage Prabhath Nishant Piyasena ◽

Jennifer L. Y. Yip ◽

David MacLeod ◽

Min Kim ◽

Venkata S. Murthy Gudlavalleti

Keyword(s):

Diabetic Retinopathy ◽

Diagnostic Test ◽

Diagnostic Test Accuracy ◽

Tertiary Level ◽

Test Accuracy ◽

Medical Clinic ◽

Diabetic Retinopathy Screening ◽

Retinopathy Screening

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Use of smartphones for detecting diabetic retinopathy: a protocol for a scoping review of diagnostic test accuracy studies

BMJ Open ◽

10.1136/bmjopen-2018-028811 ◽

2019 ◽

Vol 9 (12) ◽

pp. e028811 ◽

Cited By ~ 1

Author(s):

Choon Han Tan ◽

Willie-Henri Quah ◽

Colin S H Tan ◽

Helen Smith ◽

Lorainne Tudor Car

Keyword(s):

Diabetic Retinopathy ◽

Diagnostic Test ◽

Scoping Review ◽

Diagnostic Test Accuracy ◽

Fundus Photography ◽

Primary Data ◽

Cochrane Library ◽

Future Research ◽

Diabetic Patients ◽

Test Accuracy

IntroductionDiabetic retinopathy (DR) is a common microvascular complication of diabetes mellitus and the leading cause of impaired vision in adults worldwide. Early detection and treatment for DR could improve patient outcomes. Traditional methods of detecting DR include the gold standard Early Treatment Diabetic Retinopathy Study seven standard fields fundus photography, ophthalmoscopy and slit-lamp biomicroscopy. These modalities can be expensive, difficult to access and require involvement of specialised healthcare professionals. With the development of mobile phone technology, there is a growing interest in their use for DR identification as this approach is potentially more affordable, accessible and easier to use. Smartphones can be employed in a variety of ways for ophthalmoscopy including the use of smartphone camera, various attachments and artificial intelligence for obtaining and grading of retinal images. The aim of this scoping review is to determine the diagnostic test accuracy of various smartphone ophthalmoscopy approaches for detecting DR in diabetic patients.Methods and analysisWe will perform an electronic search of MEDLINE, Embase and Cochrane Library for literature published from 2000 onwards. Two reviewers will independently analyse studies for eligibility and assess study quality using the QUADAS-2 tool. Data for a 2⨉2 contingency table will be extracted. If possible, we will pool sensitivity and specificity data using the random-effects model and construct a summary receiver operating characteristic curve. In case of high heterogeneity, we will present the findings narratively. Subgroup analysis and sensitivity analysis will be performed where appropriate.Ethics and disseminationThis scoping review aims to provide an overview of smartphone ophthalmoscopy in DR identification. It will present findings on the accuracy of smartphone ophthalmoscopy in detecting DR, identify gaps in the literature and provide recommendations for future research. This review does not require ethical approval as we will not collect primary data.

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Diagnostic Test Accuracy of Diabetic Retinopathy Screening by Physician Graders Using a Hand Held Non-Mydriatic Retinal Camera at a Tertiary Level Medical Clinic in a Lower-Middle Income Country Setting

10.21203/rs.2.77/v1 ◽

2018 ◽

Author(s):

Mapa Mudiyanselage Prabhath Nishantha Piyasena ◽

Jennifer L.Y. Yip ◽

David MacLeod ◽

Min Kim ◽

Venkata S. Murthy Gudlavalleti

Keyword(s):

Diabetic Retinopathy ◽

Sri Lanka ◽

Diagnostic Test ◽

Predictive Value ◽

Middle Income Country ◽

Diagnostic Test Accuracy ◽

Income Country ◽

Test Accuracy ◽

Medical Clinic ◽

Middle Income

Abstract Background We identified that there was less evidence on diagnostic test accuracy (DTA) of diabetic retinopathy (DR) screening photographic studies that have used non-ophthalmologist human resources in low and middle-income country (LMIC) settings. This study is the first to assess the DTA of physician graders using hand held digital imaging in Sri Lanka. We aimed to assess DTA of DR screening using a nonmydriatic hand-held digital camera by trained general physicians in a non-ophthalmic setting. This modality will be useful for adaptation in similar settings. Methods This study is a validation of a screening intervention. We selected people with diabetes (PwDM) not previously screened or treated for DR, presenting at a tertiary medical clinic in Sri Lanka. Two-field retinal imaging was used to capture fundus images before and after pupil dilatation. The images were captured and graded by two trained, masked independent physician graders. The DTA of different levels of DR was assessed comparing physician’s grading with a retinologist’s clinical examination according to a locally adopted guideline. Results Seven hundred eligible PwDM were screened by physician graders. Their mean age was 60.8 years (SD ±10.08) and mean duration of DM was 9.9 years (SD ±8.09). Ungradable image proportion in non-mydriatic imaging was 43.4% (either eye-31.3%, both eyes 12.1%). This decreased to 12.8% (either eye-11.6%, both eyes-1.2%) following pupil dilatation. In comparison to detection of any level of DR, a referable level DR (moderate non-proliferative DR and levels above) showed a higher level of DTA. The sensitivity of the defined referable DR was 88.7% (95% CI 81.7-93.8%) for grader 1 (positive predictive value [PPV] 59.1%) and 92.5% (95% CI 86.4-96.5%) for grader 2 (PPV 68%), using mydriatic imaging, after including ungradable images as screen positives. The specificity was 94.9% (95% CI 93.6-96.0%) for grader 1 (negative predictive value [NPV] 99%) and 96.4% (95% CI 95.3-97.3%) for grader 2 (NPV 99.4%). Conclusions The Physicians grading of images from a digital hand-held nonmydriatic camera was effective in identifying referable DR, following pupil dilatation. This could be a feasible alternative modality to the existing opportunistic screening to improve the access and coverage.

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Ultrasonography for the diagnosis of extra-cranial carotid occlusion – diagnostic test accuracy meta-analysis

VASA ◽

10.1024/0301-1526/a000850 ◽

2020 ◽

Vol 49 (3) ◽

pp. 195-204

Author(s):

Djamila M. Rojoa ◽

Ahmad Q. D. Lodhi ◽

Nikos Kontopodis ◽

Christos V. Ioannou ◽

Nicos Labropoulos ◽

...

Keyword(s):

Systematic Review ◽

Diagnostic Test ◽

Sensitivity And Specificity ◽

Meta Analysis ◽

Diagnostic Test Accuracy ◽

Carotid Occlusion ◽

Test Accuracy ◽

Free Text ◽

Correct Identification ◽

Reference Standard

Summary: Background: The correct diagnosis of internal carotid artery (ICA) occlusion is crucial as it limits unnecessary intervention, whereas correct identification of patients with severe ICA stenosis is paramount in decision making and selecting patients who would benefit from intervention. We aimed to evaluate the accuracy of ultrasonography (US) in the diagnosis of ICA occlusion. Methods: We conducted a systematic review in compliance with the Preferred Reporting Items for a Systematic Review and Meta-analysis (PRISMA) of diagnostic test accuracy studies. We interrogated electronic bibliographic sources using a combination of free text and thesaurus terms to identify studies assessing the diagnostic accuracy of US in ICA occlusion. We used a mixed-effects logistic regression bivariate model to estimate summary sensitivity and specificity. We developed hierarchical summary receiver operating characteristic (HSROC) curves. Results: We identified 23 studies reporting a total of 5,675 arteries of which 722 were proven to be occluded by the reference standard. The reference standard was digital subtraction or cerebral angiography in all but two studies, which used surgery to ascertain a carotid occlusion. The pooled estimates for sensitivity and specificity were 0.97 (95% confidence interval (CI) 0.94 to 0.99) and 0.99 (95% CI 0.98 to 1.00), respectively. The diagnostic odds ratio was 3,846.15 (95% CI 1,375.74 to 10,752.65). The positive and negative likelihood ratio were 114.71 (95% CI 58.84 to 223.63) and 0.03 (95% CI 0.01 to 0.06), respectively. Conclusions: US is a reliable and accurate method in diagnosing ICA occlusion. US can be used as a screening tool with cross-sectional imaging being reserved for ambiguous cases.

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Diagnostic Test Accuracy of Diabetic Retinopathy Screening by Physician Graders Using a Hand-held Non-Mydriatic Retinal Camera at a Tertiary Level Medical Clinic

10.21203/rs.2.77/v4 ◽

2019 ◽

Author(s):

Mapa Mudiyanselage Prabhath Nishantha Piyasena ◽

Jennifer L.Y. Yip ◽

David MacLeod ◽

Min Kim ◽

Venkata S. Murthy Gudlavalleti

Keyword(s):

Diabetic Retinopathy ◽

Diagnostic Test ◽

Predictive Value ◽

Digital Camera ◽

Diagnostic Test Accuracy ◽

Test Accuracy ◽

Medical Clinic ◽

Middle Income ◽

Diabetic Retinopathy Screening ◽

Before And After

Abstract Background The evidence on diagnostic test accuracy (DTA) of diabetic retinopathy (DR) screening utilising photographic studies by non-ophthalmologist personnel in low and middle-income country (LMIC) settings is scarce. We aimed to assess DTA of DR screening using a nonmydriatic hand-held digital camera by trained general physicians in a non-ophthalmic setting. Methods This study is a validation of a screening intervention. We selected 700 people with diabetes (PwDM) > 18 years of age, not previously screened or treated for DR, presenting at a tertiary medical clinic in Sri Lanka. Two-field retinal imaging was used to capture fundus images before and after pupil dilatation, using a hand-held non-mydriatic (Visuscout 100®-Germany) digital retinal camera. The images were captured and graded by two trained, masked independent physician graders. The DTA of different levels of DR was assessed comparing physician’s grading with a retinologist’s clinical examination by mydriatic bio-microscopy, according to a locally adopted guideline. Results Seven hundred eligible PwDM were screened by physician graders. The mean age of participants was 60.8 years (SD ±10.08) and mean duration of DM was 9.9 years (SD ±8.09). Ungradable image proportion in non-mydriatic imaging was 43.4% (either eye-31.3%, both eyes 12.1%). This decreased to 12.8% (either eye-11.6%, both eyes-1.2%) following pupil dilatation. In comparison to detection of any level of DR, a referable level DR (moderate non-proliferative DR and levels above) showed a higher level of DTA. The sensitivity of the defined referable DR was 88.7% (95% CI 81.7-93.8%) for grader 1 (positive predictive value [PPV] 59.1%) and 92.5% (95% CI 86.4-96.5%) for grader 2 (PPV 68%), using mydriatic imaging, after including ungradable images as screen positives. The specificity was 94.9% (95% CI 93.6-96.0%) for grader 1 (negative predictive value [NPV] 99%) and 96.4% (95% CI 95.3-97.3%) for grader 2 (NPV 99.4%). Conclusions The Physicians grading of images from a digital hand-held non-mydriatic camera at a medical clinic, with dilatation of pupil of those who have ungradable images, provides a valid modality to identify referable level of DR. This could be a feasible alternative modality to the existing opportunistic screening to improve the access and coverage.

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Diagnostic Test Accuracy of Diabetic Retinopathy Screening by Physician Graders Using a Hand Held Non-Mydriatic Retinal Camera at a Tertiary Level Medical Clinic in a Lower-Middle Income Country Setting

10.21203/rs.2.77/v2 ◽

2019 ◽

Author(s):

Mapa Mudiyanselage Prabhath Nishantha Piyasena ◽

Jennifer L.Y. Yip ◽

David MacLeod ◽

Min Kim ◽

Venkata S. Murthy Gudlavalleti

Keyword(s):

Diabetic Retinopathy ◽

Diagnostic Test ◽

Predictive Value ◽

Digital Camera ◽

Middle Income Country ◽

Diagnostic Test Accuracy ◽

Income Country ◽

Test Accuracy ◽

Medical Clinic ◽

Middle Income

Abstract Background The evidence on diagnostic test accuracy (DTA) of diabetic retinopathy (DR) screening utilising photographic studies by non-ophthalmologist personnel in low and middle-income country (LMIC) settings is scarce. We aimed to assess DTA of DR screening using a nonmydriatic hand-held digital camera by trained general physicians in a non-ophthalmic setting. Methods This study is a validation of a screening intervention. We selected 700 people with diabetes (PwDM) > 18 years of age, not previously screened or treated for DR, presenting at a tertiary medical clinic in Sri Lanka. Two-field retinal imaging was used to capture fundus images before and after pupil dilatation, using a hand-held non-mydriatic (Visuscout 100®-Germany) digital retinal camera. The images were captured and graded by two trained, masked independent physician graders. The DTA of different levels of DR was assessed comparing physician’s grading with a retinologist’s clinical examination by mydriatic bio-microscopy, according to a locally adopted guideline. Results Seven hundred eligible PwDM were screened by physician graders. The mean age of participants was 60.8 years (SD ±10.08) and mean duration of DM was 9.9 years (SD ±8.09). Ungradable image proportion in non-mydriatic imaging was 43.4% (either eye-31.3%, both eyes 12.1%). This decreased to 12.8% (either eye-11.6%, both eyes-1.2%) following pupil dilatation. In comparison to detection of any level of DR, a referable level DR (moderate non-proliferative DR and levels above) showed a higher level of DTA. The sensitivity of the defined referable DR was 88.7% (95% CI 81.7-93.8%) for grader 1 (positive predictive value [PPV] 59.1%) and 92.5% (95% CI 86.4-96.5%) for grader 2 (PPV 68%), using mydriatic imaging, after including ungradable images as screen positives. The specificity was 94.9% (95% CI 93.6-96.0%) for grader 1 (negative predictive value [NPV] 99%) and 96.4% (95% CI 95.3-97.3%) for grader 2 (NPV 99.4%). Conclusions The Physicians grading of images from a digital hand-held non-mydriatic camera at a medical clinic, with dilatation of pupil of those who have ungradable images, provides a valid modality to identify referable level of DR. This could be a feasible alternative modality to the existing opportunistic screening to improve the access and coverage.

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