NICE – impact on glaucoma case detection

Aim:  To investigate the impact of publication of the National Institute of Clinical Excellence (NICE) guidelines (‘Glaucoma: diagnosis and management of chronic open angle glaucoma and ocular hypertension’) in April 2009, on the referrals for suspect glaucoma to Moorfields Community Eye Clinic (MCEC) at Ealing Hospital. / Methods:  The clinical data from all optometrist initiated referrals for suspect glaucoma and ocular hypertension were scrutinised by a Consultant Ophthalmologist for a 2 month period, 6 months after the publication of the NICE guidance. Each was then categorised into the following groups: glaucoma positive; glaucoma suspect; glaucoma negative; ocular hypertension (OHT) requiring further follow up in clinic; ocular hypertension to be followed up by community optometrist; other. The positive predictive value (PPV) was then calculated and a historical comparison made with previous studies. / Results:  A total of 110 new referrals were assessed during the collection period, which reflects a marked increase in numbers attending. However, there was no increase in absolute numbers of glaucoma and glaucoma suspects identified. The absolute numbers of ocular hypertensive patients rose. The PPV fell to 0.25, which is lower than found in previous studies. / Conclusions:  The rising number of new referrals and the unchanged absolute numbers of glaucoma and glaucoma suspects identified following publication of the NICE guidance, in addition to a lower PPV, makes us question what advantage in improved case detection this represents. Furthermore, is this a cost effective strategy? We believe the next step is to introduce a repeat review, with carefully considered clinical governance of any new scheme

Evaluation of a new rebound tonometer for self-measurement of intraocular pressure

BACKGROUND/AIMS: To compare the accuracy of self-obtained, partner-obtained and trainer-obtained measurements using the handheld Icare Home rebound tonometer with Goldmann applanation tonometry (GAT), and to evaluate the acceptability to subjects of Icare Home measurement. METHODS: 76 subjects were trained to use Icare Home for self-measurement using a standardised protocol. A prespecified checklist was used to assess the ability of a subject to perform self-tonometry. Accuracy of Icare Home self-measurement was compared with GAT using one eye per subject, randomly selected. Bland-Altman difference analysis was used to compare Icare Home and GAT intraocular pressure (IOP) estimates. Acceptability of self-tonometry was evaluated using a questionnaire. RESULTS: 56 subjects (74%, 95% CI 64 to 84) were able to correctly perform self-tonometry. Mean bias (95% limits of agreement) was 0.3 mm Hg (−4.6 to 5.2), 1.1 mm Hg (−3.2 to 5.3) and 1.2 mm Hg (−3.9 to 6.3) for self-assessment, partner-assessment and trainer-assessment, respectively, suggesting underestimation of IOP by Icare Home tonometry. Differences between GAT and Icare Home IOP were greater for central corneal thickness below 500 µm and above 600 µm than data points within this range. Acceptability questionnaire responses showed high agreement that the self-pressure device was easy to use (84%), the reading was quick to obtain (88%) and the measurement was comfortable (95%). CONCLUSIONS: Icare Home tonometry can be used for self-measurement by a majority of trained subjects. IOP measurements obtained using Icare Home tonometry by self-assessment and third party-assessment showed slight underestimation compared with GAT

A national survey of diagnostic tests reported by UK community optometrists for the detection of chronic open angle glaucoma

Purpose:  In the UK, the majority of cases of chronic open angle glaucoma are detected by community optometrists following a routine sight test. However, there is potential for variability in case finding strategies used. The aim of this study was to carry out a national web-based survey to determine current diagnostic tests used by optometrists in glaucoma case finding. / Methods:  Optometrists on the Association of Optometrists (AOP) electronic database were invited to participate. The survey was open for 16 weeks between April and July 2008. / Results:  A total of 1875 optometrists were eligible to enter the survey, of which 1264 answered the questions relating to diagnostic equipment. Respondents were asked to indicate their usual method of examining the optic nerve head. Direct ophthalmoscopy only was used by 25% with the majority (62%) using a combination of direct and slit-lamp binocular indirect methods. The vast majority of optometrists (78%) used non-contact tonometry to measure intraocular pressure, with only 16% routinely using a Goldmann or Perkins applanation tonometer. The perimeter most frequently used was either one of the Henson range of instruments (39%) or the Humphrey Field Analyser (22%). A smaller number of optometrists (<5%) had access to more specialised imaging equipment, such as HRT, GDx or OCT. / Conclusions:  The results of the survey demonstrate that UK optometrists are well equipped to carry out case finding for chronic open angle glaucoma, although there is a lack of standardisation with respect to equipment used

Are Eye Clinics Safe For The Road? An Observational Report

We report an observational study, based on the examination of 319 medical records, identifying the proportion of patients whose driving status was documented on the first and subsequent glaucoma clinic visits. We also established the proportion of patients with documented Driving and Vehicle Licencing Agency (DVLA)-related advice when they did not meet driving standards based on their visual acuity and/or visual fields (VF). On presentation, driving status was assessed in 61% (n=195) patients. Of the remaining 124, 44% (n=55) had their driving status documented at a subsequent visit, on an average 8 years later. Of all patients (78%, n=250) whose driving status was assessed at some stage, 42% (n=134) were drivers. Of the 203 patients who were either drivers or whose driving status was unknown, 37% (n=75) were assessed as having a visual acuity or bilateral VF defect that was below the legal limit for driving, 39 of whom were known drivers. Only 13 were advised to inform the DVLA, and only 5 patients were advised to update their spectacles or listed for surgery to improve their vision. We therefore potentially failed to perform our DVLA duty in 76% (n=57) of patients. We have made suggestions for improving the current performance in this respect based on the findings of this study

Teleglaucoma: ready to go?

Telemedicine technologies and services allow today's ophthalmic clinicians to remotely diagnose, manage and monitor several ophthalmic conditions from a distance. But is this the case for glaucomas? There has been a proliferation of telemedicine friendly devices in recent years that improves the capabilities of the clinician in managing glaucomas. The existing instruments still need to align themselves with accepted industry standards. There are successful programmes running in several areas of the world. The safety and efficacy of these programmes needs further exploration. The inability of a single device or test to diagnose glaucomas satisfactorily has also hampered progress in remotely diagnosing these conditions. There is, however, significant potential for telemedicine-friendly devices to remotely monitor the progress of glaucoma and, thereby, reduce some of the workload on an overstretched health service

Analysis of neonatal clinical trials with twin births

<p>Abstract</p> <p>Background</p> <p>In neonatal trials of pre-term or low-birth-weight infants, twins may represent 10–20% of the study sample. Mixed-effects models and generalized estimating equations are common approaches for handling correlated continuous or binary data. However, the operating characteristics of these methods for mixes of correlated and independent data are not well established.</p> <p>Methods</p> <p>Simulation studies were conducted to compare mixed-effects models and generalized estimating equations to linear regression for continuous outcomes. Similarly, mixed-effects models and generalized estimating equations were compared to ordinary logistic regression for binary outcomes. The parameter of interest is the treatment effect in two-armed clinical trials. Data from the National Institute of Child Health & Human Development Neonatal Research Network are used for illustration.</p> <p>Results</p> <p>For continuous outcomes, while the coverage never fell below 0.93, and the type I error rate never exceeded 0.07 for any method, overall linear mixed-effects models performed well with respect to median bias, mean squared error, coverage, and median width. For binary outcomes, the coverage never fell below 0.90, and the type I error rate never exceeded 0.07 for any method. In these analyses, when randomization of twins was to the same treatment group or done independently, ordinary logistic regression performed best. When randomization of twins was to opposite treatment arms, a rare method of randomization in this setting, ordinary logistic regression still performed adequately. Overall, generalized linear mixed models showed the poorest coverage values.</p> <p>Conclusion</p> <p>For continuous outcomes, using linear mixed-effects models for analysis is preferred. For binary outcomes, in this setting where the amount of related data is small, but non-negligible, ordinary logistic regression is recommended.</p

Combining macula clinical signs and patient characteristics for age-related macular degeneration diagnosis: a machine learning approach

Background: To investigate machine learning methods, ranging from simpler interpretable techniques to complex (non-linear) “black-box” approaches, for automated diagnosis of Age-related Macular Degeneration (AMD). Methods: Data from healthy subjects and patients diagnosed with AMD or other retinal diseases were collected during routine visits via an Electronic Health Record (EHR) system. Patients’ attributes included demographics and, for each eye, presence/absence of major AMD-related clinical signs (soft drusen, retinal pigment epitelium, defects/ pigment mottling, depigmentation area, subretinal haemorrhage, subretinal fluid, macula thickness, macular scar, subretinal fibrosis). Interpretable techniques known as white box methods including logistic regression and decision trees as well as less interpreitable techniques known as black box methods, such as support vector machines (SVM), random forests and AdaBoost, were used to develop models (trained and validated on unseen data) to diagnose AMD. The gold standard was confirmed diagnosis of AMD by physicians. Sensitivity, specificity and area under the receiver operating characteristic (AUC) were used to assess performance. Results: Study population included 487 patients (912 eyes). In terms of AUC, random forests, logistic regression and adaboost showed a mean performance of (0.92), followed by SVM and decision trees (0.90). All machine learning models identified soft drusen and age as the most discriminating variables in clinicians’ decision pathways to diagnose AMD. C Conclusions: Both black-box and white box methods performed well in identifying diagnoses of AMD and their decision pathways. Machine learning models developed through the proposed approach, relying on clinical signs identified by retinal specialists, could be embedded into EHR to provide physicians with real time (interpretable) support

How accurate is an LCD screen version of the Pelli–Robson test?

Purpose: To evaluate the accuracy and repeatability of a computer-generated Pelli–Robson test displayed on liquid crystal display (LCD) systems compared to a standard Pelli–Robson chart. Methods: Two different randomized crossover experiments were carried out for two different LCD systems for 32 subjects: 6 females and 10 males (40.5 ± 13.0 years) and 9 females and 7 males (27.8 ± 12.2 years), respectively, in the first and second experiment. Two repeated measurements were taken with the printed Pelli–Robson test and with the LCDs at 1 and 3 m. To test LCD reliability, measurements were repeated after 1 week. Results: In Experiment 1, contrast sensitivity (CS) measured with LCD1 resulted significantly higher than Pelli–Robson both at 1 and at 3 m of about 0.20 log 1/C in both eyes (p < 0.01). Bland–Altman plots showed a proportional bias for LCD1 measures. LCD1 measurements showed reasonable repeatability: ICC was 0.83 and 0.65 at 1 and 3 m, respectively. In Experiment 2, CS measured with LCD2 resulted significantly lower than Pelli–Robson both at 1 and at 3 m of about 0.10 log 1/C in both eyes (p < 0.01). Bland–Altman plots did not show any proportional bias for LCD2 measures. LCD2 measurements showed sufficient repeatability: ICC resulted 0.51 and 0.65 at 1 and 3 m, respectively. Conclusions: Computer-generated versions of Pelli–Robson test, displayed on LCD systems, do not provide accurate results compared to classic Pelli–Robson printed version. Clinicians should consider that Pelli–Robson computer-generated versions could be non-interchangeable to the printed version