Use of insulin glargine during embryogenesis in a pregnant woman with Type 1 diabetes
Bibliographic record
Abstract
Technical failure in photographic screening for diabetic retinopathyDiabetic retinopathy is the largest single cause of registered blindness among people of working age.At any time, 10% of the diabetic population may have retinopathy requiring ophthalmological follow-up or treatment [1].The two main approaches to diabetic retinopathy screening include regular ophthalmoscopic examination and retinal photography with subsequent grading.Digital fundus photography has greatly replaced slide and polaroid photography and is a cost-effective system.However, good quality images are essential for accurate grading to be possible.The National Screening Committee (NSC) recommends that the technical failure rate for digital fundus photography should be less than 5% (www.diabeticretinopathy.screening.nhs.uk).In order to determine if this target is achievable, we have audited the technical failure rate at St James University Hospital.We completed the audit cycle and looked at 150 consecutive retinal images in May 2002, and another 150 images in September 2002.The images were taken by two photographers, both of whom had received an initial training of 3 weeks to familiarize them with ophthalmic photography, and had 1 year of practical experience before the start of the study.Based on the National Screening Committee criteria, the set of images from each patient were classified as being a technical success or a technical failure due to photographic error, or a technical failure due to patient factors such as media opacity, small pupil or patients with difficulty in positioning.The images were considered a technical failure due to photographic error if the correct number of images had not been taken, the images were not centred well, or had poor clarity obscuring view of 1/3 or more of the temporal image or the large temporal blood vessels.If the image quality was poor, the photographers were asked to provide a red reflex image to demonstrate media opacity, small pupil, etc.With such supporting evidence, the images were to be considered technical failure due to media opacity.In its absence, it was presumed that it was a technical failure due to photographic error.Our technical failure rate in this completed audit cycle was 7%.We could not achieve the recommended technical failure rate less than 5% as suggested by NSC.In all, there were 13 (4.3%)technical failures due to media opacity, small pupil or difficult positioning of the patient.This figure did not differ much between the audits, being six in the first audit and seven in the second.There were eight technical failures due to photographic error, five in the first audit and three in the second.It is possible that continued discussion with the photographers may reduce this figure further.This study suggests that the technical failure rate is greatly dependent on patient variable factors like cataract, small pupil, etc. and hence may be difficult to achieve.However, if we are able to reduce the technical failure rate due to photographic error to less than 1%, and assuming that the images failing due to patient factor remain constant at around 4%, the standard proposed by NSC would be achievable.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".