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Record W7047011234

Erkennungsgüte und Kosteneffektivität von Screeningverfahren zur Erfassung von primären Offenwinkelglaukomen

2007· article· en· W7047011234 on OpenAlexaboutno aff

Bibliographic record

VenueGerman Medical Science (German Research Foundation) · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsnot available
Fundersnot available
KeywordsGlaucomaOphthalmoscopyIntraocular pressureOpen angle glaucomaOcular hypertensionOptic disc
DOInot available

Abstract

fetched live from OpenAlex

Health political background About 950,000 people are affected by glaucoma in Germany, about 50% of which are undiagnosed. The German Ophthalmological Society and the German Association of Ophthalmologists recommend a screening for glaucoma according to their guidelines. The Federal Joint Committee disapproved a glaucoma-screening program on expense of the compulsory health insurance in 2004. Scientific background Primary open angle glaucoma is diagnosed by evaluation of the optic disc, the retinal fibre layer and the visual field. The main examinations are ophthalmoscopy, scanning laser polarimetry, confocal scanning laser ophthalmoscopy, retinal thickness analysis and optical coherence tomography. Scotomas are diagnosed by perimetry (standard automated perimetry, short wavelength automated perimetry and frequency doubling perimetry). The intraocular pressure is the most important treatable risk factor and is measured by (contact or non-contact) tonometry. Research questions The aim of this HTA-report is to investigate the diagnostic validity and cost effectiveness of diagnostic techniques or combinations of these methods with respect to the use in a screening setting in Germany. Methods A systematic literature research was performed in 35 international databases and yielded 2602 articles. Overall 57 publications were included for assessment, according to predefined selection criteria. Results The 55 medical articles deal mainly with frequency doubling perimetry, confocal scanning laser ophthalmoscopy and scanning laser polarimetry. Few articles cover short wavelength automated perimetry, tonometry and ophalmocopic evaluations by ophthalmologists. The quality of the papers is generally low, as far as the evidence in respect of screening is concerned. No single method exists with both, high sensitivity and high specificity for screening purpose. Data are also not sufficient to recommend combinations of methods. Only two economic models on cost-effectivenes of screening investigations could be identified. No economic evaluations of the most recent methods can be found in the published literature. A British cost-effectiveness analysis calculates cost per true positives and favours a combination of ophthalmoscopy, tonometry and perimetry either for people at high risk for glaucoma or for the total population as an initial examination. A Canadian HTA-report models the cost per year of blindness avoided. The report concludes that because of a high degree of uncertainty with respect to the benefits and the high costs involved, the setting-up of a glaucoma-screening program cannot be supported. Discussion The literature shows that combinations of methods have to be used for screening of glaucoma in order to get reasonable values of sensitivity and specificity. Presently no combination of methods and no algorithm can be presented for glaucoma screening with sufficient evidence. Also no conclusions about cost-effectiveness for Germany can be made based on the available literature. Conclusions In order to find the optimal combination of methods for glaucoma-screening, population-based studies have to be performed. Therefore also no final conclusions can be drawn with respect to cost-effectiveness of glaucoma-screening methods. The economic evaluation of a clinical effective screening-method should consider the effects of blindness avoided, as well as effects on the prevention of visual impairment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.698
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.003
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.002

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.

Opus teacher head0.055
GPT teacher head0.422
Teacher spread0.367 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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