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Glaucoma management in Sweden – results from a nationwide survey

2011· article· en· W1976465030 on OpenAlexaboutno aff
Christina Lindén, Boel Bengtsson, Albert Alm, Berit Calissendorff, Ingemar Eckerlund, Anders Heijl

Bibliographic record

VenueActa Ophthalmologica · 2011
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsnot available
Fundersnot available
KeywordsGlaucomaMedicineOptometryQuarter (Canadian coin)Eye careFundus photographyPrivate practiceFundus (uterus)Family medicineOutpatient clinicOphthalmologyVisual acuity

Abstract

fetched live from OpenAlex

PURPOSE: To report the results from a nationwide survey on glaucoma management in Sweden, performed as a part of an Open Angle Glaucoma project conducted by the Swedish Council on Health Technology Assessment 2004-2008. METHODS: In 2005, a survey was distributed to all providers of glaucoma care in Sweden: public eye departments, public outpatient departments and private practices. The questionnaire included questions on number of examined patients, types of examinations during one defined week, internal organization and access to diagnostic equipment. The questionnaire was endorsed by the Swedish Ophthalmological Society. Reminders were sent out to nonresponders. RESULTS: Response rate was high; 97% (33/34) of eye departments, 85% (39/46) of outpatient departments and 55% (69/125) of private practices. Out of 29 282 visits in ophthalmic care during the study week, 7737 (26%) were related to glaucoma. Diagnostic equipment was generally available; all public eye facilities and 92% of private practices had at least one computerized perimeter, while equipment for fundus photography/imaging was available at 100% of eye departments, 82% of outpatient departments and 62% of private practices. The number of visual field tests and fundus images was rather low. Survey results indicate that patients on the average underwent bilateral field testing every 2nd year and fundus imaging every 8th year. CONCLUSION: Glaucoma care generated about a quarter of all patient visits in Swedish ophthalmic care. Access to diagnostic facilities was good. To meet modern standards of glaucoma care, glaucoma damage must be measured and followed more closely than at the time of the survey.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.676

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.072
GPT teacher head0.302
Teacher spread0.230 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations10
Published2011
Admission routes1
Has abstractyes

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