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Pretreatment Clinical Variables Associated With the Response to Intravitreal Bevacisumab (Avastin) Injection In Patients With Persistent Diabetic Macular Edema

2010· article· en· W4391154635 on OpenAlexaff
Fareed A. Warid AL-Laftah, Maha Elshafie, Dr.Mustafa Alhashimi, Aant Pai

Bibliographic record

VenueJournal of the Faculty of Medicine Baghdad · 2010
Typearticle
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsHéma-Québec
Fundersnot available
KeywordsDiabetic macular edemaMedicineOphthalmologyMacular edemaDiabetes mellitusDiabetic retinopathyRetinalEndocrinology

Abstract

fetched live from OpenAlex

Background: The purpose of the study is to determine whether the pre-treatment clinical systemic variables and optical coherence tomographic (OCT) findings are associated with the subsequent response to the intravitreal Bevacisumab (IVB) in eyes with diabetic macular edema (DME).Patients and Methods: 38 patients (45 eyes) with refractory diabetic macular edema. ; 16 females, 22 males and mean age was 57.5 year. All patients had DME not responded to other treatments. Complete eye examination; BCVA* (represented as LOGMAR for adequate statistical analysis), slitlamp exam, intraocular pressure measurement, stereoscopic biomicroscopy of the macula, and morphologic patterns of diabetic macular edema demonstrated by OCT. All patients had intravitreal injection of 0.05mL =1.25 mg Bevacizumab (Avastin; Genentech, Inc.,San Francisco, CA), and followed up for 3 months. The pre and post-operative follow-up data were analyzed by Student-t test and Mann-Whitney test for two main outcome measures; visual acuity (LOGMAR) & central foveal thickness (CFT) changes over a period of three months, and data include demographic factors, type, duration and control of diabetes mellitus (HbA1C%), grade of diabetic retinopathy, renal function (serum creatinine level), serum cholesterol, blood pressure control and previous treatment by focal laser and/or intravitreal triamcinolone injection.Results: The visual acuity and CRT improved in 30/45 eyes (67%) and 32/45 eyes (72%) respectively during a mean follow-up time of three months. The mean LogMAR visual acuities were 0.64 (SD ± 0.34), 0.61 (SD ± 0.31) and 0.60 (SD ± 0.32) at pre-injection, at 1 month post-injection and at 3 months post-injection respectively; but this mean increase in vision was statistically not significant (P value = 0.099). The mean foveal thicknesses were 444.95 μ (SD ± 127.36), 394.95 μ (SD ± 138.03) and 378.32 μ (SD ± 112.01) at pre-injection, 1 month post-injection and 3 months post-injection respectively, this decrease in the foveal thickness was statistically significant (P value < 0.001). The LogMAR and CFT values before and after IVB injection showed significant statistical correlations =(p< 0.05) in relationship to variables of diabetic duration, diabetic control (HbA1c), and OCT pattern of macular edema, serum creatinine and cholesterol.Conclusions: chronicity and inadequate control of diabetes mellitus, nephropathy, hyperlipidemia and =presence of vitreomacular attachment (VMA) are factors associated with poor vision progress after intravitreal Bevacisumab injection.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.015
GPT teacher head0.299
Teacher spread0.284 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2010
Admission routes1
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