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Record W3195936788 · doi:10.18240/ijo.2021.09.21

Association between cystatin C and diabetic retinopathy among type 2 diabetic patients in China: a Meta-analysis

2021· article· en· W3195936788 on OpenAlexaboutno aff
Nan Yang, Xiao Yang, Kui Jiang, Aimin Sang, Huiqun Wu

Bibliographic record

VenueInternational Journal of Ophthalmology · 2021
Typearticle
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsnot available
FundersQinglan Project of Jiangsu Province of ChinaScience and Technology Project of Nantong CityGovernment of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsMedicineDiabetic retinopathyInternal medicineFunnel plotMeta-analysisCystatin CConfidence intervalCochrane LibraryBody mass indexPublication biasDiabetes mellitusType 2 Diabetes MellitusType 2 diabetesRetinopathyEndocrinologyCreatinine

Abstract

fetched live from OpenAlex

AIM: To explore the correlation between cystatin C (Cys-C) and diabetic retinopathy (DR) in those patients with type 2 diabetes mellitus (DM) in China. METHODS: Articles were collected from China National Knowledge Infrastructure (CNKI), Wanfang, VIP, PubMed, EMBASE, Cochrane Library, Clinical Trials.gov, and Google Scholar. Quality and risk of bias within included studies was assessed using the Newcastle-Ottawa scale (NOS). Heterogeneity was determined by using Cochran’s Q-test and Higgins I2 statistics. Mean differences (MDs) and 95% confidence intervals (CIs) of Cys-C within the diabetes without retinopathy (DWR) and DR, DWR and non-proliferative diabetic retinopathy (NPDR), NPDR and proliferative diabetic retinopathy (PDR) were collected by using random-effects model because of high heterogeneity. Meta-analysis was conducted based on 23 articles of 2331 DR including NPDR and PDR patients and 2023 DWR patients through Review Manager 5.3. Subgroup analyses were also performed according to DM duration, body mass index (BMI), total cholesterol (TC), total triglycerides (TG), low-density lipoprotein C (LDL-C), and high-density lipoprotein C (HDL-C), sample origins and methods. Publication bias was assessed by the funnel plot. RESULTS: Cys-C level in DR patients was increased compared with that of DWR (total MD: 0.69, 95%CI: 0.41 to 0.97, Z=4.79, P<0.01). Besides, the synthesized results of the studies showed the similar findings in the DWR vs NPDR group (total MD: 0.29, 95%CI 0.20 to 0.39, Z=6.02, P<0.01) and the NPDR vs PDR group (total MD: 0.63, 95%CI 0.43 to 0.82, Z=6.33, P<0.01). Heterogeneity of most of the subgroup analyses was still obvious (I2?≥?50%, P?<?0.1). Forest plots of different subgroups indicated that there was a slight increase of Cys-C during the period between DWR and DR, DWR and NPDR, NPDR and PDR. Funnel plot showed that there was no significant publication bias. CONCLUSION: The elevated Cys-C is closely related with DR and probably plays a critical role in its progression.

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)0.001
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 score0.011
Threshold uncertainty score0.772

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.026
GPT teacher head0.323
Teacher spread0.296 · 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

Citations14
Published2021
Admission routes1
Has abstractyes

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