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Record W4404730677 · doi:10.1186/s40001-024-02155-1

Diagnostic significance of neutrophil-to-lymphocyte ratio in non-arteritic anterior ischemic optic neuropathy: a meta-analysis

2024· review· en· W4404730677 on OpenAlexaboutno aff
Erfan Kashani, Shima Nourigheimasi, Jeff Arni C. Valisno, Isaac Smith, Brandon Lucke‐Wold, Hanieh Bazrafshan, Arshin Ghaedi, Amir Mohammad Eghbalnejad Mofrad, Shokoufeh Khanzadeh

Bibliographic record

VenueEuropean journal of medical research · 2024
Typereview
Languageen
FieldMedicine
TopicIntraoperative Neuromonitoring and Anesthetic Effects
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisMedicineConfidence intervalOdds ratioDiagnostic odds ratioNeutrophil to lymphocyte ratioInternal medicineLikelihood ratios in diagnostic testingAnterior ischemic optic neuropathyLymphocyteOptic neuropathyPublication biasGastroenterologyOphthalmologyOptic nerve

Abstract

fetched live from OpenAlex

BACKGROUND: We aimed to determine the association of neutrophil-to-lymphocyte ratio (NLR) with non-arteritic anterior ischemic optic neuropathy (NAION). METHODS: We conducted a systematic review and meta-analysis according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed, Scopus and Web of Science were searched from the establishment of the database to May 5, 2022 to find the relevant studies. The quality of the included literature was evaluated with the Newcastle-Ottawa scale (NOS). The results are reflected in the form of standard mean difference (SMD) and 95% confidence interval (CI). RESULTS: = 0.0%, p = 0.60); thus, the analysis used the fixed-effect model. The pooled sensitivity of NLR was 0.69 (95% CI 0.60-0.67), and the pooled specificity was 0.59 (95% CI 0.50-0.67). The pooled positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio (DOR) of NLR were 1.71(95%CI 1.48-1.98), 0.50 (95%CI 0.41-0.62), and 3.38 (95%CI 2.57-4.44), respectively. CONCLUSIONS: Our findings suggest NLR to be a potential marker of NAION, while also implicating a role for inflammation in underlying pathophysiology.

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)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.530
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0000.000

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 head0.153
GPT teacher head0.460
Teacher spread0.307 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations2
Published2024
Admission routes1
Has abstractyes

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