Prognostic Role of Neutrophil to Lymphocyte Ratio in Contrast-Induced Nephropathy: A Systematic Review and Meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This meta-analysis assessed the use of the neutrophil-to-lymphocyte ratio (NLR) as a means of early detection of contrast-induced nephropathy (CIN) following diagnostic or therapeutic procedures. We used Web of Science, PubMed, and Scopus to conduct a systematic search. There was no limitation regarding language or date of publication. We reported standardized mean difference (SMD) with a 95% confidence interval (CI). Due to high heterogeneity, a random-effects model was used, and the Newcastle–Ottawa scale was used for quality assessment. Thirty-one articles were included in the analysis. Patients in the CIN group had elevated levels of NLR compared with those in the non-CIN group (SMD = 0.78, 95% CI = 0.52–1.04, P < .001). Similar results were observed in either prospective (SMD = 1.03, 95% CI = 0.13–1.93, P = .02) or retrospective studies (SMD = 0.70, 95% CI = 0.45–0.96, P < .001). The pooled sensitivity of NLR was 74.02% (95% CI = 66.54%–81.02%), and the pooled specificity was 60.58% (95% CI = 53.94%–66.84%). NLR shows potential as a cost-effective biomarker for predicting CIN associated with contrast-involved treatments. This could help implement timely interventions to mitigate CIN and improve outcomes.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.014 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it