Anticoagulant-related nephropathy: systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background The aim of this study was to report the prevalence and mortality associated with anticoagulant-related nephropathy (ARN) through a systematic review of the literature. Methods Electronic searches were conducted in the Medline and EMBASE databases, and manual searches were performed in the reference lists of the identified studies. The studies were selected by two independent researchers, first by evaluating the titles and abstracts and then by reading the complete texts of the identified studies. Case series, cross-sectional studies, cohort studies and case–control studies reporting the prevalence and factors associated with ARN were selected. The methodological quality was assessed using the Newcastle–Ottawa scale. Meta-analyses of the prevalence of ARN and 5-year mortality using the random effects model were performed when possible. Heterogeneity was assessed using the I2 statistic. Results Five studies were included. Prevalence of ARN ranged from 19% to 63% among the four included cohort studies. Meta-analysis of these resulted in high heterogeneity [I2 96%, summary effect 31%; 95% confidence interval (CI) 22–42%]. Subgroup meta-analysis yielded an ARN prevalence of 20% among studies that included patients with fewer comorbidities (I2 12%; 95% CI 19–22%). In a direct comparison, meta-analysis of the 5-year mortality rate between anticoagulated patients who had experienced ARN and anticoagulated patients without ARN, patients with ARN were 91% more likely to die (risk ratio = 1.91; 95% CI 1.22–3; I2 87%). Risk factors for ARN that were reported in the literature included initial excessive anticoagulation, chronic kidney disease, age, diabetes, hypertension, cardiovascular disease and heart failure. Conclusions ARN studies are scarce and heterogeneous, and present significant methodological limitations. The high prevalence of ARN reported herein suggests that this entity is underdiagnosed in clinical practice. Mortality in patients with ARN seems to be high compared with patients without this condition in observational studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.046 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.033 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".