Relationship between nephrotoxicity and long-term adefovir dipivoxil therapy for chronic hepatitis B
Bibliographic record
Abstract
BACKGROUND: To assess the relationship between adefovir dipivoxil and renal function after anti-hepatitis B virus therapy and elucidate the risk factors involved. METHODS: Based on the requirements of the Cochrane systematic review methodology, 21 observational articles on adefovir dipivoxil-associated renal dysfunction were obtained by searching various databases, between January 1, 1995 and July 1, 2016. The Newcastle Ottawa Scale was used to evaluate risk bias. Parameters for 4276 chronic hepatitis B patients were analyzed by Review Manager and R software, and glomerular filtration rate, creatinine clearance, and serum creatinine values were extracted to evaluate renal function. RESULTS: Renal dysfunction was more likely to occur in patients receiving the adefovir dipivoxil therapy (odds ratio [OR] 1.98, 95% confidence interval [CI] 1.40-2.80) than the none-adefovir dipivoxil group. Subgroup analysis showed that renal function predictive value is higher for glomerular filtration rate (OR 2.42, 95% CI 1.34-3.14), compared with serum creatinine levels (OR 1.51, 95% CI 0.75-3.04). The rate of adefovir dipivoxil-associated renal dysfunction was 12% (95% CI 0.08-0.16). Older patients and patients with renal insufficiency, hypertension, and diabetes mellitus were more prone to developing adefovir dipivoxil-associated renal dysfunction; however, integrated raw data were insufficient for further detailed analysis. CONCLUSION: Long-term adefovir dipivoxil therapy is connected to renal dysfunction in chronic hepatitis B, necessitating the monitoring of kidney function.
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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 | 0.013 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".