Impact of HCV Infection on Diabetes Patients for the Risk of End-Stage Renal Failure
Bibliographic record
Abstract
Both diabetes mellitus (DM) and hepatitis C virus infection (HCVI) are associated with chronic kidney disease (CKD). The aim of this study was to evaluate whether HCVI increases the risk of end-stage renal disease (ESRD) in patients with DM.The National Health Insurance Research database of Taiwan was used to conduct this study. After excluding patients with a prior history of CKD, all patients with a first diagnosis of DM from January 1, 2000 to December 31, 2002 were enrolled. The patients who also had HCVI were defined as index cases (HCV group, n = 9787). A comparison cohort at a 1:1 ratio of random incident patients with DM without HCVI matched by age, sex, age at the diagnosis of DM, duration between the diagnosis of DM and the index date, and various comorbidities through propensity score matching were recruited (non-HCV group, n = 9787). The patients were followed until December 31, 2011.The cumulative incidence rate of developing ESRD was significantly higher in the HCV(+) group than in the non-HCV group (P = 0.008). The incidence rate ratio (IRR) for the risk of ESRD was also significantly higher in the HCV(+) group (IRR: 1.44; 95% CI: 1.09-1.89) than in the non-HCV group, especially for those with a younger age (<50 years; IRR: 2.05; 95% CI: 1.22-3.45) and HCVI within 4 years after the diagnosis of DM (IRR: 1.85; 95% CI: 1.16-2.97). After adjusting for comorbidities in multivariate Cox proportional hazard regression analysis, HCVI (HR: 1.47; 95% CI: 1.11-1.93) was an independent factor for developing ESRD in the patients with DM. After starting dialysis for ESRD, the HCV(+) patients had a similar mortality rate to those without HCVI (P = 0.84).HCVI increases the risk of developing ESRD in patients with DM, especially in younger patients and in those who develop HCVI sooner after a diagnosis of DM.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".