The relationship between antecedent creatinine decreases and outcomes in patients undergoing hemodialysis
Bibliographic record
Abstract
INTRODUCTION: Previous studies have demonstrated an association between low serum creatinine levels and adverse outcomes in patients undergoing maintenance hemodialysis. However, little is known regarding whether long-term changes in serum creatinine predict outcomes independently and incrementally over a single point evaluation. METHODS: Serum creatinine data at index (June 2013) and for the 18 months prior to the index blood sampling (between January 2012 and June 2013) were evaluated in 346 hemodialysis patients. Patients were followed from the index blood sampling for primary (all-cause mortality) and secondary (cardiovascular death) endpoints. FINDINGS: During a median follow-up of 5.7 years, there were 82 all-cause and 25 cardiovascular deaths. Compared to patients who survived, those who died displayed a greater time-dependent reduction in creatinine levels during the 18 months prior to the index assessment, coupled with a greater decrease in predialysis body weight (interaction p = 0.007). Patients who displayed creatinine decline over the prior 18 months (∆ creatinine<0 mg/dL) had higher all-cause mortality than those who maintained creatinine levels (∆ creatinine≥0 mg/dL). After adjustment for clinical factors and baseline creatinine index, antecedent creatinine decrease was independently associated with an increased risk of all-cause mortality, with an incremental prognostic value over baseline creatinine index alone. A reduction in creatinine levels was also associated with cardiovascular death independent of the baseline creatinine index. DISCUSSION: A long-term antecedent decrease in serum creatinine levels is independently associated with clinical outcomes in hemodialysis patients, with an incremental prognostic value over baseline creatinine index alone. Our data suggest that serial creatinine measurements are a useful prognosticator in practice.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".