Monthly measurement of high‐sensitivity cardiac troponins T and creatine kinase in asymptomatic chronic hemodialysis patients: A one‐year prospective study
Bibliographic record
Abstract
BACKGROUND: Cardiology guidelines recommend measuring high-sensitivity cardiac troponin (hs-cTn) for the diagnostic work-up of acute coronary syndromes (ACS). Many hospitals measure hs-cTnT, but preliminary data have shown that hs-cTnT is higher than normal in many hemodialysis patients without evidence of ACS. The purpose of this study was therefore to determine the hs-cTnT levels every month for 1 year in asymptomatic hemodialysis patients, in order to assess their changes over time relative to creatine kinase. METHODS: Fourty-four hemodialysis patients (mean age 67 ± 14 years) were included. The predialysis levels of fifth-generation hs-cTnT, CK, and CK-MB were measured every month for 1 year using a Cobas® 6000 analyzer (Roche Diagnostics, Switzerland). RESULTS: Almost 100% of hs-cTnT measurements were higher than normal (N < 14 ng/L); the mean ± SD annual level was 84 ± 59 ng/L, ranging from a minimum of 24 ± 2 to 241 ± 28 ng/L in individual patients. The mean levels of CK and CK-MB were normal. Thirteen myocardial infarctions were analyzed, which were all associated with an initial elevation in hs-cTnT >45% from the individual baseline value. By comparison, CK and CK-MB only increased in 38% and 31% of these myocardial infarctions, respectively. DISCUSSION: hs-cTnT is persistently higher than normal in chronic hemodialysis patients. Standard algorithms for diagnosing ACS can obviously not be used and alternative diagnostic strategies need to be developed. According to our data, and given the huge variation in baseline hs-cTnT levels among patients, the use of higher cut-offs as proposed in the literature cannot be recommended. Instead, we consider that hs-cTnT should be checked at regular intervals (e.g., every 3-6 months) in order to establish individual baseline levels for hs-cTnT. This approach, in most instances, not only makes it possible to more rapidly rule-in but also to rapidly rule-out, cases of ACS in hemodialysis patients who develop cardiac symptoms.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".