Cardiac troponin‐I and its prognostic significance in a dialysis population
Bibliographic record
Abstract
BACKGROUND: The objective was to study the prevalence and specificity of elevated levels of cardiac troponin-I (cT-I) in patients on maintenance hemodialysis in relation to creatine kinase (CK), the CK-MB fraction, and the ratio CK-MB of total CK and to assess its significance for the long-term prognosis in these patients, compared to other parameters known to influence the outcome. METHODS: Predialysis blood samples were taken from 93 asymptomatic hemodialysis patients for cT-I, total CK, the CK-MB fraction, and the ratio of CK-MB to total CK. cT-I was measured by a microparticle enzyme immunoassay. The patients were followed for 1 year, after which baseline levels of cT-I and age, duration of dialysis, and the presence of diabetes mellitus and ischemic heart disease were correlated by linear regression analysis with the outcome parameter all-cause mortality. RESULTS: None of the patients had a cT-I level higher than the manufacturer's indicated cutoff point of 2.0 ng/mL for myocardial infarction, indicating a specificity of 100%. Nine of the 93 patients (9.7%) had detectable cT-I levels (>0.0 ng/mL). Twelve patients died within 1 year, among which 4 had baseline cT-I levels above 0 ng/mL. From the study variables, an elevated baseline cT-I was found to be the only factor that significantly correlated with the outcome all-cause mortality (p = 0.029). CONCLUSIONS: cT-I has a high specificity for the diagnosis of myocardial infarction in dialysis patients. Despite the relatively low number of positive test results, cT-I was found to be significantly correlated with the outcome all-cause mortality at 1 year.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".