Use of cardiac troponin T in diagnosis and prognosis of cardiac events in patients on chronic haemodialysis
Bibliographic record
Abstract
BACKGROUND: Patients undergoing chronic haemodialysis frequently have elevated serum cardiac troponin T (cTnT) levels resulting in difficulty in diagnosing acute coronary syndromes (ACS) in these patients. We sought to determine whether: (i) cTnT concentrations were consistent over time; (ii) intradialytic changes in cTnT levels were due to haemoconcentration; (iii) baseline cTnT levels predicted subsequent mortality or ACS. METHODS: We measured serial pre- and post-dialysis cTnT concentrations in 75 asymptomatic patients undergoing chronic haemodialysis at baseline, and at 48 h, 8 months and 15 months. At 15 months, we also measured pre- and post-dialysis haematocrit levels in order to adjust the post-dialysis cTnT concentration for the effect of ultrafiltration. Kaplan-Meier survival curves, log-rank tests and Cox models were employed to determine whether baseline cTnT levels predicted death or ACS within 18 months. RESULTS: Thirty-five (47%) patients had a baseline pre-dialysis cTnT concentration in the diagnostic range for an ACS (cTnT > or = 0.03 microg/l). There was a strong correlation between serial cTnT concentrations in individual patients (P<0.0001 for each time point). The median cTnT concentration was significantly greater post- than pre-dialysis (P<0.01 for each serial analysis); however, there was no significant difference following correction of post-dialysis cTnT levels for the effect of haemoconcentration (P = 0.48). Elevated baseline cTnT levels were associated with an increased risk of mortality or ACS at 18 months (P = 0.0015). CONCLUSION: In asymptomatic patients on haemodialysis, serum cTnT concentrations are frequently elevated, and they rise during dialysis due to haemoconcentration. cTnT levels fluctuate minimally in individual patients in the medium term, therefore annual measurements may be useful reference points in the diagnosis of chest pain and in the prediction of ACS and mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".