Biomarkers Enhance Discrimination and Prognosis of Type 2 Myocardial Infarction

Background: The observed incidence of type 2 myocardial infarction (T2MI) is expected to increase with the implementation of increasingly sensitive cardiac troponin (cTn) assays. However, it remains to be determined how to diagnose, risk stratify and treat patients with T2MI. We aimed to discriminate and risk-stratify T2MI using biomarkers. Methods: Patients presenting to the Emergency Department with chest pain, enrolled in the CHOPIN study, were retrospectively analyzed. Two cardiologists adjudicated type 1 MI (T1MI) and T2MI. The prognostic ability of several biomarkers alone or in combination to discriminate T2MI from T1MI was investigated using receiver operating characteristic (ROC) curve analysis. The biomarkers analyzed were cTnI, copeptin, mid-regional pro-atrial natriuretic peptide (MRproANP), C-terminal pro-endothelin-1 (CT-proET1), mid-regional pro-adrenomedullin (MRproADM) and procalcitonin. Prognostic utility of these biomarkers for all-cause mortality and major adverse cardiovascular event (MACE: a composite of acute MI, unstable angina pectoris, reinfarction, heart failure, and stroke) at 180-day follow-up was also investigated. Results: Among the 2071 patients, T1MI and T2MI were adjudicated in 94 and 176 patients, respectively. Patients with T1MI had higher levels of baseline cTnI, while those with T2MI had higher baseline levels of MR-proANP, CT-proET1, MR-proADM, and procalcitonin. The area under the ROC curve (AUC) for the diagnosis of T2MI was higher for CT-proET1, MRproADM and MR-proANP (0.765, 0.750, and 0.733, respectively) than for cTnI (0.631). Combining all biomarkers resulted in a similar accuracy to a model using clinical variables and cTnI (0.854 versus 0.884, p = 0.294). Addition of biomarkers to the clinical model yielded the highest AUC (0.917). Other biomarkers, but not cTnI, were associated with mortality and MACE at 180-day among all patients, with no interaction between the diagnosis of T1MI or T2MI. Conclusions: Assessment of biomarkers reflecting pathophysiologic processes occurring with T2MI might help differentiate it from T1MI. Additionally, all biomarkers measured, except cTnI, were significant predictors of prognosis, regardless of type of MI

Problems and Meaning Today What Can We Learn from Hattiangadi’s Failed Attempt to Explain Them Together?

Philosophers have tried to explain how science finds the truth by using new developments in logic to study scientific language and inference. R. G. Collingwood argued that only a logic of problems could take context into account. He was ignored, but the need to reconcile secure meanings with changes in context and meanings was seen by Karl Popper, W. v. O. Quine, and Mario Bunge. Jagdish Hattiangadi uses problems to reconcile the need for security with that for growth. But he mistakenly insists that all problems are mere contradictions and artificially separates rigid from flexible aspects of meanings. In order to resolve the conflict we must (1) replace the quest for rigid terms with techniques for improvement, (2) use plausible arguments to uncover confused meanings, (3) use frameworks to choose problems and to regulate meanings, and (4) employ a bootstrap approach that uses frameworks to improve meanings and refined meanings to improve frameworks