Facilitated reperfusion with prehospital glycoprotein IIb/IIIa inhibition: predictors of complete ST-segment resolution before primary percutaneous coronary intervention in the On-TIME 2 trial

NT-proBNP level before primary PCI and risk of poor myocardial reperfusion: Insight from the On-TIME II trial

BACKGROUND

N-terminal fragment of the brain natriuretic peptide prohormone (NT-proBNP), a marker for neurohumoral activation, has been associated with adverse outcome in patients with myocardial infarction. NT-proBNP levels may reflect extensive ischemia and microvascular damage, therefore we investigated the potential association between baseline NT-proBNP level and ST-resolution (STR), a marker of myocardial reperfusion, after primary percutaneous coronary intervention (pPCI).

METHODS

we performed a post-hoc analysis of the On-TIME II trial (which randomized ST-elevation myocardial infarction (STEMI) patients to pre-hospital tirofiban administration vs placebo). Patients with measured NT-proBNP before angiography were included. Multivariate logistic-regression analyses was performed to investigate the association between baseline NTproBNP level and STR one hour after pPCI.

RESULTS

Out of 984 STEMI patients, 918 (93.3%) had NT-proBNP values at baseline. Patients with STR <70% had higher NT-proBNP values compared to patients with complete STR (>70%) [Mean ±SD 375.2 ±1021.7 vs 1007.4 ±2842.3, Median (IQR) 111.7 (58.4-280.0) vs 168.0 (62.3-601.3), P <.001]. At multivariate logistic regression analysis, independent predictors associated with higher risk of poor myocardial reperfusion (STR <70%) were: NT-proBNP (OR 1.17, 95%CI 1.04-1.31, P = .009), diabetes mellitus (OR 1.87, 95%CI 1.14-3.07, P = .013), anterior infarct location (OR 2.74, 95% CI 2.00-3.77, P <.001), time to intervention (OR 1.06, 95%CI 1.01-1.11, P = .021), randomisation to placebo (OR 1.45, 95%CI 1.05-1.99, P = .022).

CONCLUSIONS

In STEMI patients, higher baseline NT-proBNP level was independently associate with higher risk of poor myocardial reperfusion, supporting the potential use of NT-proBNP as an early marker for risk stratification of myocardial reperfusion after pPCI in STEMI patients.

Bayesian network to optimize the first dose of antibiotics: application to amikacin

Objective: To construct and validate a network to predict the first dose of amikacin. Methods: Anthropometric and therapeutic data were recorded for 120 patients. Bayesian network (BN) was built to predict the dose to achieve a fixed target peak concentration of 64 mg/l. In 40 subjects, doses predicted with the BN (BND) and based on body weight (BWD) were compared with adjusted doses calculated using a pharmacokinetic software (MM-USCPACK; BID). Results: The calculated dose differed by <20% from the ideal dose in 62.5% of the patients with the BN and in 43.8% of the patients with the BW. Conclusion: BN is a promising approach to optimize the prediction of the first dose.