NT-proBNP cut-off value for ruling out heart failure in atrial fibrillation patients - A prospective clinical study.

STUDY OBJECTIVE: N-terminal pro-brain natriuretic peptide (NT-proBNP) measurements can be used to rule out heart failure in patients with sinus rhythm. Atrial fibrillation often coexists with heart failure but affects NT-proBNP levels. This study aims to identify the optimal NT-proBNP cut-off value for ruling out heart failure among atrial fibrillation patients. METHODS: This prospective study included 409 atrial fibrillation patients admitted to the emergency department. The inclusion criterion was documented atrial fibrillation on a 12­lead electrocardiogram. All patients completed a NT-proBNP blood sample, a chest X-ray and an echocardiogram. Heart failure was defined as a left ventricular ejection fraction of <40%. RESULTS: In total, 409 patients were included (mean age: 75.2 ± 11.6). The median NT-proBNP level was 2577 ng/L (quartiles: 1185-5438) and 21% had heart failure. We found a lower median NT proBNP level of 3187 ± 3973 ng/L in patients without heart failure compared to 9254 ± 8008 ng/L in patients with heart failure (absolute difference: 4131, 95% (CI): 3299-4986, p < 0.001). The area under the receiver operating characteristic curve for diagnosing heart failure was 0.82 (95% confidence interval: 0.77-0.87). The optimal cut-off value for ruling out heart failure was 739 ng/L with a sensitivity of 99%, a specificity of 18%, and a negative predictive value of 98%. CONCLUSIONS: NT-proBNP can be used to rule out heart failure in atrial fibrillation patients with a high negative predictive value, but low specificity. TRIAL REGISTRATION NUMBER: NCT04125966. https://clinicaltrials.gov/ct2/show/NCT04125966.

Inhospital cardiac arrest - the crucial first 5 min: a simulation study.

BACKGROUND: Early recognition and call for help, fast initiation of chest compressions, and early defibrillation are key elements to improve survival after cardiac arrest but are often not achieved. We aimed to investigate what occurs during the initial treatment of unannounced in situ simulated inhospital cardiac arrests and reasons for successful or inadequate initial resuscitation efforts. METHODS: We conducted unannounced full-scale in situ simulated inhospital cardiac arrest followed by a debriefing. Simulations and debriefings were video recorded for subsequent analysis. We analyzed quantitative data on actions performed and time measurements to key actions from simulations and qualitative data from transcribed debriefings. RESULTS: We conducted 36 simulations. Time to diagnosis of cardiac arrest was 37 (27; 55) s. Time to first chest compression from diagnosis of cardiac arrest was 37 (18; 74) s, time to calling the cardiac arrest team was 144 (71; 180) s, and time to first shock was 221 (181; 301) s. We observed participants perform several actions after diagnosing the cardiac arrest and before initiating chest compressions. Domains emerging from the debriefings were teaming and resources. Teaming included the themes communication, role allocation, leadership, and shared knowledge, which all included facilitators and barriers. Resources included the themes knowledge, technical issues, and organizational resources, of which all included barriers, and knowledge also included facilitators. CONCLUSION: Using unannounced in situ simulated cardiac arrests, we found that key elements such as chest compressions, calling the cardiac arrest team, and defibrillation were delayed. Perceived barriers to resuscitation performance were leadership and teaming, whereas experience, clear leadership, and recent training were perceived as important facilitators for treatment progress.