ABSTRACT
Continuous Thermodilution is a novel method of quantifying coronary flow (Q) in mL/min. To account for variability of Q within the cardiac cycle, the trace is smoothened with a 2 s moving average filter. This can sometimes be ineffective due to significant heart rate variability, ventricular extrasystoles, and deep inspiration, resulting in a fluctuating temperature trace and ambiguity in the location of the "steady state". This study aims to assess whether a longer moving average filter would smoothen any fluctuations within the continuous thermodilution traces resulting in improved interpretability and reproducibility on a test-retest basis. Patients with ANOCA underwent repeat continuous thermodilution measurements. Analysis of traces were performed at averages of 10, 15, and 20 s to determine the maximum acceptable average. The maximum acceptable average was subsequently applied as a moving average filter and the traces were re-analysed to assess the practical consequences of a longer moving average. Reproducibility was then assessed and compared to a 2 s moving average. Of the averages tested, only 10 s met the criteria for acceptance. When the data was reanalysed with a 10 s moving average filter, there was no significant improvement in reproducibility, however, it resulted in a 12% diagnostic mismatch. Applying a longer moving average filter to continuous thermodilution data does not improve reproducibility. Furthermore, it results in a loss of fidelity on the traces, and a 12% diagnostic mismatch. Overall, current practice should be maintained.
ABSTRACT
BACKGROUND: Targeted temperature management (TTM) is recommended following cardiac arrest; however, time to target temperature varies in clinical practice. We hypothesised the effects of a target temperature of 33 °C when compared to normothermia would differ based on average time to hypothermia and those patients achieving hypothermia fastest would have more favorable outcomes. METHODS: In this post-hoc analysis of the TTM-2 trial, patients after out of hospital cardiac arrest were randomized to targeted hypothermia (33 °C), followed by controlled re-warming, or normothermia with early treatment of fever (body temperature, ≥ 37.8 °C). The average temperature at 4 h (240 min) after return of spontaneous circulation (ROSC) was calculated for participating sites. Primary outcome was death from any cause at 6 months. Secondary outcome was poor functional outcome at 6 months (score of 4-6 on modified Rankin scale). RESULTS: A total of 1592 participants were evaluated for the primary outcome. We found no evidence of heterogeneity of intervention effect based on the average time to target temperature on mortality (p = 0.17). Of patients allocated to hypothermia at the fastest sites, 71 of 145 (49%) had died compared to 68 of 148 (46%) of the normothermia group (relative risk with hypothermia, 1.07; 95% confidence interval 0.84-1.36). Poor functional outcome was reported in 74/144 (51%) patients in the hypothermia group, and 75/147 (51%) patients in the normothermia group (relative risk with hypothermia 1.01 (95% CI 0.80-1.26). CONCLUSIONS: Using a hospital's average time to hypothermia did not significantly alter the effect of TTM of 33 °C compared to normothermia and early treatment of fever.
Subject(s)
Cardiopulmonary Resuscitation , Hypothermia, Induced , Hypothermia , Out-of-Hospital Cardiac Arrest , Humans , Out-of-Hospital Cardiac Arrest/therapy , Cold Temperature , Fever/therapy , Treatment OutcomeABSTRACT
BACKGROUND: Atrial fibrillation is a well-known independent risk factor for stroke yet there is no international consensus on guidelines regarding the introduction of anticoagulation in patients deemed at intermediate risk (e.g. CHA2DS2-VASc of 1). The evolution of cardiac biomarkers such as highly sensitive troponins and B-type natriuretic peptide as well as data on D-dimers, may offer incremental enhancements for personalized thromboembolism risk assessment. These markers provide prognostic data for risk of cardiovascular morbidities associated with atrial fibrillation and offer additional specificity for assessing stroke and thromboembolic risk. These assays may therefore enhance risk prognosis in atrial fibrillation alongside conventional stroke risk stratification tool patients. We seek to explore the application of personalised risk assessment using the biomarkers to aid the clinician treating the patient with atrial fibrillation deemed to be at intermediate risk of stroke. CONCLUSION: The stroke risk assessment of a patient with an intermediate risk of stroke (CHA2DS2- VASc score 1) may be improved by using cardiac biomarkers such as highly sensitive troponin, BNP and D-dimers. We explore the application of these biomarkers to provide personalised risk assessment to help a patient with AF decide on whether to commence anticoagulation.
