Total atrial conduction time provides novel information in prediction for stroke in patients with sinus rhythm.

The total atrial conduction time (TACT) measured by echocardiography predicts the risk of atrial fibrillation (AF). This study aimed to investigate whether adding the TACT to the revised Framingham stroke risk profile (rFSRP) improves the efficacy of predicting stroke incidence in patients without prior stroke or known AF. The TACT was measured in 376 consecutive patients > 18 years (58.5 ± 16.3 years; 46% male) receiving echocardiography without any prior history of stroke or AF. The primary endpoint was the occurrence of ischemic stroke, and the secondary endpoint was any documentation of AF during the 2 years of follow-up. During the follow-up period, ischemic strokes occurred in 10 patients (2.65%), and AF in 22 patients (5.85%). The TACT was significantly longer in those who later had a stroke compared with those who did not (169.4 vs. 142.7 ms, p < 0.001). Both rFSRP and TACT predicted the risk for stroke incidence. The univariate model showed that the TACT was a predictor of ischemic stroke incidence (p < 0.001; hazard ratio of 1.94 for every 10 ms; 95% confidence interval, 1.49-2.54). The addition of TACT to rFSRP significantly improved the area under the receiver operating characteristic curve (0.79 vs. 0.85, p = 0.001). Stroke risk prediction was significantly improved by the addition of TACT to rFSRP. The utility of the TACT should be further investigated in large-scale randomized clinical trials.

Real-Time Prediction of Neurally Mediated Syncope.

Neurally mediated syncope (NMS) patients suffer from sudden loss of consciousness, which is associated with a high rate of falls and hospitalization. NMS negatively impacts a subject's quality of life and is a growing cost issue in our aging society, as its incidence increases with age. In this paper, we present a solution for prediction of NMS, which is based on the analysis of the electrocardiogram (ECG) and photoplethysmogram (PPG) alone. Several parameters extracted from ECG and PPG, associated with reflectory mechanisms underlying NMS in previous publications, were combined in a single algorithm to detect impending syncope. The proposed algorithm was evaluated in a population of 43 subjects. The feature selection, distance metric selection, and optimal threshold were performed in a subset of 30 patients, while the remaining data from 13 patients were used to test the final solution. Additionally, a leave-one-out cross-validation scheme was also used to evaluate the performance of the proposed algorithm yielding the following results: sensitivity (SE)--95.2%; specificity (SP)--95.4%; positive predictive value (PPV)--90.9%; false-positive rate per hour (FPRh)-0.14 h(-1), and prediction time (aPTime)--116.4 s.

Assessment of cardiovascular function from multi-Gaussian fitting of a finger photoplethysmogram.

Monitoring of cardiovascular function on a beat-to-beat basis is fundamental for protecting patients in different settings including emergency medicine and interventional cardiology, but still faces technical challenges and several limitations. In the present study, we propose a new method for the extraction of cardiovascular performance surrogates from analysis of the photoplethysmographic (PPG) signal alone.We propose using a multi-Gaussian (MG) model consisting of five Gaussian functions to decompose the PPG pulses into its main physiological components. From the analysis of these components, we aim to extract estimators of the left ventricular ejection time, blood pressure and vascular tone changes. Using a multi-derivative analysis of the components related with the systolic ejection, we investigate which are the characteristic points that best define the left ventricular ejection time (LVET). Six LVET estimates were compared with the echocardiographic LVET in a database comprising 68 healthy and cardiovascular diseased volunteers. The best LVET estimate achieved a low absolute error (15.41 ± 13.66 ms), and a high correlation (ρ = 0.78) with the echocardiographic reference.To assess the potential use of the temporal and morphological characteristics of the proposed MG model components as surrogates for blood pressure and vascular tone, six parameters have been investigated: the stiffness index (SI), the T1_d and T1_2 (defined as the time span between the MG model forward and reflected waves), the reflection index (RI), the R1_d and the R1_2 (defined as their amplitude ratio). Their association to reference values of blood pressure and total peripheral resistance was investigated in 43 volunteers exhibiting hemodynamic instability. A good correlation was found between the majority of the extracted and reference parameters, with an exception to R1_2 (amplitude ratio between the main forward wave and the first reflection wave), which correlated low with all the reference parameters. The highest correlation ([Formula: see text] = 0.45) was found between T1_2 and the total peripheral resistance index (TPRI); while in the patients that experienced syncope, the highest agreement ([Formula: see text] = 0.57) was found between SI and systolic blood pressure (SBP) and mean blood pressure (MBP).In conclusion, the presented method for the extraction of surrogates of cardiovascular performance might improve patient monitoring and warrants further investigation.

A novel multi-parametric algorithm for faint prediction integrating indices of cardiac inotropy and vascular tone.

Neurally medicated syncope (NMS) patients suffer from sudden loss of consciousness, which is associated with a high rate of falls and hospitalization. NMS negatively impacts a subject's quality of life and is a growing cost issue for the healthcare systems in particular since mainly elderly are at risk of NMS in our aging societies. In the present paper we present an algorithm for prediction of NMS, which is based on the analysis of the electrocardiogram (ECG) and photoplethysmogram (PPG) signals. Several parameters extracted from ECG and PPG, which have been associated in previous works with reflectory mechanisms underlying NMS, were combined in a single algorithm to detect impending syncope. The proposed algorithm was validated in 43 subjects using a 3-way data split scheme and achieved the following performance: sensitivity (SE) - 100%; specificity (SP) - 92%; positive predictive value (PPV) - 85%; false positive rate per hour (FPRh) - 0.146h(-1) and; average prediction time (aPTime) - 217.58s.

[The clinical spectrum of urea cycle defects in adult patients]. / Das klinische Spektrum von Harnstoffzyklusdefekten im Erwachsenenalter.

Urea cycle defects belong to the most common metabolic disorders with a cumulative incidence of 1:8000. A common trait of urea cycle defects is a disturbed detoxification of ammonia leading to hyperammonemia in the event of a high nitrogen load. Most patients develop symptoms in the neonatal period or in infancy, e. g. vomiting, seizures and disturbed consciousness. Depending on the affected enzyme and its residual activity, patients differ in the age at first presentation, the character and severity of symptoms and in the susceptibility to metabolic derangement. The presence of hyperammonemia and an altered plasma amino acid profile give the essential diagnostic clues. Since modern therapeutic measures have prolonged the life expectancy of these patients and provided the possibility of a first presentation in adulthood, patients with urea cycle defects have become an increasing challenge in internal medicine. The reported case series illustrates the heterogeneous clinical course of these disorders from childhood to adulthood.