Prediction of fatal or near-fatal cardiac arrhythmia events in patients with depressed left ventricular function after an acute myocardial infarction†

To determine whether risk stratification tests can predict serious arrhythmic events after acute myocardial infarction (AMI) in patients with reduced left ventricular ejection fraction (LVEF <= 0.40). A total of 5869 consecutive patients were screened in 10 European centres, and 312 patients (age 65 +/- 11 years) with a mean LVEF of 31 +/- 6% were included in the study. Heart rate variability/turbulence, ambient arrhythmias, signal-averaged electrocardiogram (SAECG), T-wave alternans, and programmed electrical stimulation (PES) were performed 6 weeks after AMI. The primary endpoint was ECG-documented ventricular fibrillation or symptomatic sustained ventricular tachycardia (VT). To document these arrhythmic events, the patients received an implantable ECG loop-recorder. There were 25 primary endpoints (8.0%) during the follow-up of 2 years. The strongest predictors of primary endpoint were measures of heart rate variability, e.g. hazard ratio (HR) for reduced very-low frequency component ( <5.7 ln ms(2)) adjusted for clinical variables was 7.0 (95% CI: 2.4-20.3, P <0.001). Induction of sustained monomorphic VT during PES (adjusted HR = 4.8, 95% CI, 1.7-13.4, P = 0.003) also predicted the primary endpoint. Fatal or near-fatal arrhythmias can be predicted by many risk stratification methods, especially by heart rate variability, in patients with reduced LVEF after AM

Erityistä tukea tarvitsevien opiskelijoiden käsityksiä oppimista edistävistä tekijöistä ammatillisessa koulutuksessa

Tiivistelmä. Tämän pro gradu -tutkielman tavoitteena oli selvittää millaisia käsityksiä erityistä tukea tarvitsevilla opiskelijoilla on oppimista edistävistä tekijöistä ammatillisessa koulutuksessa. Tutkimuksessa selvitettiin käsityksiä siitä, miten opiskelija itse voi edistää oppimistaan sekä miten opettaja ja ryhmä voi edistää opiskelijan oppimista. Tutkimuksessa käytettiin laadullista ja kuvailevaa fenomenografista tutkimusmenetelmää. Aineisto kerättiin teemahaastatteluina, haastatellen yksilöllisesti viittä erityistä tukea tarvitsevaa opiskelijaa kahdesta eri ammatillisesta perustutkinnosta. Aineisto analysoitiin fenomenografisen analyysimenetelmän mukaisesti. Tutkielma on aiheeltaan ajankohtainen ja merkityksellinen, sillä ammatillisen koulutuksen reformi astui voimaan vuoden 2018 alussa. Uudistuksessa opiskelijoiden yksilölliset opintopolut ja osaamisperusteisuus ovat keskiössä. Tutkielma tuo ajankohtaista tietoa opiskelijoiden käsityksistä oppimiseen myönteisesti vaikuttavista tekijöistä. Tuloksia on mahdollista soveltaa ammatillisen koulutuksen pedagogisessa kehittämistyössä. Tutkimustulokseksi muodostui neljä oppimiseen edistävästi vaikuttavaa tekijää: aktiivinen oppijuus, opettajan taito kohdata opiskelija yksilöllisesti, ryhmän yhteisöllisyys ja oman elämän hallintataidot. Opiskelijoiden käsityksissä oppimista edistävät aktiivisen roolin ottaminen omassa oppimisprosessissa, opintojen suunnittelussa ja tavoitteiden asettamisessa. Opettajan tulee vuorovaikutustilanteessa olla läsnä ja keskittyä opiskelijaan, saada opiskelija tietoiseksi omasta potentiaalistaan, ohjata elinikäisen oppimisen taitoja sekä antaa tukea, ohjausta ja vastuuta oppimisprosessin hallintaan. Ryhmän yhteisöllisyys on voimavara oppimisessa ja sitä tulisi hyödyntää tietoisesti oppimisprosessien ohjaamisessa ja tukemisessa. Tulokset toivat esille myös oman elämän hallintataitojen edistävän vaikutuksen hyvinvointiin ja jaksamiseen. Tutkimustulosten perusteella erityistä tukea tarvitsevien opiskelijoiden oppimisen ohjaus, opintopolkujen ja osaamisen suunnittelu ja toteutus tulee toteuttaa yksilöllisemmin tiiviimmässä yhteistyössä opiskelijoiden kanssa. Opettajat ovat avainasemassa opiskelijoiden oppimisen edistäjinä

Heart Rate Dynamics after Exercise in Cardiac Patients with and without Type 2 Diabetes

Purpose: The incidence of cardiovascular events is higher in coronary artery disease patients with type 2 diabetes (CAD + T2D) than in CAD patients without T2D. There is increasing evidence that the recovery phase after exercise is a vulnerable phase for various cardiovascular events. We hypothesized that autonomic regulation differs in CAD patients with and without T2D during post-exercise condition. Methods: A symptom-limited maximal exercise test on a bicycle ergometer was performed for 68 CAD + T2D patients (age 61 ± 5 years, 78% males, ejection fraction (EF) 67 ± 8, 100% on β-blockade), and 64 CAD patients (age 62 ± 5 years, 80% males, EF 64 ± 8, 100% on β-blockade). Heart rate (HR) recovery after exercise was calculated as the slope of HR during the first 60 s after cessation of exercise (HRRslope). R–R intervals were measured before (5 min) and after exercise from 3 to 8 min, both in a supine position. R–R intervals were analyzed using time and frequency methods and a detrended fluctuation method (α1). Results: BMI was 30 ± 4 vs. 27 ± 3 kg m2 (p < 0.001); maximal exercise capacity, 6.5 ± 1.7 vs. 7.7 ± 1.9 METs (p < 0.001); maximal HR, 128 ± 19 vs. 132 ± 18 bpm (p = ns); and HRRslope, −0.53 ± 0.17 vs. −0.62 ± 0.15 beats/s (p = 0.004), for CAD patients with and without T2D, respectively. There was no differences between the groups in HRRslope after adjustment for METs, BMI, and medication (ANCOVA, p = 0.228 for T2D and, e.g., p = 0.030 for METs). CAD + T2D patients had a higher HR at rest than non-diabetic patients (57 ± 10 vs. 54 ± 6 bpm, p = 0.030), but no other differences were observed in HR dynamics at rest or in post-exercise condition. Conclusion: HR recovery is delayed in CAD + T2D patients, suggesting impairment of vagal activity and/or augmented sympathetic activity after exercise. Blunted HR recovery after exercise in diabetic patients compared with non-diabetic patients is more closely related to low exercise capacity and obesity than to T2D itself

Improved Stratification of Autonomic Regulation for risk prediction in post-infarction patients with preserved left ventricular function (ISAR-Risk)

Aims To investigate the combination of heart rate turbulence (HRT) and deceleration capacity (DC) as risk predictors in post-infarction patients with left ventricular ejection fraction (LVEF) > 30%. Methods and results We enrolled 2343 consecutive survivors of acute myocardial infarction (MI) (30% (cumulative 5-year mortality rates of 37.9% and 7.8%, respectively). Among patients with LVEF > 30%, SAF identified another high-risk group of 117 patients with 37 deaths (cumulative 5-year mortality rates of 38.6% and 6.1%, respectively). Merging both high-risk groups (i.e. LVEF ≤ 30% and/or SAF) doubled the sensitivity of mortality prediction compared with LVEF ≤ 30% alone (21.1% vs. 42.1%, P 30%, SAF identifies a high-risk group equivalent in size and mortality risk to patients with LVEF ≤ 30%

Recurrence Plot Based Measures of Complexity and its Application to Heart Rate Variability Data

The knowledge of transitions between regular, laminar or chaotic behavior is essential to understand the underlying mechanisms behind complex systems. While several linear approaches are often insufficient to describe such processes, there are several nonlinear methods which however require rather long time observations. To overcome these difficulties, we propose measures of complexity based on vertical structures in recurrence plots and apply them to the logistic map as well as to heart rate variability data. For the logistic map these measures enable us not only to detect transitions between chaotic and periodic states, but also to identify laminar states, i.e. chaos-chaos transitions. The traditional recurrence quantification analysis fails to detect the latter transitions. Applying our new measures to the heart rate variability data, we are able to detect and quantify the laminar phases before a life-threatening cardiac arrhythmia occurs thereby facilitating a prediction of such an event. Our findings could be of importance for the therapy of malignant cardiac arrhythmias

Characterization of Sleep Stages by Correlations of Heartbeat Increments

We study correlation properties of the magnitude and the sign of the increments in the time intervals between successive heartbeats during light sleep, deep sleep, and REM sleep using the detrended fluctuation analysis method. We find short-range anticorrelations in the sign time series, which are strong during deep sleep, weaker during light sleep and even weaker during REM sleep. In contrast, we find long-range positive correlations in the magnitude time series, which are strong during REM sleep and weaker during light sleep. We observe uncorrelated behavior for the magnitude during deep sleep. Since the magnitude series relates to the nonlinear properties of the original time series, while the signs series relates to the linear properties, our findings suggest that the nonlinear properties of the heartbeat dynamics are more pronounced during REM sleep. Thus, the sign and the magnitude series provide information which is useful in distinguishing between the sleep stages.Comment: 7 pages, 4 figures, revte