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P J Senden

Publications and source records attributed to P J Senden.

6 recordsLinked to original sources
PubMed2004

Does physical training increase insulin sensitivity in chronic heart failure patients?

To determine the effect of training on insulin sensitivity (IS) and how this relates to peak V(.)O(2) (peak oxygen uptake) in CHF (chronic heart failure), 77 CHF patients (New York Heart Association class, II/III; men/women, 59/18; age, 60+/-9 years; body mass index, 26.7+/-3.9 kg/m(2); left ventricular ejection fraction, 26.9+/-8.1%; expressed as means+/-S.D.) participated in the study. Patients were randomly assigned to a training or control group (TrG or CG respectively). Sixty-one patients completed the study. Patients participated in training (combined strength and endurance exercises) four times per week, two times supervised and two times at home. Before and after intervention, anthropometry, IS (euglycaemic hyperinsulinaemic clamp) and peak V(.)O(2) (incremental cycle ergometry) were assessed. Intervention did not affect IS significantly, even though IS increased by 20% in TrG and 11% in CG (not significant). Peak V(.)O(2) increased as a result of training (6% increase in TrG; 2% decrease in CG; P <0.05). In both groups (TrG and CG), the change in IS correlated positively with the change in peak V(.)O(2) ( r =0.30, P <0.05). Training resulted in an increase in peak V(.)O(2), but not in IS. Whether physical training actually increases IS in CHF patients remains unclear.

Aged↗
PubMed2004

Endothelial markers in chronic heart failure: training normalizes exercise-induced vWF release.

BACKGROUND: Chronic heart failure (CHF) is characterized by endothelial dysfunction. Vascular endothelium is important for control of haemostasis and vasoregulation. The aim of the present study was to investigate plasma levels of several endothelial markers and the exercise-induced changes on these plasma levels in CHF patients. Subsequently, the effect of a 6-month training programme on these markers is described. MATERIALS AND METHODS: Twenty-nine male CHF patients (NYHA II/III, age 60 +/- 8 year, body mass index 26.7 +/- 2.3 kg m(-2), left ventricular ejection fraction 26.3-7.2%; mean +/- SD) participated. Patients were randomly assigned to a training or control group. Training (26 weeks; combined strength and endurance exercises) was four sessions/week: two sessions supervised and two sessions at home. Before and after intervention, anthropometry, endothelial markers (haemostasis and vasoregulation), maximal workload and peak oxygen uptake were assessed. RESULTS: Physical training positively affected maximal workload. Plasma levels of endothelial markers were not affected by physical training and not related to exercise tolerance. After training, stimulated (maximal exercise) plasma von Willebrand Factor (vWF) release was present, whereas at baseline this release was absent. CONCLUSION: Physical training led to normalization of the stimulated plasma vWF release. Plasma levels of other endothelial markers were not affected by physical training either at rest or under stimulated (maximal exercise) conditions.

Aged↗
PubMed2003

Determinants of insulin sensitivity in chronic heart failure.

OBJECTIVE: To describe the determinants of insulin sensitivity (IS) in chronic heart failure (CHF), we created a model in which the influence of lifestyle factors and etiology of heart failure on IS were incorporated concomitantly with age, left ventricular ejection fraction (LVEF) and parameters of body composition. DESIGN: Observational cohort study. SETTING: Outpatient clinic for chronic heart failure. PATIENTS: Fifty-seven male CHF patients [NYHA class II-III, age 61+/-9 years, body mass index (BMI) 26.9+/-3.3 kg/m2 (mean+/-S.D.)]. INTERVENTIONS: Euglycemic hyperinsulinemic clamp, cycle ergometry, anthropometric measurements, LVEF and a physical activity questionnaire. MAIN OUTCOME MEASURES: A model explaining the variance of IS in CHF. RESULTS: IS was 18.2+/-8.6 microg.kg(-1).min(-1).mU(-1).l(-1), fasting insulin level was 15.9+/-11.0 mU/l and fasting glucose level was 5.5+/-0.6 mmol/l. Peak VO2 was 19.1+/-4.9 ml.kg(-1).min(-1) and LVEF 26.2+/-7.1%. IS was inversely associated with fasting insulin concentration (r=-0.50, P<0.001) and BMI (r=-0.54, P<0.001). After controlling for BMI, IS also revealed a correlation with age (r=-0.36, P<0.01). The model explained 60% of variance in IS: BMI contributed 20%, smoking 17%, age 17% and physical activity in daily life (DPA) 16% (all P<0.05) to the variance of IS, whereas LVEF (9%) and etiology of heart failure (8%) contributed moderately. CONCLUSIONS: In CHF patients, IS is for a major part predicted by BMI, smoking, age, daily physical activity, LVEF and etiology of heart failure.

Adult↗
PubMed2003

Diagnostic value of onset-recordings and marker annotations in dual chamber pacemaker stored electrograms.

AIMS: Stored electrograms (EGM) have recently been introduced into pacemaker therapy. New generation devices offer the possibility to store the onset of the EGM (several seconds preceding storage trigger) and marker annotations. The aim of the study was to evaluate whether the diagnostic capabilities of EGMs are improved by these new features. METHODS: We studied 65 patients (age 68+/-12 years, 41 male) implanted with a DDDR-system (PulsarMax II 1280; Guidant). During a 1-month period 319 EGMs have been recorded. EGM triggers were: Ventricular Tachycardia (VT), Non-Sustained VT (NSVT), Atrial Tachycardia Response (ATR), Pacemaker Mediated Tachycardia (PMT) and Sudden Bradycardia Response (SBR). First, each EGM was analysed with onset and markers blinded. EGMs were classified with respect to their trigger as confirmed, not-confirmed or false-positive. Analysis was then repeated with markers visible but without onset, and thereafter vice versa. Finally, EGMs were analysed with both features. It was noted whether the presence of marker annotations and/or onset-recording changed the initial classification of the stored EGMs. RESULTS: 169 EGMs were triggered by SBR, which can only be confirmed with onset recording. False positive EGMs (atrial undersensing) occurred in 12%. The remaining 150 EGMs were triggered by ATR (80%), NSVT (11%), VT (6%) and by PMT (3%). Without onset/markers 37 of these 150 EGMs (25%) could not be confirmed. With markers and onset 33/37 (89%) of these EGMs could now be classified as confirmed or false positive. These EGMs became diagnostic with onset alone in 24%, with markers alone in 24%, and with the combination of both in 41%. In 4 EGMs no definite diagnosis could be established. CONCLUSION: Stored electrograms provide direct insights into device function, thereby providing a validation of diagnostic data. The expanded recording of onset and markers results in markedly improved diagnostic capabilities - compared with conventional EGMs. These new features were necessary to interpret correctly 61% of all stored electrograms, without which a diagnosis would not have been possible. Both onset-recording and marker annotation are necessary for optimal analysis.

Aged↗
PubMed1990

Initial clinical experience with rate adaptive cardiac pacing using two sensors simultaneously.

UNLABELLED: In the rate adaptive pacemakers, all presently available sensors show one or more drawbacks. Combining two sensors in a single pacemaker, we tried to optimize its rate responsive characteristics. In this study, we present the rate adaptive behavior of a two sensor pacemaker system, using both QT interval and activity sensing. In addition, we compared the rate response with that of each sensor alone. Nine patients with an implanted QT interval sensing pacemaker, and an externally attached activity sensing pacemaker performed three exercise stress tests on treadmill. The QT interval, measured by the implanted pacemaker, and the activity level, were transmitted to an external computer. This computer contained the two sensor rate adaptive algorithm, and reprogrammed the implanted pacemaker on beat-to-beat basis. CONCLUSION: In the two sensor mode the rate increases immediately at the onset of exercise, caused by the prompt response of the activity sensor. Further rate increase is driven by the QT interval sensor and therefore proportional to the level of exercise. Furthermore, the rate decay during the recovery phase is more physiological.

Atrial Fibrillation↗