PubMed · 4743457
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H C Amstutz, G A Finerman. Knee joint replacement-development and evaluation.. https://doi.org/10.1097/00003086-197307000-00005
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BACKGROUND AND STUDY AIM: Acute cardiovascular events may be triggered by physical and mental stress. Does also the typical circadian variation of arrhythmia recurrence (morning peak of events) in patients with implanted cardioverter-defibrillator correlate with the individual circadian variation of physical and mental daily activities? PATIENTS AND METHODS: In 29 consecutive patients with a minimum of three documented ventricular tachyarrhythmias after defibrillator implantation the circadian variation of habitual daily activities was determined in a standardized interview and compared to the individual circadian variation of arrhythmic events saved in the defibrillator event memory during long-term follow-up. RESULTS: The habitually highest physical and mental activity was determined during the time period with most arrhythmic events in 55 % and 23 % of patients, respectively. A comparison of the level of activity during the time period with the highest event frequency to the mean activity level during the rest of the day (without sleeping time) revealed significantly higher physical activity during the time of day with the highest arrhythmia recurrence. There was a positive correlation between circadian variation of arrhythmic events and the sum of all activities (r = 0.34, p < 0.05) and physical activities alone (r = 0.25, p = 0.056) while a relationship to mental activities alone could not be shown (r = 0.02, p = 0.84) CONCLUSION: The circadian variation of acute cardiovascular events may be discussed as an essential factor influencing the circadian variation of habitual daily activities in patients with cardiac disease.
This study investigated the efficacy of guidelines for a motivated class teacher to enhance the application of back care principles, taught by a physical therapist, in fifth-grade elementary schoolchildren. Testing consisted of a practical test before and a practical test, knowledge test and candid camera evaluation 11 weeks after the program. Three groups were compared: an intervention group of 38 pupils, with extra guidelines for the teacher, an intervention group of 48 pupils, without extra guidelines and 34 controls. The intervention plus guidelines group, compared to the intervention group without extra teacher guidelines, obtained significantly higher posttest-pretest gain scores for five of the seven practical test items and scored significantly higher for seven of the nine items of the candid camera evaluation. Knowledge test scores did not differ significantly between the two intervention groups. Study results indicate that guidelines to a motivated class teacher improve efficacy of back care education in elementary schoolchildren.
BACKGROUND AND PURPOSE: Several prognostic factors have been identified for outcome after stroke. However, there is a need for empirically derived models that can predict outcome and assist in medical management during rehabilitation. To be useful, these models should take into account early changes in recovery and individual patient characteristics. We present such a model and demonstrate its clinical utility. METHODS: Data on functional recovery (Barthel Index) at 0, 2, 4, 6, and 12 months after stroke were collected prospectively for 299 stroke patients at 2 London hospitals. Multilevel models were used to model recovery trajectories, allowing for day-to-day and between-patient variation. The predictive performance of the model was validated with an independent cohort of 710 stroke patients. RESULTS: Urinary incontinence, sex, prestroke disability, and dysarthria affected the level of outcome after stroke; age, dysphasia, and limb deficit also affected the rate of recovery. Applying this to the validation cohort, the average difference between predicted and observed Barthel Index was -0.4, with 90% limits of agreement from -7 to 6. Predicted Barthel Index lay within 3 points of the observed Barthel Index on 49% of occasions and improved to 69% when patients' recovery histories were taken into account. CONCLUSIONS: The model predicts recovery at various stages of rehabilitation in ways that could improve clinical decision making. Predictions can be altered in light of observed recovery. This model is a potentially useful tool for comparing individual patients with average recovery trajectories. Patients at elevated risk could be identified and interventions initiated.