Asian Science Citation Index is committed to provide an authoritative, trusted and significant information by the coverage of the most important and influential journals to meet the needs of the global scientific community.  
ASCI Database
308-Lasani Town,
Sargodha Road,
Faisalabad, Pakistan
Fax: +92-41-8815544
Contact Via Web
Suggest a Journal
 
Articles by U. Schmidt
Total Records ( 3 ) for U. Schmidt
  A Butterly , E. A Bittner , E George , W. S Sandberg , M Eikermann and U. Schmidt
  Background

Postoperative residual curarization (PORC) [train-of-four ratio (T4/T1) <0.9] is associated with increased morbidity and may delay postoperative recovery room (PACU) discharge. We tested the hypothesis that postoperative T4/T1 <0.9 increases PACU length of stay.

Methods

At admission to the PACU, neuromuscular transmission was assessed by acceleromyography (stimulation current: 30 mA) in 246 consecutive patients. The potential consequences of PORC-induced increases in PACU length of stay on PACU throughput were estimated by application of a validated queuing model taking into account the rate of PACU admissions and mean length of stay in the joint system of the PACU plus patients recovering in operation theatre waiting for PACU beds.

Results

PACU length of stay was significantly longer in patients with T4/T1 <0.9 (323 min), compared with patients with adequate recovery of neuromuscular transmission (243 min). Age (P=0.021) and diagnosis of T4/T1 <0.9 (P=0.027), but not the type of neuromuscular blocking agent, were independently associated with PACU length of stay. The incidence of T4/T1 <0.9 was higher in patients receiving vecuronium. Delayed discharge significantly increases the chances of patients having to wait to enter the PACU. The presence of PORC is estimated to be associated with significant delays in recovery room admission.

Conclusions

PORC is associated with a delayed PACU discharge. The magnitude of the effect is clinically significant. In our system, PORC increases the chances of patients having to wait to enter the PACU.

  A. Patel , E. Maissi , H.-C. Chang , I. Rodrigues , M. Smith , S. Thomas , T. Chalder , U. Schmidt , J. Treasure and K. Ismail
  Aims  To assess the cost-effectiveness of motivational enhancement therapy and cognitive behaviour therapy for poorly controlled Type 1 diabetes.

Methods  Within-trial prospective economic evaluation from (i) health and social care and (ii) societal perspectives. Three hundred and forty-four adults with Type 1 diabetes for at least 2 years and persistent, suboptimal glycaemic control were recruited to a three-arm multi-centre randomized controlled trial in London and Manchester, UK. They were randomized to (i) usual care plus four sessions of motivational enhancement therapy (ii) usual care plus four sessions of motivational enhancement therapy and eight sessions of cognitive behaviour therapy or (iii) usual care alone. Outcomes were (i) costs, (ii) Quality-Adjusted Life Year gains measured by the EuroQol 5-dimensional health state index and the 36-item Short Form and (iii) diabetes control measured by change in HbA1c level at 1 year.

Results  Both intervention groups had significantly higher mean health and social care costs (+ £535 for motivational enhancement therapy and + £790 for combined motivational enhancement and cognitive behavioural therapy ), but not societal costs compared with the usual-care group. There were no differences in Quality Adjusted Life Years. There was a significantly greater HbA1c improvement in the combined motivational enhancement and cognitive behavioural therapy group (+ 0.45%; incremental cost-effectiveness ratio = £1756), but the not in the motivational enhancement therapy group. Cost-effectiveness acceptability curves suggested that both interventions had low probabilities of cost-effectiveness based on Quality Adjusted Life Years (but high based on HbA1c improvements). Imputing missing costs and outcomes confirmed these findings.

Conclusions  Neither therapy was undisputedly cost-effective compared with usual care alone, but conclusions vary depending on the relative importance of clinical and quality-of-life outcomes.

  R. Salazar , U. Schmidt , C. Huber , A. Rojano and I. Lopez
  In this study, we are interested in regulating two important variables inside of the greenhouse: temperature and CO2 enrichment for two cabins in a experimental greenhouse at the Humboldt University of Berlin. Predicting the behavior of these two variables and photosynthesis will allow us to turn on and off the controls such as heating system, vents opening or CO2 enrichment at the right time, in order to save energy and keep the plants inside of the comfort zone. Artificial Neural Networks (ANN) were used because of their ability to capture the non linear relationships governing the changes in the greenhouse environment. Temperature was predicted 5 and 10 min ahead of the sensor signal, with MSE errors between measured and predicted values of 0.088 and 0.029, respectively. The CO2 predicted from the model was used as an input in the photosynthesis model. In this last model, seven variables were used and the predictions were highly precise with a MSE errors of 0.0563 and 0.0974 for photosynthesis 5 and 10 min ahead, respectively. A sensitivity analysis was performed in the photosynthesis model showing that relative humidity is an important variable for CO2 levels and for the photosynthesis process. The predicting models will allow to achieve our final goal which is to replace the sensors and give predictive information for a higher control quality in an open loop control system.
 
 
 
Copyright   |   Desclaimer   |    Privacy Policy   |   Browsers   |   Accessibility