Etiopathology, Clinical and Imaging Characteristics of Border Zone Strokes.

Introduction: A border zone infarct (BI) is defined as an infarction that is localized to watersheds or border zones in the brain. BI is further classified into cortical border zone infarct (CBZ) and internal border zone infarct (IBZ). This study was conducted to explore the clinical and radiological characteristics of BI. Materials and Method: The study was conducted on eligible 400 acute ischemic stroke patients out of which 52 BI patients (diagnosed by the radiologist on DWI MRI images), patients >18 yrs of age were selected and divided into two groups of IBZ and CBZ infarct patients. The degree of intracranial and extracranial stenosis and characteristics on clinical presentation were assessed. The data were collected and analyzed using SPSS version 20.0 software at significance level p-value <0.05. Results: 25% and 75% of CBZ and IBZ patients, respectively, had history of presyncope or syncope before stroke. On vascular evaluation, 3.9% and 51.9% were in MCA and ICA stenosis group, respectively. Evidence of cardio embolism was found in 17.3% of patients. 53.3% of CBZ and 53.8% of IBZ patients were in ICA stenosis group, and 6.7% of CBZ and 7.7% of IBZ patients were in MCA stenosis group, with a statistically insignificant relation (p-value >0.05). Conclusion: Association of BI with events causing hypotension or hypovolemia is well-established in our study, association of BI with large vessel atherosclerosis is common, and its contribution to CBZ and IBZ seems to be equal.

Control strategy with multivariable fault tolerance module for automatic intravenous anesthesia.

In the anesthesia automation, an automatic propofol infusion system uses Bi-spectral Index Signal (BIS) as a primary feedback signal to manipulate propofol dose. However, the BIS signal may be suspended for some time due to poor EEG signal quality, noise, and many other factors. Therefore, BIS signal failure may be the main cause of inadequate propofol infusion. This fact motivates the need for integration of multivariable fault tolerance module (MFTM) and fractional-order Smith predictor controller to avoid adverse reactions of inadequate propofol dosing during BIS failure. Smith Predictor control strategy is sufficiently robust to predict feedback BIS during BIS failure via patient pharmacological modeled BIS. However, modeled BIS may not provide a guarantee of adequate propofol infusion during BIS failure and especially in the presence of hypotension and hypertension. Thus, the proposed control strategy is designed with MFTM to detect BIS sensor fault and to estimate feedback BIS during BIS failure. Further, the proposed control strategy is designed with a multivariable pharmacological patient model to analyze the cross effect of propofol infusion on BIS and hemodynamic variables. The robustness of the proposed control strategy is tested in the presence of noxious surgical stimulation, BIS sensor fault and heavy hemodynamic disturbance. The pharmacological parameters and recorded signals of 30 patients during various surgeries have been used to validate simulated results. The performance of the proposed control strategy assures optimization and smooth propofol infusion during BIS failure. The proposed system provides stability for a wide range of physiological parameters range. The proposed scheme maintains smooth BIS and MAP signal despite the delay, BIS sensor fault, and surgical disturbances.

Adaptive smith predictor controller for total intravenous anesthesia automation.

Anesthetic agent propofol needs to be administered at an appropriate rate to prevent hypotension and postoperative adverse reactions. To comprehend more suitable anesthetic drug rate during surgery is a crucial aspect. The main objective of this proposal is to design robust automated control system that work efficiently in most of the patients with smooth BIS and minimum variations of propofol during surgery to avoid adverse post reactions and instability of anesthetic parameters. And also, to design advanced computer control system that improves the health of patient with short recovery time and less clinical expenditures. Unlike existing research work, this system administrates propofol as a hypnotic drug to regulate BIS, with fast bolus infusion in induction phase and slow continuous infusion in maintenance phase of anesthesia. The novelty of the paper lies in possibility to simplify the drug sensitivity-based adaption with infusion delay approach to achieve closed-loop control of hypnosis during surgery. Proposed work uses a brain concentration as a feedback signal in place of the BIS signal. Regression model based estimated sensitivity parameters are used for adaption to avoid BIS signal based frequent adaption procedure and large offset error. Adaptive smith predictor with lead-lag filter approach is applied on 22 different patients' model identified by actual clinical data. The actual BIS and propofol infusion signals recorded during clinical trials were used to estimate patient's sensitivity parameters EC 50 and λ. Simulation results indicate that patient's drug sensitivity parameters based adaptive strategy facilitates optimal controller performance in most of the patients. Results are obtained with proposed scheme having less settling time, BIS oscillations and small offset error leads to adequate depth of anesthesia. A comparison with manual control mode and previously reported system shows that proposed system achieves reduction in the total variations of the propofol dose. Proposed adaptive scheme provides better performance with less oscillation in spite of computation delay, surgical stimulations and patient variability. Proposed scheme also provides improvement in robustness and may be suitable for clinical practices.

Healthy Worker Effect Phenomenon: Revisited with Emphasis on Statistical Methods - A Review.

Known since 1885 but studied systematically only in the past four decades, the healthy worker effect (HWE) is a special form of selection bias common to occupational cohort studies. The phenomenon has been under debate for many years with respect to its impact, conceptual approach (confounding, selection bias, or both), and ways to resolve or account for its effect. The effect is not uniform across age groups, gender, race, and types of occupations and nor is it constant over time. Hence, assessing HWE and accounting for it in statistical analyses is complicated and requires sophisticated methods. Here, we review the HWE, factors affecting it, and methods developed so far to deal with it.

Healthy worker effect phenomenon.

The Healthy Worker Effect (HWE) phenomenon has been under debate since some years. Some epidemiologists regard HWE as an ordinary method problem while others consider it a field of science by itself. This article gives definitions of HWE explained with historical background; discusses factors affecting it and suggests methods to minimize problems associated with it.