Closed-loop control of mean arterial blood pressure during surgery with alfentanil: clinical evaluation of a novel model-based predictive controller

BACKGROUND: In contrast to hypnosis, there is no surrogate parameter for analgesia in anesthetized patients. Opioids are titrated to suppress blood pressure response to noxious stimulation. The authors evaluated a novel model predictive controller for closed-loop administration of alfentanil using mean arterial blood pressure and predicted plasma alfentanil concentration (Cp Alf) as input parameters. METHODS: The authors studied 13 healthy patients scheduled to undergo minor lumbar and cervical spine surgery. After induction with propofol, alfentanil, and mivacurium and tracheal intubation, isoflurane was titrated to maintain the Bispectral Index at 55 (+/- 5), and the alfentanil administration was switched from manual to closed-loop control. The controller adjusted the alfentanil infusion rate to maintain the mean arterial blood pressure near the set-point (70 mmHg) while minimizing the Cp Alf toward the set-point plasma alfentanil concentration (Cp Alfref) (100 ng/ml). RESULTS: Two patients were excluded because of loss of arterial pressure signal and protocol violation. The alfentanil infusion was closed-loop controlled for a mean (SD) of 98.9 (1.5)% of presurgery time and 95.5 (4.3)% of surgery time. The mean (SD) end-tidal isoflurane concentrations were 0.78 (0.1) and 0.86 (0.1) vol%, the Cp Alf values were 122 (35) and 181 (58) ng/ml, and the Bispectral Index values were 51 (9) and 52 (4) before surgery and during surgery, respectively. The mean (SD) absolute deviations of mean arterial blood pressure were 7.6 (2.6) and 10.0 (4.2) mmHg (P = 0.262), and the median performance error, median absolute performance error, and wobble were 4.2 (6.2) and 8.8 (9.4)% (P = 0.002), 7.9 (3.8) and 11.8 (6.3)% (P = 0.129), and 14.5 (8.4) and 5.7 (1.2)% (P = 0.002) before surgery and during surgery, respectively. A post hoc simulation showed that the Cp Alfref decreased the predicted Cp Alf compared with mean arterial blood pressure alone. CONCLUSION: The authors' controller has a similar set-point precision as previous hypnotic controllers and provides adequate alfentanil dosing during surgery. It may help to standardize opioid dosing in research and may be a further step toward a multiple input-multiple output controller.

Are mutans streptococci detected in preschool children a reliable predictive factor for dental caries risk? A systematic review

Research suggests that mutans streptococci play an important role in cariogenesis in children but the usefulness of bacterial testing in risk assessment is unknown. Our objective was to summarize the literature assessing the association of mutans streptococci and dental caries in preschool children, (Pre)Medline (1966-2003), Embase (1980-2003), the Cochrane Register of Controlled Trials (2003, issue 3), and reference lists of included studies were searched. All abstracts found by the electronic searches (n = 981) were independently scrutinized by 2 reviewers. Minimal requirements for inclusion were assessment of preschool children without caries at baseline, reporting of mutans streptococci present in saliva or plaque at baseline and assessment of caries presence after a minimum of 6 months of follow-up. Participants' details, test methods, methodological characteristics and findings were extracted by one reviewer and cross-checked by another. Homogeneity was tested using chi2 tests. Results of plaque and saliva testing were pooled separately using a fixed effects model. Methodological quality of reports was low. Out of 9 studies included, data from 3 reports on plaque test assessment alone (n = 300) and from 4 reports on saliva test assessment alone (n = 451) were available for pooled analysis. The pooled risk ratio (95% CI) was 3.85 (2.48-5.96) in studies using plaque tests and 2.11 (1.47-3.02) in those using saliva testing. Presence of mutans streptococci, both in plaque or saliva of young caries-free children, appears to be associated with a considerable increase in caries risk. Lack of adjustment for potential confounders in the original studies, however, limits the extent to which interpretations for practice can be made.

POOR PERFORMANCE OF BOOTSTRAP CONFIDENCE INTERVALS FOR THE LOCATION OF A QUANTITATIVE TRAIT LOUCS

The aim of many genetic studies is to locate the genomic regions (called quantitative trait loci, QTLs) that contribute to variation in a quantitative trait (such as body weight). Confidence intervals for the locations of QTLs are particularly important for the design of further experiments to identify the gene or genes responsible for the effect. Likelihood support intervals are the most widely used method to obtain confidence intervals for QTL location, but the non-parametric bootstrap has also been recommended. Through extensive computer simulation, we show that bootstrap confidence intervals are poorly behaved and so should not be used in this context. The profile likelihood (or LOD curve) for QTL location has a tendency to peak at genetic markers, and so the distribution of the maximum likelihood estimate (MLE) of QTL location has the unusual feature of point masses at genetic markers; this contributes to the poor behavior of the bootstrap. Likelihood support intervals and approximate Bayes credible intervals, on the other hand, are shown to behave appropriately.

Evaluating Prediction Rules for t-Year Survivors With Censored Regression Models

Suppose that we are interested in establishing simple, but reliable rules for predicting future t-year survivors via censored regression models. In this article, we present inference procedures for evaluating such binary classification rules based on various prediction precision measures quantified by the overall misclassification rate, sensitivity and specificity, and positive and negative predictive values. Specifically, under various working models we derive consistent estimators for the above measures via substitution and cross validation estimation procedures. Furthermore, we provide large sample approximations to the distributions of these nonsmooth estimators without assuming that the working model is correctly specified. Confidence intervals, for example, for the difference of the precision measures between two competing rules can then be constructed. All the proposals are illustrated with two real examples and their finite sample properties are evaluated via a simulation study.

Matrix metalloproteinase-19 is a predictive marker for tumor invasiveness in patients with oropharyngeal squamous cell carcinoma

AIMS: To evaluate the expression of matrix metalloproteinase-19 (MMP-19) in oropharyngeal squamous cell carcinoma along with its association with structural features of invasiveness. To investigate whether MMP-19 expression correlates with lymphatic or systemic metastasis and prognosis in patients who have received definitive radiotherapy. METHODS AND RESULTS: The histological evaluation of the invasive front was based on Bryne's malignancy grading system. We correlated the immunohistochemical expression pattern with morphological parameters which characterize tumor invasiveness such as keratinization, nuclear polymorphism, invasion pattern, and the host inflammatory response. Local immunoreactivity for MMP-19 was positively correlated with tumor invasiveness as reflected in its structural characteristics and the degree of nuclear polymorphism, and negatively correlated with the inflammatory response of the host. No correlation existed between MMP-19 expression and clinicopathological features (TNM stage, grade of differentiation) or a patient''s outcome and prognosis. CONCLUSIONS: This latter finding probably reflects the unique change for MMPs from high immunoreactivity within healthy tissue areas and non-invasive tumor parts, through absence in the least invasive neoplastic regions, to strong re-expression at a highly invasive front of the same tumor. Our findings indicate that MMP-19 can be used as a marker for tumor invasiveness in patients with oropharyngeal squamous cell carcinoma.

Statistical evaluation of time-dependent metabolite concentrations: estimation of post-mortem intervals based on in situ 1H-MRS of the brain

Knowledge of the time interval from death (post-mortem interval, PMI) has an enormous legal, criminological and psychological impact. Aiming to find an objective method for the determination of PMIs in forensic medicine, 1H-MR spectroscopy (1H-MRS) was used in a sheep head model to follow changes in brain metabolite concentrations after death. Following the characterization of newly observed metabolites (Ith et al., Magn. Reson. Med. 2002; 5: 915-920), the full set of acquired spectra was analyzed statistically to provide a quantitative estimation of PMIs with their respective confidence limits. In a first step, analytical mathematical functions are proposed to describe the time courses of 10 metabolites in the decomposing brain up to 3 weeks post-mortem. Subsequently, the inverted functions are used to predict PMIs based on the measured metabolite concentrations. Individual PMIs calculated from five different metabolites are then pooled, being weighted by their inverse variances. The predicted PMIs from all individual examinations in the sheep model are compared with known true times. In addition, four human cases with forensically estimated PMIs are compared with predictions based on single in situ MRS measurements. Interpretation of the individual sheep examinations gave a good correlation up to 250 h post-mortem, demonstrating that the predicted PMIs are consistent with the data used to generate the model. Comparison of the estimated PMIs with the forensically determined PMIs in the four human cases shows an adequate correlation. Current PMI estimations based on forensic methods typically suffer from uncertainties in the order of days to weeks without mathematically defined confidence information. In turn, a single 1H-MRS measurement of brain tissue in situ results in PMIs with defined and favorable confidence intervals in the range of hours, thus offering a quantitative and objective method for the determination of PMIs.

Predictive value of known and novel alleles of CYP2B6 for efavirenz plasma concentrations in HIV-infected individuals

To assess the association of CYP2B6 allelic diversity with efavirenz (EFV) pharmacokinetics, we performed extensive genotyping of 15 relevant single nucleotide polymorphism in 169 study participants, and full resequencing of CYP2B6 in individuals with abnormal EFV plasma levels. Seventy-seven (45.5%) individuals carried a known (CYP2B6*6, *11, *15, or *18) or new loss/diminished-function alleles. Resequencing defined two new loss-of-function alleles: allele *27 (marked by 593T>C [M198T]), that results in 85% decrease in enzyme activity and allele *28 (marked by 1132C>T), that results in protein truncation at arginine 378. Median AUC levels were 188.5 microg h/ml for individuals homozygous for a loss/diminished-function allele, 58.6 microg h/ml for carriers, and 43.7 microg h/ml for noncarriers (P<0.0001). Individuals with a poor metabolizer genotype had a likelihood ratio of 35 (95% CI, 11-110) of presenting very high EFV plasma levels. CYP2B6 poor metabolizer genotypes explain to a large extent EFV pharmacokinetics and identify individuals at risk of extremely elevated EFV plasma levels.

Clinical and microbiological analysis of subjects treated with Brånemark or AstraTech implants: a 7-year follow-up study

AIMS: To assess the impact of different implant systems on the clinical conditions and the microbiota at implants, and whether the presence of bacteria at tooth sites was predictive of the presence at implant sites. MATERIALS AND METHODS: Subjects with either AstraTech or Brånemark in function for 7 years were enrolled. Sub-gingival bacterial samples at tooth and implant sites were collected with sterile endodontic paper points, and analyzed by the checkerboard DNA-DNA hybridization method (40 species). RESULTS: Fifty-four subjects, 27 supplied with AstraTech (n=132 implants) and 27 with Brånemark (n=102) implants, were studied. Test tooth sites had significantly less evidence of bleeding on probing (P<0.001) and presence of plaque (P<0.001) than implant test sites. Implant sites presented with deeper probing pocket depth than tooth sites (mean difference: 1.1 mm, standard error of differences: 0.08, 95% confidence intervals (CI): 0.9-1.3, P<0.001). Tannerella forsythia (P<0.05), Capnocytophaga sputigena (P<0.05), Actinomyces israelii (P<0.05) and Lactobacillus acidophilus (P<0.05) were found at higher levels at tooth surfaces. No differences in bacterial load for any species were found between the two implant systems. The odds of being present/absent at tooth and implants sites were only significant for Staphylococcus aureus [odds ratio (OR): 5.2 : 1, 95% CI: 1.4-18.9, P<0.01]. CONCLUSIONS: After 7 years in function, implants presented with deeper probing depths than teeth. S. aureus was commonly present at both teeth and implants sites. S. aureus at tooth sites was predictive of also being present at implant sites.

Bloodstream infections in pediatric ECLS: usefulness of daily blood culture monitoring and predictive value of biological markers. The British Columbia experience

INTRODUCTION: The incidence of bloodstream infection (BSI) in extracorporeal life support (ECLS) is reported between 0.9 and 19.5%. In January 2006, the Extracorporeal Life Support Organization (ELSO) reported an overall incidence of 8.78% distributed as follows: respiratory: 6.5% (neonatal), 20.8% (pediatric); cardiac: 8.2% (neonatal) and 12.6% (pediatric). METHOD: At BC Children's Hospital (BCCH) daily surveillance blood cultures (BC) are performed and antibiotic prophylaxis is not routinely recommended. Positive BC (BC+) were reviewed, including resistance profiles, collection time of BC+, time to positivity and mortality. White blood cell count, absolute neutrophile count, immature/total ratio, platelet count, fibrinogen and lactate were analyzed 48, 24 and 0 h prior to BSI. A univariate linear regression analysis was performed. RESULTS: From 1999 to 2005, 89 patients underwent ECLS. After exclusion, 84 patients were reviewed. The attack rate was 22.6% (19 BSI) and 13.1% after exclusion of coagulase-negative staphylococci (n = 8). BSI patients were significantly longer on ECLS (157 h) compared to the no-BSI group (127 h, 95% CI: 106-148). Six BSI patients died on ECLS (35%; 4 congenital diaphragmatic hernias, 1 hypoplastic left heart syndrome and 1 after a tetralogy repair). BCCH survival on ECLS was 71 and 58% at discharge, which is comparable to previous reports. No patient died primarily because of BSI. No BSI predictor was identified, although lactate may show a decreasing trend before BSI (P = 0.102). CONCLUSION: Compared with ELSO, the studied BSI incidence was higher with a comparable mortality. We speculate that our BSI rate is explained by underreporting of "contaminants" in the literature, the use of broad-spectrum antibiotic prophylaxis and a higher yield with daily monitoring BC. We support daily surveillance blood cultures as an alternative to antibiotic prophylaxis in the management of patients on ECLS.

Predictive control of hybrid vehicle powertrain for intelligent energy management

This thesis studies the minimization of the fuel consumption for a Hybrid Electric Vehicle (HEV) using Model Predictive Control (MPC). The presented MPC – based controller calculates an optimal sequence of control inputs to a hybrid vehicle using the measured plant outputs, the current dynamic states, a system model, system constraints, and an optimization cost function. The MPC controller is developed using Matlab MPC control toolbox. To evaluate the performance of the presented controller, a power-split hybrid vehicle, 2004 Toyota Prius, is selected. The vehicle uses a planetary gear set to combine three power components, an engine, a motor, and a generator, and transfer energy from these components to the vehicle wheels. The planetary gear model is developed based on the Willis’s formula. The dynamic models of the engine, the motor, and the generator, are derived based on their dynamics at the planetary gear. The MPC controller for HEV energy management is validated in the MATLAB/Simulink environment. Both the step response performance (a 0 – 60 mph step input) and the driving cycle tracking performance are evaluated. Two standard driving cycles, Urban Dynamometer Driving Schedule (UDDS) and Highway Fuel Economy Driving Schedule (HWFET), are used in the evaluation tests. For the UDDS and HWFET driving cycles, the simulation results, the fuel consumption and the battery state of charge, using the MPC controller are compared with the simulation results using the original vehicle model in Autonomie. The MPC approach shows the feasibility to improve vehicle performance and minimize fuel consumption.

DEVELOPMENT OF A PREDICTIVE COMBUSTION MODEL OF A SPARK IGNITED ENGINE WITH GASOLINE DIRECT INJECTION, VARIABLE VALVE TIMING, DURATION AND LIFT TECHNOLOGIES

There is a need by engine manufactures for computationally efficient and accurate predictive combustion modeling tools for integration in engine simulation software for the assessment of combustion system hardware designs and early development of engine calibrations. This thesis discusses the process for the development and validation of a combustion modeling tool for Gasoline Direct Injected Spark Ignited Engine with variable valve timing, lift and duration valvetrain hardware from experimental data. Data was correlated and regressed from accepted methods for calculating the turbulent flow and flame propagation characteristics for an internal combustion engine. A non-linear regression modeling method was utilized to develop a combustion model to determine the fuel mass burn rate at multiple points during the combustion process. The computational fluid dynamic software Converge ©, was used to simulate and correlate the 3-D combustion system, port and piston geometry to the turbulent flow development within the cylinder to properly predict the experimental data turbulent flow parameters through the intake, compression and expansion processes. The engine simulation software GT-Power © is then used to determine the 1-D flow characteristics of the engine hardware being tested to correlate the regressed combustion modeling tool to experimental data to determine accuracy. The results of the combustion modeling tool show accurate trends capturing the combustion sensitivities to turbulent flow, thermodynamic and internal residual effects with changes in intake and exhaust valve timing, lift and duration.