Ambulatory urodynamics: extramural testing of the lower and upper urinary tract by Holter monitoring of cystometrogram, uroflowmetry, and renal pelvic pressures

This article elucidates the clinical applicability and state of the art of ambulatory urodynamics. Ambulatory urodynamics have evolved into practical investigations like EAC, HFM, and EAC combined with renal pelvimetry. EAC has been shown to be the method of preference if detrusor overactivity is involved. Conventional filling cystometry has proved to be an unreliable way to exclude detrusor instability. De novo instability after suspension surgery often indicates that an existing detrusor overactivity was not identified preoperatively. EAC including flowmetry has shown considerable variance in obstructive and contractility parameters in males with LUTS indicative for BPH. This raises doubt whether the clinical flow analysis is the suitable "gold standard" as advocated by the ICS. For a real break through of EAC, less complex automatic analysis is necessary. HFM is a newer method within the range of ambulatory urodynamic tests. It has not yet been completely evaluated. But, because the technique is analogous to the office flowmetry, noninvasive and very well accepted by the patients, it is expected to be widely used. This expectation is strengthened by the fact that HFM seems to show individual therapeutic efficacy of drugs, such as alpha-blockers. As a research tool to evaluate efficacy, it is far more powerful than conventional methods because of the reduction of within-patient standard deviation to about 10%. Finally, EAC combined with pelvimetry offers a promising method for the clinical evaluation of a combined dysfunction of upper and lower urinary tract.     

Modeling the glucose regulatory system in extreme preterm infants

Background

Premature infants represent a significant proportion of the neonatal intensive care population. Blood glucose homeostasis in this group is often disturbed by immaturity of endogenous regulatory systems and the stress of their condition. Hypo- and hyperglycemia are frequently reported in very low birth weight infants, and more mature infants often experience low levels of glycemia. A model capturing the unique fundamental dynamics of the neonatal glucose regulatory system could be used to develop better blood glucose control methods.

Methods

A metabolic system model is adapted from adult critical care to the unique physiological case of the neonate. Integral-based fitting methods were used to identify time-varying insulin sensitivity and non-insulin mediated glucose uptake profiles. The clinically important predictive ability of the model was assessed by assuming insulin sensitivity was constant over prediction intervals of 1, 2 and 4 h forward and comparing model-simulated versus actual clinical glucose values for all recorded interventions. The clinical data included 1091 glucose measurements over 3567 total patient hours, along with all associated insulin and nutritional infusion data, for N = 25 total cases. Ethics approval was obtained from the Upper South A Regional Ethics Committee for this study.

Results

The identified model had a median absolute percentage error of 2.4% [IQR: 0.9-4.8%] between model-fitted and clinical glucose values. Median absolute prediction errors at 1-, 2- and 4-h intervals were 5.2% [IQR: 2.5-10.3%], 9.4% [IQR: 4.5-18.4%] and 13.6% [IQR: 6.3-27.6%] respectively.

Conclusions

The model accurately captures and predicts the fundamental dynamic behaviors of the neonatal metabolism well enough for effective clinical decision support in glycemic control. The adaptation from adult to a neonatal case is based on the data from the literature. Low prediction errors and very low fitting errors indicate that the fundamental dynamics of glucose metabolism in both premature neonates and critical care adults can be described by similar mathematical models.     

Modelling acute renal failure using blood and breath biomarkers in rats

This paper compares three methods for estimating renal function, as tested in rats. Acute renal failure (ARF) was induced via a 60-min bilateral renal artery clamp in 8 Sprague-Dawley rats and renal function was monitored for 1 week post-surgery. A two-compartment model was developed for estimating glomerular filtration via a bolus injection of a radio-labelled inulin tracer, and was compared with an estimated creatinine clearance method, modified using the Cockcroft-Gault equation for rats. These two methods were compared with selected ion flow tube-mass spectrometry (SIFT-MS) monitoring of breath analytes. Determination of renal function via SIFT-MS is desirable since results are available non-invasively and in real time. Relative decreases in renal function show very good correlation between all 3 methods (R² = 0.84, 0.91 and 0.72 for breath-inulin, inulin-creatinine, and breath-creatinine correlations, respectively), and indicate good promise for fast, non-invasive determination of renal function via breath testing.     

Simulation of cardiovascular system diseases by including the autonomic nervous system into a minimal model

Diagnosing cardiovascular system (CVS) diseases from clinically measured data is difficult, due to the complexity of the hemodynamic and autonomic nervous system (ANS) interactions. Physiological models could describe these interactions to enable simulation of a variety of diseases, and could be combined with parameter estimation algorithms to help clinicians diagnose CVS dysfunctions. This paper presents modifications to an existing CVS model to include a minimal physiological model of ANS activation. A minimal model is used so as to minimise the number of parameters required to specify ANS activation, enabling the effects of each parameter on hemodynamics to be easily understood. The combined CVS and ANS model is verified by simulating a variety of CVS diseases, and comparing simulation results with common physiological understanding of ANS function and the characteristic hemodynamics seen in these diseases. The model of ANS activation is required to simulate hemodynamic effects such as increased cardiac output in septic shock, elevated pulmonary artery pressure in left ventricular infarction, and elevated filling pressures in pericardial tamponade. This is the first known example of a minimal CVS model that includes a generic model of ANS activation and is shown to simulate diseases from throughout the CVS.     

Integral-based filtering of continuous glucose sensor measurements for glycaemic control in critical care

Hyperglycaemia is prevalent in critical illness and increases the risk of further complications and mortality, while tight control can reduce mortality up to 43%. Adaptive control methods are capable of highly accurate, targeted blood glucose regulation using limited numbers of manual measurements due to patient discomfort and labour intensity. Therefore, the option to obtain greater data density using emerging continuous glucose sensing devices is attractive. However, the few such systems currently available can have errors in excess of 20-30%. In contrast, typical bedside testing kits have errors of approximately 7-10%. Despite greater measurement frequency larger errors significantly impact the resulting glucose and patient specific parameter estimates, and thus the control actions determined creating an important safety and performance issue. This paper models the impact of the continuous glucose monitoring system (CGMS, Medtronic, Northridge, CA) on model-based parameter identification and glucose prediction. An integral-based fitting and filtering method is developed to reduce the effect of these errors. A noise model is developed based on CGMS data reported in the literature, and is slightly conservative with a mean Clarke Error Grid (CEG) correlation of R=0.81 (range: 0.68-0.88) as compared to a reported value of R=0.82 in a critical care study. Using 17 virtual patient profiles developed from retrospective clinical data, this noise model was used to test the methods developed. Monte-Carlo simulation for each patient resulted in an average absolute 1-h glucose prediction error of 6.20% (range: 4.97-8.06%) with an average standard deviation per patient of 5.22% (range: 3.26-8.55%). Note that all the methods and results are generalizable to similar applications outside of critical care, such as less acute wards and eventually ambulatory individuals. Clinically, the results show one possible computational method for managing the larger errors encountered in emerging continuous blood glucose sensors, thus enabling their more effective use in clinical glucose regulation studies.     

Frequency dependence of MR relaxation times. I. Paramagnetic ions

T1 and T2 of paramagnetic ions in free and chelated form were measured over the range of clinical magnetic resonance imaging field strengths (0.02-1.5 T). T1 values agreed with published data; however, to our knowledge, the field dependence of T2 has not been systematically studied before Mn2+, Cr3+, and Fe3+ all showed T2 reduction at high field strengths, although reduction due to Fe3+ was minimal. This is believed to be due to "contact" interactions, which have been previously noted for manganese. No such T2 reduction was seen in the chelates, except that dysprosium chelate (but not free ion) showed an anomalous decrease in T2 at high field strengths, which may possibly be explained by a dephasing effect caused by the large magnetic moment of Dy3+.     

A standardized interviewing technique for evaluating postgraduate training applicants

In an effort to streamline the personal interview and to reduce the influence of subjectivity inpreparation of ranking lists for postgraduate year-one applicants, a standardized interview was constructed for use in evaluating condidates for admission to a training program in internal medicine. The interview was conducted in a uniformly structured manner by 14 interviewers of 260 applicants. Each applicant received an interview score which correlated well with the final decision of the Intern Selection Committee. For each interviewer various measures of performance were obtained which allowed a classification into "hard" versus "easy" interviewer and indicated the comparability of each interview's evaluations with the final decisions. Thus, the standardized interview resulted in quantifiable data in the form of uniform evaluations of applicants and interviewers.