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Biomedical subjects

G Avanzolini

Publications and source records attributed to G Avanzolini.

At least 19 recordsLinked to original sources
PubMed2002

Residual stresses at the stem-cement interface of an idealized cemented hip stem.

During the operation of total hip arthroplasty, when the cement polymerizes between the stem implant and the bone, residual stresses are generated in the cement. The purpose of this study was to determine whether including residual stresses at the stem-cement interface of cemented hip implants affected the cement stress distributions due to externally applied loads. An idealized cemented hip implant subjected to bending was numerically investigated for an early post-operative situation. The finite element analysis was three-dimensional and used non-linear contact elements to represent the debonded stem-cement interface. The results showed that the inclusion of the residual stresses at the interface had up to a 4-fold increase in the von Mises cement stresses compared to the case without residual stresses.

Bone Cements↗
PubMed2001

Effect of compliant intermediate airways on total respiratory resistance and elastance in mechanical ventilation.

Total respiratory resistance and elastance were estimated off-line in a sample of 60 patients undergoing mechanical ventilation by means of two regression models in order to analyse and understand a possible physiological mechanism determining differences in inspiration and expiration. The first model considered a single value for resistance and elastance over a whole breathing cycle, whereas the second model considered separate values for inspiratory and expiratory resistance and a single value for elastance. Inspiratory resistance was found to be lower than expiratory resistance, and intermediate values were obtained for resistance estimated over the whole breathing cycle. Student's t-test showed a highly significant difference between these resistance estimates, and principal components analysis demonstrated a significant increase in information when both inspiratory and expiratory resistances were used. Minor differences were found between values of elastance calculated with the two approaches. In an attempt to interpret these experimental results, a lung model incorporating the non-linear viscoelastic properties of the intermediate airways was considered. This model suggested that changes in intermediate airway volume play a significant role in breathing mechanics during artificial ventilation and indicated that inspiratory and expiratory resistance could be useful parameters for locating airway obstruction.

Airway Resistance↗
PubMed2001

An integrated model of the human ventilatory control system: the response to hypercapnia.

This work presents a mathematical model of the human respiratory control system, based on physiological knowledge. It includes three compartments for gas storage and exchange (lungs, brain tissue and other body tissues), and various kinds of feedback mechanisms. These comprehend peripheral chemoreceptors in the carotid body, central chemoreceptors in the medulla and a central ventilatory depression. The latter acts by reducing the response of the central neural system to the afferent peripheral chemoreceptor activity during prolonged hypoxia of the brain tissue. Furthermore, the model considers local blood flow adjustments in response to O2 and CO2 arterial pressure changes. In this study, the model has been validated by simulating the response to square changes in alveolar PCO2, performed at different constant levels of alveolar PO2. A good agreement with data reported in the literature has been checked. Subsequently, a sensitivity analysis on the role of the main feedback mechanisms on ventilation response to CO2 has been performed. The results suggest that the ventilatory response to CO2 challenges during hyperoxia can be almost completely ascribed to the central chemoreflex, while, during normoxia, the peripheral chemoreceptors provide a modest contribution too. By contrast, the response to hypercapnic stimuli during hypoxia involves a complex superimposition among different factors with disparate dynamics. Hence, results suggest that the ventilatory response to hypercapnia during hypoxia is more complex than that provided by simple empirical models, and that discrimination between the central and peripheral components based on time constants may be misleading.

Carbon Dioxide↗
PubMed2001

An integrated model of the human ventilatory control system: the response to hypoxia.

The mathematical model of the respiratory control system described in a previous companion paper is used to analyse the ventilatory response to hypoxic stimuli. Simulation of long-lasting isocapnic hypoxia at normal alveolar PCO2 (40 mmHg=5.33 kPa) shows the occurrence of a biphasic response, characterized by an initial peak and a subsequent hypoxic ventilatory decline (HVD). The latter is about as great as 2/3 of the initial peak and can be mainly ascribed to prolonged neural hypoxia. If isocapnic hypoxia is performed during hypercapnia (PACO2=48 mmHg =6.4 kPa), the ventilatory response is stronger and HVD is minimal (about 1/10-1/5 of the initial peak). During poikilocapnic hypoxia, ventilation exhibits smaller changes compared with the isocapnic case, with a rapid return toward baseline within a few minutes. Moreover, a significant undershoot occurs at the termination of the hypoxic period. This undershoot may lead to apnea and to a transient destabilization of the control system if the peripheral chemoreflex gain and time delay are twofold greater than basal.

Apnea↗
PubMed2001

Role of the mechanical properties of tracheobronchial airways in determining the respiratory resistance time course.

A physiologically based simulation model of breathing mechanics was considered in an attempt to interpret and explain the time course of input respiratory resistance during the breathing cycle, observed in recent studies on ventilated patients. The model assumes a flow-dependent Rohrer resistance for the upper extrathoracic airways and volume-dependent resistance and elastance for the intermediate airways. A volume-dependent resistance describes the dissipative pressure loss in the lower airways, and two constant elastances represent lung and chest wall elasticity. Simulated mouth flow and pressure signals obtained in a variety of well-controlled conditions were used to analyze total respiratory resistance and elastance estimated by an on-line algorithm based on a time-varying parameter model. These estimates were compared with those provided by classical estimation algorithms based on time-invariant models with two, three, and four parameters. The results show that the four-parameter model is difficult to identify, while the three-parameter one offers no substantial advantage for estimating input resistance with respect to the more simple two-parameter model. In contrast, the time-varying approach provides good on-line estimates of the simulated end-expiration and end-inspiration resistances. These values provide further information of potential clinical utility, with respect to time-invariant models. For example, the results show that the difference between the end-expiration and end-inspiration resistance increases when obstructions shift from the upper to the lower airways. The similarity of the results obtained with measured and simulated data indicates that, in spite of its simplicity, the simulation model describes important physiological mechanisms underlying changes in respiratory input resistance, specifically the mechanical properties of intermediate airways.

Airway Resistance↗
PubMed2000

Prediction of solute kinetics, acid-base status, and blood volume changes during profiled hemodialysis.

A mathematical model of solute kinetics oriented to the simulation of hemodialysis is presented. It includes a three-compartment model of body fluids (plasma, interstitial and intracellular), a two-compartment description of the main solutes (K+, Na+, Cl-, urea, HCO3-, H+), and acid-base equilibrium through two buffer systems (bicarbonate and noncarbonic buffers). Tentative values for the main model parameters can be given a priori, on the basis of body weight and plasma concentration values measured before beginning the session. The model allows computation of the amount of sodium removed during hemodialysis, and may enable the prediction of plasma volume and osmolarity changes induced by a given sodium concentration profile in the dialysate and by a given ultrafiltration profile. Model predictions are compared with clinical data obtained during 11 different profiled hemodialysis sessions, both with all parameters assigned a priori, and after individual estimation of dialysances and mass-transfer coefficients. In most cases, the agreement between the time pattern of model solute concentrations in plasma and clinical data was satisfactory. In two sessions, blood volume changes were directly measured in the patient, and in both cases the agreement with model predictions was acceptable. The present model can be used to improve the dialysis session taking some characteristics of individual patients into account, in order to minimize intradialytic unbalances (such as hypotension or disequilibrium syndrome).

Acid-Base Equilibrium↗
PubMed1999

Mathematical modeling of solute kinetics and body fluid changes during profiled hemodialysis.

A mathematical model of solute kinetics oriented to improve hemodialysis treatment is presented. It includes a two-compartment description of the main solutes (K+, Na+, Cl-, urea, HCO3-, H+, CO2), acid-base equilibrium through two buffer systems (bicarbonate and non-carbonic buffers) and a three-compartment model of body fluids (plasma, interstitial and intracellular). The main model parameters can be individually assigned a priori, on the basis of body weight and plasma concentration values measured before beginning the session. Model predictions are compared with clinical data obtained during 11 different hemodialysis sessions performed on six patients with profiled sodium concentration in the dialysate and profiled ultrafiltration rate. In all cases, the agreement between the time pattern of model solute concentrations in plasma and clinical data turns out fairly good as to urea, sodium, chloride and potassium kinetics. Finally, the time patterns of plasma bicarbonate concentration and pH can be reproduced fairly well with the model, provided CO2 concentration remains constant. Only in two sessions, blood volume was directly measured in the patient, and in both cases the agreement with model predictions was good. In conclusion, the model allows a priori computation of the amount of sodium removed during hemodialysis, and may enable the prediction of plasma volume changes and plasma osmolarity changes induced by a given sodium concentration profile in the dialysate and by a given ultrafiltration profile. Hence, it can be used to improve the dialysis session taking the characteristics of individual patients into account, in order to minimize intradialytic imbalances (such as hypotension or disequilibrium syndrome).

Acid-Base Equilibrium↗
PubMed1998

A simple mathematical model applied to selection of the sodium profile during profiled haemodialysis.

BACKGROUND: Among dialysis patients in the last 10 years the incidence of intradialytic dysequilibrium syndrome and symptomatic hypotension has increased significantly. Profiled haemodialysis (PHD), a new dialysis technique based on intradialytic modulation of the dialysate sodium concentration according to pre-elaborated individual profiles, has been set up to reduce intradialytic imbalances and the incidence of dysequilibrium syndrome and symptomatic hypotension. The present paper illustrates a new mathematical model for solute kinetics, single-compartment for sodium and two-compartment for urea, aimed at improving the use of PHD. The model allows the sodium profile to be elaborated a priori, before each dialysis session, according to the patient's clinical needs and respecting the individual sodium mass removal and weight gain. METHOD: The mathematical model was first derived and then applied to determining a rational dialysate sodium profile. A procedure which allows the method to be tuned to individual clinical needs on the basis of routine measurements performed before each session is also presented. The proposed method was validated in vivo during seven dialysis sessions, each performed on a different patient. RESULTS: The comparison between data predicted by the model and those obtained in vivo shows a good correspondence in particular concerning the time pattern of blood urea and sodium. The comparison between the model prediction and in vivo determined sodium and urea plasma curves showed standard deviations (2.25 mEq/l for sodium and 0.87 mmol/l for urea) only slightly higher than those attributable to laboratory measurement errors. Moreover, in vivo implementation of PHD by our model enables one to remove an amount of sodium mass comparable with the a priori quantity predicted by the model.

Aged↗
PubMed1997

Autonomic nervous function during haemodialysis assessed by spectral analysis of heart-rate variability.

1. Short-term autonomic response to haemodialysis-induced hypovolaemia was studied in 30 patients undergoing chronic haemodialysis by analysing power spectra of heart-period variability. Patients were classified as haemodynamically stable (15 patients) and unstable (15 patients) according to their past history of cardiovascular collapse during the treatment. Blood volume, systolic arterial pressure and heart period were measured during sessions that ended without the occurrence of collapse. 2. No significant differences were observed when comparing blood volume, heart rate and arterial pressure of stable and unstable patients during the dialysis, and the two groups could not be distinguished merely on the basis of these haemodynamic parameters. Conversely, spectral analysis of beat-to-beat heart-period variability showed markedly different power patterns: in stable patients power was mainly in the low-frequency (LF) band (0.06-0.15 Hz), whereas in unstable patients it was mainly in the high-frequency (HF) band (0.15-0.4 Hz). 3. The efficiency of the autonomic response to hypovolaemia was evaluated by the ratio between the powers in the LF and HF bands. Stable patients exhibited an LF/HF power ratio systematically greater than unstable patients during the entire dialysis, and on the basis of this index the two groups were clearly separated. 4. Results obtained with spectral analysis lead us to conclude that reduced efficiency in the autonomic control of cardiovascular functions could be the main cause of the haemodynamic instability of patients prone to collapse.

Aged↗
PubMed1997

Heart rate variability spectral indices for haemodynamic classification of haemodialysis patients.

The usefulness of spectral indices extracted from the heart rate variability (HRV) in discriminating between hypotension-prone and hypotension-resistant haemodialysis patients was investigated. In 30 patients, classified as hypotension resistant (stable group) or hypotension prone (unstable group), beat-to-beat heart period was measured during haemodialysis sessions terminated without collapses. HRV was analysed in the frequency domain combining classic autoregressive spectral estimation with two eigen decomposition-based techniques: the reduced rank approximation (RRA) of the autocorrelation matrix and the Pisarenko harmonic decomposition (PHD). Five spectral indices were obtained: the ratio between the powers in the LF and HF bands (LF/HF), the same ratio calculated after application of RRA (LF/HFRRA), the frequency of the main oscillatory component of HRV estimated through PHD with a decomposition order equal to 1 (F1) and equal to 2 (F2) and the difference between the frequencies of the two oscillatory components resolved in the latter cas (Fd). The performances of these indices in discriminating between the two groups of patients were evaluated estimating the misclassification probability (Pm) of a Bayesian quadratic classifier. The HRV spectral pattern was markedly different: in the stable patients power was mainly in the low-frequency band, whereas in the unstable group it was mainly in the high-frequency band. The frequency of the main oscillatory component was significantly greater in the unstable group than in the stable one. Spectral indices displayed good discrimination power, increasing with the length of the dialysis interval. Best performances were achieved by LF/HFRRA both over short dialysis periods (Pm approximately 12% over 20 min intervals) and over longer periods (Pm = 3.3% over 160 min); similar results were obtained with Fd over short periods and LF/HF over long periods. Spectral HRV indices demonstrate, therefore, a diagnostic value in discriminating between hypotension-resistant and hypotension-prone patients.

Bayes Theorem↗
PubMed1997

An algorithm for the rational choice of sodium profile during hemodialysis.

The incidence of intradialytic disequilibrium syndrome and symptomatic hypotension has increased significantly among dialysis patients over the last ten years. Profiled hemodialysis (PHD) is a new technique, based on the intradialytic modulation of dialysate sodium concentration, which aspires to reduce to previous imbalances. This paper presents a new algorithm for the determination of a rational dialysate sodium profile during PHD. A mathematical model of solute kinetics, monocompartmental for sodium and bicompartmental for urea is used. The algorithm allows the sodium profile to be elaborated a priori before each dialysis session, respecting the individual sodium mass removal and weight gain. A procedure allowing the adjustment of the method to the individual characteristics, on the basis of routine measurements performed before each session is also presented. The method was validated during seven dialysis sessions. Comparison between data measured in vivo and those predicted by the model showed standard deviations corresponding to the range of laboratory measurement errors: 1.50 mEq/L for sodium and 0.87 mmol/L for urea. In vivo implementation of PHD by our algorithm allows one to remove an amount of sodium close to that established a priori on the basis of patient's need.

Aged↗
PubMed1996

An expert system based on causal knowledge: validation on post-cardiosurgical patients.

A new expert system for the analysis of post-cardiosurgical patients in Intensive Care Units is described, and a preliminary validation performed. The inference engine employs a hybrid reasoning method which integrates quantitative and qualitative simulation techniques in an original manner. The long-term knowledge consists of a causal network which reproduces the main relationships between physiological quantities involved in the course after cardiac surgery. Emphasis has been given to respiratory and metabolic, as well as cardiovascular quantities both in the systemic and pulmonary circulations. Preliminary system validation has been performed on a set of 40 cardiosurgical patients, previously classified either at normal-risk (17 patients) or at high-risk (23 patients) by means of statistical classification techniques. In most cases, predictions of the expert system substantially agree with those provided by the more traditional statistical method. The system, however, is also able to furnish detailed explanations on the possible physiological causes responsible for the patient status. In particular, simulation results indicate that a reduction in the cardiac index (19 cases) and an increase in the oxygen utilization coefficient (19 cases) are the most critical alterations in the high-risk patients. The system imputes the reduced cardiac index to a rise in total systemic resistance (15 high-risk patients), a decrease in cardiac strength (2 high-risk patients) or an insufficient filling volume of the systemic circulation (4 high-risk patients). Furthermore, in 6 high-risk patients the depressed cardiac outflow occurs with a reduction in the arterial oxygen content, mainly imputable to an insufficiency of blood hemoglobin content. Finally, two examples of the complete expert system explanatory capabilities are shown with reference to a pair of high-risk patients and discussed.

Blood Circulation↗
PubMed1996

Parametric analysis of heart rate variability during hemodialysis.

The problem of evaluating short-term autonomic response to hypovolemia in patients under chronic hemodialysis treatment is considered. Power spectra of the beat-to-beat heart rate variability were evaluated during the dialysis treatment in twenty hemodynamically stable and unstable patients, using a parametric technique. The autoregressive model coefficients were calculated by the modified covariance method, while model order was selected according to the minimum description length criterion. Reported results demonstrate that stable and unstable patients present markedly different spectral patterns. The efficiency of the compensatory response to hemodialysis-induced hypovolemia was evaluated through the ratio between the powers in LF and HF bands. Stable patients exhibit a LF/HF ratio greater than one with large fluctuations over the whole dialysis session. In contrast, all the unstable patients are characterized by a value of LF/HF lower than one and with a reduced time variability. This result suggests that the hemodynamic instability of the hypotension-prone patients may be due to a deficiency in the short-term compensatory response to the hemodialysis-induced hypovolemia.

Algorithms↗
PubMed1996

A simple mathematical model of intradialytic sodium kinetics: "in vivo" validation during hemodialysis with constant or variable sodium.

A simple mathematical model of the intradialytic relationship between natraemia and dialysate sodium concentration is presented. The model includes a bicompartmental description of sodium, urea and fluid kinetics and an algebraic characterization of diffusive/convective mass-transfer across the dialysis membrane. Its ability to provide realistic responses has been validated comparing model predictions by a priori parameter tuning against quantities measured during in vivo sessions with both constant and variable dialysate sodium concentration. A quantitative analysis of model predictions indicates that the mean deviation between data calculated by the model and those measured in vivo is 1.32 mEq/l for sodium and 0.76 mmol/l for urea, values which do not greatly exceed the measurement errors of current instruments. The model's predictive capacity thus proves reliable. The ability of the model to calculate the amount of sodium removed and the time course of intra-extracellular volumes during the dialysis session makes it possible to forecast the patient's clinical tolerance to a given sodium dialysate concentration.

Adult↗
PubMed1995

Analytic solution of the Variable-Volume Double-Pool urea kinetics model applied to parameter estimation in hemodialysis.

An analytic solution of the Variable-Volume Double-Pool urea kinetics model and its application to the estimation of clinically relevant parameters of the patient-machine system, are presented. These include the urea distribution volume and generation rate and the mean dialyzer clearance. The estimation of these parameters is based on the assumption of constant values for the diffusion coefficient between the two pools and the intra-extracellular volume ratio. Results obtained by computer simulations show that the effect of a +/- 50% variation of these parameters influences the estimates less than standard measurement errors. Starting from these results, four methods to in vivo estimate the urea distribution volume and generation rate from blood samples are compared. Two methods are based on the analytic solution of the double-pool model using seven samples (reference method) or three samples (new clinical method). The remaining methods are based on urea mass-balance and are largely used in the clinical practice. These last techniques differ from each other for the blood sample taken at the end of the treatment or 30 min later. The results obtained from hemofiltration sessions show that the urea generation rate is accurately estimated by all methods. The total distribution volume is still accurately estimated by the new clinical method while it is systematically underestimated by the urea mass-balance when the blood sample at the end of dialysis is used. Instead, a high overcompensation results using the blood sample taken 30 min after the end of dialysis. Finally, the new clinical method also provides reliable estimates for the dialyzer clearance starting from only three blood samples all taken during dialysis.

Algorithms↗
PubMed1995

Extraction of discriminant features in post-cardiosurgical intensive care units.

A linear transformation, based on the Karhunen-Loève expansion, is applied to 13 physiological variables, measured in 200 surgical patients, in order to extract a limited number of features well representative of the differences between normal and high-risk classes of subjects. This transformation may be considered as a mapping from the primitive 13-dimensional space to a lower dimensional one, without severely reducing class separability. The efficacy of both transformed and primitive variables in the separation of normal and high-risk subjects is compared using the error probability, i.e. the probability that a patient is assigned to the wrong class. In particular, its upper bound is evaluated through the Kullback divergence and its estimate is computed, from the available samples, by applying a quadratic classifier. The results obtained show that only two transformed variables are able to present a divergence better than the most effective set of eight primitive variables. In agreement with the divergence criterion, the classifier provides a recognition error lower than 5% and greater than 13% when using the two best transformed and the two best primitive variables, respectively. Even though the new variables do not have a direct physiological meaning, this limitation has been partially overcome by calculating the correlation matrix between transformed and primitive variables. The results presented show that the first two transformed variables are strongly related to the most discriminant primitive ones (i.e. cardiac index, oxygen delivery and arterio-venous oxygen difference). In conclusion, the transformation of variables proposed appears to be extremely attractive for practical applications, since it allows recognition systems to be designed which exhibit both high performance and great simplicity.

Algorithms↗
PubMed1995

Sensitivity analysis for estimating urea kinetics parameters during hemodialysis.

In this paper a time-varying volume, double-pool urea kinetics model is considered and a sensitivity analysis is carried out to determine those patient parameters that have greater influence on the time course of blood urea nitrogen concentration (BUN) during and between dialysis treatment. The model parameters include the urea generation rate, the initial distribution volume of the urea, the ratio between intracellular and extracellular volumes, and the mass transfer coefficient between the two pools. The analysis demonstrates that BUN is highly sensitive to the urea generation rate and total distribution volume whereas it is influenced by the remaining parameters to a much lesser extent. In addition, the location of the absolute maxima of BUN sensitivity functions suggests the rational placement of a reduced number of blood samples that may still allow sufficiently accurate estimates for the parameters of clinical interest, such as the urea generation rate, total distribution volume, and the ratio between intracellular and extracellular volumes. This conclusion has been confirmed by simulation studies where parameter estimation has been performed with a varying number of observation points.

Blood Urea Nitrogen↗