Real-time algorithm for changes detection in depth of anesthesia signals

This paper presents a real-time algorithm for changes detection in depth of anesthesia signals. A Page-Hinkley test (PHT) with a forgetting mechanism (PHT-FM) was developed. The samples are weighted according to their "age" so that more importance is given to recent samples. This enables the detection of the changes with less time delay than if no forgetting factor was used. The performance of the PHT-FM was evaluated in a two-fold approach. First, the algorithm was run offline in depth of anesthesia (DoA) signals previously collected during general anesthesia, allowing the adjustment of the forgetting mechanism. Second, the PHT-FM was embedded in a real-time software and its performance was validated online in the surgery room. This was performed by asking the clinician to classify in real-time the changes as true positives, false positives or false negatives. The results show that 69 % of the changes were classified as true positives, 26 % as false positives, and 5 % as false negatives. The true positives were also synchronized with changes in the hypnotic or analgesic rates made by the clinician. The contribution of this work has a high impact in the clinical practice since the PHT-FM alerts the clinician for changes in the anesthetic state of the patient, allowing a more prompt action. The results encourage the inclusion of the proposed PHT-FM in a real-time decision support system for routine use in the clinical practice. © 2012 Springer-Verlag

Evaluation of SLOG/TCI-III pediatric system on target control infusion of propofol

<p>Abstract</p> <p>Background</p> <p>The target-controlled infusion-III (SLOG/TCI-III) system was derived from a model set up by the local pediatric population for target control infusion of propofol.</p> <p>Methods</p> <p>The current study aimed at evaluating the difference between target concentrations of propofol and performance, which was measured using the SLOG/TCI-III system in children. Thirty children fulfilling the I-II criteria according to American Society of Anesthesiology were enrolled in the study. The target plasma concentration of propofol was fed into the SLOG/TCI-III system and compared with the measured concentrations of propofol. Blood samples were collected and analyzed by high performance liquid chromatography with fluorescence detector. The performance error (PE) was determined for each measured blood propofol concentration. The performances of the TCI-III system were determined by the median performance error (MDPE), the median absolute performance error (MDAPE), and Wobble (the median absolute deviation of each PE from the MDPE), respectively.</p> <p>Results</p> <p>Concentration against target concentration showed good linear correlation: concentration = 1.3428 target concentration - 0.2633 (r = 0.8667). The MDPE and MDAPE of the pediatric system were 10 and 22%, respectively, and the median value for Wobble was 24%. MDPE and MDAPE were less than 15 and 30%, respectively.</p> <p>Conclusions</p> <p>The performance of TCI-III system seems to be in the accepted limits for clinical practice in children.</p

An Adaptive Monitoring Scheme for Automatic Control of Anaesthesia in dynamic surgical environments based on Bispectral Index and Blood Pressure.

During surgical procedures, bispectral index (BIS) is a well-known measure used to determine the patient's depth of anesthesia (DOA). However, BIS readings can be subject to interference from many factors during surgery, and other parameters such as blood pressure (BP) and heart rate (HR) can provide more stable indicators. However, anesthesiologist still consider BIS as a primary measure to determine if the patient is correctly anaesthetized while relaying on the other physiological parameters to monitor and ensure the patient's status is maintained. The automatic control of administering anesthesia using intelligent control systems has been the subject of recent research in order to alleviate the burden on the anesthetist to manually adjust drug dosage in response physiological changes for sustaining DOA. A system proposed for the automatic control of anesthesia based on type-2 Self Organizing Fuzzy Logic Controllers (T2-SOFLCs) has been shown to be effective in the control of DOA under simulated scenarios while contending with uncertainties due to signal noise and dynamic changes in pharmacodynamics (PD) and pharmacokinetic (PK) effects of the drug on the body. This study considers both BIS and BP as part of an adaptive automatic control scheme, which can adjust to the monitoring of either parameter in response to changes in the availability and reliability of BIS signals during surgery. The simulation of different control schemes using BIS data obtained during real surgical procedures to emulate noise and interference factors have been conducted. The use of either or both combined parameters for controlling the delivery Propofol to maintain safe target set points for DOA are evaluated. The results show that combing BIS and BP based on the proposed adaptive control scheme can ensure the target set points and the correct amount of drug in the body is maintained even with the intermittent loss of BIS signal that could otherwise disrupt an automated control system

Relation between acute and long-term cognitive decline after surgery: Influence of metabolic syndrome.

IntroductionThe relationship between persistent postoperative cognitive decline and the more common acute variety remains unknown; using data acquired in preclinical studies of postoperative cognitive decline we attempted to characterize this relationship.MethodsLow capacity runner (LCR) rats, which have all the features of the metabolic syndrome, were compared postoperatively with high capacity runner (HCR) rats for memory, assessed by trace fear conditioning (TFC) on the 7th postoperative day, and learning and memory (probe trial [PT]) assessed by the Morris water-maze (MWM) at 3 months postoperatively. Rate of learning (AL) data from the MWM test, were estimated by non-linear mixed effects modeling. The individual rat's TFC result at postoperative day (POD) 7 was correlated with its AL and PT from the MWM data sets at postoperative day POD 90.ResultsA single exponential decay model best described AL in the MWM with LCR and surgery (LCR-SURG) being the only significant covariates; first order AL rate constant was 0.07 s(-1) in LCR-SURG and 0.16s(-1) in the remaining groups (p&lt;0.05). TFC was significantly correlated with both AL (R=0.74; p&lt;0.0001) and PT (R=0.49; p&lt;0.01).ConclusionSeverity of memory decline at 1 week after surgery presaged long-lasting deteriorations in learning and memory

Mechanism-Based Modeling of Perioperative Variations in Hemoglobin Concentration in Patients Undergoing Laparoscopic Surgery

Hemoglobin concentration ([Hb]) in the perioperative setting should be interpreted in the context of the variables and processes that may affect it to differentiate the dilution effects caused by changes in intravascular volume. However, it is unclear what variables and processes affect [Hb]. Here, we modeled the perioperative variations in [Hb] to identify the variables and processes that govern [Hb] and to describe their effects.We first constructed a mechanistic framework based on the main variables and processes related to the perioperative [Hb] variations. We then prospectively studied patients undergoing laparoscopic surgery, divided into 2 consecutive cohorts for the development and validation of the model. The study protocol consisted of serial measurements of [Hb] along with recordings of hemoglobin mass loss, blood volume loss, fluid infusion, urine volume, and inflammatory biomarkers measurements, up to 96 hours postoperatively. Mathematical fitting was performed using nonlinear mixed-effects. Additionally, we performed simulations to explore the effects of blood loss and fluid therapy protocols on [Hb].We studied 154 patients: 118 enrolled in the development group and 36 in the validation group. We characterized the perioperative course of [Hb] using a mass balance model that accounted for hemoglobin losses during surgery, and a 2-compartment model that estimated fluid kinetics and intravascular volume changes. During model development, we found that urinary fluid elimination represented only 24% of the total fluid elimination, and that total fluid elimination was inhibited after surgery in a time-dependent manner and influenced by age. Also, covariate evaluation showed a significant association between the type of surgery and proportion of fluid eliminated via urine. In contrast, neither the type of infused solution, blood volume loss nor inflammatory biomarkers were found to correlate with model parameters. In the validation analysis, the model demonstrated a considerable predictive capacity, with 95% of the predicted [Hb] within -4.4 and +5.5 g/L. Simulations demonstrated that hemoglobin mass loss determined most of the postoperative changes in [Hb], while intravascular volume changes due to fluid infusion, distribution, and elimination induced smaller but clinically relevant variations. Simulated patients receiving standard fluid therapy protocols exhibited a hemodilution effect that resulted in a [Hb] decrease between 7 and 15 g/L at the end of surgery, and which was responsible for the lowest [Hb] value during the perioperative period.Our model provides a mechanistic and quantitative understanding of the causes underlying the perioperative [Hb] variations.Copyright © 2023 International Anesthesia Research Society