Category Archives: Anesth Analg

Predicting Deep Hypnotic State From Sleep Brain Rhythms Using Deep Learning: A Data-Repurposing Approach.

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Predicting Deep Hypnotic State From Sleep Brain Rhythms Using Deep Learning: A Data-Repurposing Approach.
Anesth Analg. 2020 May;130(5):1211-1221
Authors: Belur Nagaraj S, Ramaswamy SM, Weerink MAS,… Continue reading

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Autonomous Systems in Anesthesia: Where Do We Stand in 2020? A Narrative Review.

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Autonomous Systems in Anesthesia: Where Do We Stand in 2020? A Narrative Review.
Anesth Analg. 2020 May;130(5):1120-1132
Authors: Zaouter C, Joosten A, Rinehart J, Struys MMRF, Hemmerling TM
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Target-Controlled Infusion: A Mature Technology.

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Target-Controlled Infusion: A Mature Technology.

Anesth Analg. 2015 Oct 29;

Authors: Absalom AR, Glen JI, Zwart GJ, Schnider TW, Struys MM

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The History of Target-Controlled Infusion.

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The History of Target-Controlled Infusion.

Anesth Analg. 2015 Oct 29;

Authors: Struys MM, Smet T, Glen JI, Vereecke HE, Absalom AR, Schnider TW

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The Safety of Target-Controlled Infusions.

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The Safety of Target-Controlled Infusions.

Anesth Analg. 2015 Oct 29;

Authors: Schnider TW, Minto CF, Struys MM, Absalom AR

Abstract

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Comparisons of Electroencephalographically Derived Measures of Hypnosis and Antinociception in Response to Standardized Stimuli During Target-Controlled Propofol-Remifentanil Anesthesia.

Comparisons of Electroencephalographically Derived Measures of Hypnosis and Antinociception in Response to Standardized Stimuli During Target-Controlled Propofol-Remifentanil Anesthesia.
Anesth Analg. 2015 Oct 26;
Aut… Continue reading

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Using Nursing Activities Score to Assess Nursing Workload on a Medium Care Unit.

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Using Nursing Activities Score to Assess Nursing Workload on a Medium Care Unit.
Anesth Analg. 2015 Nov;121(5):1274-1280
Authors: Armstrong E, de Waard MC, de Grooth HS, Heymans MW, Miranda DR, Girbes… Continue reading

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The Validity of Eadyn in Spontaneously Breathing Patients.

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The Validity of Eadyn in Spontaneously Breathing Patients.
Anesth Analg. 2015 Nov;121(5):1400
Authors: Vos JJ, Scheeren TW, Kalmar AF
PMID: 26484470 [PubMed – as supplied by publisher]

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In Response.

In Response.

Anesth Analg. 2015 Mar;120(3):693-694

Authors: Eleveld DJ, Proost JH, Absalom AR, Cortínez LI, Struys MM

PMID: 25695587 [PubMed – as supplied by publisher]

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Analysis of Remifentanil with Liquid Chromatography-Tandem Mass Spectrometry and an Extensive Stability Investigation in EDTA Whole Blood and Acidified EDTA Plasma.

Analysis of Remifentanil with Liquid Chromatography-Tandem Mass Spectrometry and an Extensive Stability Investigation in EDTA Whole Blood and Acidified EDTA Plasma.

Anesth Analg. 2015 Feb 16;

Authors: Koster RA, Vereecke HE, Greijdanus B, Touw DJ, Struys MM, Alffenaar JW

Abstract
BACKGROUND:: Remifentanil is a μ-opioid receptor agonist that was developed as a synthetic opioid for use in anesthesia and intensive care medicine. Remifentanil is rapidly metabolized in both blood and tissues, which results in a very short duration of action. Even after blood sampling, remifentanil is unstable in whole blood and plasma through endogenous esterases and chemical hydrolysis. The instability of remifentanil in these matrices makes sample collection and processing a critical phase in the bioanalysis of remifentanil.
METHODS:: We have developed a fast and simple sample preparation method using protein precipitation followed by liquid chromatography-tandem mass spectrometry analysis. To improve the stability of remifentanil, citric acid, ascorbic acid, and formic acid were investigated for acidification of EDTA plasma. The stability of remifentanil was investigated in stock solution, EDTA whole blood, EDTA plasma, and acidified EDTA plasma at ambient temperature, 4°C, 0°C, and at -20°C.
RESULTS:: The analytical method was fully validated based on the Food and Drug Administration guidelines for bioanalytical method validation with a large linear range of 0.20 to 250 ng/mL remifentanil in EDTA plasma acidified with formic acid. The stability results of remifentanil in EDTA tubes, containing whole blood placed in ice water, showed a decrease of approximately 2% in 2 hours. EDTA plasma acidified with citric acid, formic acid, and ascorbic acid showed 0.5%, 4.2%, and 7.2% remifentanil degradation, respectively, after 19 hours at ambient temperature. Formic acid was chosen because of its volatility and thus liquid chromatography-tandem mass spectrometry compatibility. The use of formic acid added to EDTA plasma improved the stability of remifentanil, which was stable for 2 days at ambient temperature, 14 days at 4°C, and 103 days at -20°C.
CONCLUSIONS:: The analytical method we developed uses a simple protein precipitation and maximal throughput by a 2-point calibration curve and short run times of 2.6 minutes. Best sample stability is obtained by placing tubes containing EDTA whole blood in ice water directly after sampling, followed by centrifugation and transfer of the EDTA plasma to tubes with formic acid. The stability of remifentanil in EDTA plasma was significantly improved by the addition of 1.5 μL formic acid per milliliter of EDTA plasma. This analytical method and sample pretreatment are suitable for remifentanil pharmacokinetic studies.

PMID: 25692453 [PubMed – as supplied by publisher]

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Accuracy of the composite variability index as a measure of the balance between nociception and antinociception during anesthesia.

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Accuracy of the composite variability index as a measure of the balance between nociception and antinociception during anesthesia.
Anesth Analg. 2014 Aug;119(2):288-301
Authors: Sahinovic MM, Eleveld… Continue reading

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Performance of propofol target-controlled infusion models in the obese: pharmacokinetic and pharmacodynamic analysis.

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Performance of propofol target-controlled infusion models in the obese: pharmacokinetic and pharmacodynamic analysis.

Anesth Analg. 2014 Aug;119(2):302-10

Authors: Cortínez LI, De la Fuente N, Eleveld DJ, Oliveros A, Crovari F, Sepulveda P, Ibacache M, Solari S

Abstract
BACKGROUND: Obesity is associated with important physiologic changes that can potentially affect the pharmacokinetic (PK) and pharmacodynamic (PD) profile of anesthetic drugs. We designed this study to assess the predictive performance of 5 currently available propofol PK models in morbidly obese patients and to characterize the Bispectral Index (BIS) response in this population.
METHODS: Twenty obese patients (body mass index >35 kg/m), aged 20 to 60 years, scheduled for laparoscopic bariatric surgery, were studied. Anesthesia was administered using propofol by target-controlled infusion and remifentanil by manually controlled infusion. BIS data and propofol infusion schemes were recorded. Arterial blood samples to measure propofol were collected during induction, maintenance, and the first 2 postoperative hours. Median performance errors (MDPEs) and median absolute performance errors (MDAPEs) were calculated to measure model performance. A PKPD model was developed using NONMEM to characterize the propofol concentration-BIS dynamic relationship in the presence of remifentanil.
RESULTS: We studied 20 obese adults (mean weight: 106 kg, range: 85-141 kg; mean age: 33.7 years, range: 21-53 years; mean body mass index: 41.4 kg/m, range: 35-52 kg/m). We obtained 294 arterial samples and analyzed 1431 measured BIS values. When total body weight (TBW) was used as input of patient weight, the Eleveld allometric model showed the best (P < 0.0001) performance with MDPE = 18.2% and MDAPE = 27.5%. The 5 tested PK models, however, showed a tendency to underestimate propofol concentrations. The use of an adjusted body weight with the Schnider and Marsh models improved the performance of both models achieving the lowest predictive errors (MDPE = <10% and MDAPE = <25%; all P < 0.0001). A 3-compartment PK model linked to a sigmoidal inhibitory Emax PD model by a first-order rate constant (ke0) adequately described the propofol concentration-BIS data. A lag time parameter of 0.44 minutes (SE = 0.04 minutes) to account for the delay in BIS response improved the fit. A simulated effect-site target of 3.2 μg/mL (SE = 0.17 μg/mL) was estimated to obtain BIS of 50, in the presence of remifentanil, for a typical patient in our study.
CONCLUSIONS: The Eleveld allometric PK model proved to be superior to all other tested models using TBW. All models, however, showed a trend to underestimate propofol concentrations. The use of adjusted body weight instead of TBW with the traditional Schnider and Marsh models markedly improved their performance achieving the lowest predictive errors of all tested models. Our results suggest no relevant effect of obesity on both the time profile of BIS response and the propofol concentration-BIS relationship.

PMID: 24977639 [PubMed – indexed for MEDLINE]

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A general purpose pharmacokinetic model for propofol.

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A general purpose pharmacokinetic model for propofol.

Anesth Analg. 2014 Jun;118(6):1221-37

Authors: Eleveld DJ, Proost JH, Cortínez LI, Absalom AR, Struys MM

Abstract
BACKGROUND: Pharmacokinetic (PK) models are used to predict drug concentrations for infusion regimens for intraoperative displays and to calculate infusion rates in target-controlled infusion systems. For propofol, the PK models available in the literature were mostly developed from particular patient groups or anesthetic techniques, and there is uncertainty of the accuracy of the models under differing patient and clinical conditions. Our goal was to determine a PK model with robust predictive performance for a wide range of patient groups and clinical conditions.
METHODS: We aggregated and analyzed 21 previously published propofol datasets containing data from young children, children, adults, elderly, and obese individuals. A 3-compartmental allometric model was estimated with NONMEM software using weight, age, sex, and patient status as covariates. A predictive performance metric focused on intraoperative conditions was devised and used along with the Akaike information criteria to guide model development.
RESULTS: The dataset contains 10,927 drug concentration observations from 660 individuals (age range 0.25-88 years; weight range 5.2-160 kg). The final model uses weight, age, sex, and patient versus healthy volunteer as covariates. Parameter estimates for a 35-year, 70-kg male patient were: 9.77, 29.0, 134 L, 1.53, 1.42, and 0.608 L/min for V1, V2, V3, CL, Q2, and Q3, respectively. Predictive performance is better than or similar to that of specialized models, even for the subpopulations on which those models were derived.
CONCLUSIONS: We have developed a single propofol PK model that performed well for a wide range of patient groups and clinical conditions. Further prospective evaluation of the model is needed.

PMID: 24722258 [PubMed – indexed for MEDLINE]

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Why are we using pulse oximetry but not neuromuscular monitoring routinely: the real world scenario?

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Why are we using pulse oximetry but not neuromuscular monitoring routinely: the real world scenario?
Anesth Analg. 2014 Mar;118(3):690
Authors: de Boer HD, Booij LH
PMID: 24557114 [PubMed – i… Continue reading

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Perioperative calibration of noninvasive hemoglobin monitoring.

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Perioperative calibration of noninvasive hemoglobin monitoring.
Anesth Analg. 2014 Feb;118(2):481
Authors: Kalmar AF, Poterman M, Scheeren TW
PMID: 24445645 [PubMed – indexed for MEDLINE]

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Bedside assessment of total systemic vascular compliance, stressed volume, and cardiac function curves in intensive care unit patients.

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Bedside assessment of total systemic vascular compliance, stressed volume, and cardiac function curves in intensive care unit patients.

Anesth Analg. 2012 Oct;115(4):880-7

Authors: Maas JJ, Pinsky MR, Aarts LP, Jansen JR

Abstract
BACKGROUND: Mean systemic filling pressure (Pmsf) can be measured at the bedside with minimally invasive monitoring in ventilator-dependent patients using inspiratory hold maneuvers (Pmsf(hold)) as the zero flow intercept of cardiac output (CO) to central venous pressure (CVP) relation. We compared Pmsf(hold) with arm vascular equilibrium pressure during vascular occlusion (Pmsf(arm)) and their ability to assess systemic vascular compliance (Csys) and stressed volume by intravascular fluid administration.
METHODS: In mechanically ventilated postoperative cardiac surgery patients, inspiratory holds at varying airway pressures and arm stop-flow maneuvers were performed during normovolemia and after each of 10 sequential 50-mL bolus colloid infusions. We measured CVP, Pmsf(arm), stroke volume, and CO during fluid administration steps to construct CVP to CO (cardiac function) curves and Δvolume/ΔPmsf (compliance) curves. Pmsf(hold) was measured before and after fluid administration. Stressed volume was determined by extrapolating the Pmsf-volume curve to zero pressure intercept.
RESULTS: Fifteen patients were included. Pmsf(hold) and Pmsf(arm) were closely correlated. Csys was linear (64.3 ± 32.7 mL · mm Hg(-1), 0.97 ± 0.49 mL · mm Hg(-1) · kg(-1) predicted body weight). Stressed volume was estimated to be 1265 ± 541 mL (28.5% ± 15% predicted total blood volume). Cardiac function curves of patients with an increase of >12% to 500 mL volume extension (volume responsive) were steep, whereas the cardiac function curves of the remaining patients were flat.
CONCLUSIONS: Csys, stressed volume, and cardiac function curves can be determined at the bedside and can be used to characterize patients’ hemodynamic status.

PMID: 22763909 [PubMed – indexed for MEDLINE]

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Determination of Vascular Waterfall Phenomenon by Bedside Measurement of Mean Systemic Filling Pressure and Critical Closing Pressure in the Intensive Care Unit.

Determination of Vascular Waterfall Phenomenon by Bedside Measurement of Mean Systemic Filling Pressure and Critical Closing Pressure in the Intensive Care Unit.
Anesth Analg. 2012 Feb 17;
Authors: Maas JJ, de Wilde RB, Aarts … Continue reading

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An assessment of clinical interchangeability of TEG and RoTEM thromboelastographic variables in cardiac surgical patients.

An assessment of clinical interchangeability of TEG and RoTEM thromboelastographic variables in cardiac surgical patients.
Anesth Analg. 2010 Aug;111(2):339-44
Authors: Venema LF, Post WJ, Hendriks HG, Huet RC, de Wolf JT, de … Continue reading

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Closed loop anesthesia: are we getting close to finding the holy grail?

Closed loop anesthesia: are we getting close to finding the holy grail?
Anesth Analg. 2011 Mar;112(3):516-8
Authors: Absalom AR, De Keyser R, Struys MM
PMID: 21350226 [PubMed – indexed for MEDLINE]

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