Оценка качества базовых и расширенных реанимационных мероприятий в многопрофильном стационаре (симуляционный курс)

The survival of patients after the sudden circulatory arrest (SCA) depends not only on immediate onset of resuscitative measures, but also on their quality.The purpose of the study. The purpose is to assess the compliance of basic and expanded resuscitative measures carried out by healthcare providers in hospitals with modern national and international guidelines within the frames of a stimulation course.Materials and Methods. The research was perfomed in a multifield hospital in Moscow, in 2016. It consisted of two phases. During the first phase, within the frames of a simulation course, providers' skills in the cardiopul monary resuscitation (CPR) and chest compression (CC) technique mastership were evaluated. During the second stage, their skills in expanded CPR and ability to work as a part of resuscitation teams were assessed. During the simulation, all team activities were recorded (both audio and video); CC parameters were also registered using a CC pressure control sensor (hereinafter referred to as a sensor) and audiovisual tips. The European Resuscitation Council Guidelines for Resuscitation 2015 were used as reference criteria. The analysis was performed using the ZOLL RescueNet Code Review® software. A statistical analysis was performed using the Statistica 7.0 software (MannWhitney Utest). The data were presented as a mean, median ± 25—75 percentiles (25—75 IQR), minimum and maximum values. The difference was considered significant at P<0.05.Results. Test results of most healthcare providers were unsatisfactory when the CPR was performed without sensors and audiovisual tips: the percentage of target CCs was not more than 10% in 72% of providers (n=18). When the CPR was performed with sensors and audiovisual tips regulating the CC quality, the percentage of target CCs was 65.7%. i.e. it was significantly higher than that during the CPR without the sensor and the tips (P=0.0000). While only one provider was able to perform the target CC without the sensor and the tips (4%), 12 providers were able to do it with the sensor (48%) (P=0.0000). In all resuscitation teams, there was a lack in compliance with the ECR 2015 guidelines for expanded CPR, as well as ineffective team work was revealed. Chest compressions did not comply with recommended parameters; pauses before and after defibrillator discharge were too long. In most cases, there was hyperventilation during the artificial lung ventilation. The safety principle was not followed by one of resuscitation teams during the defibrillation procedure.Conclusion. The obtained data demonstrate that healthcare providers have poor skills in basic and expanded CPR. Therefore, it is important to train and retrain healthcare providers in basic and expanded CPR within the frames of simulation training courses on a regular basis (in accordance with European Resuscitation Council Guidelines for Resuscitation 2015 and National Resuscitation Council). During training, the use of technical means of monitoring of the chest compression quality control in CPR should be warranted. It is important to arrange regular retraining in order to keep the skills uptodate, as well as regular debriefings on the CPR quality after each case of resuscitation measures in a hospital.На выживаемость больных при внезапной остановке кровообращения (ВОК) влияет не только немедленное начало реанимационных мероприятий, но и их качество.Цель исследования. Оценить в рамках симуляционного курса соответствие современным национальным и международным рекомендациям базовых и расширенных реанимационных мероприятий, проводимых медицинскими работниками в стационаре.Материалы и методы. Исследование проведено в многопрофильном стационаре г. Москвы в 2016 г. и организовано в два этапа. На первом этапе в рамках симуляционного курса проводилась оценка владения медицинскими работниками навыками базовой сердечнолегочной реанимации (СЛР) и качества выполнения компрессий грудной клетки (КГК); на втором — навыками расширенной СЛР и работы в составе реанимационных бригад. Во время выполнения бригадами учебного сценария проводилась аудио и видео запись, а также регистрировались параметры КГК с помощью датчика контроля качества КГК (далее — датчик) и аудиовизуальных подсказок прибора. В качестве референсных критериев использовали рекомендации Европейского совета по реанимации 2015 г. Анализ полученных данных проводился с помощью программного обеспечения ZOLL RescueNet Code Review®. Статистический анализ данных был выполненпри помощи пакета Statistica 7,0 (тест МаннаУитни), данные были представлены в виде средней, медианы ± 25 —75 перцентилей (2575 IQR), минимальных и максимальных значений. Достоверным считалось различие при p<0,05.Результаты. При проведении СЛР без использования датчика и аудиовизуальных подсказок у большинства медицинских работников результаты были неудовлетворительными: процент целевых КГК составил не более 10% у 72% медицинских работников (n=18). При проведении СЛР с использованием датчика и аудиовизуальными подсказками по качеству КГК процент целевых КГК составил 65,7%, что было достоверно выше, чем при работе без датчика и подсказок (p=0,0000). Если без использования датчика и подсказок целевые КГК выполнил только один медицинский работник (4%), то с датчиком — 12 (48%) (p=0,0000). Во всех реанимационных бригадах было зарегистрировано несоответствие последовательности действий алгоритму расширенной реанимации ЕСР 2015 г. и неэффективная командная работа. Компрессии грудной клетки не соответствовали рекомендованным параметрам, паузы до и после нанесения разряда дефибриллятора — длительными; в большинстве случаев при проведении искусственной вентиляции легких была гипервентиляция. В одной из реанимационных бригад был нарушен принцип безопасности при проведении дефибрилляции.Заключение. Полученные нами данные свидетельствуют о недостаточном владении медицинскими работниками стационара практическими навыками базовой и расширенной СЛР. В связи с этим актуальным является обучение и регулярный ретренинг медицинских работников в формате симуляционных курсов по базовой и расширенной СЛР (в соответствии с рекомендациями Европейского совета по реанимации 2015 г. и Национального совета по реанимации). На данных курсах и при проведении СЛР в стационаре целесообразно использовать технические средства контроля качества компрессий грудной клетки. Важным является проведение регулярных ретренингов для поддержания практического навыка на должном уровне, а также дебрифинг по качеству СЛР после каждого случая проведения реанимационных мероприятий в стационаре

Predictive modeling and simulation of silica aerogels by using aggregation algorithms

Silica aerogels are highly porous solids with very low densities and thermal conductivities. Their high porosity results in a fractal morphology which has a strong influence on their mechanical properties. The geometric structure of silica aerogels can be described by diffusion-limited cluster-cluster aggregation (DLCA) models. In this work, the DLCA method is implemented to model silica aerogel networks and investigate the influence of different input parameters, as for example, varying particle sizes on their fractal properties. The resulting model networks are characterized for their fractal properties and compared with the small angle X-ray scattering (SAXS) results of silica aerogels. Furthermore, their mechanical properties are simulated using the finite element method. There, the effect of varying densities on their mechanical properties is examined. In addition, an artificial neural network (ANN) is trained based on the input parameters of the DLCA algorithm to predict the fractal properties of the silica aerogel model. By inverting the ANN it is possible to identify the necessary inputs to generate desired fractal morphologies with specific mechanical properties

Data-driven inverse design and optimisation of silica aerogel model networks

Silica aerogels are highly porous ultralight materials with extremely low density and thermal conductivity. These exceptional properties of silica aerogels are often accounted to microstructure morphology, thus making them of keen research interest for analysing their structure-property relationships. The classical approach for this involved the microstructure modelling of the silica aerogels with aggregation-based modelling algorithm viz., diffusion-limited cluster-cluster aggregation (DLCA) and then performing finite element method (FEM) on the generated representative volume element (RVEs). However, the process often requires large computation time and resources. The objective of this work was thus to introduce an artificial intelligence approach based on neural networks and reinforcement learning to eliminate the necessity of generating and simulating 3D silica aerogel models for predicting their structural and mechanical properties. To this end for the forward prediction of the elastic modulus and fractal dimension of the silica aerogels from DLCA parameters, an artificial neural network was developed. Furthermore, to reverse engineer the material and perform inverse material design, a reinforcement learning framework was developed, that is shown to have learned to determine appropriate DLCA model parameters as actions for a desired fractal dimension and elastic modulus

Towards thermo-viscoelastic experimental characterisation and numerical modelling of VHB polymer

In this study, we have presented a wide variety of temperature experiments of a commercially available VHB polymer ranging from -30◦C to 80◦C at various strain rates and stretch levels under homogeneous deformation and temperature fields. The study demonstrates a pronounced influence of the temperature field on mechanical responses of the VHB polymer. After a wide range of experiments, we have proposed a finite-strain thermo-viscoelastic constitutive model where a non-linear evolution law is devised based on the classical concept of multiplicative decomposition of the deformation gradient. Then, decoupled one-dimensional equations are fitted to identify relevant material parameters appearing in the model. The thermo-viscoelastic model validation shows its excellent capability to predict the experimental results

Machine learning-based structure–property predictions in silica aerogels

The structural features in silica aerogels are known to be modelled effectively by the diffusion-limited cluster–cluster aggregation (DLCA) approach. In this paper, an artificial neural network (ANN) is developed for predicting the fractal properties of silica aerogels, given the input parameters for a DLCA algorithm. This approach of machine learning substitutes the necessity of first generating the DLCA structures and then simulating and characterising their fractal properties. The developed ANN demonstrates the capability of predicting the fractal dimension for any given set of DLCA parameters within an accuracy of R2 = 0.973. Furthermore, the same ANN is subsequently inverted for predicting the input parameters for reconstructing a DLCA model network of silica aerogels, for a given desired target fractal dimension. There, it is shown that the fractal dimension is not a unique characteristic defining the network structure of silica aerogels, and the same fractal dimension can be obtained for different sets of DLCA input parameters. However, the problem of non-uniqueness is solved by using a guided gradient descent approach for predictive modelling purposes within certain bounds of the input parameter-space. Model DLCA structures are generated from the constrained and unconstrained inversion, and are compared against several parameters, amongst them, the pore-size distributions. The constrained inversion of the ANN is shown to predict the DLCA model parameters for a desired fractal dimension within an error of 2%

Retrospective analysis of prostate cancer detection using mpMR/US-fusion and cognitive biopsy

Introduction. Transrectal biopsy under US-control has been standard diagnostic method for prostate cancer (PCa) detection for over 30 years. However, TRUS-guided biopsy is not without well-known drawbacks. MR-targeted biopsy methods were proposed to eliminate the drawbacks and improve detection rate of clinically significant Pca. Cognitive and mpMR/US-fusion biopsies have become the most widely used MR-targeted biopsies. However, there are contradictory data on detection of clinically significant Pca when comparing mpMR/US-fusion and cognitive biopsies.Objective. To compare the detection rate of clinically significant prostate cancer performing cognitive and mpMR/US-fusion biopsies.Materials and methods. Inclusion criteria: PSA > 2.0 ng/ml and/or a positive DRE, and/or a suspicious lesion on TRUS, and PI-RADSv2.1 score ≥ 3. The outcomes evaluated are the detection of clinically significant Pca (ISUP ≥ 2), the overall PСa detection, the detection of clinically insignificant Pca, histological yield (proportion of positive cores, maximum cancer core length).Results. Retrospective data analysis was performed: cognitive biopsy was performed in 102 patients and mpMR/US-fusion biopsy in 176 patients. The median age was 63 years, prostate volume 46 cc. The median PSA was 6.4 ng/ml in the mpMR/US-fusion and 6.7 ng/ml in the cognitive biopsy group. MpMR/US-fusion and cognitive biopsies were comparable about the detection rate of clinically significant (30.3% vs 25.0%; p=0.329) and overall Pca detection rate (50.5% and 42.1%; p = 0.176). It was detected to be less clinically insignificant Pca in the cognitive biopsy group (11.8% vs. 25.5%; p = 0.007).  The proportion of positive cores (30.5% and 29.5% respectively; p = 0.754) and maximum cancer core length (6.6 mm vs 7.6 mm; p = 0.320) were equal when comparing cognitive and mpMR/US-fusion biopsies. The proportion of positive cores with clinically significant Pca was higher in the cognitive biopsy group (18.6% vs 13.1%; p = 0.029).Conclusion. Both cognitive and mpMR/US-fusion biopsies are equally accurate for clinically significant Pca detection. Therefore, cognitive biopsy may be an alternative to mpMR/US-fusion biopsy in hospitals where mpMR/US-fusion technology is not currently available

Проспективное исследование выявляемости рака предстательной железы при выполнении мультипараметрической магнитно-резонансной/ ультразвуковой fusion, стандартной и сатурационной биопсии

Background. Currently, about 80 % of men with low-grade prostate cancer (per ISUP 1 (International Society of Urological Pathology)) have indications for radical treatment. Overdiagnosis of low-grade cancer is associated with the use of systematic biopsy methods (standard transrectal, saturation) under ultrasound control for diagnosis verification. To improve prostate cancer diagnosis, the European Association of Urology (2019) recommended multiparametric magnetic resonance imaging before biopsy, and in case of detection of a suspicious lesion magnetic resonance imaging (MRI)-targeted biopsy. In clinical practice, the most common method of MRI-targeted biopsy is multiparametric MRI ultrasound-guided (mpMRI/US) fusion biopsy. However, some studies show contradictory results in detection of prostate cancer using systematic and MRI-targeted biopsy techniques.Aim. To compare detection of clinically significant prostate cancer (ISUP ≥2) using mpMRI/US fusion, standard, and saturation biopsy.Materials and methods. The study included 96 patients. The following inclusion criteria were applied: prostate-specific antigen >2 ng/mL and/or detection of a suspicious lesion during digital rectal and/or transrectal ultrasound examination, and PI-RADS (Prostate Imaging Reporting and Data System) v.2.1 score ≥3. At the first stage, “unblinded” urologist performed a transperineal mpMRI/US fusion and saturation biopsies. At the second stage, “blinded” urologist performed standard transrectal biopsy. Clinically significant cancer was defined as ISUP ≥2.Results. Median age was 63 years, prostate volume – 47 cm3, prostate-specific antigen – 6.82 ng/mL. MpMRI/US fusion, standard, and saturation biopsies were comparable in regard to the rate of detection of clinically significant (29, 24, 28 %; p = 0.81) and clinically insignificant (25, 26, 35 %; p = 0.43) cancer. Overall prostate cancer detection rates were also similar: 54, 50, 63 %, respectively (p = 0.59). The percentages of positive cores in mpMRI/US fusion, standard, and saturation biopsies were 33, 10 and 13 %, respectively (p <0.01). The maximal core length in mpMRI/US was 6.4 mm, in standard biopsy – 6.35 mm, in saturation biopsy – 5.1 mm (p = 0.7).Conclusion. Detection rates of clinically significant, clinically insignificant prostate cancer and overall detection rate are comparable between systematic biopsy techniques and mpMRI/US fusion biopsy.Введение. В настоящее время до 80 % мужчин с раком предстательной железы (РПЖ) низкой степени злокачественности (ISUP 1 (по классификации Международного общества урологических патологов)) подлежат радикальному лечению. Гипердиагностика РПЖ низкой степени злокачественности обусловлена использованием для верифиации диагноза так называемых систематических методов биопсии предстательной железы, выполняемых под ультразвуковым (УЗ) контролем (стандартная трансректальная, сатурационная). В целях улучшения диагностики РПЖ Европейской ассоциацией урологов рекомендовано (2019) перед биопсией всем пациентам проводить мультипараметрическую магнитно-резонансную томографию, в случае обнаружения подозрительного очага выполнять магнитно-резонансную (МР) прицельную биопсию. Наибольшее распространение получила мультипараметрическая МР/УЗ (мпМР/УЗ) fusion-биопсия. Однако в ряде исследований представлены противоречивые результаты выявляемости РПЖ при сравнении систематических и МР-прицельных методов биопсии.Цель исследования – сравнение выявляемости клинически значимого РПЖ (ISUP ≥2) при проведении мпМР/УЗ fusion, стандартной и сатурационной биопсии.Материалы и методы. В исследование были включены 96 пациентов. Критерии включения: уровень простатического специфического антигена >2 нг/мл, и/или обнаружение подозрительного очага при проведении пальцевого ректального и/или трансректального ультразвукового исследования, и ≥3 баллов по критериям PI-RADS (Prostate Imaging Reporting and Data System) v.2.1. Первым этапом «расслепленный» уролог выполнял трансперинеальную мпМР/УЗ fusion и сатурационную биопсию, вторым этапом «ослепленный» уролог проводил стандартную трансректальную биопсию. Клинически значимый РПЖ определяли как ISUP ≥2.Результаты. Медиана возраста пациентов составила 63 года, объема предстательной железы – 47 см3, уровня простатического специфического антигена – 6,82 нг/мл. При сравнении результатов мпМР/УЗ fusion, стандартной и сатурационной биопсии не обнаружены статистически достоверные различия в отношении выявляемости клинически значимого (29, 24 и 28 % соответственно; p = 0,81) и клинически незначимого (25, 26 и 35 % соответственно; p = 0,43) рака. Общая выявляемость РПЖ также сопоставима – 54, 50 и 63 % соответственно (p = 0,59). Доля положительных биоптатов составила 33, 10 и 13 % соответственно (p <0,01). Максимальная длина биоптата, пораженного раком, при мпМР/УЗ fusion-биопсии – 6,4 мм, при стандартной – 6,35 мм, при сатурационной – 5,1 мм (p = 0,7).Заключение. Выявляемость клинически значимого, клинически незначимого и общая выявляемость РПЖ сопоставимы при проведении как систематических методов биопсии, так и мпМР/УЗ fusion-биопсии.ps