Inteligencia artificial en enfermedades infecciosas / Artificial intelligence in infectious diseases

Estamos asistiendo a una verdadera revolución tecnológi-ca en el campo de la salud. Los procesos basados en la aplicación de la inteligencia artificial (IA) y el aprendizaje automático (AA) están llegando progresivamente a todas las áreas disciplinares, y su aplicación en el campo de las enfermedades infecciosas es ya vertiginoso, acelerado por la pandemia de COVID-19.Hoy disponemos de herramientas que no solamente pue-den asistir o llevar adelante el proceso de toma de deci-siones basadas en guías o algoritmos, sino que también pueden modificar su desempeño a partir de los procesos previamente realizados. Desde la optimización en la identificación de microorganis-mos resistentes, la selección de candidatos a participar en ensayos clínicos, la búsqueda de nuevos agentes terapéu-ticos antimicrobianos, el desarrollo de nuevas vacunas, la predicción de futuras epidemias y pandemias, y el segui-miento clínico de pacientes con enfermedades infecciosas hasta la asignación de recursos en el curso de manejo de un brote son actividades que hoy ya pueden valerse de la inteligencia artificial para obtener un mejor resultado. El desarrollo de la IA tiene un potencial de aplicación expo-nencial y sin dudas será uno de los determinantes principa-les que moldearán la actividad médica del futuro cercano.Sin embargo, la maduración de esta tecnología, necesaria para su inserción definitiva en las actividades cotidianas del cuidado de la salud, requiere la definición de paráme-tros de referencia, sistemas de validación y lineamientos regulatorios que todavía no existen o son aún solo inci-pientes

We are in the midst of a true technological revolution in healthcare. Processes based upon artificial intelligence and machine learning are progressively touching all disciplinary areas, and its implementation in the field of infectious diseases is astonishing, accelerated by the COVID-19 pandemic. Today we have tools that can not only assist or carry on decision-making processes based upon guidelines or algorithms, but also modify its performance from the previously completed tasks. From optimization of the identification of resistant pathogens, selection of candidates for participating in clinical trials, the search of new antimicrobial therapeutic agents, the development of new vaccines, the prediction of future epidemics and pandemics, the clinical follow up of patients suffering infectious diseases up to the resource allocation in the management of an outbreak, are all current activities that can apply artificial intelligence in order to improve their final outcomes.This development has an exponential possibility of application, and is undoubtedly one of the main determinants that will shape medical activity in the future.Notwithstanding the maturation of this technology that is required for its definitive insertion in day-to-day healthcare activities, should be accompanied by definition of reference parameters, validation systems and regulatory guidelines that do not exist yet or are still in its initial stages

COVID-19 vaccines reduce mortality in hospitalized patients with oxygen requirements: Differences between vaccine subtypes. A multicontinental cohort study.

The aim of this study was to analyze whether the coronavirus disease 2019 (COVID-19) vaccine reduces mortality in patients with moderate or severe COVID-19 disease requiring oxygen therapy. A retrospective cohort study, with data from 148 hospitals in both Spain (111 hospitals) and Argentina (37 hospitals), was conducted. We evaluated hospitalized patients for COVID-19 older than 18 years with oxygen requirements. Vaccine protection against death was assessed through a multivariable logistic regression and propensity score matching. We also performed a subgroup analysis according to vaccine type. The adjusted model was used to determine the population attributable risk. Between January 2020 and May 2022, we evaluated 21,479 COVID-19 hospitalized patients with oxygen requirements. Of these, 338 (1.5%) patients received a single dose of the COVID-19 vaccine and 379 (1.8%) were fully vaccinated. In vaccinated patients, mortality was 20.9% (95% confidence interval [CI]: 17.9-24), compared to 19.5% (95% CI: 19-20) in unvaccinated patients, resulting in a crude odds ratio (OR) of 1.07 (95% CI: 0.89-1.29; p = 0.41). However, after considering the multiple comorbidities in the vaccinated group, the adjusted OR was 0.73 (95% CI: 0.56-0.95; p = 0.02) with a population attributable risk reduction of 4.3% (95% CI: 1-5). The higher risk reduction for mortality was with messenger RNA (mRNA) BNT162b2 (Pfizer) (OR 0.37; 95% CI: 0.23-0.59; p < 0.01), ChAdOx1 nCoV-19 (AstraZeneca) (OR 0.42; 95% CI: 0.20-0.86; p = 0.02), and mRNA-1273 (Moderna) (OR 0.68; 95% CI: 0.41-1.12; p = 0.13), and lower with Gam-COVID-Vac (Sputnik) (OR 0.93; 95% CI: 0.6-1.45; p = 0.76). COVID-19 vaccines significantly reduce the probability of death in patients suffering from a moderate or severe disease (oxygen therapy).

Aprendizaje automático aplicado en área de la salud: parte 2 / Machine Learning In Healthcare: part 2

En el artículo anterior se introdujo el tema y se desarrolló cómo es la recolección y análisis de datos, la selección y entrenamiento de modelos de aprendizaje automático supervisados y los métodos de validación interna que permiten corroborar si el modelo arroja resultados similares a los de otros conjuntos de entrenamiento y de prueba. En este artículo continuaremos con la descripción de la evaluación del rendimiento, la selección del modelo más adecuado para identificar la característica que se va a evaluar y la validación externa del modelo. Además, el artículo resume los desafíos existentes en la implementación del Machine Learning desde la investigación al uso clínico. (AU)

In the previous article, we introduced topics such as data collection and analysis, selection and training of supervised machine learning models and methods of internal validation that allow to corroborate whether the model yields similar results to other training and test sets.In this article, we will continue with the description of the performance evaluation, selecting the most appropriate model to identify the characteristic to evaluate and the external validation of the model. In addition, the article summarizes the actual challenges in the implementation of machine learning from research to clinical use. (AU)

Aprendizaje automático aplicado en área de la salud: parte 1 / Machine learning in healthcare: part 1

Este será el primero de dos artículos donde se tratarán los pasos necesarios para desarrollar un proyecto de aplicación de técnicas de Machine Learning en Salud, que introduce nociones sobre la recolección y análisis de datos, la selección y entrenamiento de modelos de aprendizaje auto-mático de tipo supervisado y los métodos de validación interna para cada modelo. (AU)

This will be the first of two articles where the steps needed to apply machine learning methods in healthcare will be discussed. It will introduce fundamental notions about data collection, selection and training of supervised ML models as well as the methods of internal validation. In a second article, we will discuss about the performance evaluation to select the most appropriate model and its external validation. (AU)

Design and development of an early warning score for covid-19 hospitalized patients.

Pandemics pose a major challenge for public health preparedness, requiring a coordinated international response and the development of solid containment plans. Early and accurate identification of high-risk patients in the course of the current COVID-19 pandemic is vital for planning and making proper use of available resources. The purpose of this study was to identify the key variables that account for worse outcomes to create a predictive model that could be used effectively for triage. Through literature review, 44 variables that could be linked to an unfavorable course of COVID-19 disease were obtained, including clinical, laboratory, and X-ray variables. These were used for a 2-round modified Delphi processing with 14 experts to select a final list of variables with the greatest predictive power for the construction of a scoring system, leading to the creation of a new scoring system: the COVID-19 Severity Index. The analysis of the area under the curve for the COVID-19 Severity Index was 0.94 to predict the need for ICU admission in the following 24 hours against 0.80 for NEWS-2. Additionally, the digital medical record of the Hospital Italiano de Buenos Aires was electronically set for an automatic calculation and constant update of the COVID-19 Severity Index. Specifically designed for the current COVID-19 pandemic, COVID-19 Severity Index could be used as a reliable tool for strategic planning, organization, and administration of resources by easily identifying hospitalized patients with a greater need of intensive care.

La pandemia por COVID-19 planteó un desafío para el sistema salud, debido a la gran demanda de pacientes hospitalizados. La identificación temprana de pacientes hospitalizados con riesgo de evolución desfavorable es vital para asistir en forma oportuna y planificar la demanda de recursos. El propósito de este estudio fue identificar las variables predictivas de mala evolución en pacientes hospitalizados por COVID-19 y crear un modelo predictivo que pueda usarse como herramienta de triage. A través de una revisión narrativa, se obtuvieron 44 variables vinculadas a una evolución desfavorable de la enfermedad COVID-19, incluyendo variables clínicas, de laboratorio y radiográficas. Luego se utilizó un procesamiento por método Delphi modificado de 2 rondas para seleccionar una lista final de variables incluidas en el score llamado COVID-19 Severity Index. Luego se calculó el Área Bajo la Curva (AUC) del score para predecir el pase a terapia intensiva en las próximas 24 horas. El score presentó un AUC de 0,94 frente a 0,80 para NEWS-2. Finalmente se agregó el COVID-19 Severity Index a la historia clínica electrónica de un hospital universitario de alta complejidad. Se programó para que el mismo se actualice de manera automática, facilitando la planificación estratégica, organización y administración de recursos a través de la identificación temprana de pacientes hospitalizados con mayor riesgo de transferencia a la Unidad de Cuidados Intensivos.

Design and development of an early warning score for COVID-19 hospitalized patients / Diseño y desarrollo de un sistema de alerta temprana para pacientes hospitalizados por COVID-19

Abstract Pandemics pose a major challenge for public health preparedness, requiring a coordinated international response and the development of solid containment plans. Early and accurate identifica tion of high-risk patients in the course of the current COVID-19 pandemic is vital for planning and making proper use of available resources. The purpose of this study was to identify the key variables that account for worse outcomes to create a predictive model that could be used effectively for triage. Through literature review, 44 variables that could be linked to an unfavorable course of COVID-19 disease were obtained, including clinical, laboratory, and X-ray variables. These were used for a 2-round modified Delphi processing with 14 experts to select a final list of variables with the greatest predictive power for the construction of a scoring system, leading to the creation of a new scoring system: the COVID-19 Severity Index. The analysis of the area under the curve for the COVID-19 Severity Index was 0.94 to predict the need for ICU admission in the following 24 hours against 0.80 for NEWS-2. Additionally, the digital medical record of the Hospital Italiano de Buenos Aires was electronically set for an automatic calculation and constant update of the COVID-19 Severity Index. Specifically designed for the current COVID-19 pandemic, COVID-19 Severity Index could be used as a reliable tool for strategic planning, organization, and administration of resources by easily identifying hospitalized patients with a greater need of intensive care.

Resumen La pandemia por COVID-19 planteó un desafío para el sistema salud, debido a la gran demanda de pacientes hospitalizados. La identificación temprana de pacientes hospitalizados con riesgo de evo lución desfavorable es vital para asistir en forma oportuna y planificar la demanda de recursos. El propósito de este estudio fue identificar las variables predictivas de mala evolución en pacientes hospitalizados por COVID-19 y crear un modelo predictivo que pueda usarse como herramienta de triage. A través de una revisión narrativa, se obtuvieron 44 variables vinculadas a una evolución desfavorable de la enfermedad COVID-19, incluyendo variables clínicas, de laboratorio y radiográficas. Luego se utilizó un procesamiento por método Delphi modificado de 2 rondas para seleccionar una lista final de variables incluidas en el score llamado COVID-19 Severity Index. Luego se calculó el Área Bajo la Curva (AUC) del score para predecir el pase a terapia intensiva en las próximas 24 horas. El score presentó un AUC de 0,94 frente a 0,80 para NEWS-2. Finalmente se agregó el COVID-19 Severity Index a la historia clínica electrónica de un hospital universitario de alta complejidad. Se programó para que el mismo se actualice de manera automática, facilitando la planificación estratégica, organización y administración de recursos a través de la identificación temprana de pacientes hospitalizados con mayor riesgo de transferencia a la Unidad de Cuidados Intensivos.

[Ewing sarcoma of the bone. Multidisciplinary approach and oncological results in 88 patients]. / Sarcoma de Ewing óseo. Enfoque multidisciplinario y resultados oncológicos en 88 pacientes.

Ewing sarcoma of the bone is a rare, highly aggressive tumor that typically affects children and young adults. In Argentina, the lack of Ewing's sarcoma registries reflects in the absence of information regarding prevalence, treatment protocols and patient's outcome. The purpose of this study was to analyze, in a group of patients diagnosed with Ewing sarcoma of the bone, treated with chemotherapy and limb-conserving surgery, their overall survival rate, local recurrence rate, and oncological risk factors. A retrospective research was conducted between 1990 and 2017. Eighty-eight patients with Ewing sarcoma of the bone matched the inclusion criteria. Median age was 14.5 years and median follow-up was 8.8 years. Overall survival rate was 79.5%, 69% and 64% at 2, 5 and 10 years respectively. Negative prognostic factors, associated with less survival rate after univariate analysis, were: bad response to chemotherapy (tumoral necrosis 0-89%), age > 16 years-old, central tumor localization and local recurrence. Gender and tumor size were not significant prognostic factors. After multivariate analysis, response to chemotherapy remained statistical significant. Local recurrence-free survival rate at 2 and 5 years was 87%. Tumor response to chemotherapy (0-89%) was the only significant factor for local recurrence. We consider that limb-salvage surgery, with neoadjuvant and adjuvant chemotherapy, are the mainstays of treatment for Ewing's sarcoma, with an overall survival rate, at 5 years, of 69%. In this population, response to chemotherapy is the most relevant prognostic factor, being associated with both local recurrence and overall survival.

El sarcoma de Ewing óseo es un tumor poco frecuente, agresivo, que afecta principalmente a niños y adultos jóvenes. Existe ausencia de registros en nuestro país respecto de la prevalencia de esta enfermedad, los esquemas de tratamiento utilizados y sus resultados. El objetivo fue analizar, en un grupo de pacientes con sarcoma de Ewing óseo tratados con quimioterapia y cirugía de conservación de miembro, las tasas de supervivencia global, de recurrencia local y los factores de riesgo oncológicos. Se incluyó a 88 pacientes. La edad media de la serie fue de 14.5 años y el seguimiento promedio de 8.8 años. La tasa de supervivencia global fue de 79.5% a los 2 años, de 69% a 5 años y de 64% a 10 años. Los factores pronósticos negativos asociados a menor supervivencia fueron: mala respuesta a la quimioterapia, edad > de 16 años, localización central, y recurrencia local. En el análisis multivariable únicamente la respuesta a la quimioterapia tuvo significancia estadística. La tasa libre de recurrencia local a 2 y 5 años fue del 87%. La mala respuesta a la quimioterapia fue el único factor significativo para la recurrencia local. Consideramos que la cirugía de conservación de miembro asociada a quimioterapia pre y postoperatoria debe ser el tratamiento para el sarcoma de Ewing óseo, alcanzando de esta manera una supervivencia global a 5 años del 69%. En nuestra serie, la respuesta a la quimioterapia ha sido el factor pronóstico más relevante para supervivencia y recurrencia local.

Sarcoma de Ewing óseo: Enfoque multidisciplinario y resultados oncológicos en 88 pacientes / Ewing sarcoma of the bone. Multidisciplinary approach and oncological results in 88 patients

El sarcoma de Ewing óseo es un tumor poco frecuente, agresivo, que afecta principalmente a niños y adultos jóvenes. Existe ausencia de registros en nuestro país respecto de la prevalencia de esta enfermedad, los esquemas de tratamiento utilizados y sus resultados. El objetivo fue analizar, en un grupo de pacientes con sarcoma de Ewing óseo tratados con quimioterapia y cirugía de conservación de miembro, las tasas de supervivencia global, de recurrencia local y los factores de riesgo oncológicos. Se incluyó a 88 pacientes. La edad media de la serie fue de 14.5 años y el seguimiento promedio de 8.8 años. La tasa de supervivencia global fue de 79.5% a los 2 años, de 69% a 5 años y de 64% a 10 años. Los factores pronósticos negativos asociados a menor supervivencia fueron: mala respuesta a la quimioterapia, edad ≥ de 16 años, localización central, y recurrencia local. En el análisis multivariable únicamente la respuesta a la quimioterapia tuvo significancia estadística. La tasa libre de recurrencia local a 2 y 5 años fue del 87%. La mala respuesta a la quimioterapia fue el único factor significativo para la recurrencia local. Consideramos que la cirugía de conservación de miembro asociada a quimioterapia pre y postoperatoria debe ser el tratamiento para el sarcoma de Ewing óseo, alcanzando de esta manera una supervivencia global a 5 años del 69%. En nuestra serie, la respuesta a la quimioterapia ha sido el factor pronóstico más relevante para supervivencia y recurrencia local.

Ewing sarcoma of the bone is a rare, highly aggressive tumor that typically affects children and young adults. In Argentina, the lack of Ewing's sarcoma registries reflects in the absence of information regarding prevalence, treatment protocols and patient´s outcome. The purpose of this study was to analyze, in a group of patients diagnosed with Ewing sarcoma of the bone, treated with chemotherapy and limb-conserving surgery, their overall survival rate, local recurrence rate, and oncological risk factors. A retrospective research was conducted between 1990 and 2017. Eighty-eight patients with Ewing sarcoma of the bone matched the inclusion criteria. Median age was 14.5 years and median follow-up was 8.8 years. Overall survival rate was 79.5%, 69% and 64% at 2, 5 and 10 years respectively. Negative prognostic factors, associated with less survival rate after univariate analysis, were: bad response to chemotherapy (tumoral necrosis 0-89%), age > 16 years-old, central tumor localization and local recurrence. Gender and tumor size were not significant prognostic factors. After multivariate analysis, response to chemotherapy remained statistical significant. Local recurrence-free survival rate at 2 and 5 years was 87%. Tumor response to chemotherapy (0-89%) was the only significant factor for local recurrence. We consider that limb-salvage surgery, with neoadjuvant and adjuvant chemotherapy, are the mainstays of treatment for Ewing's sarcoma, with an overall survival rate, at 5 years, of 69%. In this population, response to chemotherapy is the most relevant prognostic factor, being associated with both local recurrence and overall survival.

Bandt-Pompe symbolization dynamics for time series with tied values: A data-driven approach.

In 2002, Bandt and Pompe [Phys. Rev. Lett. 88, 174102 (2002)] introduced a successfully symbolic encoding scheme based on the ordinal relation between the amplitude of neighboring values of a given data sequence, from which the permutation entropy can be evaluated. Equalities in the analyzed sequence, for example, repeated equal values, deserve special attention and treatment as was shown recently by Zunino and co-workers [Phys. Lett. A 381, 1883 (2017)]. A significant number of equal values can give rise to false conclusions regarding the underlying temporal structures in practical contexts. In the present contribution, we review the different existing methodologies for treating time series with tied values by classifying them according to their different strategies. In addition, a novel data-driven imputation is presented that proves to outperform the existing methodologies and avoid the false conclusions pointed by Zunino and co-workers.

User-centered design improves the usability of drug-drug interaction alerts: Experimental comparison of interfaces.

Clinical Decision Support Systems can alert health professionals about drug interactions when they prescribe medications. The Hospital Italiano de Buenos Aires in Argentina developed an electronic health record with drug-drug interaction alerts, using traditional software engineering techniques and requirements. Despite enhancing the drug-drug interaction knowledge database, the alert override rate of this system was very high. We redesigned the alert system using user-centered design (UCD) and participatory design techniques to enhance the drug-drug interaction alert interface. This paper describes the methodology of our UCD. We used crossover method with realistic, clinical vignettes to compare usability of the standard and new software versions in terms of efficiency, effectiveness, and user satisfaction. Our study showed that, compared to the traditional alert system, the UCD alert system was more efficient (alerts faster resolution), more effective (tasks completed with fewer errors), and more satisfying. These results indicate that UCD techniques that follow ISO 9241-210 can generate more usable alerts than traditional design.

User-Centered Design Improves the Usability of Drug-Drug Interaction Alerts: A Validation Study in the Real Scenario.

Decision support systems can alert physicians to the existence of drug interactions. The Hospital Italiano de Buenos Aires, Argentina, has an in-house electronic health record with computerized physician order entry and clinical decision support. It includes a drug-drug interaction alert system, initially developed under traditional engineering techniques. As we detected a high alert override rate, we rebuilt the knowledge database and redesigned the alert interface with User-Centered Design techniques. A laboratory crossover study using clinical vignettes showed that new alerts were more usable than traditional ones.This paper aimed to validate these results through a controlled and randomized experimental study with two branches (old vs. new design) in a real setting. We analyzed, quantitatively, every fired alert between April 2015 and September 2016. Finally, we performed user surveys and qualitative interviews to inquire about their satisfaction and perceptions.In real scenarios, user-centered design alerts were more usable, being more effective and satisfactory, but less efficient than traditional alerts. "Safe omission", as a new concept, emerged from our stratified analyses and interviews.

Autonomic function in sleep apnea patients: increased heart rate variability except during REM sleep in obese patients.

The objective of this study was to examine heart rate variability (HRV) among sleep stages in obstructive sleep apnea (OSA) patients. The study was retrospective within subjects and examined the sleep stages and HRV in relation to OSA, age, body mass index (BMI), and sex. Data collected during diagnostic polysomnograms were used in this study. There were 105 clinical patients undergoing polysomnography for suspected OSA. We sampled the electrocardiogram (ECG) from wakefulness, stage 2, and REM sleep and analyzed for frequency domain HRV. Sampled epochs were free of apnea and arousals. Heart rate variability decreased with age. Total frequency variability (TF) and low frequency variability (LF) in wakefulness and REM sleep increased as apnea severity increased. Measures of TF, LF, and the LF/HF ratio were greatest in REM sleep. There was less LF and TF in Stage REM sleep in patients with higher BMI. In conclusion, the decrease in HRV with aging is a robust finding that occurs even in a clinical sleep apnea population. However, apnea does not mimic aging effects on the heart because HRV increased as apnea severity increased. The decrease in HRV during REM sleep in the obese apnea patients suggests the possibility of an autonomic dysfunction in this subgroup.

Juxtaaortic counterpulsation: comparison with intraaortic counterpulsation in an animal model of acute heart failure.

This study was designed to compare the effects of juxtaaortic balloon counterpulsation (JABC), performed in ascending aorta and the aortic arch, with those yielded by intraaortic balloon counterpulsation (IABC) in descending aorta, in experimental animals during induced cardiac failure. JABC was achieved with a manufactured Dacron prosthesis and a balloon pump placed between the prosthesis and the wrapped aorta. JABC resulted in a significant increase of cardiac output (from 2.33+/-0.82 to 2.61+/-1.12 L/min, p < 0.05), cardiac index (from 0.071+/-0.025 to 0.080+/-0.033 L/min/kg, p < 0.05) and diastolic pressure augmentation evaluated through diastolic and systolic areas beneath the aortic pressure curve (DABAC/SABAC) index (from 0.94+/-0.21 to 1.10+/-0.33, p < 0.01). End diastolic aortic pressure showed a significant decrease with JABC (from 31.90+/-7.09 to 27.83+/-9.72 mm Hg, p < 0.05). A close association between percentage of DABAC/SABAC increases obtained with IABC and JABC was observed (r2 = 0.67; p < 0.001). Counterpulsation obtained by a juxtaaortic catheter placed in the arch and the ascending wrapped aorta results in an effective hemodynamic improvement comparable with that achieved by an intraaortic catheter in open chest sheep.

A biphasic model of limb venous compliance: a comparison with linear and exponential models.

Compliance is not linear within the physiological range of pressures, and linear modeling may not describe venous physiology adequately. Forearm and calf venous compliance were assessed in nine subjects. Venous compliance was modeled by using a biphasic model with high- and low-pressure linear phases separated by a breakpoint. This model was compared with a linear model and several exponential models. The biphasic, linear, and two-parameter exponential models best represented the data. The mean coefficient of determination for the biphasic model was greater than for the linear and exponential models in the calf (biphasic 0.94 +/- 0.04, exponential 0.81 +/- 0.16, P = not significant; and linear 0.54 +/- 0.05, P < 0.05) and forearm (biphasic 0.83 +/- 0.17, exponential 0.79 +/- 0.15, P = not significant; and linear 0.51 +/- 0.06, P < 0.05). The breakpoint pressure in the biphasic model was higher in the calf than the forearm, 34.4 +/- 3.9 vs. 29.1 +/- 4.5 mmHg, P < 0.05. A biphasic model can describe limb venous compliance and delineate differences in venous physiology at high and low pressures. The steep low-pressure phase of the compliance curve extends to higher pressures in the calf than in the forearm, thereby enlarging the range of pressures over which hemodynamic regulation by the calf venous circulation occurs.

Quantitative sensory testing cannot differentiate simulated sensory loss from sensory neuropathy.

OBJECTIVE: To differentiate the quantitative sensory testing (QST) results of subjects simulating small and large fiber sensory loss from those of normal subjects and subjects with sensory peripheral neuropathy. BACKGROUND: QST is used to measure sensory thresholds in clinical, epidemiologic, and research studies. It is not known whether there are objective test results that characterize the subject seeking to deceive the examiner. METHODS: The Computer Aided Sensory Examination IV 4, 2, and 1 stepping algorithm was used to determine vibration and cold perception in nine naïve subjects. Subjects were asked to simulate sensory loss (on two occasions) and to respond normally on one occasion. Test results were compared to those of subjects with diabetic sensory neuropathy. Each QST trial was performed three times. RESULTS: Reproducibility, measured by the intraclass correlation coefficient, was similar in all groups for the vibration perception test (simulation 1: 0.68 [95% CI 0.31, 0.91], simulation 2: 0.82 [95% CI 0.54, 0.95], normal response: 0.77 [95% CI 0.47, 0.94], and subjects with peripheral neuropathy: 0.76 [95% CI 0.18, 0.95]) and the cold perception test (simulation 1: 0.53 [95% CI 0.12, 0.85], simulation 2: 0.82 [95% CI 0.55, 0.95], normal subjects: 0.67 [95% CI 0.30, 0.90] and subjects with peripheral neuropathy: 0.88 [95% CI 0.57, 0.97]), all just noticeable difference units. There were no differences between performance characteristics in the two simulation trials. Responses to null stimuli did not differentiate between groups. CONCLUSION: Test performance characteristics do not permit discrimination among subjects simulating sensory loss, subjects with normal responses, and subjects with peripheral neuropathy.

A new approach to assist postoperative heart failure in an animal model: juxta-aortic counterpulsation.

Aortic counterpulsation is a useful technique frequently used in postcardiotomy heart failure. An acute heart failure model in open chest sheep was chosen to evaluate hemodynamic improvement with a counterpulsation balloon pump in juxta-aortic position. This was achieved with a manufactured Dacron prosthesis and a balloon pump placed between the prosthesis and the aorta. Juxta-aortic balloon pump counterpulsation in acute experimental heart failure resulted in a significant improvement of hemodynamic parameters: increase of cardiac output (from 0.86 +/- 0.04 to 1.29 +/- 0.09 L/min, p < 0.05) and cardiac index (from 0.03 +/- 0.01 to 0.04 +/- 0.01 L/min per kg, p < 0.05), and decrease of systemic vascular resistance (from 89.76 +/- 6.69 to 66.56 +/- 6.02 mm Hg/L per min, p < 0.05). The extent of aortic diastolic pressure change evaluated through the diastolic and systolic areas beneath the aortic pressure curve (DABAC/SABAC) index before cardiac failure induction showed a significant increase compared with unassisted values (from 0.81 +/- 0.10 to 1.12 +/- 0.09, p < 0.05). Assisted values of DABAC/SABAC index after heart failure induction also showed a significant increase compared with unassisted values (from 0.78 +/- 0.21 to 1.17 +/- 0.38, p < 0.05). Treatment of experimental acute heart failure by juxta-aortic balloon pump counterpulsation allows an effective hemodynamic improvement in open chest sheep.

Contrapulsación aortica experimental y clínica: su evaluación por medio de un nuevo índice no invasivo / Experimental and clinical aortic contrapulsation: its evaluation by means of a new noninvasive index

La insuficiencia cardíaca refractaria al tratamiento médico tiene el carácter de epidemia y afecta a grandes masas de la población del planeta. La asistencia circulatoria es un área de desarrollo de la bioingeniería que trata de encontrar la solución ocasionada por el síndrome de insuficiencia cardíaca intratable. La asistencia circulatoria puede ser estudiada de dos maneras, mediante dispositivos mecánicos o mediante bioasistencia circulatoria usando colgajos musculares electroestimulados. Existe una forma de asistencia mecánica que puede ser lograda tanto por dispositivos como por bioasistencia: la contrapulsación aórtica, ya sea mecánica o biológica, es una técnica eficaz en el tratamiento de la insuficiencia cardíaca. En este estudio se utilizó un modelo animal de insuficiencia cardíaca en ovejas para comparar los resultados obtenidos mediante contrapulsación biológica torácica y abdominal realizadas con colgajos de músculo dorsal ancho y diafragma, respectivamente. La contrapulsación biológica torácica y abdominal deteminaron una significativa mejoría hemodinámica en insuficiencia cardíaca inducida. El índice de viabilidad subendocárdiaca utilizado para evaluar el grado de contrapulsación abdominal como en la torácica (p<0.05). En esta serie experimental se incluyó la utilización de un nuevo índice no invasivo de contrapulsación que utiliza las áreas bajo el perfil de presión aórtica... (TRUNCADO)(AU)