What patients consider to be a 'good' doctor, and what doctors consider to be a 'good' patient.

BACKGROUND: From a patient's point of view, an 'ideal' doctor could be defined as one having personal qualities for interpersonal relationships, technical skills and good intentions. However, doctors' opinions about what it means to be a 'good' patient have not been systematically investigated. AIM: To explore how patients define the characteristics of a 'good' and a 'bad' doctor, and how doctors define a 'good' and a 'bad' patient. MATERIAL AND METHODS: We surveyed a cohort of 107 consecutive patients attending a community teaching hospital in February 2019, who were asked to define the desirable characteristics of a good/bad doctor. Additionally, a cohort of 115 physicians working at the same hospital was asked to define the desirable characteristics of a good/bad patient. Responses were subjected to content analysis. Simultaneously, an algorithm in Python was used to automatically categorize responses throughout text-mining. RESULTS: The predominant patients' perspective alluded to desirable personal qualities more importantly than proficiency in knowledge and technical skills. Doctors would be satisfied if patients manifested positive personality characteristics, were prone to avoid decisional and personal conflicts, had a high adherence to treatment, and trusted the doctor. The text-mining algorithm was accurate to classify individuals' opinions. CONCLUSIONS: Ideally, fusing the skills of the scientist to the reflective capabilities of the medical humanist will fulfill the archetype of what patients consider to be a 'good' doctor. Doctors' preferences reveal a "paternalistic" style, and his/her opinions should be managed carefully to avoid stigmatizing certain patients' behaviors.

Validation of a form for assessing the professional performance of residents in cardiology by nurses.

BACKGROUND: There is a strong need for transformation in our assessment systems from one that evaluates performance based on levels of training to another that focuses on professional competence to meet the expected requirements for the practice of the profession. The aim of this study is to validate for the first time a Spanish version of a new tool for assessing the professional performance of residents by nurses newly developed in the Ottawa Hospital (O-RON). MATERIALS AND METHODS: After the author's written authorization, the original O-RON form was translated and cross-culturally adapted. Then we conducted a prospective observational study in two cardiology centers in the city of Buenos Aires. The validity of the tools was evaluated by the ability of the instrument to discriminate the level of experience of the residents according to their post-graduate year level. Data is expressed as percentages and frequencies of the qualifications obtained in the different questions. The chi-square test was used to assess the significance of the differences obtained. A generalizability test was used to evaluate reliability. Feasibility was defined as a minimum of 4 assessments per resident per evaluation round. Satisfaction of evaluators was assessed using a survey with a 10-point scale designed by the authors. RESULTS: A total of 838 evaluations were performed. Regarding validity, the 15-item form could significantly discriminate the experience of the residents according to their postgraduate year level (P < 0,005). Thirty evaluations per resident are required to obtain reliable results. The tool is feasible to implement and an average of 4.55 assessment per resident per evaluation round were achieved throughout the entire experience. This value remained stable during the 8 rounds (1st: 4.65; 2nd: 4.34; 3rd: 4.47; 4th: 6.17; 5th: 4.56; 6th: 4.08; 7th: 4.36; 8th: 3.91). The levels of satisfaction among the evaluators were acceptable. CONCLUSION: The Spanish version of the O-RON form can provide residents with a valuable source of feedback from the eyes of nurses on important aspects of their professional training. This tool, positively assessed by the raters, significantly discriminates residents' experience. Its implementation is feasible in our environment, and it is user-friendly, though it requires a considerable number of assessments to achieve high reliability.

[NT-Pro-BNP levels performance before and after reversion to sinus rhythm in patients with preserved ventricular function]. / Descenso de los niveles de propéptido natriurético de tipo B-N terminal luego de la reversión de pacientes con fibrilación auricular y función ventricular conservada.

Our objective was to evaluate changes of N-terminal pro-BNP (NT-Pro-BNP) levels at baseline and after restoration to sinus rhythm in hemodynamic stable patients with lone atrial fibrillation (LAF) with preserved left ventricular function. NT-Pro-BNP levels were obtained before and after cardioversion in thirty hemodynamic stable patients with LAF and preserved left ventricular function. At baseline levels of NT-Pro BNP levels were significatively higher than a normal control group. NT-Pro-BNP levels decreased significantly following cardioversion from 529 (157-1763) to 318 (98-870) pg/ml, p < 0.0001. Decreasing of N-terminal pro-BNP concentrations was observed after any mode of cardioversion: electrical or pharmacologic, 345 (153-1151) pg/ml to 169 (86-407) pg/ml, p: 0.02 and from 1624 (541-4010) pg/ml to 856 (532-1160) pg/ml, p < 0.001, respectively. N-terminal pro-BNP decreasing was observed mainly in patients with length of LAF longer than 8 hours: 1289 (338-2103) to 410 (169-905) pg/ml, p < 0.001 but no difference was detected when such length was less than 8 hours: 274 (137-2300) to 286 (82-1440), p = NS. Our study showed that baseline levels of NT-pro-BNP decreased shortly after reversion of patients with LAF to sinus rhythm. This performance occurs predominantly in patients with LAF length of at least eight hours.

Tolerance for Uncertainty, Personality Traits and Specialty Choice Among Medical Students.

OBJECTIVE: The objective was to explore the tolerance for uncertainty in its different aspects (risk, ambiguity and complexity) in medical students at different times of their careers, and to relate these tolerance levels with their predominant personality traits and specialty choices. A secondary objective was to build a hypothetical model aimed at explaining the potential relationships of dependency between gender, personality traits, tolerance for uncertainty and specialty choice using a structural equation modeling (SEM) analysis. DESIGN/SETTING/PARTICIPANTS: A prospective cross-sectional study including two cohorts of second-year (n = 155) and sixth-year (n = 157) medical students was performed during 2017 at the Buenos Aires University School of Medicine. Both student cohorts completed instruments assessing tolerance for different types of uncertainty: (1) complexity (Tolerance for Ambiguity scale); (2) risk (Pearson Risk Attitude scale); and (3) ambiguity (Ambiguity Aversion in Medicine scale). Information on age, gender and specialty choice in sixth-year medical students was included, plus the Big Five Inventory-10 (BFI-10) personality test. RESULTS: Sixth-year students showed significantly lower scores than second-year students at tolerance for complexity (p = 0.0003) and ambiguity (p = 0.008). Sixth-year students choosing a surgical specialty were associated with low tolerance for risk and ambiguity, and moderate for complexity. Conversely, students choosing a clinical specialty were related with high tolerance for risk, moderate for ambiguity, and low for complexity. Logistic regression analysis including the uncertainty questionnaires plus BFI-10 categories demonstrated that only the "neuroticism" personality trait was independently associated with a surgical specialty choice (OR: 1.31, 95%CI: 1.03-1.67). The final SEM that best represented the data showed good fit statistics: chi-square (p = 0.108), and RMSEA (p = 0.047). CONCLUSIONS: Tolerance for uncertainty in its different dimensions was associated with personality traits and specialty choice among medical students. A SEM analysis could satisfactorily explain the hypothetical relationships of dependency between gender, personality traits, tolerance for uncertainty, and specialty choice.

Treatment of individual predictors with neural network algorithms improves Global Registry of Acute Coronary Events score discrimination.

Objective: The aim of this study was to develop, train, and test different neural network (NN) algorithm-based models to improve the Global Registry of Acute Coronary Events (GRACE) score performance to predict in-hospital mortality after an acute coronary syndrome. Methods: We analyzed a prospective database, including 40 admission variables of 1255 patients admitted with the acute coronary syndrome in a community hospital. Individual predictors included in GRACE score were used to train and test three NN algorithm-based models (guided models), namely: one- and two-hidden layer multilayer perceptron and a radial basis function network. Three extra NNs were built using the 40 admission variables of the entire database (unguided models). Expected mortality according to GRACE score was calculated using the logistic regression equation. Results: In terms of receiver operating characteristic area and negative predictive value (NPV), almost all NN algorithms outperformed logistic regression. Only radial basis function models obtained a better accuracy level based on NPV improvement, at the expense of positive predictive value (PPV) reduction. The independent normalized importance of variables for the best unguided NN was: creatinine 100%, Killip class 61%, ejection fraction 52%, age 44%, maximum creatine-kinase level 41%, glycemia 40%, left bundle branch block 35%, and weight 33%, among the top 8 predictors. Conclusions: Treatment of individual predictors of GRACE score with NN algorithms improved accuracy and discrimination power in all models with respect to the traditional logistic regression approach; nevertheless, PPV was only marginally enhanced. Unguided variable selection would be able to achieve better results in PPV terms.

Objetivo: El objetivo fue desarrollar, entrenar y probar diferentes modelos basados en algoritmos de redes neuronales (RN) para mejorar el rendimiento del score del Registro Global de Eventos Coronarios Agudos (GRACE) para predecir la mortalidad hospitalaria después de un síndrome coronario agudo. Métodos: Analizamos una base de datos prospectiva que incluía 40 variables de ingreso de 1255 pacientes con síndrome coronario agudo en un hospital comunitario. Las variables incluidas en la puntuación GRACE se usaron para entrenar y probar tres algoritmos basados en RN (modelos guiados), a saber: perceptrones multicapa de una y dos capas ocultas y una red de función de base radial. Se construyeron tres RN adicionales utilizando las 40 variables de admisión de toda la base de datos (modelos no guiados). La mortalidad esperada según el GRACE se calculó usando la ecuación de regresión logística. Resultados: En términos del área ROC y valor predictivo negativo (VPN), casi todos los algoritmos RN superaron la regresión logística. Solo los modelos de función de base radial obtuvieron un mejor nivel de precisión basado en la mejora del VPN, pero a expensas de la reducción del valor predictivo positivo (VPP). La importancia normalizada de las variables incluidas en la mejor RN no guiada fue: creatinina 100%, clase Killip 61%, fracción de eyección 52%, edad 44%, nivel máximo de creatina quinasa 41%, glucemia 40%, bloqueo de rama izquierda 35%, y peso 33%, entre los 8 predictores principales. Conclusiones: El tratamiento de las variables del score GRACE mediante algoritmos de RN mejoró la precisión y la discriminación en todos los modelos con respecto al enfoque tradicional de regresión logística; sin embargo, el VPP solo mejoró marginalmente. La selección no guiada de variables podría mejorar los resultados en términos de PPV.

Correlation between moral courage score and social desirability score of the medical residents and fellows in Argentina.

Purpose: Moral courage is the conviction to take action on one's ethical beliefs despite the risk of adverse consequences.. It aimed to evaluate the correlation between social desirability score and moral courage scores of medical residents and fellows, and to explore gender and specialty-based differences of moral courage scores. Methods: In April 2018, the Moral Courage Scale for Physicians (MCSP), the Professional Moral Courage (PMC) scale and the Marlowe-Crowne scale to measure social desirability were administered to 87 medical residents from Hospital Alemán of Buenos Aires, Argentina. Results: Cronbach's alpha coefficients were 0.78, 0.74 and 0.81 for the Marlowe-Crowne, MCSP and PMC scales, respectively. Correlation analysis showed that moral courage scores were poorly correlated with social desirability scores, while both moral courage scales were highly correlated with each other. Physicians who were training in a surgical specialty showed lower moral courage scores than nonsurgical specialty trainees, and male from any specialty tended to have lower moral courage scores than females. Particularly, individuals performing a surgical specialty ranked lower when assessing "multiple values", "endurance of threats", and "going beyond compliance" dimensions from PMC scale. Male individuals tended to rank lower than females on "multiple values", "moral goals" and "endurance of threats" dimensions. Conclusion: There was a poor correlation between two validated moral courage scores and social desirability score of the medical residents and fellows in Argentina. Conversely, both moral courage tools showed a good correlation and concordance between them, making these scales reasonably interchangeable.

Continuous Monitoring of Coronary Care Mortality Using the Global Registry for Acute Coronary Events (GRACE) Score.

BACKGROUND: The aim was to assess the utility of cumulative sum techniques for continuous monitoring of coronary care outcomes, applied to patients with acute coronary syndrome stratified by the Global Registry for Acute Coronary Events (GRACE) risk score. METHODS: A prospective longitudinal study to assess GRACE score for real-time monitoring of coronary care mortality in a community hospital was conducted between January 2012 and December 2017. An expected-to-observed probability of death chart for individual risk and a variable life-adjusted display were used to monitor the results. RESULTS: A total of 1,255 patients undergoing acute coronary syndrome were included in the analysis. GRACE-based variable life-adjusted plots monitoring in-hospital mortality showed that observed death rates remained in general within the expected 95% confidence limit over time, and these behaviors were similar for ST-segment elevation and non-ST-segment elevation myocardial infarction. In-hospital all-cause mortality was 2.6% for the overall population, and 56% of these cases corresponded to unexpected deaths; conversely, unexpected survival occurred in 5.2% of survivors. CONCLUSIONS: Continuous monitoring of coronary care mortality based on cumulative sum charts and the GRACE score demonstrated the occurrence of series of favorable and unfavorable outcomes on a real-time basis. Additionally, plotting the expected-to-observed probability of death for individual cases was useful to individualize unexpected deaths in low-risk patients. Although overall coronary care performance was adequate according to the GRACE score, we found that there is still some room for improvement, since over half of the deaths occurring in low-risk patients were potentially preventable.

Self-estimation of surgical skills and competencies based on the learning curve theory in medical residents and fellows.

OBJECTIVE: The aim was to explore how in-training junior physicians perceive their surgical performance compared with the one externally rated by their senior surgeon trainers, using a general learning curve model. METHODS: Between April and June 2018, a prospective study was conducted at a community hospital associated with a school of medicine. To assess how in-training physicians estimated their surgical performance, 48 surgical residents and fellows were invited to choose one among six options using a scale ranging from "novice" to "automatic expert." In addition, five senior surgeons who supervised the residents/fellows were asked to give their own opinions on each surveyed physician's expertise level, according to the same categories. Concordance analysis was done to compare residents' and fellows' self-perceived skills and their actual performance as estimated by senior surgeons. RESULTS: Self-assessments tended to overestimate residents' and fellows' position on the learning curve; particularly for "proficient" over "competent," and for "automatic expert" over "expert" categories (p = 0.025). The average degree of agreement among senior physicians was 50.0%. Comparison between residents' and fellows' perceived skills and their performances as estimated by senior surgeons showed a weak concordance (kappa = 0.494, 95% confidence interval 0.359-0.631, p < 0.0001). CONCLUSIONS: Nearly 51% of the residents/fellows included in some surgical specialty training program overestimated his/her actual performance as evaluated by classical learning curve categories. Underestimation of self-assessed performance was also observed in 17% of respondents. A better feedback from expert observers to in-training surgeons could result in a more accurate self-perception of their real surgical skills and competencies.

OBJETIVO: Evaluar cómo los médicos en formación (juniors) perciben su propio desempeño quirúrgico en comparación con la calificación otorgada por sus instructores (seniors) según un modelo de curva de aprendizaje. MÉTODOS: Entre abril y junio de 2018 se realizó un estudio prospectivo en un hospital comunitario. Para evaluar cómo los médicos juniors estimaban su propio desempeño, 48 residentes/becarios de especialidades quirúrgicas eligieron una entre seis opciones excluyentes en una escala entre «novicio¼ y «experto automático¼. Además, cinco cirujanos que supervisaban a los residentes/becarios dieron sus propias opiniones sobre el nivel de desempeño de cada médico encuestado, usando las mismas categorías. Se realizó un análisis de concordancia para comparar las habilidades autopercibidas y el desempeño real según lo estimado por los cirujanos seniors. RESULTADOS: Cuarenta y siete juniors y 50 seniors completaron la encuesta. El 51% sobrestimó y el 17% subestimó su ubicación en la curva de aprendizaje con respecto a los observadores externos (p = 0.025). El grado promedio de acuerdo entre seniors fue del 50%. La comparación entre la autopercepción de los juniors con respecto a sus observadores seniors mostró una concordancia pobre (kappa = 0.494; intervalo de confianza del 95% [IC 95%]: 0.359-0.631; p < 0.0001; sesgo promedio de Bland-Altman: 0.40; IC 95%: 0.11-0.70). CONCLUSIONES: La mitad de los residentes/fellows sobrestimó, y uno de cada seis subestimó, su verdadera ubicación en la curva de aprendizaje en comparación a la opinión de los seniors. Un mejor conocimiento de la existencia de este sesgo de estimación del propio desempeño podría redundar en una mejor confiabilidad del juicio médico.

Treatment of individual predictors with neural network algorithms improves Global Registry of Acute Coronary Events score discrimination / El tratamiento con redes neuronales de las variables del Global Registry of Acute Coronary mejora la discriminación del score

Abstract Objective: The aim of this study was to develop, train, and test different neural network (NN) algorithm-based models to improve the Global Registry of Acute Coronary Events (GRACE) score performance to predict in-hospital mortality after an acute coronary syndrome. Methods: We analyzed a prospective database, including 40 admission variables of 1255 patients admitted with the acute coronary syndrome in a community hospital. Individual predictors included in GRACE score were used to train and test three NN algorithm-based models (guided models), namely: one- and two-hidden layer multilayer perceptron and a radial basis function network. Three extra NNs were built using the 40 admission variables of the entire database (unguided models). Expected mortality according to GRACE score was calculated using the logistic regression equation. Results: In terms of receiver operating characteristic area and negative predictive value (NPV), almost all NN algorithms outperformed logistic regression. Only radial basis function models obtained a better accuracy level based on NPV improvement, at the expense of positive predictive value (PPV) reduction. The independent normalized importance of variables for the best unguided NN was: creatinine 100%, Killip class 61%, ejection fraction 52%, age 44%, maximum creatine-kinase level 41%, glycemia 40%, left bundle branch block 35%, and weight 33%, among the top 8 predictors. Conclusions: Treatment of individual predictors of GRACE score with NN algorithms improved accuracy and discrimination power in all models with respect to the traditional logistic regression approach; nevertheless, PPV was only marginally enhanced. Unguided variable selection would be able to achieve better results in PPV terms.

Resumen Objetivo: El objetivo fue desarrollar, entrenar y probar diferentes modelos basados en algoritmos de redes neuronales (RN) para mejorar el rendimiento del score del Registro Global de Eventos Coronarios Agudos (GRACE) para predecir la mortalidad hospitalaria después de un síndrome coronario agudo. Métodos: Analizamos una base de datos prospectiva que incluía 40 variables de ingreso de 1255 pacientes con síndrome coronario agudo en un hospital comunitario. Las variables incluidas en la puntuación GRACE se usaron para entrenar y probar tres algoritmos basados en RN (modelos guiados), a saber: perceptrones multicapa de una y dos capas ocultas y una red de función de base radial. Se construyeron tres RN adicionales utilizando las 40 variables de admisión de toda la base de datos (modelos no guiados). La mortalidad esperada según el GRACE se calculó usando la ecuación de regresión logística. Resultados: En términos del área ROC y valor predictivo negativo (VPN), casi todos los algoritmos RN superaron la regresión logística. Solo los modelos de función de base radial obtuvieron un mejor nivel de precisión basado en la mejora del VPN, pero a expensas de la reducción del valor predictivo positivo (VPP). La importancia normalizada de las variables incluidas en la mejor RN no guiada fue: creatinina 100%, clase Killip 61%, fracción de eyección 52%, edad 44%, nivel máximo de creatina quinasa 41%, glucemia 40%, bloqueo de rama izquierda 35%, y peso 33%, entre los 8 predictores principales. Conclusiones: El tratamiento de las variables del score GRACE mediante algoritmos de RN mejoró la precisión y la discriminación en todos los modelos con respecto al enfoque tradicional de regresión logística; sin embargo, el VPP solo mejoró marginalmente. La selección no guiada de variables podría mejorar los resultados en términos de PPV.

Comparación pronóstica entre scores de riesgo y la aplicación de redes neuronales para la predicción de la mortalidad a corto y mediano plazo en pacientes con insuficiencia cardíaca / Prognostic Comparison between Risk Scores and Neural Networks to Predict Short- and Mid-Term Mortality in Acute Heart Failure

RESUMEN Introducción: En el contexto de la insuficiencia cardíaca (IC) existen scores de riesgo para evaluar la mortalidad por cualquier causa durante el primer año, con áreas bajo la curva ROC que oscilan entre 0,59 y 0,80. Objetivo: Desarrollar y validar un modelo basado en algoritmos de redes neuronales (RN) destinado a mejorar el rendimiento de los modelos tradicionales para predecir mortalidad a corto y mediano plazo de pacientes con IC aguda. Material y métodos: Se analizó una base de datos con 181 variables de 483 pacientes con IC aguda en un hospital de comunidad de la Ciudad de Buenos Aires (junio de 2005-junio de 2019). Se utilizaron 25 variables para calcular 5 modelos de riesgo validados para predecir la mortalidad a 30 días, 6 meses y un año: EFFECT, ADHERE, GWTG-HF, 3C-HF y ACUTE-HF. Resultados: La edad media fue 78 ± 11,1años, 58% eran varones, el 35% de las IC eran de etiología isquémico necrótica, y la fracción de eyección media fue 52% (35-60). En término de discriminación a 30 días, fueron mejores el score EFFECT (ROC: 0,68) y el 3C-HF (ROC: 0,67) que el ACUTE- HF (ROC: 0,54). A los 6 meses y al año, el score EFFECT (ROC: 0,69 y 0,69) superó al ADHERE (ROC: 0,53 y 0,56) (p=0,011 y p = 0,003, respectivamente), y los scores EFFECT GWRG-HF (ROC: 0,68 y 0,66) y 3C-HF (ROC: 0,67 y 0,67) superaron al score ACUTE-HF (ROC: 0,53 y 0,56). De los algoritmos de RN los mejores resultados se obtuvieron con un perceptrón multicapa (PMC) con dos capas ocultas. Se usó una RN de arquitectura de capas 24-9-7-2 con los siguientes resultados: ROC: 0,82, valor predictivo negativo (VPN) 93,2% y valor predictivo positivo (VPP) 66,7% para mortalidad a 30 días; ROC: 0,87, VPN: 89,1% y VPP: 78,6% para mortalidad a 6 meses; y ROC: 0,85, VPN: 85,6% y VPP: 78,9% para mortalidad al año. En términos de discriminación, los algoritmos de RN superaron a los scores tradicionales ( p <0,001). Los factores que obtuvieron ≥50% de importancia estandarizada para predecir la mortalidad a los 30 días fueron en orden descendente la creatinina sérica, la hemoglobina, la frecuencia respiratoria, la urea, el sodio, la edad y la presión arterial sistólica. Agregaron capacidad pronóstica la clase III-IV NYHA y la demencia para mortalidad a 6 meses, y la frecuencia cardíaca y la disfunción renal crónica para mortalidad al año. Conclusiones: Los modelos con algoritmos de RN fueron significativamente superiores a los scores de riesgo tradicionales en nuestros pacientes con IC. Estos hallazgos constituyen una hipótesis de trabajo a validar con una mayor muestra de casos y en forma multicéntrica.

ABSTRACT Background: Heart failure (HF) risk scores to assess all-cause mortality during the first year have areas under the ROC curve (AUC) ranging between 0.59 and 0.80 Objective: To develop and validate a neural network (NN) algorithm-based model to improve traditional scores' performance for predicting short- and mid-term mortality of patients with acute HF. Methods: A prospective clinical database was analyzed including 483 patients admitted with diagnosis of acute HF in a coronary care unit community hospital of Buenos Aires, between June 2005 and June 2019. Among 181 demographic, laboratory, treatment and follow-up variables, only 25 were selected to calculate five acute heart failure risk scores aimed to predict 30-day, 6-month and 1-year mortality: EFFECT, ADHERE, GWTG-HF, 3C-HF, and ACUTE-HF. Results: Mean age was 78 ± 11.1 years, 58% were men, 35% had ischemic necrotic HF and median left ventricular ejection fraction was 52% (35-60). At 30 days, the EFFECT score (AUC:0.68) and the 3C-HF score (AUC: 0.68) showed better performance than the ACUTE-HF score (AUC: 0.54). At 6-month and 1-year follow-up, the EFFECT score (ROC: 0.69 and 0.69) outperformed the ADHERE score (AUC: 0.53 and 0.56), and EFFECT (AUC: 0.69 and 0.69), GWRG-HF (AUC = 0.68 and 0.66), and 3C-HF (AUC:0.67 and 0.67) scores outperformed the ACUTE-HF score (AUC:0.53 and 0.56). The best results with NN algorithms were obtained with a two-hidden layer multilayer perceptron. A 24-9-7-2-layer architecture NN was used with the following results: AUC: 0.82, negative predictive value (NPV) 93.2% and positive predictive value (PPV) 66.7% for 30-day mortality; AUC: 0.87, NPV: 89.1% and PPV: 78,6% for 6-month mortality; and AUC: 0.85, NPV: 85.6% and PPV: 78.9% for 1-year mortality. In terms of discrimination, NN algorithms outperformed all the traditional scores (p <0.001). For this algorithm, the most influential factors in descending order that scored ≥50% normalized importance to predict 30-day mortality were serum creatinine, hemoglobin, respiratory rate, blood urea nitrogen, serum sodium, age and systolic blood pressure. Also, NYHA functional class III-IV and dementia added prognostic capacity to 6-month mortality, and heart rate and chronic kidney disease to 1-year mortality. Conclusions: The models with NN algorithms were significantly superior to traditional risk scores in our population of patients with HF. These findings constitute a working hypothesis to be validated with a larger and multicenter sample of cases.

What patients consider to be a good doctor, and what doctors consider to be a good patient / Cómo definen los pacientes a un buen médico, y cómo definen los médicos a un buen paciente

ABSTRACT Background: From a patient's point of view, an 'ideal' doctor could be defined as one having personal qualities for interpersonal relationships, technical skills and good intentions. However, doctors' opinions about what it means to be a 'good' patient have not been systematically investigated. Aim: To explore how patients define the characteristics of a 'good' and a 'bad' doctor, and how doctors define a 'good' and a 'bad' patient. Material and Methods: We surveyed a cohort of 107 consecutive patients attending a community teaching hospital in February 2019, who were asked to define the desirable characteristics of a good/bad doctor. Additionally, a cohort of 115 physicians working at the same hospital was asked to define the desirable characteristics of a good/bad patient. Responses were subjected to content analysis. Simultaneously, an algorithm in Python was used to automatically categorize responses throughout text-mining. Results: The predominant patients' perspective alluded to desirable personal qualities more importantly than proficiency in knowledge and technical skills. Doctors would be satisfied if patients manifested positive personality characteristics, were prone to avoid decisional and personal conflicts, had a high adherence to treatment, and trusted the doctor. The text-mining algorithm was accurate to classify individuals' opinions. Conclusions: Ideally, fusing the skills of the scientist to the reflective capabilities of the medical humanist will fulfill the archetype of what patients consider to be a 'good' doctor. Doctors' preferences reveal a "paternalistic" style, and his/her opinions should be managed carefully to avoid stigmatizing certain patients' behaviors.

Antecedentes: Desde la perspectiva del paciente, un médico "ideal" podría definirse como aquel que tiene cualidades para las relaciones interpersonales, habilidades técnicas y buenas intenciones. Sin embargo, las opiniones de los médicos sobre lo que significa ser un "buen" paciente no se han investigado sistemáticamente. Objetivo: Explorar cómo los pacientes definen las características de un "buen" y "mal" médico, y cómo los médicos definen un "buen" y "mal" paciente. Material y Métodos: Encuestamos a una cohorte de 107 pacientes consecutivos que asistieron a un hospital comunitario en febrero de 2019, a quienes se les pidió que definieran las características deseables de un médico bueno/malo. Además, se pidió a una cohorte de 115 médicos que trabajaban en el mismo hospital que definieran las características deseables de un paciente bueno/malo. Las respuestas se sometieron a un análisis de contenido. Simultáneamente, se utilizó un algoritmo en Python para clasificar automáticamente las respuestas mediante minería de texto. Resultados: Los pacientes aludieron que las cualidades personales del médico eran más importantes que la competencia en conocimiento y las habilidades técnicas. Los médicos estarían satisfechos si los pacientes mostraran características positivas de personalidad, fueran propensos a evitar conflictos, tuvieran una alta adherencia al tratamiento y confiaran en el médico. El algoritmo de minería de texto clasificó las opiniones de los encuestados en forma precisa. Conclusiones: Idealmente, fusionar las habilidades del científico con las capacidades reflexivas del médico humanista cumplirá con el arquetipo de lo que los pacientes consideran un "buen" médico. Las preferencias de los médicos revelan un estilo "paternalista", y sus opiniones deben manejarse con cuidado para evitar estigmatizar los comportamientos de ciertos pacientes.

Desarrollo y validación externa de un puntaje predictivo de mediastinitis posoperatoria en cirugía cardíaca derivado del registro multicéntrico CONAREC XVI / Development and External Validation of a Predictive Score of Postoperative Mediastinitis in Cardiovascular Surgery Derived from the CONAREC XVI Multicenter Registry

RESUMEN Objetivos: El objetivo de este análisis fue definir variables predictoras independientes para la aparición de mediastinitis pos-cirugía cardíaca, y desarrollar un puntaje validado para estratificar el riesgo de manifestación de mediastinitis. Materiales y métodos: Se analizaron datos el estudio CONAREC XVI de adultos sometidos a cirugía cardíaca entre 2007 y 2008, en 49 centros de 16 provincias argentinas. Se definió mediastinitis como la presencia de signos clínicos o cultivos positivos. Se evaluaron variables epidemiológicas, clínicas, tipo de cirugía, variables intraoperatorias y posoperatorias, estudios complementarios. Se realizó un análisis de regresión logística múltiple para identificar variables independientemente asociadas a la manifestación de mediastinitis posoperatoria. Se consideró como significativa un error alfa menor del 5% a dos colas. Se construyó un score y se realizó una validación externa con pacientes de otros centros quirúrgicos. Resultados: Se analizaron 2553 pacientes: 1465 (57,4%) sometidos a cirugía coronaria, 359 (14,1%) a reemplazo valvular aórtico, 169 (6,6%) a cirugía valvular mitral, 312 (12,2%) a cirugía combinada y 248 (9,7%) a otras. La incidencia de mediastinitis fue 1,88% en la población global. Las variables asociadas al desarrollo de mediastinitis fueron: antecedente de tabaquismo, OR: 2,3 (IC 95% 1,1-5,1) p = 0,02, disfunción ventricular grave, OR: 2,8 (IC 95% 1,3-6,2) p = 0,001, reoperación, OR: 4,6 (IC 95% 1,8-11,3) p = 0,001, e insuficiencia renal posoperatoria, OR: 4,3 (IC 95% 1,9-9,6) p = 0,0001. Se construyó un score de riesgo adjudicando los siguientes puntajes según la presencia o ausencia de cada una de los cuatros variables del modelo resultante: 1 punto en caso de disfunción ventricular grave, 1 punto para el antecedente de tabaquismo, 2 puntos para el desarrollo de insuficiencia renal y 2 puntos para la necesidad de reoperación. El área ROC para mortalidad fue 0,72 (IC 95% 0,64-0,81) (Hosmer Lemeshow p = 0,9). El grupo de validación incluyó 1657 pacientes con edad media fue de 62,8 ± 13 años. Se observó una incidencia de mediastinitis de 1,6%. El área ROC para desarrollo de mediastinitis fue 0,70 (IC 95% 0,58-0,80), p = 0,001. Conclusiones: La construcción de un score de riesgo predictivo del desarrollo de mediastinitis en el posoperatorio de cirugía cardíaca resulta relevante para su aplicación en la práctica diaria, tanto para la prevención como para la detección temprana de esta grave complicación.

ABSTRACT Objective: The aim of this analysis was to define independent predictive variables for the development of mediastinitis after cardiovascular surgery and develop a validated score to stratify the risk for mediastinitis. Methods: Data were retrieved from the CONAREC XVI study comprising adults undergoing cardiovascular surgery between September 2007 and October 2008 in 49 centers of 16 provinces in Argentina. Mediastinitis was defined as the presence of clinical signs attributable to the condition or positive cultures. Epidemiological and clinical variables, type of surgery, intraoperative and postoperative variables and complementary tests were evaluated. A logistic regression model was used to identify the independent variables associated with perioperative mediastinitis. A two-tailed alpha error < 0.05 was considered statistically significant. A score was constructed and was externally validated in patients from other surgical centers. Results: A total of 2553 patients were analyzed: coronary artery bypass graft surgery, 1465 patients (57.4%); aortic valve replacement, 359 (14.1%); mitral valve surgery, 169 (6.6%); combined procedure (revascularization-valve surgery), 312 (12.2%); other procedures, 248 (9.7%). The overall incidence of medistinitis was 1.88%. The variables associated with the development of mediastinitis were: smoking habits (OR, 2.3; 95% CI,1.1-5,1; p=0.02), severe left ventricular dysfunction (OR, 2.8; 95% CI, 1.3-6.2; p=0.001), reoperation (OR, 4,6; 95% CI,1.8-11.3; p=0.01) and postoperative renal failure (OR, 4.3; 95% CI, 1.9-9,6; p=0.0001). A risk score was constructed assigning 1 point for severe left ventricular dysfunction, 1 point for the history of smoking habits, 2 points for the development of renal failure and 2 points for need for reoperation. The area under the ROC curve for mortality was 0.72 (95% CI, 0.64-0,81; Hosmer Lemeshow test p=0.9). The external validation was performed on 1657 patients, mean age 62.8±13.3 years. The incidence of mediastinitis was 1.6%. The area under the ROC curve for the development of mediastinitis was 0.70 (95% CI, 0.58-0.80; p=0.001). Conclusions: The construction of a predictive score for the development of postoperative mediastinitis after cardiovascular surgery is relevant for daily practice for the prevention and early detection of this severe complication.

The importance of gender differences in the diagnosis and management of cardiovascular disease.

For many years, the majority of the observational and epidemiological studies assessing coronary artery disease patients, national and international clinical guidelines, registries and randomized trials have focused almost exclusively on men whereas women were usually excluded in most series. This underrepresentation of women in the medical literature in this field has resulted in few data being available regarding the clinical course of the condition, its management and clinical outcomes in this specific population, despite the relatively high prevalence of ischemic heart disease in women. The situation has changed -at least partially- in the past few years with publications focusing on this issue and reporting the existence of inequalities between genders regarding the diagnosis and treatment of coronary heart disease. This article will briefly review gender differences in the clinical presentation, diagnostic strategies and prognosis of coronary heart disease.

Gender differences in the treatment of chronic ischemic heart disease: prognostic implications.

Despite the relatively high prevalence of coronary artery disease in women, there are little data on the investigation and treatment of ischemic heart disease in this population. In the last couple of decades authors have addressed health problems in minorities, including women. The great majority of these studies included the acute coronary syndrome population but most recent ones have focused on the management of stable angina from a gender perspective. Many of those studies showed that there are inequities between genders regarding the care of patients with ischemic heart disease. Although little is known about the prognostic implications of such differences, studies have shown that suboptimal treatment in women leads to poor clinical outcomes. Gender-specific and both epidemiological and pathophysiological data are needed.

Descenso de los niveles de propéptido natriurético de tipo B-N terminal luego de la reversión de pacientes con fibrilación auricular y función ventricular conservada / NT-Pro-BNP levels performance before and after reversion to sinus rhythm in patients with preserved ventricular function

El objetivo fue comparar los niveles de Pro Péptido Natriurético tipo B-N terminal (Pro-BNP-NT) basales y post reversión en pacientes con fibrilación auricular solitaria (FAS) de comienzo reciente y con función ventricular izquierda conservada. Se determinaron niveles del Pro BNP NT antes y después de su reversión en treinta pacientes con FAS de comienzo reciente y fracción de eyección de ventrículo izquierdo ≥ 50%. Basalmente, los niveles de Pro BNP NT fueron significativamente más elevados respecto a un grupo control sano: 529 pg/ml (157-1763) versus 31.5 pg/ml (24-76), p < 0.0001. Las concentraciones de Pro BNP NT descendieron significativamente luego de la cardioversión de 529 (157-1763) a 318 (98-870) pg/ml, p < 0.001. Los descensos se objetivaron tanto luego de la cardioversión eléctrica como de la obtenida por vía farmacológica, 345 (153-1151) pg/ml a 169 (86-407) pg/ml, p: 0.02 y de 1624 (541-4010) pg/ml a 856 (532-1160) pg/ml, p < 0.001, respectivamente. Este fenómeno se observó fundamentalmente en aquellos con una FAS con duración mayor a 8 horas: 1289 (338-2103) a 410 (169-905) pg/ml, p < 0.001. No se observó correlación entre los cambios de la frecuencia cardíaca y del Pro BNP NT pre y post cardioversión a ritmo sinusal. Se observaron descensos significativos de Pro BNP NT basalmente y post reversión (tanto farmacológica como eléctrica) en pacientes con FA de reciente aparición y función ventricular conservada. Estos descensos fueron más ostensibles a partir de las 8 horas de duración de la arritmia.

Our objective was to evaluate changes of N-terminal pro-BNP (NT-Pro-BNP) levels at baseline and after restoration to sinus rhythm in hemodynamic stable patients with lone atrial fibrillation (LAF) with preserved left ventricular function. NT-Pro-BNP levels were obtained before and after cardioversion in thirty hemodynamic stable patients with LAF and preserved left ventricular function. At baseline levels of NT-Pro BNP levels were significatively higher than a normal control group. NTPro-BNP levels decreased significantly following cardioversion from 529 (157-1763) to 318 (98-870) pg/ml, p < 0.0001. Decreasing of N-terminal pro-BNP concentrations was observed after any mode of cardioversion: electrical or pharmacologic, 345 (153-1151) pg/ml to 169 (86-407) pg/ml, p: 0.02 and from 1624 (541-4010) pg/ml to 856 (532-1160) pg/ml, p < 0.001, respectively. N-terminal pro-BNP decreasing was observed mainly in patients with length of LAF longer than 8 hours: 1289 (338-2103) to 410 (169-905) pg/ml, p < 0.001 but no difference was detected when such length was less than 8 hours: 274 (137-2300) to 286 (82-1440), p = NS. Our study showed that baseline levels of NT-pro-BNP decreased shortly after reversion of patients with LAF to sinus rhythm. This performance occurs predominantly in patients with LAF length of at least eight hours.