[Numerical expression of the clinical course of the disease. Data management]. / Expresión numérica del curso clínico de la enfermedad. Manejo de datos.

Data management "behind the scenes" refers to collection, cleaning, imputation, and demarcation; and despite of being indispensable processes, they are usually neglected and thus, generate erroneous information. During the collection are errors: omission of covariates, deviation from the objective, and insufficient quality. The omission of covariates distorts the result attributed to the main manoeuvre. Deviation from the primary objective commonly occurs when the outcome is rare, delayed, or subjective and promotes substitution by non-equivalent surrogate variables. Moreover, insufficient quality occurs due to inadequate instruments, omission of the measurement procedure, or measurements out of context, such as attribution at the wrong time or equivalent. Furthermore, cleaning implies identifying erroneous, extreme, and missing values, which may or may not be imputed, depending on the percentage. The values of the manoeuvre or the outcome are never imputed, nor are patients eliminated due to a lack of values. Finally, the demarcation of each variable seeks to give it a clinical meaning about the outcome, for which a hierarchical sequence of criteria is followed: 1) previous clinical study, 2) expert agreement, 3) clinical judgment of the investigator/investigators, and 4) statistics. Acting without quality controls in data management frequently causes involuntary lies and confuses instead of clarifying.

El manejo de datos "tras bambalinas" se refiere a los procesos de recopilación, limpieza, imputación y demarcación; los cuales, aun siendo indispensables, usualmente suelen ser descuidados, por lo que generan información errónea. Durante la recopilación son errores: omisión de covariables, desvío del objetivo, y calidad insuficiente. La omisión de covariables distorsiona el resultado atribuido a la maniobra principal. El desvío del objetivo primario es común cuando el desenlace es raro, tardado o subjetivo y promueve la sustitución por variables subrogadas no equivalentes. Además, la calidad insuficiente, sucede por instrumentos inadecuados, omisión del procedimiento de medición, o medición fuera de contexto -como atribución a destiempo o equivalente-. Por otro lado, la limpieza implica identificar valores erróneos, extremos y faltantes, que podrán ser o no imputados, dependiendo del porcentaje se imputará comúnmente por la medida de resumen. Nunca se imputan los valores de la maniobra ni del desenlace, ni se eliminan pacientes por falta de valores. Finalmente, la demarcación de cada variable busca un significado clínico en referencia al desenlace, para ello se sigue una secuencia jerárquica de criterios: 1) estudio clínico previo, 2) acuerdo de expertos, 3) juicio clínico del investigador/investigadores y 4) estadística. Actuar sin controles de calidad en el manejo de datos provoca frecuentemente mentiras involuntarias y confunde en lugar de esclarecer.

Diet Quality, Physical Activity, and Weight Changes and Their Association With 6-Year Risk of Metabolic Syndrome in Mexican Adults.

Background. Among lifestyle factors, obesity has been postulated as the most important risk factor for metabolic syndrome (MS). Lifestyle factors such as physical activity (PA), diet quality, and weight management are so closely related, it is not clear if the role of lifestyle factors is exclusively through its effect on weight, or if they contribute independently. Objective. To examine the effect of lifestyle factors such as diet quality, weight change, and leisure time PA on MS occurrence in lean and overweight/obese (OW/OB) adults over a 6-year period. Methods. This was a longitudinal analysis of data from adults participating in the Health Workers Cohort Study. Results. A total of 1046 participants were included; 37.2% of the OW/OB group and 16.2% of the lean participants developed MS. Becoming overweight had a hazard ratio (HR) of 3.06 for developing MS compared with remaining lean (95% CI = 1.98, 4.74). Going from OW/OB to lean was associated with lower risk of MS (HR = 0.41; 95% CI = 0.22, 0.79). Among OW/OB, becoming active was associated with lower risk (HR = 0.63; 95% CI = 0.42, 0.95) in comparison with an inactive pattern; diet quality was not associated with occurrence of MS. Conclusion. Weight change was the most relevant factor predicting MS over a 6-year period.

Risk Assessment of Dyslipidemias, Hyperglycemia, Hyperuricemia, and Hypertension Utilizing Self-Reported Body Silhouettes.

Objective: Self-reported body silhouette is an anthropometric instrument that has been utilized as a screening tool for underweight, overweight, obesity, and other abnormal anthropometric variables. Herein, we analyzed the risk associated with the self-reported body silhouette in the scope of dyslipidemias, hyperglycemia, hyperuricemia, and hypertension. Methods: Adult participants of the Health Workers Cohort Study enrolled between March 2004 and April 2006 were included. Then, risk analysis was performed considering dyslipidemias as serum triglycerides, high total cholesterol, high LDL-C, low HDL-C, hyperglycemia, hyperuricemia, and hypertension. Results: A total of 2,297 males and 5,003 females were analyzed. The median ages of the studied population was 39 (30-49) and 41 (31-50) years for males and females, respectively. Overall, there is a stepwise increase in the risk of presenting dyslipidemias, hyperglycemia, hyperuricemia, and hypertension as the self-reported body silhouette number increases, this tendency was observed in both males and females. Conclusion: Self-reported body silhouette is a useful risk assessment tool for dyslipidemias, hyperglycemia, hyperuricemia, and hypertension in Mexican adults. Applications of questioners containing this silhouette might be considered a valuable public health instrument due to their low cost, relative simplicity, and absence of specialized equipment, training, or respondent knowledge.

[Diagnostic performance of the FINDRISC questionnaire to identify insulin resistance in adults]. / Certeza diagnóstica del instrumento FINDRISC para identificar resistencia a la insulina en adultos.

Background: Insulin resistance (IR) is a state prior to the development of type 2 diabetes (T2D) and it is reversible with lifestyle modification. However, it is underdiagnosed due to the difficulty in its measurement. Objective: To evaluate the diagnostic performance of the FINDRISC questionnaire to identify IR. Material and methods: An analytical cross-sectional study was performed in adults aged 20 to 60 years without previous diagnosis of T2D. Those using steroids and pregnant women were excluded. IR was diagnosed through the Triglycerides/glucose index. A ROC curve was used to establish the cut-off point for the diagnosis of IR. Sensitivity, specificity, predictive values and likelihood ratios were calculated. Risk measurement for IR was performed with the FINDRISC instrument. Results: A total of 253 participants were included, with a prevalence of IR of 60.8%. The area under the curve of the FINDRISC instrument was 0.813 (95% confidence interval [95% CI] 0.759-0.865), with a cut-off point of 8. Sensitivity was 94.8% and specificity was 48.5%, positive predictive value was 74% and negative 86%, with a positive likelihood ratio of 1.84 and a negative of 0.11. Conclusions: The FINDRISC instrument is a useful screening tool to identify subjects with IR at the first level of care. A score ≥ 8 identifies subjects with IR.

Introducción: la resistencia a la insulina (RI) es un estado previo al desarrollo de diabetes tipo 2 (DT2) y es reversible con modificación en el estilo de vida. Sin embargo, este estado se encuentra subdiagnosticado por la dificultad en su medición. Objetivo: evaluar el desempeño diagnóstico del cuestionario FINDRISC para identificar RI. Material y métodos: se realizó un estudio transversal analítico en adultos de 20 a 60 años sin diagnóstico previo de DT2. Fueron excluidos quienes utilizaran esteroides y mujeres embarazadas. La RI fue diagnosticada mediante el índice triglicéridos/glucosa. Una curva ROC fue utilizada para establecer el punto de corte para el diagnóstico de RI. Se calculó sensibilidad, especificidad, valores predictivos y razones de verosimilitud. La medición del riesgo para RI se realizó con el instrumento FINDRISC. Resultados: se incluyeron 253 participantes, con una prevalencia de RI de 60.8%. El área bajo la curva del instrumento FINDRISC fue de 0.813 (intervalo de confianza del 95% [IC 95%] 0.759-0.865), con un punto de corte de 8. La sensibilidad fue de 94.8%, con una especificidad de 48.5%, valor predictivo positivo de 74% y negativo de 86%, con una razón de verosimilitud positiva de 1.84 y una negativa de 0.11. Conclusiones: el instrumento FINDRISC puede ser una herramienta útil para identificar a sujetos con resistencia a la insulina en el primer nivel de atención. Un puntaje igual o mayor que 8 identifica a sujetos con RI.

Results from the 2022 Mexican report card on physical activity for children and adolescents.

Introduction: The Mexican Report Card on Physical Activity for Children and Adolescents aims to assess the prevalence of movement behaviors and opportunities to perform them. Methods: Data on 11 indicators were obtained from national health surveys, census data, government documents, websites, and published studies. Data were compared against established benchmarks, and a grade between 0 and 10 was assigned to each indicator. Results: For Daily Behaviors, we found 34.5% of Mexican children and adolescents meet Physical Activity recommendations (Grade 3), 48.4% participate in Organized Sports (Grade 5), 35-75.8% engage in Active Play outdoors (Grade 4), 54.1% use Active Transportation (Grade 5), 43.6% spend <2 h in Sedentary Behavior per day (Grade 4), and 65-91% meet Sleep recommendations (Grade 7). Girls have lower physical activity levels and sports participation than boys of the same age. For Physical Fitness, we found 56.2-61.8% of children and adolescents have an adequate body mass index for their age (Grade 6). For Sources of Influence, we found 65-67% of parents engage in physical activity or sports in a week (Grade 7), 32.2-53.3% of basic education schools have a physical education teacher (Grade 6), and 37% of neighborhoods in Mexico have sidewalks with trees (Grade 4). Regarding Government, several policies and programs aimed at improving children physical activity were launched but their impact and allocated implementation budget are unknown (Grade 6). Discussion: Mexican children and adolescents engage in low levels of movement behaviors and have limited opportunities to perform such behaviors. The grades and recommendations provided here should be considered to improve such opportunities.

Effect of a Low-Glycemic Load Diet Intervention on Maternal and Pregnancy Outcomes in Obese Pregnant Women.

The increased prevalence of obese, pregnant women who have a higher risk of glucose intolerance warrants the need for nutritional interventions to improve maternal glucose homeostasis. In this study, the effect of a low-glycemic load (GL) (n = 28) was compared to a high-GL (n = 34) dietary intervention during the second half of pregnancy in obese women (body mass index (BMI) > 30 or a body fat >35%). Anthropometric and metabolic parameters were assessed at baseline (20 week) and at 28 and 34 weeks gestation. For the primary outcome 3h-glucose-iAUC (3h-incremental area under the curve), mean between-group differences were non-significant at every study timepoint (p = 0.6, 0.3, and 0.8 at 20, 28, and 34 weeks, respectively) and also assessing the mean change over the study period (p = 0.6). Furthermore, there was no statistically significant difference between the two intervention groups for any of the other examined outcomes (p ≥ 0.07). In the pooled cohort, there was no significant effect of dietary GL on any metabolic or anthropometric outcome (p ≥ 0.2). A post hoc analysis comparing the study women to a cohort of overweight or obese pregnant women who received only routine care showed that the non-study women were more likely to gain excess weight (p = 0.046) and to deliver large-for-gestational-age (LGA) (p = 0.01) or macrosomic (p = 0.006) infants. Thus, a low-GL diet consumed during the last half of pregnancy did not improve pregnancy outcomes in obese women, but in comparison to non-study women, dietary counseling reduced the risk of adverse outcomes.

Back to the clinic. Methods II. The Architecture of Clinical Research. Subject interaction, maneuvers and disease throughout time.

Medicine is characterized by the application of the scientific method through clinical judgment, by correct interpretation and use of the clinical course and/or natural history of the disease; its best description is observed in the architecture of clinical research. Through a temporal sequence, this model explains the phenomenon of causality with three sections: baseline status, maneuver, and outcome. The baseline status assesses who the patient is, where does he come from, his general conditions, the diagnosis, stage and aggressiveness of the pathology, complications, previous therapies, socioeconomic-cultural level, habits, therapeutic indications or contraindications, and the expected evolution is anticipated. In the maneuver, risk or prognostic factors, specific or symptomatic treatment, and general measures can be evaluated. In the outcome, early and late evolution are monitored. The model also allows the causes of follow-up loss to be determined. Anticipating patient evolution by recognizing his condition, disease, and expected effect of medical decisions allows acting in advance, since waiting for the manifestations of the evolutionary process of disease results in detriment to the patient.

La medicina se caracteriza por la aplicación del método científico a través del juicio clínico, por la correcta interpretación y el uso del curso clínico o historia natural de la enfermedad; su descripción más lograda la observamos en la arquitectura de la investigación clínica. A través de una secuencia temporal, este modelo explica el fenómeno de causalidad con tres apartados: estado basal, maniobra y desenlace. En el estado basal se evalúa quién es el paciente, de donde proviene, sus condiciones generales, el diagnóstico, el estadio y la agresividad de la patología, las complicaciones, terapias previas, nivel socioeconómi­co-cultural, hábitos, indicaciones o contraindicaciones terapéuticas y se prevé la evolución esperada. De la maniobra se pueden evaluar los factores de riesgo o pronóstico, tratamiento específico, sintomático y medidas generales. En el desenlace se vigila la evolución temprana y tardía. El modelo también permite determinar las causas de pérdida de seguimiento. Anticipar la evo­lución del paciente al reconocer su condición, enfermedad y efecto esperado de la decisiones médicas permite actuar antici­padamente, ya que esperar las manifestaciones del proceso evolutivo de la enfermedad resulta en detrimento del paciente.

De vuelta a la clínica. Métodos II. Arquitectura de la investigación clínica. Interacción sujeto, maniobras y enfermedad a través del tiempo / Back to the clinic. Methods II. Architecture of clinical research. Subject interaction, maneuvers and disease throughout time

Resumen La medicina se caracteriza por la aplicación del método científico a través del juicio clínico, por la correcta interpretación y el uso del curso clínico o historia natural de la enfermedad; su descripción más lograda la observamos en la arquitectura de la investigación clínica. A través de una secuencia temporal, este modelo explica el fenómeno de causalidad con tres apartados: estado basal, maniobra y desenlace. En el estado basal se evalúa quién es el paciente, de donde proviene, sus condiciones generales, el diagnóstico, el estadio y la agresividad de la patología, las complicaciones, terapias previas, nivel socioeconómico-cultural, hábitos, indicaciones o contraindicaciones terapéuticas y se prevé la evolución esperada. De la maniobra se pueden evaluar los factores de riesgo o pronóstico, tratamiento específico, sintomático y medidas generales. En el desenlace se vigila la evolución temprana y tardía. El modelo también permite determinar las causas de pérdida de seguimiento. Anticipar la evolución del paciente al reconocer su condición, enfermedad y efecto esperado de la decisiones médicas permite actuar anticipadamente, ya que esperar las manifestaciones del proceso evolutivo de la enfermedad resulta en detrimento del paciente.

Abstract Medicine is characterized by the application of the scientific method through clinical judgment, by correct interpretation and use of the clinical course and/or natural history of the disease; its best description is observed in the architecture of clinical research. Through a temporal sequence, this model explains the phenomenon of causality with three sections: baseline status, maneuver, and outcome. The baseline status assesses who the patient is, where does he come from, his general conditions, the diagnosis, stage and aggressiveness of the pathology, complications, previous therapies, socioeconomic-cultural level, habits, therapeutic indications or contraindications and the expected evolution is anticipated. In the maneuver, risk or prognostic factors, specific or symptom treatment, and general measures could be evaluated. In the outcome, early and late evolution are monitored. The model also allows the causes of follow-up loss to be determined. Anticipating patient evolution by recognizing his condition, disease, and expected effect of medical decisions allows acting in advance, since waiting for the manifestations of the evolutionary process of disease results in detriment to the patient.

[The relevance and irrelevance of charts in clinical research]. / Pertinencia e impertinencia de los gráficos en la investigación clíni-ca.

Charts are a visual aid that is used in articles in order to highlight the results of an investigation. They allow illustrating the results with the purpose of making them clearer. Charts, just like statistical tests, are selected based on the objective of the study, the types of variable, and the statistical analyzes to be illustrated. Some of the most commonly used charts in clinical practice are frequency histograms, which illustrate qualitative variables or frequencies; also error charts, that are used for normally distributed quantitative variables; box plots or violin plots are used for distribution-free quantitative variables, and survival curves are for variables that include the person-time variable. The aforementioned charts can be used to illustrate the comparisons between maneuvers and outcome depending on the type of variable that is being analyzed. When two groups are compared and the dependent variable is dichotomous, forest plots are used; for multivariate models, the chart depends on the type of analysis. As for logistic regression and linear regression, tree diagrams are used; and scatter plots are used for linear regression. Survival plots are used for Cox proportional hazards. Although charts can be very useful, if they are misused, they can show differences where there are none, which leads to a misinterpretation of the studies. In this article, we will use examples to complement the topics that were previously addressed in the articles of this series.

Los gráficos constituyen una ayuda visual que usan los artículos para resaltar los resultados de una investigación. Estos permiten ilustrar los resultados con el fin de hacerlos más claros. Los gráficos, al igual que las pruebas estadísticas, se seleccionan a partir del objetivo del estudio, de los tipos de variable y de los análisis estadísticos que se desee ilustrar. Algunos de los gráficos más usados en la práctica clínica son los histogramas de frecuencia que ilustran las variables cualitativas o frecuencias, los gráficos de error se usan para variables cuantitativas con distribución normal, el gráfico de cajas o gráfico de violín para variables cuantitativas de libre distribución y las curvas de supervivencia para las variables que incluyen la variable tiempo/persona. Estos mismos gráficos pueden ser usados para ilustrar las comparaciones entre maniobras y desenlace dependiendo del tipo de variable que se analice. Cuando se comparan dos grupos y la variable dependiente es dicotómica se usan gráficos de bosque. Para los modelos multivariados los gráficos dependen del tipo de análisis, en el caso de la regresión logística se utilizan gráficos de árbol y para la regresión lineal, de dispersión; y para los riesgos proporcionales de Cox, gráficos de supervivencia. Si bien los gráficos son de gran utilidad, mal utilizados pueden mostrar diferencias donde no las hay, provocando una errónea interpretación de los estudios. En este artículo complementaremos con ejemplos los temas abordados con anterioridad en los artículos de esta misma serie.

[Correlation: not all correlation entails causality]. / Correlación: no toda correlación implica causalidad.

The concept of correlation entails having a couple of observations (X and Y), that is to say, the value that Y acquires for a determined value of X; the correlation makes it possible to examine the trend of two variables to be grouped together. We know that, with increasing age, blood pressure figures also increase, therefore, if we want to answer a research question like "what is the connection between age and blood pressure?" the relevant statistical test is a correlation test. This test makes it possible to quantify the magnitude of the correlation between two variables, but it is also helpful for predicting values. If these variables had a perfect correlation, the value of the variable Y could be deduced by knowing the value of X. Because of these advantages, the correlation is one of the most frequently used tests in the clinical setting since, in addition to measuring the direction and magnitude of the association of two variables, it is one of the foundations for prediction models, such as linear regression model, logistic regression model and Cox proportional hazards model.

El concepto de correlación implica contar con un par de observaciones (X y Y), es decir, el valor que toma Y para determinado valor de X; la correlación permite examinar la tendencia de dos variables a ir juntas, por ejemplo, sabemos que al incrementar la edad también aumentan las cifras de presión arterial, por lo tanto, si queremos responder una pregunta de investigación como ¿cuál es la relación entre edad y presión arterial?, la prueba estadística pertinente es una prueba de correlación. Esta prueba permite cuantificar la magnitud de la correlación entre dos variables y ayuda a predecir valores. Si estas variables tuvieran una correlación perfecta se podría inferir el valor de la variable Y conociendo el valor de X. Debido a estas ventajas, la correlación es una de las pruebas más usadas en el ámbito clínico, ya que además de medir la dirección y magnitud de la asociación de dos variables, es uno de los fundamentos de los modelos de predicción, como los modelos de regresión lineal, logística y riesgos proporcionales de Cox.

De vuelta a la clínica. Métodos I. Diseños de investigación. Mayor calidad de información, mayor certeza a la respuesta.

Research designs refer to the way information is obtained and are limited by ethical, economic and temporal viability. Research designs are standardized strategies to reduce biases, which in the architectural model of research are identified in the baseline state, the maneuver and the outcome; hence, there are no specific designs for each question. The design with the lowest probability of bias is the clinical trial, followed by cohort and case-control studies and, finally, by cross-sectional surveys. Among the main characteristics that give merit to research designs are the following: population inquiry, which refers to the situation of the population in relation to the clinical course/natural history of the disease; the maneuver, or action that is expected to modify the baseline state, which can be observational or experimental; follow-up, or documented monitoring that is given to each subject, which can be longitudinal or cross-sectional; and directionality, which can prolective or retrolective and refers to the timing of data collection for research purposes. It will always be better having a valuable question, even when answered with a design with higher risk of bias, than a question that is irrelevant or has no applicability.

Los diseños de investigación se refieren a la forma como se obtiene la información y están limitados por viabilidad ética, económica y temporal. Son estrategias estandarizadas para disminuir los sesgos que en el modelo arquitectónico de la investigación se identifican en el estado basal, maniobra y desenlace; de ahí que no hay diseños específicos para cada pregunta. El diseño con menor probabilidad de sesgos es el ensayo clínico, seguido de la cohorte, el estudio de casos y controles y, finalmente, la encuesta transversal. Entre las principales características que dan mérito a los diseños están las siguientes: la pesquisa de la población, que se refiere a la ubicación de la población en relación con el curso clínico o historia natural de la enfermedad; la maniobra, o acción que se espera modifique la condición basal, que puede ser observacional o experimental; el seguimiento, o monitoreo documentado que se le da a cada sujeto, que puede ser longitudinal o transversal; y la direccionalidad, prolectiva o retrolectiva, que alude al tiempo de recopilación de la información con fines de investigación. Siempre será mejor tener una pregunta valiosa, incluso cuando se responda con un diseño con mayor riesgo de sesgos, que una pregunta irrelevante o sin aplicabilidad.

De vuelta a la clínica. Métodos I. Diseños de investigación. Mayor calidad de información, mayor certeza a la respuesta / Back to the clinic. Methods I. Research designs. Higher quality of information, greater certainty to the answer

Resumen Los diseños de investigación se refieren a la forma como se obtiene la información y están limitados por viabilidad ética, económica y temporal. Son estrategias estandarizadas para disminuir los sesgos que en el modelo arquitectónico de la investigación se identifican en el estado basal, maniobra y desenlace; de ahí que no hay diseños específicos para cada pregunta. El diseño con menor probabilidad de sesgos es el ensayo clínico, seguido de la cohorte, el estudio de casos y controles y, finalmente, la encuesta transversal. Entre las principales características que dan mérito a los diseños están las siguientes: la pesquisa de la población, que se refiere a la ubicación de la población en relación con el curso clínico o historia natural de la enfermedad; la maniobra, o acción que se espera modifique la condición basal, que puede ser observacional o experimental; el seguimiento, o monitoreo documentado que se le da a cada sujeto, que puede ser longitudinal o transversal; y la direccionalidad, prolectiva o retrolectiva, que alude al tiempo de recopilación de la información con fines de investigación. Siempre será mejor tener una pregunta valiosa, incluso cuando se responda con un diseño con mayor riesgo de sesgos, que una pregunta irrelevante o sin aplicabilidad.

Abstract Research designs refer to the way information is obtained and are limited by ethical, economic and temporal viability. Research designs are standardized strategies to reduce biases, which in the architectural model of research are identified in the baseline state, the maneuver and the outcome; hence, there are no specific designs for each question. The design with the lowest probability of bias is the clinical trial, followed by cohort and case-control studies and, finally, by cross-sectional surveys. Among the main characteristics that give merit to research designs are the following: population inquiry, which refers to the situation of the population in relation to the clinical course/natural history of the disease; the maneuver, or action that is expected to modify the baseline state, which can be observational or experimental; follow-up, or documented monitoring that is given to each subject, which can be longitudinal or cross-sectional; and directionality, which can prolective or retrolective and refers to the timing of data collection for research purposes. It will always be better having a valuable question, even when answered with a design with higher risk of bias, than a question that is irrelevant or has no applicability.

Small bowel transit time of capsule endoscopy as a factor for the detection of lesions in potential small bowel bleeding.

BACKGROUND: the relationship between small bowel transit time (SBTT) of the capsule endoscopy (CE) and the diagnosis of small bowel bleeding (SBB) is controversial. OBJECTIVE: to evaluate the relationship between SBTT and CE and the identification of SBB. MATERIAL AND METHODS: CE was divided according to SBTT into < 4 hours and ≥ 4 hours. RESULTS: CE with SBTT ≥ 4 hours identified more angioectasias (p = 0.023), single lesions (p = 0.029) and jejunal lesions (p = 0.001) with an OR of 3.13 (95% CI, 1.61-6.10, p = 0.001) to identify the cause of SBB. CONCLUSIONS: CE SBTT of ≥ 4 hours increases the diagnosis of SBB.

De vuelta a la clínica: sin justificación no existe pregunta de investigación que valga.

A clinical research question requires the concurrence of clinical experience and knowledge on methodology and statistics in that who formulates it. Initially, a research question should have a structure that clearly establishes what is that which is being sought (consequence or outcome), in whom (baseline status), and by action of what (maneuver). Subsequently, its reasoning must explore four aspects: feasibility and reasonableness of the questioning, lack of a prior answer, relevance of the answer to be obtained, and applicability. Once these aspects are satisfactorily covered, the question can be regarded as being "clinically relevant", which is different from being statistically significant, which refers to the probability of the result being driven by chance, which does not reflect the relevance of the question or the outcome. One should never forget that every maneuver entails adverse events that, when serious, discredit good results. It is imperative to have the possible answer estimated from within the structure of the question. The function of clinical research is to corroborate or reject a hypothesis, rather than to empirically test to find out what the outcome is.

La formulación de una pregunta de investigación clínica requiere la concurrencia de experiencia clínica y conocimiento en metodología y estadística. Inicialmente, la pregunta de investigación debe contar con una estructura que deje claro qué se busca (consecuencia o desenlace), en quién (estado basal) y por acción de qué (maniobra). Posteriormente, su argumentación debe explorar cuatro aspectos: factibilidad y sensatez del cuestionamiento, ausencia de respuesta previa, relevancia de la respuesta a obtener y aplicabilidad. Una vez que estos aspectos han sido cubiertos en forma satisfactoria puede considerarse que la pregunta es "clínicamente relevante", que es diferente a significancia estadística (la probabilidad de que el resultado se deba al azar y que no refleja la relevancia de la pregunta ni de los resultados). Nunca se debe olvidar que toda maniobra conlleva eventos adversos, que cuando son graves demeritan los buenos resultados. Es imperativo estimar la posible respuesta desde la estructura de la pregunta; la función de la investigación clínica es corroborar o rechazar una hipótesis, no probar empíricamente para ver qué resulta.

De vuelta a la clínica: sin justificación no existe pregunta de investigación que valga / Back to the clinic: without justification there is no worthwhile research question

Resumen La formulación de una pregunta de investigación clínica requiere la concurrencia de experiencia clínica y conocimiento en metodología y estadística. Inicialmente, la pregunta de investigación debe contar con una estructura que deje claro qué se busca (consecuencia o desenlace), en quién (estado basal) y por acción de qué (maniobra). Posteriormente, su argumentación debe explorar cuatro aspectos: factibilidad y sensatez del cuestionamiento, ausencia de respuesta previa, relevancia de la respuesta a obtener y aplicabilidad. Una vez que estos aspectos han sido cubiertos en forma satisfactoria puede considerarse que la pregunta es "clínicamente relevante", que es diferente a significancia estadística (la probabilidad de que el resultado se deba al azar y que no refleja la relevancia de la pregunta ni de los resultados). Nunca se debe olvidar que toda maniobra conlleva eventos adversos, que cuando son graves demeritan los buenos resultados. Es imperativo estimar la posible respuesta desde la estructura de la pregunta; la función de la investigación clínica es corroborar o rechazar una hipótesis, no probar empíricamente para ver qué resulta.

Abstract A clinical research question requires the concurrence of clinical experience and knowledge on methodology and statistics in that who formulates it. Initially, a research question should have a structure that clearly establishes what is that which is being sought (consequence or outcome), in whom (baseline status), and by action of what (maneuver). Subsequently, its reasoning must explore four aspects: feasibility and reasonableness of the questioning, lack of a prior answer, relevance of the answer to be obtained, and applicability. Once these aspects are satisfactorily covered, the question can be regarded as being "clinically relevant", which is different from being statistically significant, which refers to the probability of the result being driven by chance, which does not reflect the relevance of the question or the outcome. One should never forget that every maneuver entails adverse events that, when serious, discredit good results. It is imperative to have the possible answer estimated from within the structure of the question. The function of clinical research is to corroborate or reject a hypothesis, rather than to empirically test to find out what the outcome is.

Clinical practice guidelines for the treatment of systemic lupus erythematosus by the Mexican College of Rheumatology. / Guía de práctica clínica para el manejo del lupus eritematoso sistémico propuesta por el Colegio Mexicano de Reumatología.

There are national and international clinical practice guidelines for systemic lupus erythematosus treatment. Nonetheless, most of them are not designed for the Mexican population or are devoted only to the treatment of certain disease manifestations, like lupus nephritis, or are designed for some physiological state like pregnancy. The Mexican College of Rheumatology aimed to create clinical practice guidelines that included the majority of the manifestations of systemic lupus erythematosus, and also incorporated guidelines in controversial situations like vaccination and the perioperative period. The present document introduces the «Clinical Practice Guidelines for the Treatment of Systemic Lupus Erythematosus¼ proposed by the Mexican College of Rheumatology, which could be useful mostly for non-rheumatologist physicians who need to treat patients with systemic lupus erythematosus without having the appropriate training in the field of rheumatology. In these guidelines, the reader will find recommendations on the management of general, articular, kidney, cardiovascular, pulmonary, neurological, hematologic and gastrointestinal manifestations, and recommendations on vaccination and treatment management during the perioperative period.

[List of Ethical Principles for Medical Research Involving Human Subjects]. / Lista para Aspectos Éticos de Investigaciones en Humanos.

The ethical principles of a research proposal are not contained only in a paragraph or in the informed consent form; actually, they are an essential part of the whole protocol from the beginning to the end. In a complementary manner to the regulatory and educative documents, our objective in this article is to propose a checklist of questions so researches can ensure they have included the necessary information and precautions to meet the ethical considerations that are required for every research with human beings, which shall be called List of Ethical Principles for Medical Research Involving Human Subjects. We propose questions that researchers must ask themselves when they compose the background, justification, objectives, research question, hypothesis, selection criteria, sample size calculation, sampling, research design, statistical analysis plan, ethical aspects, publication plan, and references.

Los aspectos éticos de una propuesta de investigación no están contenidos solamente en un apartado y en el formulario de consentimiento informado, en realidad forman parte esencial de todo el protocolo desde el inicio hasta el final. De manera complementaria a los documentos regulatorios y educativos, el objetivo en este artículo es proponer una lista de cotejo de preguntas para que el investigador pueda asegurarse de haber incluido la información y elementos necesarios para cumplir con los aspectos éticos que toda investigación con seres humanos demanda, a la cual llamaremos LAEIH (Lista para Aspectos Éticos de Investigaciones en Humanos). Proponemos preguntas que deben hacerse los investigadores al redactar los antecedentes, la justificación, objetivos, pregunta de investigación, hipótesis, criterios se selección, cálculo de tamaño de muestra, muestreo, diseño de investigación, plan de análisis estadístico, aspectos éticos, plan de publicación y referencias.

Current state of biosimilars in Mexico: The position of the Mexican College of Rheumatology, 2016. / Escenario actual de los medicamentos biocomparables en México: posicionamiento del Colegio Mexicano de Reumatología, 2016.

The present document is a position statement of the Mexican College of Rheumatology on the use of biosimilars in rheumatic diseases. This position considers that biosimilars should be considered as interchangeable, that automatic substitution without previous notice in stable patients during follow-up is not ethical, that the approval of a biosimilar should only be given after exhaustive review of preclinical and clinical data marked by Mexican regulations, that it should be clearly stated in the nomenclature of biologic drugs which is the innovator and which is the biosimilar, that it is not correct to choose a biosimilar as treatment based only on economic reasons or extrapolate indications based only on the approval of the innovator and in the absence of safety and efficacy data for the biosimilar.

[Clinical research XXIII. From clinical judgment to meta-analyses]. / Investigación clínica XXIII. Del juicio clínico a los metaanálisis.

Systematic reviews (SR) are studies made in order to ask clinical questions based on original articles. Meta-analysis (MTA) is the mathematical analysis of SR. These analyses are divided in two groups, those which evaluate the measured results of quantitative variables (for example, the body mass index -BMI-) and those which evaluate qualitative variables (for example, if a patient is alive or dead, or if he is healing or not). Quantitative variables generally use the mean difference analysis and qualitative variables can be performed using several calculations: odds ratio (OR), relative risk (RR), absolute risk reduction (ARR) and hazard ratio (HR). These analyses are represented through forest plots which allow the evaluation of each individual study, as well as the heterogeneity between studies and the overall effect of the intervention. These analyses are mainly based on Student's t test and chi-squared. To take appropriate decisions based on the MTA, it is important to understand the characteristics of statistical methods in order to avoid misinterpretations.

Las revisiones sistemáticas (RS) son estudios que intentan contestar una pregunta clínica por medio del uso de artículos originales. Los metaanálisis (MTA) son el análisis matemático de las revisiones sistemáticas. Estos análisis se dividen en dos grandes grupos: aquellos que evalúan los resultados medidos como variables cuantitativas (por ejemplo, el índice de masa corporal ­IMC­) y aquellos que evalúan variables cualitativas (por ejemplo, si un paciente está vivo o muerto, o si ha mejorado o no de su enfermedad). Los primeros utilizan en general la diferencia de medias. Para los segundos se puede utilizar el cálculo de razón de momios (RM) u odds ratio (OR), riesgo relativo (RR), reducción absoluta del riesgo (RAR), hazard ratio (HR), etcétera. Estos análisis se grafican por medio de forest plots que permiten tanto la evaluación individual de los estudios como la del resultado final, así como la heterogenidad de estas comparaciones. Asimismo, estos análisis se basan en análisis estadísticos básicos como la t de Student y la chi cuadrada. Para la toma de decisiones basadas en las RS y en los MTA, es importante evaluar cuidadosamente los posibles sesgos y los apartados estadísticos con el fin evitar malas interpretaciones.