Impacto de la pandemia por SARS-CoV-2 en el índice de masa corporal de niños asistidos en la Ciudad Autónoma de Buenos Aires / Impact of the SARS-CoV-2 pandemic on the body mass index of children seen in the City of Buenos Aires

Introducción. El sobrepeso y la obesidad infantil constituyen un problema de salud pública. El inicio de la pandemia por COVID-19 pudo haber favorecido esta patología. El puntaje Z del índice de masa corporal (Z-IMC) es un indicador aceptado para su diagnóstico y seguimiento. Objetivo. Evaluar si la prevalencia de sobrepeso y obesidad, y el Z-IMC en niños de 2 a 5 años aumentó durante la pandemia. Población y métodos. Estudio de cohorte retrospectiva. Se incluyeron pacientes asistidos en efectores públicos de salud del Gobierno de la Ciudad Autónoma de Buenos Aires (GCABA), de 2 a 5 años de edad, con registro de peso y talla en dos consultas, antes y después de haber comenzado el aislamiento social preventivo y obligatorio (ASPO). Se registró estado nutricional (Z-IMC) y variación del Z-IMC entre ambas consultas. Resultados. Se evaluaron 3866 sujetos, edad promedio 3,4 ± 0,8 años; el 48,1 % fueron mujeres. El intervalo promedio entre consultas fue 14,3 ± 2,5 meses. La prevalencia de sobrepeso/obesidad aumentó del 12,6 % (IC95% 11,6-13,6) al 20,9 % (IC95% 19,6-22-2); p <0,001, al igual que el Z-IMC (0,4 ± 1,1 vs. 0,8 ± 1,3; p <0,001). Conclusión. La prevalencia de sobrepeso y obesidad, y el Z-IMC en niños de 2 a 5 años aumentó significativamente durante la pandemia.

Introduction. Childhood overweight and obesity are a public health problem. The onset of the COVID-19 pandemic may have contributed to this condition. The body mass index (BMI) Z-score has been accepted as an indicator for overweight and obesity diagnosis and follow-up. Objective. To assess whether the prevalence of overweight and obesity and the BMI Z-score in children aged 2 to 5 years increased during the pandemic. Population and methods. Retrospective, cohort study. Patients included were those seen at public health care facilities in the City of Buenos Aires (CABA), who were aged 2 to 5 years, had weight and height values recorded at 2 different visits, before and after the establishment of the preventive and mandatory social isolation policy. Patients' nutritional status (BMI Z-score) and the variation in this indicator between both visits were recorded. Results. A total of 3866 subjects were assessed; their average age was 3.4 ± 0.8 years; 48.1% were girls. The average interval between both visits was 14.3 ± 2.5 months. The prevalence of overweight/ obesity increased from 12.6% (95% CI: 11.6­13.6) to 20.9% (95% CI: 19.6­22.2), p < 0.001, and so did the BMI Z-score (0.4 ± 1.1 versus 0.8 ± 1.3, p < 0.001). Conclusion. The prevalence of overweight and obesity and the BMI Z-score in children aged 2 to 5 years increased significantly during the pandemic.

Impact of the SARS-CoV-2 pandemic on the body mass index of children seen in the City of Buenos Aires. / Impacto de la pandemia por SARS-CoV-2 en el índice de masa corporal de niños asistidos en la Ciudad Autónoma de Buenos Aires.

Introduction. Childhood overweight and obesity are a public health problem. The onset of the COVID-19 pandemic may have contributed to this condition. The body mass index (BMI) Z-score has been accepted as an indicator for overweight and obesity diagnosis and follow-up. Objective. To assess whether the prevalence of overweight and obesity and the BMI Z-score in children aged 2 to 5 years increased during the pandemic. Population and methods. Retrospective, cohort study. Patients included were those seen at public health care facilities in the City of Buenos Aires (CABA), who were aged 2 to 5 years, had weight and height values recorded at 2 different visits, before and after the establishment of the preventive and mandatory social isolation policy. Patients' nutritional status (BMI Z-score) and the variation in this indicator between both visits were recorded. Results. A total of 3866 subjects were assessed; their average age was 3.4 ± 0.8 years; 48.1% were girls. The average interval between both visits was 14.3 ± 2.5 months. The prevalence of overweight/ obesity increased from 12.6% (95% CI: 11.6-13.6) to 20.9% (95% CI: 19.6-22.2), p < 0.001, and so did the BMI Z-score (0.4 ± 1.1 versus 0.8 ± 1.3, p < 0.001). Conclusion. The prevalence of overweight and obesity and the BMI Z-score in children aged 2 to 5 years increased significantly during the pandemic.

Introducción. El sobrepeso y la obesidad infantil constituyen un problema de salud pública. El inicio de la pandemia por COVID-19 pudo haber favorecido esta patología. El puntaje Z del índice de masa corporal (Z-IMC) es un indicador aceptado para su diagnóstico y seguimiento. Objetivo. Evaluar si la prevalencia de sobrepeso y obesidad, y el Z-IMC en niños de 2 a 5 años aumentó durante la pandemia. Población y métodos. Estudio de cohorte retrospectiva. Se incluyeron pacientes asistidos en efectores públicos de salud del Gobierno de la Ciudad Autónoma de Buenos Aires (GCABA), de 2 a 5 años de edad, con registro de peso y talla en dos consultas, antes y después de haber comenzado el aislamiento social preventivo y obligatorio (ASPO). Se registró estado nutricional (Z-IMC) y variación del Z-IMC entre ambas consultas. Resultados. Se evaluaron 3866 sujetos, edad promedio 3,4 ± 0,8 años; el 48,1 % fueron mujeres. El intervalo promedio entre consultas fue 14,3 ± 2,5 meses. La prevalencia de sobrepeso/obesidad aumentó del 12,6 % (IC95% 11,6-13,6) al 20,9 % (IC95% 19,6-22-2); p <0,001, al igual que el Z-IMC (0,4 ± 1,1 vs. 0,8 ± 1,3; p <0,001). Conclusión. La prevalencia de sobrepeso y obesidad, y el Z-IMC en niños de 2 a 5 años aumentó significativamente durante la pandemia.

Waiting for the next winter. Outpatient pediatric visits for respiratory infections before, during, and after the COVID-19 pandemic in the city of Buenos Aires.

INTRODUCTION: During the COVID-19 pandemic, pediatric visits due to acute lower respiratory infections (ALRIs) decreased, but most reports are from hospitalized patients. There is little information on this phenomenon in outpatients, who are the majority in ALRI. We evaluated the impact of the COVID-19 pandemic on ALRI-related outpatient visits in the City of Buenos Aires. METHODS: Observational study including all outpatient visits of children under 2 years of age to the public health system of the City of Buenos Aires, between 1 January 2018 and 31 December 2022. We analyzed the total number of visits and the ALRI-related visits, and their distribution throughout the study period. RESULTS: A total of 704,426 visits were registered, 7.38% of them due to ALRI. ALRI-related visits decreased from the implementation of a national lockdown (2020) and increased again as the restriction measures decreased, particularly the return to full school attendance (2021). In general, the proportion of ALRI-related visits was significantly higher in the cold months than in the warm ones (9.8% vs. 5.5%; odds ratio: 1.76, 95% confidence interval: 1.73-1.79; p < .001). This difference was observed before (2018 and 2019) and after the pandemic (2022), but not in 2020-2021. The peak of ALRI-related visits occurred in the cold months in pre-pandemic years (2018-2019), did not appear in 2020, reappeared delayed in 2021, and recovered seasonality in 2022. CONCLUSION: Outpatient ALRI-related visits decreased significantly in the city of Buenos Aires during the COVID-19 pandemic and currently seem to have recovered their magnitude and seasonality.

Sobreuso de ecografía transvaginal en un hospital universitario privado de Argentina: estudio de corte transversal / Transvaginal ultrasound overuse in a private university hospital in Argentina: a cross-sectional study

Introducción. Si bien contamos con recomendaciones basadas en la evidencia en contra de realizar tamizaje de cáncer ovárico con ecografía transvaginal debido a que aumenta el riesgo de resultados falsamente positivos y de cascadas diagnósticas, sin disminuir la mortalidad por esta enfermedad, su solicitud en mujeres sanas es frecuente. Sin embargo, no conocemos la magnitud de la implementación de esta práctica, que constituye un cuidado de bajo valor. Objetivo. Documentar el sobreuso de ecografías transvaginales realizadas en forma ambulatoria en un hospital universitario privado de Argentina. Métodos. Estudio de corte transversal de una muestra aleatoria de ecografías realizadas en forma ambulatoria durante 2017 y 2018. Mediante revisión manual de las historias clínicas, la solicitud de cada ecografía fue clasificada como apropiada cuando algún problema clínico justificaba su realización, o inapropiada cuando había sido realizada con fines de control de salud o por una condición clínica sin indicación de seguimiento ecográfico. Resultados. De un total de 1.997 ecografías analizadas, realizadas a 1.954 mujeres adultas (edad promedio 50 años),1.345 (67,4 %; intervalo de confianza [IC] 95 % 65,2 a 69,4) habían sido solicitadas en el contexto de un control de saludo sin un problema asociado en la historia clínica y otras 54 (8,3 %; IC 95 % 6,3 a 10,7), por condiciones de salud para las que no hay recomendaciones de realizar seguimiento ecográfico. Conclusiones. Esta investigación documentó una alta proporción de sobre utilización de la ecografías transvaginales en nuestra institución. Futuras investigaciones permitirán comprender los motivos que impulsan esta práctica y ayudarán a diseñar intervenciones para disminuir estos cuidados de bajo valor. (AU)

Background. Although we have evidence-based recommendations against screening for ovarian cancer with transvaginalultrasound because it increases the risk of false positive results and diagnostic cascades without reducing mortality from this disease, its request in healthy women is frequent. However, we do not know the magnitude of the implementation of this practice, which constitutes low-value care. Objective. To document the overuse of transvaginal ultrasounds performed on an outpatient basis in a private university hospital in Argentina. Methods. Cross-sectional study of a random sample of outpatient ultrasounds performed during 2017 and 2018. Through a manual review of the medical records, the request for each ultrasound was classified as appropriate when a clinical problem justified its performance or inappropriate when it was carried out for health control purposes or for a clinical condition that had no indication for ultrasound follow-up. Results. Of a total of 1997 ultrasounds analyzed, performed on 1954 adult women (average age 50 years), 1,345 (67.4 %;95 % confidence interval [CI] 65.2 to 69.4) had been requested in the context of a health check-up or without a documented problem in the medical history that would support its performance, and another 54 (8.3 %; 95 % CI 6.3 to 10.7), for health conditions for which there are no treatment recommendations to perform ultrasound follow-up. Conclusions. This research documented a high proportion of overuse of transvaginal ultrasound in our institution. Future research will allow us to understand the reasons that drive this practice and will help design interventions to reduce thislow-value care. (AU)

Impacto de la contaminación ambiental en las consultas por enfermedad respiratoria en niños menores de 2 años.

Introducción: La contaminación del aire incrementaría el riesgo de infección respiratoria aguda (IRA) en pediatría. Objetivo: evaluar el impacto de la contaminación del aire en las consultas por IRA realizadas en efectores del Gobierno de la Ciudad de Buenos Aires. Método: estudio ecológico, de series temporales. Fuentes de información: Agencia de Protección Ambiental, Servicio Meteorológico Nacional e Historia de Salud Integral del Sistema de Gestión Hospitalaria. Población: Pacientes menores de 2 años que consultaron por IRA a un efector del GCBA y que residían en una comuna con monitoreo ambiental continuo, durante el 2018. Variables de predicción: Niveles diarios de CO, NO2, PM10 de las estaciones de monitoreo ambiental continuo de la Ciudad Autónoma de Buenos Aires. Variables de resultado: número de consultas totales y por IRA. Variables a controlar: efector, sexo y temperatura media. Se construyó una definición operativa para seleccionar en la base de datos a las consultas objeto de estudio. Resultados: Se registraron 80.287 consultas, 24.847 por IRA (30%). Las consultas por IRA tuvieron correlación positiva en la estación "Córdoba" con el N2O (RR: 1,13 [1,00-1,28]). El número de consultas por IRA en los meses fríos fue mayor que en los cálidos (19,9% vs 11,9%; RR:1,67 [1,61-1,72]). Conclusión: Los valores promedios de PM10 y N2O muestran correlación con el número de las consultas totales y por infección respiratoria aguda, respectivamente. Las consultas se incrementaron durante el invierno.

Acute respiratory health effects of air pollution on consultations in children under 2 years old / [Impacto de la contaminación ambiental en las consultas por enfermedad respiratoria en niños menores de 2 años.]

Introduction: Air pollution would increase the risk of severe infection repiratory in pediatrics. Research Sources: Environmental Protection Agency, National Meteorological. Service and Integral Health History of the Hospital Management System. Population: Patients under 2 years old who consulted for severe infection repiratory in effectors of Buenos Aires City Government and lived commune with continuous environmental monitoring during 2018. Predictors were daily levels of air pollutants (carbon monoxide, nitrous dioxide, particulate matter < 10 µ). Pollutants were measured at three monitoring stations. Temporal variables (media temperature), sex and effector were controlled. Result Variable: Total numbers of visits and total numbers of visits for severe infection respiratory. To select in the data base the visits to analyze an operative definition was made. Objective: Review impact of air pollution visits for severe infection repiratory in effectors of Buenos Aires City Government. Method: Ecologic research, time-series. Results: 80.287 visits were registered, 24.847 for severe infection respiratory (30%). The visits for severe infection respiratory had positive correlation in Cordoba station with N2O (RR: 1,13 [1,00-1,28]). The numbers of visits for severe infection respiratory was higher during cold months than warm months. (19,9% vs 11,9%; RR:1,67 [1,61-1,72]). Conclusion: average values of PM10 and N2O show correlation with the numbers of total visits and visits for severe infection respiratory. The visits increase during winter.

Introducción: La contaminación del aire incrementaría el riesgo de infección respiratoria aguda (IRA) en pediatría. Objetivo: evaluar el impacto de la contaminación del aire en las consultas por IRA realizadas en efectores del Gobierno de la Ciudad de Buenos Aires. Método: Estudio ecológico, de series temporales. Fuentes de información: Agencia de Protección Ambiental, Servicio Meteorológico Nacional e Historia de Salud Integral del Sistema de Gestión Hospitalaria. Población: Pacientes menores de 2 años que consultaron por IRA a un efector del GCBA y que residían en una comuna con monitoreo ambiental continuo, durante el 2018. Variables de predicción: Niveles diarios de CO, NO2, PM10 de las estaciones de monitoreo ambiental continuo de la Ciudad Autónoma de Buenos Aires. Variables de resultado: número de consultas totales y por IRA. Variables a controlar: efector, sexo y temperatura media. Se construyó una definición operativa para seleccionar en la base de datos a las consultas objeto de estudio. Resultados: Se registraron 80.287 consultas, 24.847 por IRA (30%). Las consultas por IRA tuvieron correlación positiva en la estación "Córdoba" con el N2O (RR: 1,13 [1,00-1,28]). El número de consultas por IRA en los meses fríos fue mayor que en los cálidos (19,9% vs 11,9%; RR:1,67 [1,61-1,72]). Conclusión: Los valores promedios de PM10 y N2O muestran correlación con el número de las consultas totales y por infección respiratoria aguda, respectivamente. Las consultas se incrementaron durante el invierno.

Quantitative and qualitative analysis of Argentine breast cancer prevention campaigns disseminated by still images on social networks during October 2019. / Análisis cuantitativo y cualitativo de las campañas argentinas de prevención de cáncer de mama difundidas mediante imágenes fijas en redes sociales durante octubre del 2019.

OBJECTIVES: To quantitatively document the degree of compliance of institutional messages broadcast on social networks with the recommendations of the National Cancer Institute (INC) in Argentina during October 2019, in the context of breast cancer prevention campaigns, and to qualitatively analyze the pictorial and textual elements that make up their dissemination pieces. MATERIALS AND METHODS: Quantitative and qualitative analysis of 171 dissemination pieces issued during October 2019 by 54 institutions, based on the evaluation of their compliance with INC recommendations, the description of the main discordant recommendations (quantitative analysis) and the qualitative analysis of 30 pieces. RESULTS: None of the issued messages mentioned potential screening harms. Only the messages of the National Ministry of Health complied completely with the INC recommendations, while the remaining ones recommended mammograms at younger ages or at shorter intervals. Breast self-examination was the most frequent recommendation among those who didn't comply. The images of female bodies linked to common stereotypes of sex and beauty, and paternalistic discourses appealing to fear and guilt were predominant. CONCLUSIONS: The messages broadcasted in the analyzed diffusion pieces did not comply with the INC recommendations, despite the fact that the latter are supported by scientific evidence. On the other hand, the messages reinforce sex and beauty stereotypes, guilt and the medical-hegemonic model.

OBJETIVOS.: Documentar cuantitativamente el grado de concordancia con las recomendaciones del Instituto Nacional del Cáncer (INC) de los mensajes institucionales emitidos en redes sociales de Argentina durante octubre de 2019, en el contexto de las campañas de prevención del cáncer mamario, y analizar cualitativamente los elementos icónicos y textuales que conforman sus piezas de difusión. MATERIALES Y MÉTODOS.: Análisis cuantitativo y cualitativo de 171 piezas de difusión emitidas durante octubre de 2019 por 54 instituciones, a partir de la evaluación de su concordancia con las recomendaciones del INC, la descripción de las principales recomendaciones discordantes (análisis cuantitativo) y el análisis cualitativo de 30 piezas. RESULTADOS.: Ninguno de los mensajes emitidos mencionó potenciales daños del tamizaje. Solamente los del Ministerio de Salud de la Nación fueron totalmente concordantes con las recomendaciones del INC, mientras que los restantes recomendaban realizar mamografías a edades más tempranas o a intervalos más breves. El autoexamen mamario fue la recomendación más frecuente entre las discordantes. Predominaron las imágenes de cuerpos femeninos vinculadas con los estereotipos predominantes de género y belleza, y los discursos paternalistas que apelan al miedo y a la culpa. CONCLUSIONES.: Los mensajes emitidos en las piezas de difusión analizadas no fueron concordantes con las recomendaciones del INC, a pesar de que estas últimas están respaldadas por evidencia científica. Por otro lado, los mensajes refuerzan los estereotipos de género y belleza, la culpa y el modelo médico-hegemónico.

Análisis cuantitativo y cualitativo de las campañas argentinas de prevención de cáncer de mama difundidas mediante imágenes fijas en redes sociales durante octubre del 2019 / Quantitative and qualitative analysis of Argentine breast cancer prevention campaigns disseminated by still images on social networks during October 2019

Objetivos. Documentar cuantitativamente el grado de concordancia con las recomendaciones del Instituto Nacional del Cáncer (INC) de los mensajes institucionales emitidos en redes sociales de Argentina durante octubre de 2019, en el contexto de las campañas de prevención del cáncer mamario, y analizar cualitativamente los elementos icónicos y textuales que conforman sus piezas de difusión. Materiales y métodos. Análisis cuantitativo y cualitativo de 171 piezas de difusión emitidas durante octubre de 2019 por 54 instituciones, a partir de la evaluación de su concordancia con las recomendaciones del INC, la descripción de las principales recomendaciones discordantes (análisis cuantitativo) y el análisis cualitativo de 30 piezas. Resultados. Ninguno de los mensajes emitidos mencionó potenciales daños del tamizaje. Solamente los del Ministerio de Salud de la Nación fueron totalmente concordantes con las recomendaciones del INC, mientras que los restantes recomendaban realizar mamografías a edades más tempranas o a intervalos más breves. El autoexamen mamario fue la recomendación más frecuente entre las discordantes. Predominaron las imágenes de cuerpos femeninos vinculadas con los estereotipos predominantes de género y belleza, y los discursos paternalistas que apelan al miedo y a la culpa. Conclusiones. Los mensajes emitidos en las piezas de difusión analizadas no fueron concordantes con las recomendaciones del INC, a pesar de que estas últimas están respaldadas por evidencia científica. Por otro lado, los mensajes refuerzan los estereotipos de género y belleza, la culpa y el modelo médico-hegemónico.

Objectives. To quantitatively document the degree of compliance of institutional messages broadcast on social networks with the recommendations of the National Cancer Institute (INC) in Argentina during October 2019, in the context of breast cancer prevention campaigns, and to qualitatively analyze the pictorial and textual elements that make up their dissemination pieces. Materials and methods. Quantitative and qualitative analysis of 171 dissemination pieces issued during October 2019 by 54 institutions, based on the evaluation of their compliance with INC recommendations, the description of the main discordant recommendations (quantitative analysis) and the qualitative analysis of 30 pieces. Results. None of the issued messages mentioned potential screening harms. Only the messages of the National Ministry of Health complied completely with the INC recommendations, while the remaining ones recommended mammograms at younger ages or at shorter intervals. Breast self-examination was the most frequent recommendation among those who didn't comply. The images of female bodies linked to common stereotypes of sex and beauty, and paternalistic discourses appealing to fear and guilt were predominant. Conclusions. The messages broadcasted in the analyzed diffusion pieces did not comply with the INC recommendations, despite the fact that the latter are supported by scientific evidence. On the other hand, the messages reinforce sex and beauty stereotypes, guilt and the medical-hegemonic model.

An algorithm for identifying visits due to pediatric lower acute respiratory infections in electronic clinical records. / [Algoritmo para identificación de consultas por infección respiratoria aguda baja en pediatría en registros clínicos electrónicos.]

Background: Due to ambiguities in terminology, acute lower respiratory infections (ALRI) in childhood are frequently not properly recorded, especially during outpatient visits. A tool that accurately identifies them, would assess the impact on respiratory health of massive harms, and design policies to prevent or mitigate their effects. We aimed to design an algorithm that allows identifying children with ALRI based on data from the electronic clinical record (ECR) of the Government of the City of Buenos Aires (GCBA). Methods: From the ECR-GCBA database, we randomly selected 1000 outpatient visits of patients aged under 2 years. Terms showing that the visit was due to LARI were searched using an algorithm based on hard rules. Another dataset including 800 visits was used to adjust the algorithm and, finally, its performance was tested in a third dataset of 800 queries corresponding to the entire year 2018. Results: In the validation set, our tool identified LARI with sensitivity 88.24%, specificity 97.5%, PPV 86.07% and NPV 97.93%. Conclusion: Our search algorithm allows us to identify with acceptable precision the outpatient visits related to LARI in children under 2 years of age from electronic clinical records.

Introducción: Debido a ambigüedades en la nomenclatura, las infecciones respiratorias agudas bajas (IRAB) en la infancia frecuentemente no son debidamente registradas, especialmente durante las consultas ambulatorias. Contar con una herramienta que las identifique con precisión, permitirá evaluar el impacto en la salud respiratoria de noxas de alcance masivo y diseñar las políticas para prevenirlas o mitigar sus efectos. Nuestro objetivo fue construir un algoritmo que permita identificar niños con IRAB a partir de los datos de la historia clínica electrónica (HCE) del Gobierno de la Ciudad de Buenos Aires (GCBA). Métodos: Utilizando la HCE-GCBA, se seleccionaron aleatoriamente 1000 consultas ambulatorias de pacientes menores de 2 años. Se buscaron términos que hicieran referencia a que la consulta era motivada por IRAB, con los que se desarrolló un algoritmo basado en reglas duras. Se utilizó otro set de datos de 800 consultas para ajustar el algoritmo y, finalmente, se validó su desempeño en un tercer set de 800 consultas correspondientes a todo el año 2018. Resultados: En el set de validación, la herramienta desarrollada identificó IRAB con sensibilidad 88,24%, especificidad 97,5%, VPP 86,07% y VPN 97,93%. Conclusión: El algoritmo de búsqueda desarrollado permite identificar con aceptable precisión las consultas ambulatorias relacionadas con IRAB en niños menores de 2 años.

Lower Respiratory Tract Infections in Children, Weather and Google Search Trends.

This is an exploratory study on different variables known to be associated with epidemiological outbreaks of lower respiratory tract infections in children under 2 years raised to identify patterns and potential predictors for making strategic decisions in terms of strengthening health teams in periods of greatest demand.

Development and validation of various phenotyping algorithms for Diabetes Mellitus using data from electronic health records.

BACKGROUND AND OBJECTIVE: Recent progression towards precision medicine has encouraged the use of electronic health records (EHRs) as a source for large amounts of data, which is required for studying the effect of treatments or risk factors in more specific subpopulations. Phenotyping algorithms allow to automatically classify patients according to their particular electronic phenotype thus facilitating the setup of retrospective cohorts. Our objective is to compare the performance of different classification strategies (only using standardized problems, rule-based algorithms, statistical learning algorithms (six learners) and stacked generalization (five versions)), for the categorization of patients according to their diabetic status (diabetics, not diabetics and inconclusive; Diabetes of any type) using information extracted from EHRs. METHODS: Patient information was extracted from the EHR at Hospital Italiano de Buenos Aires, Buenos Aires, Argentina. For the derivation and validation datasets, two probabilistic samples of patients from different years (2005: n = 1663; 2015: n = 800) were extracted. The only inclusion criterion was age (≥40 & <80 years). Four researchers manually reviewed all records and classified patients according to their diabetic status (diabetic: diabetes registered as a health problem or fulfilling the ADA criteria; non-diabetic: not fulfilling the ADA criteria and having at least one fasting glycemia below 126 mg/dL; inconclusive: no data regarding their diabetic status or only one abnormal value). The best performing algorithms within each strategy were tested on the validation set. RESULTS: The standardized codes algorithm achieved a Kappa coefficient value of 0.59 (95% CI 0.49, 0.59) in the validation set. The Boolean logic algorithm reached 0.82 (95% CI 0.76, 0.88). A slightly higher value was achieved by the Feedforward Neural Network (0.9, 95% CI 0.85, 0.94). The best performing learner was the stacked generalization meta-learner that reached a Kappa coefficient value of 0.95 (95% CI 0.91, 0.98). CONCLUSIONS: The stacked generalization strategy and the feedforward neural network showed the best classification metrics in the validation set. The implementation of these algorithms enables the exploitation of the data of thousands of patients accurately.

A rule-based electronic phenotyping algorithm for detecting clinically relevant cardiovascular disease cases.

BACKGROUND: The implementation of electronic medical records (EMR) is becoming increasingly common. Error and data loss reduction, patient-care efficiency increase, decision-making assistance and facilitation of event surveillance, are some of the many processes that EMRs help improve. In addition, they show a lot of promise in terms of data collection to facilitate observational epidemiological studies and their use for this purpose has increased significantly over the recent years. Even though the quantity and availability of the data are clearly improved thanks to EMRs, still, the problem of the quality of the data remains. This is especially important when attempting to determine if an event has actually occurred or not. We sought to assess the sensitivity, specificity, and agreement level of a codes-based algorithm for the detection of clinically relevant cardiovascular (CaVD) and cerebrovascular (CeVD) disease cases, using data from EMRs. METHODS: Three family physicians from the research group selected clinically relevant CaVD and CeVD terms from the international classification of primary care, Second Edition (ICPC-2), the ICD 10 version 2015 and SNOMED-CT 2015 Edition. These terms included both signs, symptoms, diagnoses and procedures associated with CaVD and CeVD. Terms not related to symptoms, signs, diagnoses or procedures of CaVD or CeVD and also those describing incidental findings without clinical relevance were excluded. The algorithm yielded a positive result if the patient had at least one of the selected terms in their medical records, as long as it was not recorded as an error. Else, if no terms were found, the patient was classified as negative. This algorithm was applied to a randomly selected sample of the active patients within the hospital's HMO by 1/1/2005 that were 40-79 years old, had at least one year of seniority in the HMO and at least one clinical encounter. Thus, patients were classified into four groups: (1) Negative patients (2) Patients with CaVD but without CeVD; (3) Patients with CeVD but without disease CaVD; (4) Patients with both diseases. To facilitate the validation process, a stratified sample was taken so that each of the groups represented approximately 25% of the sample. Manual chart review was used as the gold standard for assessing the algorithm's performance. One-third of the patients were assigned randomly to each reviewer (Cohen's kappa 0.91). Both coded and un-coded (free text) sections of the EMR were reviewed. This was done from the first present clinical note in the patients chart to the last one registered prior to 1/1/2005. RESULTS: The performance of the algorithm was compared against manual chart review. It yielded high sensitivity (0.99, 95% CI 0.938-0.9971) and acceptable specificity (0.86, 95% CI 0.818-0.895) for detecting cases of CaVD and CeVD combined. A qualitative analysis of the false positives and false negatives was performed. CONCLUSIONS: We developed a simple algorithm, using only standardized and non-standardized coded terms within an EMR that can properly detect clinically relevant events and symptoms of CaVD and CeVD. We believe that combining it with an analysis of the free text using an NLP approach would yield even better results.

Development and Validation of Various Phenotyping Algorithms for Diabetes Mellitus Using Data from Electronic Health Records.

Precision medicine requires extremely large samples. Electronic health records (EHR) are thought to be a cost-effective source of data for that purpose. Phenotyping algorithms help reduce classification errors, making EHR a more reliable source of information for research. Four algorithm development strategies for classifying patients according to their diabetes status (diabetics; non-diabetics; inconclusive) were tested (one codes-only algorithm; one boolean algorithm, four statistical learning algorithms and six stacked generalization meta-learners). The best performing algorithms within each strategy were tested on the validation set. The stacked generalization algorithm yielded the highest Kappa coefficient value in the validation set (0.95 95% CI 0.91, 0.98). The implementation of these algorithms allows for the exploitation of data from thousands of patients accurately, greatly reducing the costs of constructing retrospective cohorts for research.