¿Por qué los graduados en medicina no quieren ser médicos de familia? / Why do medical graduates not want to be family doctors?

Objetivo: conocer la prioridad concedida a la elección de Medicina Familiar (MF) en Castilla-La Mancha (CLM) entre los opositores MIR de 2019-2022 que escogieron plaza en esta comunidad, y los factores asociados con esta elección. Métodos: se trata de un análisis de datos secundarios. De la web del Ministerio de Sanidad, se obtuvo información de 1.223 opositores: sexo, nacionalidad, puntuación en el examen y total, número en la oposición, especialidad y provincia elegidas. El análisis estadístico se ha realizado con SPSS 25.0: estadística descriptiva, comparación de proporciones y medianas, y cálculo de la probabilidad de elección de MF relacionada con el número en la oposición (Kaplan-Meier). Resultados: el 67,4% eran mujeres; el 89% eran españoles. Un 29,1% eligieron MF. Las medianas del número para elegirla aumentó a lo largo de los años: 7.106 (rango intercuartiles [RI]: 6.993,1-7.218,9), 7.511 (RI: 7.378,2-7.643,7), 8.159 (RI: 8.036,5-8.281,5), 8.821 (RI: 8.551,2-9.090,8), respectivamente de 2019 a 2022, con diferencias estadísticamente significativas (p < 0,0001). Los valores correspondientes para el resto de especialidades no mostraron diferencias significativas entre los 4 años, pero eran significativamente inferiores (p < 0,0001) a las de MF. No existían diferencias por sexo para la elección de MF. Solo en 2020 fue más precoz la elección de MF en Albacete (p = 0,037), sin diferencias en el global de los 4 años en cuanto a la elección de provincia. Conclusión: la elección de plazas de MF en CLM se hace con números altos de la oposición MIR. En los últimos años se ha venido produciendo un progresivo retraso en dicha elección. (AU)

Aim: to ascertain the priority given to the choice of family medicine (FM) posts in Castilla-La Mancha (CLM) among resident intern competitive examination candidates in 2019 and 2022 who chose this autonomous community and the factors associated with this choice. Method: this is an analysis of secondary data. The following was obtained from the Spanish Ministry of Health website about 1223 candidates: sex, nationality, score in the examination; total, competitive examination position, specialty and province chosen. Statistical analysis was performed with SPSS 25.0: descriptive statistics, comparison of proportions and medians and probability of FM post choice related to candidate order (Kaplan-Meier). Results: a total of 67.4% were women; 89% were Spanish; 29.1% chose FM. The median number selecting FM increased over the years: 7.106 (interquartile range [IR]: 6993.1-7218.9), 7.511 (RI: 7378.2-7643.7), 8159 (RI: 8036, 5-8281.5), 8821 (RI: 8551.2-9090.8), respectively from 2019 to 2022, with statistically significant differences (P<0.0001). The corresponding values for the other specialties did not reveal any statistically significant differences among the four years. However, they were statistically significantly lower (P<0.0001) than those for FM. There were no differences by sex for choosing FM. Only in 2020 FM was chosen earlier in Albacete (P=0.037). There were no differences in the overall four-year period in regard to choice of province. Conclusion: FM posts in Castilla-La Mancha are chosen with high classification numbers from the resident intern entrance examinations. In recent years there has been a gradual delay in this choice. (AU)

Factores asociados con una evolución desfavorable en pacientes diagnosticados de COVID-19 y seguidos en atención primaria en 2020 / Factors associated with an unfavorable evolution in patients diagnosed with COVID-19 and followed up in primary care in 2020

Objetivo: Conocer los factores asociados con una evolución desfavorable (ED) de pacientes diagnosticados de COVID-19 con seguimiento total o parcial en atención primaria. Diseño: Serie de casos. Emplazamiento: Centro de salud urbano. Participantes: Pacientes de 18 o más años diagnosticados de COVID-19, con confirmación analítica, en 2020 y seguidos por sus médicos de familia, seleccionados por muestreo sistemático. Mediciones principales: Variable dependiente: ingreso en hospital o fallecimiento por COVID-19. Variables independientes: edad, sexo, antecedentes personales, y datos clínicos y de tratamiento relacionados con la enfermedad. Análisis estadístico, con SPSS 25.0: estadística descriptiva, comparación de proporciones (X2) y medianas (U de Mann-Whitney). Se completó el análisis con regresión logística. Resultados: Se incluyeron en el estudio 610 pacientes, cuya mediana de edad era de 49 años (rango intercuartiles: 35-61); 51,8% eran mujeres. Presentaron ED 14,9% (IC 95%: 12,0-17,8). Las variables sociodemográficas o relacionadas con antecedentes personales que mostraron una asociación independiente con una ED fueron edad (OR: 1,066; IC 95%:1,038-1,095), sexo (OR para hombre: 3,277; IC 95%: 1,304-8,235) y ser fumador o exfumador (OR: 2,565; IC 95%: 1,135-5,800). En cuanto a variables clínicas propias de la enfermedad, esa asociación se encontró para alteración de la conciencia (OR: 62,829; IC 95%: 9,177-430,149), disnea (OR: 14,339; IC 95%:6,046-34,009), expectoración (OR: 4,764; IC 95%: 1,858-12,213) y astenia (OR: 3,993; IC 95%: 1,705-9,351). Conclusiones: Presentaron una ED 14,9% de los pacientes diagnosticados de COVID-19. Una mayor edad, el sexo masculino y ser fumador o exfumador aumentaban la probabilidad de ED. Los datos clínicos que mejor predecían la ED fueron alteración de la conciencia, disnea, expectoración y astenia.(AU)

Aim: To know the factors associated with an unfavorable evolution (UE) of patients diagnosed with COVID-19 with total or partial follow-up in primary care. Design: A case series. Setting: Urban health center. Participants: By systematic sampling, patients ≥18 years, diagnosed with COVID-19, with analytical confirmation, in 2020 and followed up by their family doctors, were selected. Main measurements: Dependent variable: hospital admission or death due to COVID-19. Independent variables: age, sex, medical background, clinical data and treatments related to the disease. Statistical analysis, with SPSS 25.0: descriptive analysis, comparison of proportions (chi square) and medians (Mann–Whitney U). The analysis is completed with logistic regression. Results: 610 patients were included in the study. The median age was 49 years (interquartile range: 35–61); 51.8% were women; 14.9% presented UE (95% CI: 12.0–17.8). The sociodemographic variables or the variables related to medical background that showed an independent association with UE were age (OR: 1.066; 95% CI: 1.038–1.095), sex (OR for men: 3.277; 95% CI: 1.304–8.235) and being a smoker or former smoker (OR: 2.565; 95% CI: 1.135–5.800). Regarding the clinical variables of the disease, an association was found for altered consciousness (OR: 62.829; 95% CI: 9.177–430.149), dyspnea (OR: 14.339; 95% CI: 6.046–34.009), expectoration (OR: 4.764; 95% CI: 1.858-12.213)) and asthenia (OR: 3.993; 95% CI: 1.705–9.351). Conclusions: 14.9% of the patients diagnosed with COVID-19 presented an UE. Older age, male sex and being a smoker or former smoker increased the probability of it. Altered consciousness, dyspnea, expectoration, and asthenia were the clinical data that best predicted UE.(AU)

[Factors associated with an unfavorable evolution in patients diagnosed with COVID-19 and followed up in primary care in 2020]. / Factores asociados con una evolución desfavorable en pacientes diagnosticados de COVID-19 y seguidos en atención primaria en 2020.

AIM: To know the factors associated with an unfavorable evolution (UE) of patients diagnosed with COVID-19 with total or partial follow-up in primary care. DESIGN: A case series. SETTING: Urban health center. PARTICIPANTS: By systematic sampling, patients ≥18 years, diagnosed with COVID-19, with analytical confirmation, in 2020 and followed up by their family doctors, were selected. MAIN MEASUREMENTS: Dependent variable: hospital admission or death due to COVID-19. INDEPENDENT VARIABLES: age, sex, medical background, clinical data and treatments related to the disease. Statistical analysis, with SPSS 25.0: descriptive analysis, comparison of proportions (chi square) and medians (Mann-Whitney U). The analysis is completed with logistic regression. RESULTS: 610 patients were included in the study. The median age was 49 years (interquartile range: 35-61); 51.8% were women; 14.9% presented UE (95% CI: 12.0-17.8). The sociodemographic variables or the variables related to medical background that showed an independent association with UE were age (OR: 1.066; 95% CI: 1.038-1.095), sex (OR for men: 3.277; 95% CI: 1.304-8.235) and being a smoker or former smoker (OR: 2.565; 95% CI: 1.135-5.800). Regarding the clinical variables of the disease, an association was found for altered consciousness (OR: 62.829; 95% CI: 9.177-430.149), dyspnea (OR: 14.339; 95% CI: 6.046-34.009), expectoration (OR: 4.764; 95% CI: 1.858-12.213)) and asthenia (OR: 3.993; 95% CI: 1.705-9.351). CONCLUSIONS: 14.9% of the patients diagnosed with COVID-19 presented an UE. Older age, male sex and being a smoker or former smoker increased the probability of it. Altered consciousness, dyspnea, expectoration, and asthenia were the clinical data that best predicted UE.