Presión asistencial y demora en las salas de fisioterapia de atención primaria en Andalucía / Health care pressure and delay in the physiotherapy rooms of primary care in Andalucia

IntroducciónLa puesta en marcha del Plan de Apoyo de las Familias Andaluzas (Decreto 137/2002) ha supuesto una reforma bastante positiva para la fisioterapia de atención primaria (AP) en Andalucía, si bien esta ha sido lenta, irregular, con recursos insuficientes y poco homogéneos.ObjetivosConocer la variabilidad de las ratios «fisioterapeuta de AP por habitantes» en todas las salas de Andalucía, observar su influencia en los indicadores asistenciales de los que se dispone y hallar los factores de riesgo que afectan a los tiempos de espera para el inicio del tratamiento fisioterápico.Material y métodosEstudio observacional descriptivo ecológico. Periodo de estudio: primer semestre de 2008. Fuente de información: Sistema de Información para la Gestión de AP. El análisis estadístico realizado se ha valorado de acuerdo a los criterios psicométricos de escalas numéricas. Se ha utilizado análisis bivariante, regresión lineal, regresión logística y análisis multivariante.ResultadosExiste una gran variabilidad de ratio fisioterapeuta de AP por habitantes en las salas de fisioterapia de Andalucía. Se ha obtenido una ecuación que calcula la probabilidad de demora en días para el inicio de tratamiento fisioterápico de un paciente con derivación normal que depende, especialmente, de la cantidad de población asignada al fisioterapeuta de AP y de la demora que provoca la derivación de pacientes preferentes. Habiendo comprobado la relación que existe entre estas variables, parece conveniente y prioritario el incremento de los recursos humanos en las salas con ratios elevadas(AU)

IntroductionThe setting up of the ‘Supportive Plan for Andalusian Families’ (Decree 137/2002) has resulted in a very positive reform for the Andalusian Primary Health Care Physiotherapy, even though it has been slow and irregular, with deficient and not very homogeneous resources.ObjectivesTo know the variability for Primary Health Care physiotherapist/inhabitant ratio in all of the Andalusian rooms, to observe its influence on all the available care indicators, and to find the risk factors that may affect the waiting times to initiation of physiotherapy treatment.Material and methodsEcological, descriptive, observational study. Study period: first half of 2008 (January to June). Information source: Information System for Primary Health Care Management. The statistical analysis performed was carried out in accordance with psychometric criteria of numerical scales. Bivariate analysis, linear regression, logistic regression and multivariate analysis were used.ResultsThere is high variability in the Primary Health Care physiotherapist/inhabitant ratio in Andalusian physiotherapy rooms. An equation has been obtained for the calculation of the ‘days of delay probability’ until the initiation of physiotherapy for a normal-referred patient. The research shows how this probability of delay depends mainly on the total population assigned to each Primary Health Care physiotherapist, and on the delay caused by priority-referred patients. Having confirmed the relationship between these variables, increasing the human resources in those rooms with higher ratios seems to be an advisable and high priority action(AU)

[Final size attained in type 1 diabetes children]. / Talla final en diabéticos tipo 1 diagnosticados en la edad pediátrica.

OBJECTIVE: To describe the final height and height-gain in relation to target height, in children with type 1 diabetes mellitus, and analyse their relationship to different variables. PATIENTS AND METHODS: Retrospective analysis of the growth data of 52 children (27 girls) diagnosed with type 1 diabetes mellitus before 14 years old, and followed up until their final height was attained. MAIN VARIABLES: final height, target height, illness duration, glycated haemoglobin (HbA1c), insulin dose, BMI, and other autoimmune diseases. RESULTS: The height SDS (standard deviation scale) at diagnosis was slightly higher (0.734 in boys and 0.563 in girls). During the development of the disease, a growth reduction was seen, which was significantly higher in boys of prepubertal age (p = 0.016). The mean final height attained was 173.14 +/- 5.28 cm in boys and 161.9 +/- 6.97 cm in girls. Height gain was 1.56 +/- 3.66 in boys (SDS = -0.034) and 2.26 +/- 6.13 in girls (SDS = 0.385). The only variable significantly related to height gain was mean glycated-haemoglobin (growth reduction of 2 cm for every increment of 1% in mean glycated-haemoglobin). CONCLUSIONS: At onset, diabetic children were slightly taller than the general population. A growth reduction was shown as the disease developed, significantly higher in boys of prepubertal age. The final height in boys was slightly lower than the mean, but in girls was similar to the general population. Both sexes attained their target height, although the height gain was less in boys. Poorer metabolic control was associated with reduced height gain.

Design and debugging databases for statistical analysis.

Any form of data analysis requires the prior creation of a database to house the study information collected in one format or other (questionnaire, clinical history, etc.). The design of such databases should be optimised to allow adequate statistical analysis without the drawing of wrong conclusions. In addition, prior to analysis, debugging or filtering of the variables is required in order to avoid doubling the effort made in extracting the results. The present study offers a series of suggestions for database design and debugging, to ensure that the later statistical analyses are based on the revised data.

Design and debugging databases for statistical analysis

Any form of data analysis requires the prior creation of a database to house the study information collected in one format or other (questionnaire, clinical history, etc.). The design of such databases should be optimised to allow adequate statistical analysis without the drawing of wrong conclusions. In addition, prior to analysis, debugging or filtering of the variables is required in order to avoid doubling the effort made in extracting the results. The present study offers a series of suggestions for database design and debugging, to ensure that the later statistical analyses are based on the revised data (AU)

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Talla final en diabéticos tipo 1 diagnosticados en la edad pediátrica / Final size attained in type 1 diabetes children

Objetivo: describir la talla final y la ganancia sobre la talla diana, en un grupo de niños diabéticos tipo 1 y analizar su relación con distintas variables. Pacientes y métodos: estudio retrospectivo de 52 pacientes (27 mujeres) diagnosticados de diabetes tipo 1 antes de los 14 años y seguidos hasta la talla final. Variables principales: talla final, talla diana, tiempo de evolución de la diabetes, glucohemoglobina (HbA1c) media, requerimiento insulínico, índice de masa corporal, enfermedades autoinmunes asociadas. Resultados: al inicio de la diabetes la escala de desviación estándar (EDE) de talla se encontraba ligeramente por encima de la media (0,734 en varones y 0,563 en mujeres). A lo largo de la evolución se produce un pérdida de talla generalizada, más acusada en varones en etapa prepuberal (p=0,016). La talla final alcanzada fue 173,14±5,28cm en varones (EDE=−0,034) y 161,9±6,97cm en mujeres (EDE=0,385). La ganancia de talla fue 1,56±3,66cm en varones y 2,26±6,13cm en mujeres. La única variable relevante relacionada significativamente con la ganancia de talla fue la HbA1c media (pérdida de 2cm por cada aumento del 1% de HbA1c media a igualdad del resto de las variables). Conclusiones: nuestros resultados indican que, aunque al inicio de la diabetes los niños tienen una talla algo mayor que la de la población de referencia, se produce una pérdida de talla durante la evolución de la enfermedad, más acusada en varones en periodo prepuberal. Ello produce que la talla final de los varones se encuentre ligeramente por debajo de la media, mientras que las mujeres alcanzan una talla final similar a la de la población de referencia. Ambos sexos alcanzaron su talla diana, pero en varones la ganancia sobre ésta fue escasa. El mal control metabólico se relacionó con la menor ganancia de talla en niños diabéticos (AU)

Objective: To describe the final height and height-gain in relation to target height, in children with type 1 diabetes mellitus, and analyse their relationship to different variables. Patients and methods: Retrospective analysis of the growth data of 52 children (27 girls) diagnosed with type 1 diabetes mellitus before 14 years old, and followed up until their final height was attained. Main variables: final height, target height, illness duration, glycated haemoglobin (HbA1c), insulin dose, BMI, and other autoimmune diseases. Results: The height SDS (standard deviation scale) at diagnosis was slightly higher (0.734 in boys and 0.563 in girls). During the development of the disease, a growth reduction was seen, which was significantly higher in boys of prepubertal age (p=0.016). The mean final height attained was 173.14±5.28cm in boys and 161.9±6.97cm in girls. Height gain was 1.56±3.66 in boys (SDS=−0.034) and 2.26±6.13 in girls (SDS=0.385). The only variable significantly related to height gain was mean glycated-haemoglobin (growth reduction of 2cm for every increment of 1% in mean glycated-haemoglobin). Conclusions: At onset, diabetic children were slightly taller than the general population. A growth reduction was shown as the disease developed, significantly higher in boys of prepubertal age. The final height in boys was slightly lower than the mean, but in girls was similar to the general population. Both sexes attained their target height, although the height gain was less in boys. Poorer metabolic control was associated with reduced height gain (AU)

[Use of the propensity score methodology in health care research]. / Uso de la metodología propensity score en la investigación sanitaria.

Observational studies are frequently used in biomedical research to determine associations between a treatment or exposure and the effects they can produce. Randomized control trials have been developed with the same purpose. Although they provide more precise results, they are more complex and costly. The use of propensity score methodology in observational studies helps to decrease the appearance of bias that they normally present, making them more accurate and with better reliability than randomized control trials. Given the increase in the use of the propensity score methodology in clinical research in recent years, we consider that it is of particular interest to make a description of it, highlighting its application scope and different use techniques.

Uso de la metodología propensity score en la investigación sanitaria / Use of the propensity score methodology in health care research

En la investigación biomédica es frecuente el diseño de estudios observacionales para determinar la asociación entre un tratamiento o exposición y el efecto que pueden producir. Con el mismo fin se desarrollan los estudios aleatorizados, que aunque obtienen resultados más precisos, son más complejos y costosos. La aplicación de la metodología propensity score (PS) en los estudios observacionales hace que disminuya la aparición de los sesgos que normalmente presentan, acercándolos en precisión y fiabilidad a los estudios aleatorizados. Dado el incremento que se ha producido en los últimos años respecto a la utilización de metodología PS en investigación clínica, consideramos que es de especial interés realizar una descripción de la misma, resaltando su ámbito de aplicación y las diferentes técnicas de uso (AU)

Observational studies are frequently used in biomedical research to determine associations between a treatment or exposure and the effects they can produce. Randomized control trials have been developed with the same purpose. Although they provide more precise results, they are more complex and costly. The use of propensity score methodology in observational studies helps to decrease the appearance of bias that they normally present, making them more accurate and with better reliability than randomized control trials. Given the increase in the use of the propensity score methodology in clinical research in recent years, we consider that it is of particular interest to make a description of it, highlighting its application scope and different use techniques (AU)