Comunicación interna en atención primaria

ObjetivosEstudiar la comunicación interna entre los profesionales de la atención primaria.DiseñoEstudio descriptivo, transversal.EmplazamientoÁmbito de Atención Primaria Costa de Ponent del Institut Català de la Salut.ParticipantesTodos los trabajadores del ámbito (n=3.565).MedicionesEncuesta dividida en 3 partes: a) preguntas sociodemográficas; b) preguntas que valoraban del 0 al 10 la importancia y el funcionamiento actual de diferentes cuestiones, y c) preguntas sobre nuevas herramientas de comunicación.ResultadosRespondieron un 39% de los encuestados (n=1.388), con una edad media de 43,2 años (intervalo de confianza [IC] del 95%, 42,75-43,65), y el 28,9% eran varones. Las mayores diferencias entre importancia y actualidad se dieron a «enterarse de los proyectos antes de que se publiquen en los medios de comunicación», «conocerlos por vía oficial y no por rumores» y «conocer los proyectos de otros equipos». Las menores diferencias se produjeron en la comunicación dentro de los equipos. Los medicos consideran más importante la comunicación ascendente. Los médicos son los que valoran mejor la comunicación dentro de los equipos, y los profesionales de la unidad de atención al usuario (UAU), los que la valoran peor. Los médicos son los que más importancia dan a enterarse a tiempo de los proyectos. El 55% de los encuestados no utiliza el servicio de intranet, la mayor parte por falta de tiempo. El segundo motivo de esta falta de uso es su dificultad. Un 62% lee el correo electrónico más de 2-3 veces por semana El 89% de los encuestados querría tener un boletín electrónico. Los trabajadores de más edad usan menos las nuevas tecnologías.ConclusionesEs necesario mejorar la comunicación descendente, ascendente y transversal, especialmente la ascendente de los médicos, y la de los equipos para los profesionales de la UAU. Debe dotarse a la intranet de instrumentos que agilicen el trabajo y ofrecerse formación en el manejo de las nuevas tecnologías.ObjectivesTo study internal communication between primary care health professionalsDesignCross-sectional, descriptive.SettingCatalan Health Institute Costa de Ponent Primary Care Area, Spain.ParticipantsAll workers in the area (n=3565).MeasurementsThree part questionnaire: a) sociodemographic questions; b) questions scoring from 0 to 10 the current importance and operation of certain aspects; and c) questions on new communication tools.ResultsOf those sent a questionnaire, 39% (n=1388) responded, with a mean age of 43.2 years (95% CI, 42.75- 43.65), 28.9% being male.The major differences between importance and current events were said to be “to be informed of projects before they appear in the communication media,” “by official routes and not by rumour,” and “to be aware of projects of other teams.” The least communicated within teams. The doctors considered upward communication to be more important. Doctors are those who appreciate communication within teams better and the professionals of the users services unit (UAU) less so. Doctors are the ones who give more importance to being informed of projects at the time.55% do not use the intranet, mainly due lack of time. The second reason is that they find it difficult.Sixty-two per cent read e-mail >2-3 times per week. Eighty-nine per cent want an electronic bulletin. The older workers use new technologies less.ConclusionsDownward, upward, and sideways communication needs to be improved, particularly upwards by doctors, and that of the teams for the UAU professionals. Intranet tools must be provided that make the work easier and training in handling new technologies must be offered

Stratification of biological therapies by pathobiology in biologic-naive patients with rheumatoid arthritis (STRAP and STRAP-EU): two parallel, open-label, biopsy-driven, randomised trials

Background Despite highly effective targeted therapies for rheumatoid arthritis, about 40% of patients respond poorly, and predictive biomarkers for treatment choices are lacking. We did a biopsy-driven trial to compare the response to rituximab, etanercept, and tocilizumab in biologic-naive patients with rheumatoid arthritis stratified for synovial B cell status. Methods STRAP and STRAP-EU were two parallel, open-label, biopsy-driven, stratified, randomised, phase 3 trials done across 26 university centres in the UK and Europe. Biologic-naive patients aged 18 years or older with rheumatoid arthritis based on American College of Rheumatology (ACR)–European League Against Rheumatism classification criteria and an inadequate response to conventional synthetic disease-modifying antirheumatic drugs (DMARDs) were included. Following ultrasound-guided synovial biopsy, patients were classified as B cell poor or B cell rich according to synovial B cell signatures and randomly assigned (1:1:1) to intravenous rituximab (1000 mg at week 0 and week 2), subcutaneous tocilizumab (162 mg per week), or subcutaneous etanercept (50 mg per week). The primary outcome was the 16-week ACR20 response in the B cell-poor, intention-to-treat population (defined as all randomly assigned patients), with data pooled from the two trials, comparing etanercept and tocilizumab (grouped) versus rituximab. Safety was assessed in all patients who received at least one dose of study drug. These trials are registered with the EU Clinical Trials Register, 2014-003529-16 (STRAP) and 2017-004079-30 (STRAP-EU). Findings Between June 8, 2015, and July 4, 2019, 226 patients were randomly assigned to etanercept (n=73), tocilizumab (n=74), and rituximab (n=79). Three patients (one in each group) were excluded after randomisation because they received parenteral steroids in the 4 weeks before recruitment. 168 (75%) of 223 patients in the intention-to-treat population were women and 170 (76%) were White. In the B cell-poor population, ACR20 response at 16 weeks (primary endpoint) showed no significant differences between etanercept and tocilizumab grouped together and rituximab (46 [60%] of 77 patients vs 26 [59%] of 44; odds ratio 1·02 [95% CI 0·47–2·17], p=0·97). No differences were observed for adverse events, including serious adverse events, which occurred in six (6%) of 102 patients in the rituximab group, nine (6%) of 108 patients in the etanercept group, and three (4%) of 73 patients in the tocilizumab group (p=0·53). Interpretation In this biologic-naive population of patients with rheumatoid arthrtitis, the dichotomic classification into synovial B cell poor versus rich did not predict treatment response to B cell depletion with rituximab compared with alternative treatment strategies. However, the lack of response to rituximab in patients with a pauci-immune pathotype and the higher risk of structural damage progression in B cell-rich patients treated with rituximab warrant further investigations into the ability of synovial tissue analyses to inform disease pathogenesis and treatment response

Genomic and Metabolomic Profile Associated to Microalbuminuria

<div><p>To identify factors related with the risk to develop microalbuminuria using combined genomic and metabolomic values from a general population study. One thousand five hundred and two subjects, Caucasian, more than 18 years, representative of the general population, were included. Blood pressure measurement and albumin/creatinine ratio were measured in a urine sample. Using SNPlex, 1251 SNPs potentially associated to urinary albumin excretion (UAE) were analyzed. Serum metabolomic profile was assessed by ¹H NMR spectra using a Brucker Advance DRX 600 spectrometer. From the total population, 1217 (mean age 54±19, 50.6% men, ACR>30 mg/g in 81 subjects) with high genotyping call rate were analysed. A characteristic metabolomic profile, which included products from mitochondrial and extra mitochondrial metabolism as well as branched amino acids and their derivative signals, were observed in microalbuminuric as compare to normoalbuminuric subjects. The comparison of the metabolomic profile between subjects with different UAE status for each of the genotypes associated to microalbuminuria revealed two SNPs, the rs10492025_TT of <i>RPH3A</i> gene and the rs4359_CC of <i>ACE</i> gene, with minimal or no statistically significant differences. Subjects with and without microalbuminuria, who shared the same genotype and metabolomic profile, differed in age. Microalbuminurics with the CC genotype of the rs4359 polymorphism and with the TT genotype of the rs10492025 polymorphism were seven years older and seventeen years younger, respectively as compared to the whole microalbuminuric subjects. With the same metabolomic environment, characteristic of subjects with microalbuminuria, the TT genotype of the rs10492025 polymorphism seems to increase and the CC genotype of the rs4359 polymorphism seems to reduce risk to develop microalbuminuria.</p></div

Bar chart showing metabolic differences between microalbuminuria and no microalbuminuria normalized with respect to changes in the entire cohort.

<p>The bars represent the difference in the average metabolic levels between microalbuminuria and no microalbuminuria for each SNP divided by the same difference calculated for the entire cohort. SNPs with bars closer to 1 (dotted line) show UAE associated metabolic changes similar to those of the global population (irrespective of genotype). On the other hand, SNPs with bars closer to 0 exhibit minimal or no metabolic changes associated to UAE. Bars with negative values indicate a UAE associated metabolic change opposite to that detected in global population. Metabolites from top to bottom are: creatinine; creatine phosphate; leucine; glucose; proline; phosphocholine; choline; creatine+creatine phosphate; albumin; trimethylamine; citrate+dimethylamine; glutamine; 3-hydroxyisovalerate; pyruvate; N-acetylglutamine; lipids ( = CH-CH2-CH2-)+aminobutyrate; isoleucine; lipids (βCH2); alanine; lactate; lipids (-CH2-)n; valine; valine+isoleucine; leucine+isoleucine; lipids (-CH3) and cholesterol.</p

SNPs associated to UAE in the general population.

<p><i>*dbSNP; adjusted by age, sex, BMI, Systolic BP and fasting glucose</i>.</p

Patterns of statistical significance, calculated as p-values, for the comparison of metabolic profiles between normoalbuminuria and microalbuminuria in the whole population (first column) and in individuals with different SNPs (rest of the columns).

<p>(○) p>0.01; (light grey circle) p<0.01; (dark grey circle) p<0.001; (•) p<0.00001. Percent of microalbuminuria in each genotype is included between brackets ().</p

Box plots showing metabolite relative levels in blood serum of subjects without microalbuminuria (box in the left) and with microalbuminuria (box in the right).

<p>Boxes denote interquartile range, lines denote median, and whiskers denote tenth and ninetieth percentiles. Levels are expressed as area of the metabolite of interest divided with respect total aliphatic spectral area. *, p-value<0.01; ***, p-value<0.00001.</p

General characteristics of the study population grouped by urinary albumin excretion.

<p><i>() percentage</i>.</p