The spectrum of pulmonary manifestations associated with mixed connective tissue disease ranges from pulmonary hypertension and interstitial lung disease to pleural effusions, alveolar hemorrhage, and complications from the thromboembolic disease. Interstitial lung disease in mixed connective tissue disease is a frequently occurring entity, although in most cases it tends to be self-limited or slowly progressive. Despite this, a significant percentage of patients may present a progressive fibrosing phenotype, thus posing a great challenge regarding its therapeutic approach, given the scarcity of clinical studies that compare the efficacy of immunosuppressants available to date. Due to this, many recommendations are extrapolated from other diseases with similar characteristics such as systemic sclerosis and systemic lupus erythematosus. That is why it is proposed to carry out an advanced search of the literature in order to clarify its clinical, radiological, and therapeutic characteristics to achieve its evaluation from a holistic point of view.

Background: Chikungunya virus (CHIKV) diagnosis has become a challenge for primary care physicians in areas where the Zika virus and/or Dengue virus are present. Case definitions for the three arboviral infections overlap. Methods: A cross-sectional analysis was carried out. A bivariate analysis was made using confirmed CHIKV infection as the outcome. Variables with significant statistical association were included in an agreement consensus. Agreed variables were analyzed in a multiple regression model. The area under the receiver operating characteristic (ROC) curve was calculated to determine a cut-off value and performance. Results: 295 patients with confirmed CHIKV infection were included. A screening tool was created using symmetric arthritis (4 points), fatigue (3 points), rash (2 points), and ankle joint pain (1 point). The ROC curve identified a cut-off value, and a score ≥ 5.5 was considered positive for identifying CHIKV patients with a sensibility of 64.4% and a specificity of 87.4%, positive predictive value of 85.5%, negative predictive value of 67.7%, area under the curve of 0.72, and an accuracy of 75%. Conclusion: We developed a screening tool for CHIKV diagnosis using only clinical symptoms as well as proposed an algorithm to aid the primary care physician.

Background Chikungunya virus (CHIKV) diagnosis have become a challenge for primary care physicians in areas where zika virus and/or dengue virus are present. Case definitions for the three arboviral infections are overlapping. Method A cross-sectional analysis was carried out. A bivariate analysis was made using confirmed CHIKV infection as the outcome. Variables with significant statistical association were included in an agreement consensus. Agreed variables were analysed in multiple regression model. The area under the receiver operating characteristic (ROC) curve was calculated to determine a cut-off value and performance. Results 295 patients with confirmed CHIKV infection were included. A screening tool was made using symmetric arthritis (4 points), fatigue (3 points), rash (2 points) and ankle joint pain (1 point). The ROC curve identified a cut-off value and a score ≥ 5.5 was considered positive to identify CHIKV patients with a sensibility of 64.4% and a specificity of 87.4%, positive predictive value of 85.5%, negative predictive value of 67.7%, area under the curve of 0.72, and an accuracy of 75%. Conclusion We developed a screening tool for CHIKV diagnosis using only clinical symptoms as well as proposed an algorithm to aid the primary care physician.

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