The contributions of social interdisciplinary practices in problem-based learning medicine course

[EN] Traditional and basic disciplines of medicine schools are rarely invited to participate of interdisciplinary experiences outside the classroom. Although exists vast literature on problem-based learning medicine courses, there are few studies focusing the socialization of students to learn more complex topics. In this paper, the authors revisited the diagnostic of local health based on Charles Maguerez’s arch method that enables the collective construction of knowledge, starting with the observation of family health center attributions. Students were encouraged to collaborate with health agents to investigate the causes of illness in the community. Dengue emerged as a main health problem and it was used as central theme. After the students had theorized about main problems, they developed a strategy in order to propose alternatives for a communitarian intervention plan. Then, day-care and healthcare centers, schools, health agents and students of medicine were involved in a multiple educational approach to increase the awareness of community on dengue prevention. The analysis of data reveals that problem-based learning with social insertion helped the students to develop skills and core competences to a more realistic practice of socialized medicine integrated with health service.Da Silva, M.; Costa, P.; Fernandes, MC.; Tavares, AC.; Santana, MN.; Margotto, M. (2015). The contributions of social interdisciplinary practices in problem-based learning medicine course. En 1ST INTERNATIONAL CONFERENCE ON HIGHER EDUCATION ADVANCES (HEAD' 15). Editorial Universitat Politècnica de València. 250-257. https://doi.org/10.4995/HEAD15.2015.255OCS25025

Development and validation of the dystonia-pain classification System : a multicenter study

Abstract: Background: Dystonia is associated with disabling nonmotor symptoms like chronic pain (CP), which is prevalent in dystonia and significantly impacts the quality of life (QoL). There is no validated tool for assessing CP in dystonia, which substantially hampers pain management. Objective: The aim was to develop a CP classification and scoring system for dystonia. Methods: A multidisciplinary group was established to develop the Dystonia-Pain Classification System (Dystonia- PCS). The classification of CP as related or unrelated to dystonia was followed by the assessment of pain severity score, encompassing pain intensity, frequency, and impact on daily living. Then, consecutive patients with inherited/idiopathic dystonia of different spatial distribution were recruited in a cross-sectional multicenter validation study. Dystonia-PCS was compared to validated pain, mood, QoL, and dystonia scales (Brief Pain Inventory, Douleur Neuropathique-4 questionnaire, European QoL-5 Dimensions-3 Level Version, and Burke–Fahn–Marsden Dystonia Rating Scale). Results: CP was present in 81 of 123 recruited patients, being directly related to dystonia in 82.7%, aggravated by dystonia in 8.8%, and nonrelated to dystonia in 7.5%. affected by this disorder. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. Dystonia-PCS had excellent intra-rater (Intraclass Correlation Coefficient - ICC: 0.941) and inter-rater (ICC: 0.867) reliability. In addition, pain severity score correlated with European QoL-5 Dimensions-3 Level Version’s pain subscore (r = 0.635, P < 0.001) and the Brief Pain Inventory’s severity and interference scores (r = 0.553, P < 0.001 and r = 0.609, P < 0.001, respectively). Conclusions: Dystonia-PCS is a reliable tool to categorize and quantify CP impact in dystonia and will help improve clinical trial design and management of CP in patients affected by this disorder

The Parkinson`s disease pain classification system (PDPCS): results from an international mechanism-based classification approach

Abstract: Pain is a common non-motor symptom in patients with Parkinson’s disease (PD) but the correct diagnosis of the respective cause remains difficult because suitable tools are lacking, so far. We developed a framework to differentiate PD- from non-PD-related pain and classify PD-related pain into three groups based on validated mechanistic pain descriptors (nociceptive, neuropathic, or nociplastic), which encompasses the previously described PD pain types. Severity of PD-related pain syndromes was scored by ratings of intensity, frequency, and interference with daily living activities. The PD-Pain Classification System (PD-PCS) was compared with classic pain measures (ie, brief pain inventory (BPI) and McGill pain questionnaire (MPQ), PDQ-8 quality of life score, MDS-UPDRS scores, and non-motor symptoms). 159 non-demented PD patients (disease duration 10.2±7.6 years) and 37 healthy controls were recruited in four centers. PD-related pain was present in 122 patients (77%), with 24 (15%) suffering one or more syndromes at the same time. PD-related nociceptive, neuropathic, or nociplastic pain was diagnosed in 87 (55%), 25 (16%), or 35 (22%), respectively. Pain unrelated to PD was present in 35 (22%) patients. Overall, PD-PCS severity score significantly correlated with pain’s BPI and MPQ ratings, presence of dyskinesia and motor fluctuations, PDQ-8 scores, depression and anxiety measures. Moderate intra- and inter-rater reliability were observed. The PD-PCS is a valid and reliable tool for differentiating PD-related pain from PD-unrelated pain. It detects and scores mechanistic pain subtypes in a pragmatic and treatment-oriented approach, unifying previous classifications of PD-pain