LINAMARA RIZZO BATTISTELLA
Projetos de Pesquisa
Unidades Organizacionais
Departamento de MedicinaLegal, Ética Médica e Medicina Social e do Trabalho, Faculdade de Medicina - Docente
Instituto de Medicina Física e de Reabilitação, Hospital das Clínicas, Faculdade de Medicina
FMUSP, Hospital das Clínicas, Faculdade de Medicina
LIM/40 - Laboratório de Imunohematologia e Hematologia Forense, Hospital das Clínicas, Faculdade de Medicina - Líder
Instituto de Medicina Física e de Reabilitação, Hospital das Clínicas, Faculdade de Medicina
FMUSP, Hospital das Clínicas, Faculdade de Medicina
LIM/40 - Laboratório de Imunohematologia e Hematologia Forense, Hospital das Clínicas, Faculdade de Medicina - Líder
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- Electroencephalography as a Biomarker for Functional Recovery in Spinal Cord Injury Patients(2021) SIMIS, Marcel; CAMSARI, Deniz Doruk; IMAMURA, Marta; FILIPPO, Thais Raquel Martins; SOUZA, Daniel Rubio De; BATTISTELLA, Linamara Rizzo; FREGNI, FelipeBackground Functional changes after spinal cord injury (SCI) are related to changes in cortical plasticity. These changes can be measured with electroencephalography (EEG) and has potential to be used as a clinical biomarker. Method In this longitudinal study participants underwent a total of 30 sessions of robotic-assisted gait training (RAGT) over a course of 6 weeks. The duration of each session was 30 min. Resting state EEG was recorded before and after 30-session rehabilitation therapy. To measure gait, we used the Walking Index for Spinal Cord Injury Scale, 10-Meter- Walking Test, Timed-Up-and-Go, and 6-Min-Walking Test. Balance was measured using Berg Balance Scale. Results Fifteen participants with incomplete SCI who had AIS C or D injuries based on American Spinal Cord Injury Association Impairment Scale classification were included in this study. Mean age was 35.7 years (range 17-51) and the mean time since injury was 17.08 (range 4-37) months. All participants showed clinical improvement with the rehabilitation program. EEG data revealed that high beta EEG activity in the central area had a negative correlation with gait (p = 0.049; beta coefficient: -0.351; and adj-R-2: 0.23) and balance (p = 0.043; beta coefficient: -0.158; and adj-R-2:0.24) measured at baseline, in a way that greater high beta EEG power was related to worse clinical function at baseline. Moreover, improvement in gait and balance had negative correlations with the change in alpha/theta ratio in the parietal area (Gait: p = 0.049; beta coefficient: -0.351; adj-R-2: 0.23; Balance: p = 0.043; beta coefficient: -0.158; and adj-R-2: 0.24). Conclusion In SCI, functional impairment and subsequent improvement following rehabilitation therapy with RAGT correlated with the change in cortical activity measured by EEG. Our results suggest that EEG alpha/theta ratio may be a potential surrogate marker of functional improvement during rehabilitation. Future studies are necessary to improve and validate these findings as a neurophysiological biomarker for SCI rehabilitation.
conferenceObject Barriers and Facilitators to Healthcare Service Access among Persons with Spinal Cord Injury (SCI)(2022) BYCHKOVSKA, O.; EGEN, C.; STROM, V.; JUOCEVICIUS, A.; TEDERKO, P.; ARORA, M.; BATTISTELLA, L. Rizzo; ENGKASAN, J. P.; GEMPERLI, A.- Using Brain Oscillations and corticospinal excitability to Understand and Predict Post-stroke Motor Function(2017) THIBAUT, Aurore; SIMIS, Marcel; BATTISTELLA, Linamara Rizzo; FANCIULLACCI, Chiara; BERTOLUCCI, Federica; HUERTA-GUTIERREZ, Rodrigo; CHISARI, Carmelo; FREGNI, FelipeWhat determines motor recovery in stroke is still unknown and finding markers that could predict and improve stroke recovery is a challenge. In this study, we aimed at understanding the neural mechanisms of motor function recovery after stroke using neurophysiological markers by means of cortical excitability (transcranial magnetic stimulation-TMS) and brain oscillations (electroencephalography-EEG). In this cross-sectional study, 55 subjects with chronic stroke (62 +/- 14 yo, 17 women, 32 +/- 42 months post-stroke) were recruited in two sites. We analyzed TMS measures (i.e., motor threshold-MT-of the affected and unaffected sides) and EEG variables (i.e., power spectrum in different frequency bands and different brain regions of the affected and unaffected hemispheres) and their correlation with motor impairment as measured by Fugl-Meyer. Multiple univariate and multivariate linear regression analyses were performed to identify the predictors of good motor function. A significant interaction effect of MT in the affected hemisphere and power in beta bandwidth over the central region for both affected and unaffected hemispheres was found. We identified that motor function positively correlates with beta rhythm over the central region of the unaffected hemisphere, while it negatively correlates with beta rhythm in the affected hemisphere. Our results suggest that cortical activity in the affected and unaffected hemisphere measured by EEG provides new insights on the association between high-frequency rhythms and motor impairment, highlighting the role of an excess of beta in the affected central cortical region in poor motor function in stroke recovery.
- Acute Effect of Robotic Therapy (G-EO System) on the Lower Limb Temperature Distribution of a Patient with Stroke Sequelae(2019) ALFIERI, Fabio Marcon; DIAS, Caren da Silva; SANTOS, Artur Cesar Aquino dos; BATTISTELLA, Linamara RizzoRobotic therapy has been gaining prominence in poststroke rehabilitation programs. An example of these devices is the G-EO System, which simulates gait as well as other more complexes standards of gait such as the steps on stairs. However, to the best of our knowledge, there are no studies that apply thermography as a tool to evaluate stroke patients who undertook rehabilitation programs with the aid of robotic devices. The patient IWPS undergoes sequelae of hemorrhagic stroke for 19 months and consequently hemiplegia, had scores of 93 points in the Fugl-Meyer scale, is undertaking a physical rehabilitation program for six months, has no complaints of discomfort due to thermic sensitivity imbalances between the plegic and the contralateral sides, and voluntarily reports that he realizes functionality improvements especially, according to his perception, due to the aid of the robotic therapy in his gait training with the G-EO System. The thermographic images were captured by an infrared sensor FLIR T650SC. By analyzing the temperature differences between both hemispheres of the body, before, immediately after, and 30 minutes after a robotic therapy for gait training, we observed that the values firstly increased immediately after the training, but after the 30-minute rest an important thermoregulation was achieved.
- Robot-Assisted Therapy and Constraint-Induced Movement Therapy for Motor Recovery in Stroke: Results From a Randomized Clinical Trial(2021) TERRANOVA, Thais Tavares; SIMIS, Marcel; SANTOS, Artur Cesar Aquino; ALFIERI, Fabio Marcon; IMAMURA, Marta; FREGNI, Felipe; BATTISTELLA, Linamara RizzoBackground: Stroke is one of the leading causes of adult disability, and up to 80% of stroke survivors undergo upper extremity motor dysfunction. Constraint-Induced Movement Therapy (CIMT) and Robot-Assisted Therapy (RT) are used for upper limb stroke rehabilitation. Although CIMT and RT are different techniques, both are beneficial; however, their results must be compared. The objective is to establish the difference between RT and CIMT after a rehabilitation program for chronic stroke patients. Method: This is a randomized clinical trial, registered at ClinicalTrials.gov (ID number NCT02700061), in which patients with stroke received sessions of RT or CIMT protocol, combined with a conventional rehabilitation program for 12 weeks. The primary outcome was measured by Wolf Motor Function Test (WMFT) and Fugl-Meyer Assessment-Upper Limb (FMA-UL). Activities of daily living were also assessed. Results: Fifty one patients with mild to moderate upper limb impairment were enrolled in this trial, 25 women and 26 men, mean age of 60,02 years old (SD 14,48), with 6 to 36 months after stroke onset. Function significantly improved regardless of the treatment group. However, no statistical difference was found between both groups as p-values of the median change of function measured by WMFT and FMA were 0.293 and 0.187, respectively. Conclusion: This study showed that Robotic Therapy (RT) was not different from Constraint-Induced Movement Therapy (CIMT) regardless of the analyzed variables. There was an overall upper limb function, motor recovery, functionality, and activities of daily living improvement regardless of the interventions. At last, the combination of both techniques should be considered in future studies.
- Monitoring heart rate variability on-line used mobile telephone 3G e-health service oriented(2013) GOROSO, D. G.; SILVA, R. R. da; BATTISTELLA, L. R.; ODSTRCIL, M.; PAOLINI, M.We are living an epidemic of cardiovascular and cerebrovascular diseases that have led to many researchers worldwide increase their technical studies and methods of identification, diagnosis and treatment. Moreover, risk estimate based on factors such as age, sex, blood pressure, smoking, and lipid levels is still incomplete and depend on interest of subject by going to the hospital to do lab tests. The Brazilian experience that recorded each year over 90.000 deaths caused by cardiovascular and cerebrovascular diseases, only in 2008 the Unified Health System log about 200.000 hospitalizations, which resulted in an approximate cost of $ 180 million public resource. In addition, this is responsible for approximately 40% of early retirements and leading cause of disability in the age group above 50 years. Following the premise that ""The best cure is prevention"", this work seeks to provide a mobile tool to prevent early cardiac arrhythmia by means of monitoring on-line and assessing heart rate variability. Preliminary results proved effective in Sao Paulo for study of heart rate variability. This new service uses mobile phone to record, evaluate and transmit information, which currently is in clinical validation.
- Functional and Neural Correlates Associated with Conditioned Pain Modulation in Patients with Chronic Knee Osteoarthritis Pain: A Cross-Sectional Study(2023) SIMIS, Marcel; PACHECO-BARRIOS, Kevin; VASQUEZ-AVILA, Karen; REBELLO-SANCHEZ, Ingrid; PARENTE, Joao; CASTELO-BRANCO, Luis; MARDUY, Anna; MELO, Paulo S. de; IMAMURA, Marta; BATTISTELLA, Linamara; FREGNI, FelipeIn this study, we aimed to assess the factors that predict a dysfunctional conditioned pain modulation (CPM) in chronic knee OA. Methods: This is a cross-sectional analysis of patients with chronic knee OA from a prospective cohort study in Brazil (n = 85). We performed linear and logistic multivariate regression models using the purposeful selection approach to test the relationship between the CPM in both knees (average) as a dependent variable and demographics, clinical, and neurophysiological as independent variables. Results: A significant negative association between WOMAC pain scores and CPM (beta: 0.13) was found. This association was modified by the subjects' race, being stronger in the non-white subjects. In our logistic regression models, pain intensity indexed with the WOMAC pain scale remained a significant association with dichotomized CPM. Furthermore, a significant CPM association with balance, indexed with the Berg Balance score, was evidenced ( beta: 0.04). Neurophysiological variables showed a significant negative relationship with CPM, such as the relative power of delta oscillations in the frontal area ( beta: 3.11) and central area ( beta: 3.23). There was no significant relationship between CPM and the following domains: cognitive, emotion, sleep, opioid receptor polymorphisms, and intrinsic variables of OA disease. There was no association of CPM with TMS-indexed inhibitory markers. Conclusions: These results may indicate that less function of the pain descending inhibitory system in patients with OA is correlated with higher activity-related pain (WOMAC), less balance, and cortical plasticity especially with increased low-frequency (delta) brain oscillations. These associations seem modified by race.
- Data-driven, cross-disciplinary collaboration: lessons learned at the largest academic health center in Latin America during the COVID-19 pandemic(2024) RITTO, Ana Paula; ARAUJO, Adriana Ladeira de; CARVALHO, Carlos Roberto Ribeiro de; SOUZA, Heraldo Possolo De; FAVARETTO, Patricia Manga e Silva; SABOYA, Vivian Renata Boldrim; GARCIA, Michelle Louvaes; KULIKOWSKI, Leslie Domenici; KALLAS, Esper Georges; PEREIRA, Antonio Jose Rodrigues; COBELLO JUNIOR, Vilson; SILVA, Katia Regina; ABDALLA, Eidi Raquel Franco; SEGURADO, Aluisio Augusto Cotrim; SABINO, Ester Cerdeira; RIBEIRO JUNIOR, Ulysses; FRANCISCO, Rossana Pulcineli Vieira; MIETHKE-MORAIS, Anna; LEVIN, Anna Sara Shafferman; SAWAMURA, Marcio Valente Yamada; FERREIRA, Juliana Carvalho; SILVA, Clovis Artur; MAUAD, Thais; GOUVEIA, Nelson da Cruz; LETAIF, Leila Suemi Harima; BEGO, Marco Antonio; BATTISTELLA, Linamara Rizzo; DUARTE, Alberto Jose da Silva; SEELAENDER, Marilia Cerqueira Leite; MARCHINI, Julio; FORLENZA, Orestes Vicente; ROCHA, Vanderson Geraldo; MENDES-CORREA, Maria Cassia; COSTA, Silvia Figueiredo; CERRI, Giovanni Guido; BONFA, Eloisa Silva Dutra de Oliveira; CHAMMAS, Roger; BARROS FILHO, Tarcisio Eloy Pessoa de; BUSATTO FILHO, GeraldoIntroduction The COVID-19 pandemic has prompted global research efforts to reduce infection impact, highlighting the potential of cross-disciplinary collaboration to enhance research quality and efficiency.Methods At the FMUSP-HC academic health system, we implemented innovative flow management routines for collecting, organizing and analyzing demographic data, COVID-related data and biological materials from over 4,500 patients with confirmed SARS-CoV-2 infection hospitalized from 2020 to 2022. This strategy was mainly planned in three areas: organizing a database with data from the hospitalizations; setting-up a multidisciplinary taskforce to conduct follow-up assessments after discharge; and organizing a biobank. Additionally, a COVID-19 curated collection was created within the institutional digital library of academic papers to map the research output.Results Over the course of the experience, the possible benefits and challenges of this type of research support approach were identified and discussed, leading to a set of recommended strategies to enhance collaboration within the research institution. Demographic and clinical data from COVID-19 hospitalizations were compiled in a database including adults and a minority of children and adolescents with laboratory confirmed COVID-19, covering 2020-2022, with approximately 350 fields per patient. To date, this database has been used in 16 published studies. Additionally, we assessed 700 adults 6 to 11 months after hospitalization through comprehensive, multidisciplinary in-person evaluations; this database, comprising around 2000 fields per subject, was used in 15 publications. Furthermore, thousands of blood samples collected during the acute phase and follow-up assessments remain stored for future investigations. To date, more than 3,700 aliquots have been used in ongoing research investigating various aspects of COVID-19. Lastly, the mapping of the overall research output revealed that between 2020 and 2022 our academic system produced 1,394 scientific articles on COVID-19.Discussion Research is a crucial component of an effective epidemic response, and the preparation process should include a well-defined plan for organizing and sharing resources. The initiatives described in the present paper were successful in our aim to foster large-scale research in our institution. Although a single model may not be appropriate for all contexts, cross-disciplinary collaboration and open data sharing should make health research systems more efficient to generate the best evidence.
- The Impact of Artificial Intelligence on Waiting Time for Medical Care in an Urgent Care Service for COVID-19: Single-Center Prospective Study(2022) BIN, Kaio Jia; MELO, Adler Araujo Ribeiro; ROCHA, Jose Guilherme Moraes Franco da; ALMEIDA, Renata Pivi de; COBELLO JUNIOR, Vilson; MAIA, Fernando Liebhart; FARIA, Elizabeth de; PEREIRA, Antonio Jose; BATTISTELLA, Linamara Rizzo; ONO, Suzane KiokoBackground: To demonstrate the value of implementation of an artificial intelligence solution in health care service, a winning project of the Massachusetts Institute of Technology Hacking Medicine Brazil competition was implemented in an urgent care service for health care professionals at Hospital das Clinicas of the Faculdade de Medicina da Universidade de Sao Paulo during the COVID-19 pandemic. Objective: The aim of this study was to determine the impact of implementation of the digital solution in the urgent care service, assessing the reduction of nonvalue-added activities and its effect on the nurses' time required for screening and the waiting time for patients to receive medical care. Methods: This was a single-center, comparative, prospective study designed according to the Public Health England guide ""Evaluating Digital Products for Health."" A total of 38,042 visits were analyzed over 18 months to determine the impact of implementing the digital solution. Medical care registration, health screening, and waiting time for medical care were compared before and after implementation of the digital solution. Results: The digital solution automated 92% of medical care registrations. The time for health screening increased by approximately 16% during the implementation and in the first 3 months after the implementation. The waiting time for medical care after automation with the digital solution was reduced by approximately 12 minutes compared with that required for visits without automation. The total time savings in the 12 months after implementation was estimated to be 2508 hours. Conclusions: The digital solution was able to reduce nonvalue-added activities, without a substantial impact on health screening, and further saved waiting time for medical care in an urgent care service in Brazil during the COVID-19 pandemic.
- Digital Platform for Continuous Monitoring of Patients Using a Smartwatch: Longitudinal Prospective Cohort Study(2023) BIN, Kaio Jia; PRETTO, Lucas Ramos De; SANCHEZ, Fabio Beltrame; CASTRO, Fabio Pacheco Muniz De Souza e; RAMOS, Vinicius Delgado; BATTISTELLA, Linamara RizzoBackground: Since the COVID-19 pandemic, there has been a boost in the digital transformation of the human society, where wearable devices such as a smartwatch can already measure vital signs in a continuous and naturalistic way; however, the security and privacy of personal data is a challenge to expanding the use of these data by health professionals in clinical follow-up for decision-making. Similar to the European General Data Protection Regulation, in Brazil, the Lei Geral de Protecao de Dados established rules and guidelines for the processing of personal data, including those used for patient care, such as those captured by smartwatches. Thus, in any telemonitoring scenario, there is a need to comply with rules and regulations, making this issue a challenge to overcome.Objective: This study aimed to build a digital solution model for capturing data from wearable devices and making them available in a safe and agile manner for clinical and research use, following current laws.Methods: A functional model was built following the Brazilian Lei Geral de Protecao de Dados (2018), where data captured by smartwatches can be transmitted anonymously over the Internet of Things and be identified later within the hospital. A total of 80 volunteers were selected for a 24-week follow-up clinical trial divided into 2 groups, one group with a previous diagnosis of COVID-19 and a control group without a previous diagnosis of COVID-19, to measure the synchronization rate of the platform with the devices and the accuracy and precision of the smartwatch in out-of-hospital conditions to simulate remote monitoring at home.Results: In a 35-week clinical trial, >11.2 million records were collected with no system downtime; 66% of continuous beats per minute were synchronized within 24 hours (79% within 2 days and 91% within a week). In the limit of agreement analysis, the mean differences in oxygen saturation, diastolic blood pressure, systolic blood pressure, and heart rate were -1.280% (SD 5.679%), -1.399 (SD 19.112) mm Hg, -1.536 (SD 24.244) mm Hg, and 0.566 (SD 3.114) beats per minute, respectively. Furthermore, there was no difference in the 2 study groups in terms of data analysis (neither using the smartwatch nor the gold-standard devices), but it is worth mentioning that all volunteers in the COVID-19 group were already cured of the infection and were highly functional in their daily work life.Conclusions: On the basis of the results obtained, considering the validation conditions of accuracy and precision and simulating an extrahospital use environment, the functional model built in this study is capable of capturing data from the smartwatch and anonymously providing it to health care services, where they can be treated according to the legislation and be used to support clinical decisions during remote monitoring.