Validation of Electronic Health Record Phenotyping of Bipolar Disorder Cases and Controls

Objective: The study was designed to validate use of elec-tronic health records (EHRs) for diagnosing bipolar disorder and classifying control subjects. Method: EHR data were obtained from a health care system of more than 4.6 million patients spanning more than 20 years. Experienced clinicians reviewed charts to identify text features and coded data consistent or inconsistent with a diagnosis of bipolar disorder. Natural language processing was used to train a diagnostic algorithm with 95% specificity for classifying bipolar disorder. Filtered coded data were used to derive three additional classification rules for case subjects and one for control subjects. The positive predictive value (PPV) of EHR-based bipolar disorder and subphenotype di- agnoses was calculated against diagnoses from direct semi- structured interviews of 190 patients by trained clinicians blind to EHR diagnosis. Results: The PPV of bipolar disorder defined by natural language processing was 0.85. Coded classification based on strict filtering achieved a value of 0.79, but classifications based on less stringent criteria performed less well. No EHR- classified control subject received a diagnosis of bipolar dis- order on the basis of direct interview (PPV=1.0). For most subphenotypes, values exceeded 0.80. The EHR-based clas- sifications were used to accrue 4,500 bipolar disorder cases and 5,000 controls for genetic analyses. Conclusions: Semiautomated mining of EHRs can be used to ascertain bipolar disorder patients and control subjects with high specificity and predictive value compared with diagnostic interviews. EHRs provide a powerful resource for high-throughput phenotyping for genetic and clinical research.

Improving the Psychometric Utility of the Hypomania Checklist (HCL-32): a Rasch Analysis Approach

Background The HCL-32 is a widely-used screening questionnaire for hypomania. We aimed to use a Rasch analysis approach to (i) evaluate the measurement properties, principally unidimensionality, of the HCL-32, and (ii) generate a score table to allow researchers to convert raw HCL-32 scores into an interval-level measurement which will be more appropriate for statistical analyses. Methods Subjects were part of the Bipolar Disorder Research Network (BDRN) study with DSM-IV bipolar disorder (n=389). Multidimensionality was assessed using the Rasch fit statistics and principle components analysis of the residuals (PCA). Item invariance (differential item functioning, DIF) was tested for gender, bipolar diagnosis and current mental state. Item estimates and reliabilities were calculated. Results Three items (29, 30, 32) had unacceptable fit to the Rasch unidimensional model. Item 14 displayed significant DIF for gender and items 8 and 17 for current mental state. Item estimates confirmed that not all items measure hypomania equally. Limitations This sample was recruited as part of a large ongoing genetic epidemiology study of bipolar disorder and may not be fully representative of the broader clinical population of individuals with bipolar disorder. Conclusion The HCL-32 is unidimensional in practice, but measurements may be further strengthened by the removal of four items. Re-scored linear measurements may be more appropriate for clinical research.

Optimization of a multielectrode array (MEA)-based approach to study the impact of Aβ on the SH-SY5Y cell line

The human brain stores, integrates, and transmits information recurring to millions of neurons, interconnected by countless synapses. Though neurons communicate through chemical signaling, information is coded and conducted in the form of electrical signals. Neuroelectrophysiology focus on the study of this type of signaling. Both intra and extracellular approaches are used in research, but none holds as much potential in high-throughput screening and drug discovery, as extracellular recordings using multielectrode arrays (MEAs). MEAs measure neuronal activity, both in vitro and in vivo. Their key advantage is the capability to record electrical activity at multiple sites simultaneously. Alzheimer’s disease (AD) is the most common neurodegenerative disease and one of the leading causes of death worldwide. It is characterized by neurofibrillar tangles and aggregates of amyloid-β (Aβ) peptides, which lead to the loss of synapses and ultimately neuronal death. Currently, there is no cure and the drugs available can only delay its progression. In vitro MEA assays enable rapid screening of neuroprotective and neuroharming compounds. Therefore, MEA recordings are of great use in both AD basic and clinical research. The main aim of this thesis was to optimize the formation of SH-SY5Y neuronal networks on MEAs. These can be extremely useful for facilities that do not have access to primary neuronal cultures, but can also save resources and facilitate obtaining faster high-throughput results to those that do. Adhesion-mediating compounds proved to impact cell morphology, viability and exhibition of spontaneous electrical activity. Moreover, SH-SY5Y cells were successfully differentiated and demonstrated acute effects on neuronal function after Aβ addition. This effect on electrical signaling was dependent on Aβ oligomers concentration. The results here presented allow us to conclude that the SH-SY5Y cell line can be successfully differentiated in properly coated MEAs and be used for assessing acute Aβ effects on neuronal signaling.

Curricular internship report in medical writing at Blueclinical, Portugal

The contents of this report are a summary of the activities carried out during the 8-month internship as an Associate Medical Writer at Blueclinical Ltd, Matosinhos, Portugal. Mainly my activities were related to medical writing, particularly writing the clinical research protocols, clinical study reports, writing manuscript and preparing poster presentations. In addition to these activities, I also participated in performance of a clinical trial from beginning to end. During the period of its realization, I was able to familiarize myself with all the steps of the Phase I clinical trial.

Social Cognition, Negative Symptoms and Psychosocial Functioning in Schizophrenia.

Although functional recovery could be advocated as an achievable treatment goal, many effective interventions for the treatment of psychotic symptoms, such as antipsychotic drugs, may not improve functioning. The last two decades of cognitive and clinical research on schizophrenia were a turning point for the firm acknowledgment of how relevant social cognitive deficits and negative symptoms could be in predicting psychosocial functioning. The relevance of social cognition dysfunction in schizophrenia patients’ daily living is now unabated. In fact, social cognition deficits could be the most significant predictor of functionality in patients with schizophrenia, non-redundantly with neurocognition. Emerging evidence suggests that negative symptoms appear to play an indirect role, mediating the relationship between neurocognition and social cognition with functional outcomes. Further explorations of this mediating role of negative symptoms have revealed that motivational deficits appear to be particularly important in explaining the relationship between both neurocognitive and social cognitive dysfunction and functional outcomes in schizophrenia. In this paper we will address the relative contribution of two key constructs—social cognitive deficits and negative symptoms, namely how intertwined they could be in daily life functioning of patients with schizophrenia.

Polymyalgia Rheumatica (PMR) Special Interest Group at OMERACT 11: outcomes of importance for patients with PMR

We worked toward developing a core outcome set for clinical research studies in polymyalgia rheumatica (PMR) by conducting (1) patient consultations using modified nominal group technique; (2) a systematic literature review of outcome measures in PMR; (3) a pilot observational study of patients presenting with untreated PMR, and further discussion with patient research partners; and (4) a qualitative focus group study of patients with PMR on the meaning of stiffness, using thematic analysis. (1) Consultations included 104 patients at 4 centers. Symptoms of PMR included pain, stiffness, fatigue, and sleep disturbance. Function, anxiety, and depression were also often mentioned. Participants expressed concerns about diagnostic delay, adverse effects of glucocorticoids, and fear of relapse. (2) In the systematic review, outcome measures previously used for PMR include pain visual analog scores (VAS), morning stiffness, blood markers, function, and quality of life; standardized effect sizes posttreatment were large. (3) Findings from the observational study indicated that asking about symptom severity at 7 AM, or "on waking," appeared more relevant to disease activity than asking about symptom severity "now" (which depended on the time of assessment). (4) Preliminary results were presented from the focus group qualitative study, encompassing broad themes of stiffness, pain, and the effect of PMR on patients' lives. It was concluded that further validation work is required before a core outcome set in PMR can be recommended. Nevertheless, the large standardized effect sizes suggest that pain VAS is likely to be satisfactory as a primary outcome measure for assessing response to initial therapy of PMR. Dissection of between-patient heterogeneity in the subsequent treatment course may require attention to comorbidity as a potential confounding factor.

A longitudinal qualitative exploration of healthcare and informal support needs among survivors of critical illness: the RELINQUISH protocol.

Introduction and background: Survival following critical illness is associated with a significant burden of physical, emotional and psychosocial morbidity. Recovery can be protracted and incomplete, with important and sustained effects upon everyday life, including family life, social participation and return to work. In stark contrast with other critically ill patient groups (eg, those following cardiothoracic surgery), there are comparatively few interventional studies of rehabilitation among the general intensive care unit patient population. This paper outlines the protocol for a sub study of the RECOVER study: a randomised controlled trial evaluating a complex intervention of enhanced ward-based rehabilitation for patients following discharge from intensive care. Methods and analysis: The RELINQUISH study is a nested longitudinal, qualitative study of family support and perceived healthcare needs among RECOVER participants at key stages of the recovery process and at up to 1 year following hospital discharge. Its central premise is that recovery is a dynamic process wherein patients’ needs evolve over time. RELINQUISH is novel in that we will incorporate two parallel strategies into our data analysis: (1) a pragmatic health services-oriented approach, using an a priori analytical construct, the ‘Timing it Right’ framework and (2) a constructivist grounded theory approach which allows the emergence of new themes and theoretical understandings from the data. We will subsequently use Qualitative Health Needs Assessment methodology to inform the development of timely and responsive healthcare interventions throughout the recovery process. Ethics and dissemination: The protocol has been approved by the Lothian Research Ethics Committee (protocol number HSRU011). The study has been added to the UK Clinical Research Network Database (study ID. 9986). The authors will disseminate the findings in peer reviewed publications and to relevant critical care stakeholder groups.

Perspetiva atual e futura da nova regulamentação da investigação clínica

A investigação clínica na Europa, e em particular em Portugal, tem vindo a perder competitividade, uma situação preocupante face aos benefícios que a investigação representa para os doentes, instituições, profissionais de saúde e comunidade científica. O quadro regulamentar da investigação clínica em Portugal sofreu alterações significativas em 2014 com a implementação da Lei n.º 21/2014. Adicionalmente, o Regulamento UE n.º 536/2014, publicado no mesmo ano, será implementado a partir de maio de 2016, entrando diretamente em vigor nos países membros. Esta nova regulamentação contribuiu positivamente para o desenvolvimento da investigação clínica em Portugal. No entanto é fundamental colocar em prática todas a medidas promulgadas para que haja um crescimento sustentado do número de estudos clínicos em Portugal.

Reading Performance in Children with Visual Function Anomalies

Aims: To compare reading performance in children with and without visual function anomalies and identify the influence of abnormal visual function and other variables in reading ability. Methods: A cross-sectional study was carried in 110 children of school age (6-11 years) with Abnormal Visual Function (AVF) and 562 children with Normal Visual Function (NVF). An orthoptic assessment (visual acuity, ocular alignment, near point of convergence and accommodation, stereopsis and vergences) and autorefraction was carried out. Oral reading was analyzed (list of 34 words). Number of errors, accuracy (percentage of success) and reading speed (words per minute - wpm) were used as reading indicators. Sociodemographic information from parents (n=670) and teachers (n=34) was obtained. Results: Children with AVF had a higher number of errors (AVF=3.00 errors; NVF=1.00 errors; p<0.001), a lower accuracy (AVF=91.18%; NVF=97.06%; p<0.001) and reading speed (AVF=24.71 wpm; NVF=27.39 wpm; p=0.007). Reading speed in the 3rd school grade was not statistically different between the two groups (AVF=31.41 wpm; NVF=32.54 wpm; p=0.113). Children with uncorrected hyperopia (p=0.003) and astigmatism (p=0.019) had worst reading performance. Children in 2nd, 3rd, or 4th grades presented a lower risk of having reading impairment when compared with the 1st grade. Conclusion: Children with AVF had reading impairment in the first school grade. It seems that reading abilities have a wide variation and this disparity lessens in older children. The slow reading characteristics of the children with AVF are similar to dyslexic children, which suggest the need for an eye evaluation before classifying the children as dyslexic.

Improving drug discovery using hybrid softcomputing methods

Virtual screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. Most VS methods suppose a unique binding site for the target, but it has been demonstrated that diverse ligands interact with unrelated parts of the target and many VS methods do not take into account this relevant fact. This problem is circumvented by a novel VS methodology named BINDSURF that scans the whole protein surface in order to find new hotspots, where ligands might potentially interact with, and which is implemented in last generation massively parallel GPU hardware, allowing fast processing of large ligand databases. BINDSURF can thus be used in drug discovery, drug design, drug repurposing and therefore helps considerably in clinical research. However, the accuracy of most VS methods and concretely BINDSURF is constrained by limitations in the scoring function that describes biomolecular interactions, and even nowadays these uncertainties are not completely understood. In order to improve accuracy of the scoring functions used in BINDSURF we propose a hybrid novel approach where neural networks (NNET) and support vector machines (SVM) methods are trained with databases of known active (drugs) and inactive compounds, being this information exploited afterwards to improve BINDSURF VS predictions.

Improvement of Virtual Screening Predictions using Computational Intelligence Methods

Virtual Screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. However, the accuracy of most VS methods is constrained by limitations in the scoring function that describes biomolecular interactions, and even nowadays these uncertainties are not completely understood. In order to improve accuracy of scoring functions used in most VS methods we propose a hybrid novel approach where neural networks (NNET) and support vector machines (SVM) methods are trained with databases of known active (drugs) and inactive compounds, this information being exploited afterwards to improve VS predictions.

Improving drug discovery using a neural networks based parallel scoring function

Virtual Screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. Most VS methods suppose a unique binding site for the target, but it has been demonstrated that diverse ligands interact with unrelated parts of the target and many VS methods do not take into account this relevant fact. This problem is circumvented by a novel VS methodology named BINDSURF that scans the whole protein surface to find new hotspots, where ligands might potentially interact with, and which is implemented in massively parallel Graphics Processing Units, allowing fast processing of large ligand databases. BINDSURF can thus be used in drug discovery, drug design, drug repurposing and therefore helps considerably in clinical research. However, the accuracy of most VS methods is constrained by limitations in the scoring function that describes biomolecular interactions, and even nowadays these uncertainties are not completely understood. In order to solve this problem, we propose a novel approach where neural networks are trained with databases of known active (drugs) and inactive compounds, and later used to improve VS predictions.

Meta-analysis and cross-validation of a hyperglycemic status predictor model based on salivary glucose

Poster presented at the First International Congress of CiiEM - From Basic Sciences To Clinical Research. Egas Moniz, Caparica, Portugal, 27-28 November 2015.

HPLC quantitative determination of acrylic monomers released from resins used in dental restoration

Poster presented at the First International Congress of CiiEM - From Basic Sciences To Clinical Research. Egas Moniz, Caparica, Portugal, 27-28 November 2015