Predicting long-term outcome after acute ischemic stroke: a simple index works in patients from controlled clinical trials

Background and Purpose—An early and reliable prognosis for recovery in stroke patients is important for initiation of individual treatment and for informing patients and relatives. We recently developed and validated models for predicting survival and functional independence within 3 months after acute stroke, based on age and the National Institutes of Health Stroke Scale score assessed within 6 hours after stroke. Herein we demonstrate the applicability of our models in an independent sample of patients from controlled clinical trials. Methods—The prognostic models were used to predict survival and functional recovery in 5419 patients from the Virtual International Stroke Trials Archive (VISTA). Furthermore, we tried to improve the accuracy by adapting intercepts and estimating new model parameters. Results—The original models were able to correctly classify 70.4% (survival) and 72.9% (functional recovery) of patients. Because the prediction was slightly pessimistic for patients in the controlled trials, adapting the intercept improved the accuracy to 74.8% (survival) and 74.0% (functional recovery). Novel estimation of parameters, however, yielded no relevant further improvement. Conclusions—For acute ischemic stroke patients included in controlled trials, our easy-to-apply prognostic models based on age and National Institutes of Health Stroke Scale score correctly predicted survival and functional recovery after 3 months. Furthermore, a simple adaptation helps to adjust for a different prognosis and is recommended if a large data set is available. (Stroke. 2008;39:000-000.)

Outcome Prediction of Consciousness Disorders in the Acute Stage Based on a Complementary Motor Behavioural Tool.

INTRODUCTION: Attaining an accurate diagnosis in the acute phase for severely brain-damaged patients presenting Disorders of Consciousness (DOC) is crucial for prognostic validity; such a diagnosis determines further medical management, in terms of therapeutic choices and end-of-life decisions. However, DOC evaluation based on validated scales, such as the Revised Coma Recovery Scale (CRS-R), can lead to an underestimation of consciousness and to frequent misdiagnoses particularly in cases of cognitive motor dissociation due to other aetiologies. The purpose of this study is to determine the clinical signs that lead to a more accurate consciousness assessment allowing more reliable outcome prediction. METHODS: From the Unit of Acute Neurorehabilitation (University Hospital, Lausanne, Switzerland) between 2011 and 2014, we enrolled 33 DOC patients with a DOC diagnosis according to the CRS-R that had been established within 28 days of brain damage. The first CRS-R assessment established the initial diagnosis of Unresponsive Wakefulness Syndrome (UWS) in 20 patients and a Minimally Consciousness State (MCS) in the remaining13 patients. We clinically evaluated the patients over time using the CRS-R scale and concurrently from the beginning with complementary clinical items of a new observational Motor Behaviour Tool (MBT). Primary endpoint was outcome at unit discharge distinguishing two main classes of patients (DOC patients having emerged from DOC and those remaining in DOC) and 6 subclasses detailing the outcome of UWS and MCS patients, respectively. Based on CRS-R and MBT scores assessed separately and jointly, statistical testing was performed in the acute phase using a non-parametric Mann-Whitney U test; longitudinal CRS-R data were modelled with a Generalized Linear Model. RESULTS: Fifty-five per cent of the UWS patients and 77% of the MCS patients had emerged from DOC. First, statistical prediction of the first CRS-R scores did not permit outcome differentiation between classes; longitudinal regression modelling of the CRS-R data identified distinct outcome evolution, but not earlier than 19 days. Second, the MBT yielded a significant outcome predictability in the acute phase (p<0.02, sensitivity>0.81). Third, a statistical comparison of the CRS-R subscales weighted by MBT became significantly predictive for DOC outcome (p<0.02). DISCUSSION: The association of MBT and CRS-R scoring improves significantly the evaluation of consciousness and the predictability of outcome in the acute phase. Subtle motor behaviour assessment provides accurate insight into the amount and the content of consciousness even in the case of cognitive motor dissociation.

Agreement and clinical comparison between a new swept-source optical coherence tomography-based optical biometer and an optical low-coherence reflectometry biometer

Purpose To compare measurements taken using a swept-source optical coherence tomography-based optical biometer (IOLmaster 700) and an optical low-coherence reflectometry biometer (Lenstar 900), and to determine the clinical impacts of differences in their measurements on intraocular lens (IOL) power predictions. Methods Eighty eyes of 80 patients scheduled to undergo cataract surgery were examined with both biometers. The measurements made using each device were axial length (AL), central corneal thickness (CCT), aqueous depth (AQD), lens thickness (LT), mean keratometry (MK), white-to-white distance (WTW), and pupil diameter (PD). Holladay 2 and SRK/T formulas were used to calculate IOL power. Differences in measurement between the two biometers were determined using the paired t-test. Agreement was assessed through intraclass correlation coefficients (ICC) and Bland–Altman plots. Results Mean patient age was 76.3±6.8 years (range 59–89). Using the Lenstar, AL and PD could not be measured in 12.5 and 5.25% of eyes, respectively, while IOLMaster 700 took all measurements in all eyes. The variables CCT, AQD, LT, and MK varied significantly between the two biometers. According to ICCs, correlation between measurements made with both devices was excellent except for WTW and PD. Using the SRK/T formula, IOL power prediction based on the data from the two devices were statistically different, but differences were not clinically significant. Conclusions No clinically relevant differences were detected between the biometers in terms of their measurements and IOL power predictions. Using the IOLMaster 700, it was easier to obtain biometric measurements in eyes with less transparent ocular media or longer AL.

The Comparative Effectiveness of EEG Biomarkers in Antidepressant Response and Illness Prediction in Major Depressive Disorder

Thesis (Ph.D, Neuroscience Studies) -- Queen's University, 2016-08-27 00:55:35.782

Structured professional judgement approach to risk assessment: generalisability across patient groups for the prediction of adverse outcomes in secure mental health care

This is a redacted version of the the final thesis. Copyright material has been removed to comply with UK Copyright Law.

Using multivariate sequential patterns to improve survival prediction in intensive care burn unit

Resuscitation and stabilization are key issues in Intensive Care Burn Units and early survival predictions help to decide the best clinical action during these phases. Current survival scores of burns focus on clinical variables such as age or the body surface area. However, the evolution of other parameters (e.g. diuresis or fluid balance) during the first days is also valuable knowledge. In this work we suggest a methodology and we propose a Temporal Data Mining algorithm to estimate the survival condition from the patient’s evolution. Experiments conducted on 480 patients show the improvement of survival prediction.

Parental Rejection, Personality, and Depression in the Prediction of Suicidality in a Sample of Nonclinical Young Adults

This study tested a prediction model of suicidality in a sample of young adults. Predictor variables included perceived parental rejection, self-criticism, neediness, and depression. Participants (N 5 165) responded to the Depressive Experiences Questionnaire,theInventoryforAssessingMemoriesofParentalRearingBehavior, theCenterforEpidemiologicalStudiesDepressionScale,andtheSuicideBehaviors Questionnaire—Revised. Perceived parental rejection, personality, and depression wereassessedinitiallyatTime1,anddepressionagainandsuicidalitywereassessed 5 months later at Time 2. The proposed structural equation model fit the observed data well in a sample of young adults. Parental rejection demonstrated direct and indirect relationships with suicidality, and self-criticism and neediness each had indirect associations with suicidality. Depression was directly related to suicidality. Implications for clinical practice are discussed.

Applications of metrological techniques for clinical implementation of dosimetry and radiobiology in molecular radiotherapy

Molecular radiotherapy (MRT) is a fast developing and promising treatment for metastasised neuroendocrine tumours. Efficacy of MRT is based on the capability to selectively "deliver" radiation to tumour cells, minimizing administered dose to normal tissues. Outcome of MRT depends on the individual patient characteristics. For that reason, personalized treatment planning is important to improve outcomes of therapy. Dosimetry plays a key role in this setting, as it is the main physical quantity related to radiation effects on cells. Dosimetry in MRT consists in a complex series of procedures ranging from imaging quantification to dose calculation. This doctoral thesis focused on several aspects concerning the clinical implementation of absorbed dose calculations in MRT. Accuracy of SPECT/CT quantification was assessed in order to determine the optimal reconstruction parameters. A model of PVE correction was developed in order to improve the activity quantification in small volume, such us lesions in clinical patterns. Advanced dosimetric methods were compared with the aim of defining the most accurate modality, applicable in clinical routine. Also, for the first time on a large number of clinical cases, the overall uncertainty of tumour dose calculation was assessed. As part of the MRTDosimetry project, protocols for calibration of SPECT/CT systems and implementation of dosimetry were drawn up in order to provide standard guidelines to the clinics offering MRT. To estimate the risk of experiencing radio-toxicity side effects and the chance of inducing damage on neoplastic cells is crucial for patient selection and treatment planning. In this thesis, the NTCP and TCP models were derived based on clinical data as help to clinicians to decide the pharmaceutical dosage in relation to the therapy control and the limitation of damage to healthy tissues. Moreover, a model for tumour response prediction based on Machine Learning analysis was developed.

Challenges and Opportunities of Machine Learning for Clinical and Omics Data

Clinical and omics data are a promising field of application for machine learning techniques even though these methods are not yet systematically adopted in healthcare institutions. Despite artificial intelligence has proved successful in terms of prediction of pathologies or identification of their causes, the systematic adoption of these techniques still presents challenging issues due to the peculiarities of the analysed data. The aim of this thesis is to apply machine learning algorithms to both clinical and omics data sets in order to predict a patient's state of health and get better insights on the possible causes of the analysed diseases. In doing so, many of the arising issues when working with medical data will be discussed while possible solutions will be proposed to make machine learning provide feasible results and possibly become an effective and reliable support tool for healthcare systems.

Machine Learning methods for hepatocellular malignancies segmentation and MVI prediction

The aim of this thesis project is to automatically localize HCC tumors in the human liver and subsequently predict if the tumor will undergo microvascular infiltration (MVI), the initial stage of metastasis development. The input data for the work have been partially supplied by Sant'Orsola Hospital and partially downloaded from online medical databases. Two Unet models have been implemented for the automatic segmentation of the livers and the HCC malignancies within it. The segmentation models have been evaluated with the Intersection-over-Union and the Dice Coefficient metrics. The outcomes obtained for the liver automatic segmentation are quite good (IOU = 0.82; DC = 0.35); the outcomes obtained for the tumor automatic segmentation (IOU = 0.35; DC = 0.46) are, instead, affected by some limitations: it can be state that the algorithm is almost always able to detect the location of the tumor, but it tends to underestimate its dimensions. The purpose is to achieve the CT images of the HCC tumors, necessary for features extraction. The 14 Haralick features calculated from the 3D-GLCM, the 120 Radiomic features and the patients' clinical information are collected to build a dataset of 153 features. Now, the goal is to build a model able to discriminate, based on the features given, the tumors that will undergo MVI and those that will not. This task can be seen as a classification problem: each tumor needs to be classified either as “MVI positive” or “MVI negative”. Techniques for features selection are implemented to identify the most descriptive features for the problem at hand and then, a set of classification models are trained and compared. Among all, the models with the best performances (around 80-84% ± 8-15%) result to be the XGBoost Classifier, the SDG Classifier and the Logist Regression models (without penalization and with Lasso, Ridge or Elastic Net penalization).

The Clinical Impact Of Cerebellar Grey Matter Pathology In Multiple Sclerosis.

The cerebellum is an important site for cortical demyelination in multiple sclerosis, but the functional significance of this finding is not fully understood. To evaluate the clinical and cognitive impact of cerebellar grey-matter pathology in multiple sclerosis patients. Forty-two relapsing-remitting multiple sclerosis patients and 30 controls underwent clinical assessment including the Multiple Sclerosis Functional Composite, Expanded Disability Status Scale (EDSS) and cerebellar functional system (FS) score, and cognitive evaluation, including the Paced Auditory Serial Addition Test (PASAT) and the Symbol-Digit Modalities Test (SDMT). Magnetic resonance imaging was performed with a 3T scanner and variables of interest were: brain white-matter and cortical lesion load, cerebellar intracortical and leukocortical lesion volumes, and brain cortical and cerebellar white-matter and grey-matter volumes. After multivariate analysis high burden of cerebellar intracortical lesions was the only predictor for the EDSS (p<0.001), cerebellar FS (p = 0.002), arm function (p = 0.049), and for leg function (p<0.001). Patients with high burden of cerebellar leukocortical lesions had lower PASAT scores (p = 0.013), while patients with greater volumes of cerebellar intracortical lesions had worse SDMT scores (p = 0.015). Cerebellar grey-matter pathology is widely present and contributes to clinical dysfunction in relapsing-remitting multiple sclerosis patients, independently of brain grey-matter damage.

An Efficient Protocol For The Generation Of Monocyte Derived Dendritic Cells Using Serum-free Media For Clinical Applications In Post Remission Aml Patients.

Protocols for the generation of dendritic cells (DCs) using serum as a supplementation of culture media leads to reactions due to animal proteins and disease transmissions. Several types of serum-free media (SFM), based on good manufacture practices (GMP), have recently been used and seem to be a viable option. The aim of this study was to evaluate the results of the differentiation, maturation, and function of DCs from Acute Myeloid Leukemia patients (AML), generated in SFM and medium supplemented with autologous serum (AS). DCs were analyzed by phenotype characteristics, viability, and functionality. The results showed the possibility of generating viable DCs in all the conditions tested. In patients, the X-VIVO 15 medium was more efficient than the other media tested in the generation of DCs producing IL-12p70 (p=0.05). Moreover, the presence of AS led to a significant increase of IL-10 by DCs as compared with CellGro (p=0.05) and X-Vivo15 (p=0.05) media, both in patients and donors. We concluded that SFM was efficient in the production of DCs for immunotherapy in AML patients. However, the use of AS appears to interfere with the functional capacity of the generated DCs.

The Value Of The 2005 International Society Of Urological Pathology (isup) Modified Gleason Grading System As A Predictor Of Biochemical Recurrence After Radical Prostatectomy.

To compare time and risk to biochemical recurrence (BR) after radical prostatectomy of two chronologically different groups of patients using the standard and the modified Gleason system (MGS). Cohort 1 comprised biopsies of 197 patients graded according to the standard Gleason system (SGS) in the period 1997/2004, and cohort 2, 176 biopsies graded according to the modified system in the period 2005/2011. Time to BR was analyzed with the Kaplan-Meier product-limit analysis and prediction of shorter time to recurrence using univariate and multivariate Cox proportional hazards model. Patients in cohort 2 reflected time-related changes: striking increase in clinical stage T1c, systematic use of extended biopsies, and lower percentage of total length of cancer in millimeter in all cores. The MGS used in cohort 2 showed fewer biopsies with Gleason score ≤ 6 and more biopsies of the intermediate Gleason score 7. Time to BR using the Kaplan-Meier curves showed statistical significance using the MGS in cohort 2, but not the SGS in cohort 1. Only the MGS predicted shorter time to BR on univariate analysis and on multivariate analysis was an independent predictor. The results favor that the 2005 International Society of Urological Pathology modified system is a refinement of the Gleason grading and valuable for contemporary clinical practice.

Vascular Pattern In Enchondroma And Chondrosarcoma: Clinical And Immunohistologic Study.

Although cartilaginous tumors have low microvascular density, vessels are important for the provision of nutrition so that the tumor can grow and generate metastasis. The aim of this study was to assess the value of the vascular pattern classification as a prognostic tool in chondrosarcomas (CSs) and its relation with vascular endothelial growth factor (VEGF) expression. This was a retrospective study of 21 enchondromas and 57 conventional CSs. Clinical data and outcome were retrieved from medical files. CSs histologic grades (on a scale of 1 to 3) were determined according to the World Health Organization classification. The vascular pattern (on a scale of A to C) was assessed through CD34, according to Kalinski. CD105 and VEGF were also evaluated. Poor outcome was significantly associated with vascular pattern groups B and C. Higher vascular pattern were 6.5 times more frequent in moderate-grade and high-grade CSs than in grade 1 CS. On multivariate analysis, a clear correlation was found between VEGF overexpression and B/C vascular patterns. Only 18 (benign and malignant) tumors stained for CD105. The results point to the use of the vascular pattern classification as a prognostic tool in CSs and to differentiate low-grade from moderate-grade/high-grade CSs. Vascular pattern might be also used to complement histologic grade, VEGF immunostaining, and microvascular density, for indicating a patient's prognosis. Low-grade CSs develop under low neoangiogenesis, which conforms to the slow growth rate of these tumors.

Evaluation Of Different Treatment Methods Against Denture Stomatitis: A Randomized Clinical Study.

The aim of this clinical study was to determine the efficacy of Uncaria tomentosa (cat's claw) against denture stomatitis (DS). Fifty patients with DS were randomly assigned into 3 groups to receive 2% miconazole, placebo, or 2% U tomentosa gel. DS level was recorded immediately, after 1 week of treatment, and 1 week after treatment. The clinical effectiveness of each treatment was measured using Newton's criteria. Mycologic samples from palatal mucosa and prosthesis were obtained to determinate colony forming units per milliliter (CFU/mL) and fungal identification at each evaluation period. Candida species were identified with HiCrome Candida and API 20C AUX biochemical test. DS severity decreased in all groups (P < .05). A significant reduction in number of CFU/mL after 1 week (P < .05) was observed for all groups and remained after 14 days (P > .05). C albicans was the most prevalent microorganism before treatment, followed by C tropicalis, C glabrata, and C krusei, regardless of the group and time evaluated. U tomentosa gel had the same effect as 2% miconazole gel. U tomentosa gel is an effective topical adjuvant treatment for denture stomatitis.