This project set out to derive a prediction rule based on preoperative clinical variables to identify patients with high risk of developing atrial fibrillation following cardiac surgery. Methods: Prospectively collected data from a perioperative database was corroborated with chart review to identify eligible patients who had non-emergent surgery in 2010. Details on 28 preoperative variables were collected and significant predictors (p<0.2) were inserted into multivariable logistic regression and recursive partitioning. Results: 305 (30.5%) of 999 patients developed new onset postoperative atrial fibrillation. Eleven variables were significantly associated with atrial fibrillation, however, both final models included only three: left atrial dilatation, mitral valve disease and age. Bootstrapping with 5000 samples confirmed that both final models provide consistent predictions. Coefficients from the logistic regression model were converted into a simple seven point predictive score. Conclusions: This simple risk score can identify patients at higher risk of developing atrial fibrillation after cardiac surgery.

Defined as a platelet count <100x109/L with no known cause, immune thrombocytopenia (ITP) is a diagnosis of exclusion, meaning other thrombocytopenic conditions must be ruled out before establishing the ITP diagnosis. This can lead to errors, unnecessary exposures to expensive and harmful treatments, and increased patient anxiety and distress. In the absence of a standardized diagnostic test, a clinical prediction model, called the Predict-ITP tool, was developed to aid hematologists in establishing the ITP diagnosis among patients who present with thrombocytopenia. Based on a cohort of 839 patients referred to an academic hematology clinic and using penalized logistic regression, the following predictor variables for the ITP diagnosis were identified: 1) high platelet variability index; 2) lowest platelet count; 3) highest mean platelet volume; and 4) history of a major bleed. Internal validation was completed using bootstrap resampling, and showed good discrimination and excellent calibration. Following internal validation and prior to implementation, the Predict-ITP Tool must undergo external validation by evaluating the tool’s performance in a different cohort. A study protocol was developed with the objective of externally validating the Predict-ITP Tool by collecting data from 960 patients from 11 clinics across Canada. The tool will compute the probability of ITP using information available at the time of the initial consultation, and results will be compared with either the local hematologist’s diagnosis at the end of follow-up or the adjudicated diagnosis. Discrimination (the ability to differentiate between patients with and without ITP) and calibration (the agreement between predicted and actual classifications) of the tool will be assessed. The Predict-ITP Tool must demonstrate good discrimination (c-statistic ≥ 0.8) and excellent calibration (calibration-in-the-large close to 0; calibration slope close to 1) to achieve external validation. If implemented, this tool will improve diagnostic accuracy and reduce delays in diagnosis and unnecessary treatments and investigations. / Thesis / Master of Science (MSc) / There lack of a standardized test to diagnose immune thrombocytopenia (ITP) leads to delays in care, use of incorrect treatments, and increased patient anxiety. The Predict-ITP Tool was developed to classify patients as ITP or non-ITP using the following data: 1) platelet counts in the recent past; 2) the highest mean platelet volume; and 3) major bleeding at any time in the past. The preliminary internal validation study showed promise. I developed a study protocol to externally validate the Predict-ITP Tool that will collect data from 960 patients from 11 clinics across Canada to see how accurately the tool would have performed to classify patients as ITP or non-ITP at the first hematology visit compared with the gold standard clinical diagnosis by the hematologist or an independent expert committee. A successful external validation that demonstrates the tool’s predictive accuracy in an external population must be completed before widespread use.

京都大学 / 新制・課程博士 / 博士(医学) / 甲第25182号 / 医博第5068号 / 京都大学大学院医学研究科医学専攻 / (主査)教授 今中 雄一, 教授 西浦 博, 教授 村井 俊哉 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

Background: Patients with primary reports of neck pain often present with impairments of mobility, proprioception and motor control within the cervical spine, and these impairments can negatively impact patient outcomes. Cervical spine manipulation (CSM), which involves the use of thrust techniques, has been shown to be effective for some patients presenting with a primary report of neck pain. It would be useful for clinicians to have a decision making tool, such as a clinical prediction rule (CPR), that could accurately identify that subgroup of patients that would respond dramatically to CSM. The purpose of this project was to develop that CPR. Research Design and Methods: A prospective, cohort study of consecutive patients referred to physical therapy with a primary complaint of neck pain. Eligible patients who consented to participate completed a series of self-report measures, and then received a detailed standardized history and physical examination consisting of a variety of factors commonly used to assess patients with neck pain. Regardless of the results of the clinical examination, all patients received a standardized treatment regimen consisting of CSM and exercise. Depending on response to treatment, patients were treated for one to two treatment sessions over approximately 1 week. At the end of their participation in the study, patients were classified as having experienced a successful outcome or not based on a well-accepted patient-reported reference standard of success, the Global Rating of Change Scale. Analysis: Sensitivity, specificity, and positive and negative likelihood ratios were calculated for all potential predictor variables. Univariate techniques and step-wise logistic regression were used to determine the most parsimonious set of variables for prediction of treatment success. Variables retained in the regression model were used to develop a multivariate CPR to identify patients with neck pain likely to benefit from CSM. Results: Eighty-two patients were included in data analysis of which 32 (39%) had achieved a successful outcome. A CPR with 4 variables (symptom duration < 38 days, positive expectation that manipulation will help, difference in cervical rotation range of motion to either side ¡Ý 10 degrees, and pain with spring (PA) testing of the middle cervical spine) was identified. If 3 of the 4 variables (+LR 13.5) were present the chance of experiencing a successful outcome improved from 39% to 90%. Discussion: The CPR should improve decision-making for patients with neck pain by providing the ability to a priori identify patients with neck pain who are likely to benefit from CSM and exercise. However, this is only the first step in the process of developing and testing a CPR as future studies will be necessary to validate the results and should also include long-term follow-up and a comparison group to further examine the predictive value of the variables identified in the CPR.

京都大学 / 新制・課程博士 / 博士(社会健康医学) / 甲第24094号 / 社医博第125号 / 新制||社医||12(附属図書館) / 京都大学大学院医学研究科社会健康医学系専攻 / (主査)教授 佐藤 俊哉, 教授 中山 健夫, 教授 松田 秀一 / 学位規則第4条第1項該当 / Doctor of Public Health / Kyoto University / DFAM

京都大学 / 新制・課程博士 / 博士(医学) / 甲第24191号 / 医博第4885号 / 新制||医||1060(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 中山 健夫, 教授 松村 由美, 教授 万代 昌紀 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

Anterior knee pain (AKP) is a common, chronic lower limb musculoskeletal overuse condition that represents substantial morbidity to those affected, and has a significant impact on the health care industry. Health practitioners frequently prescribe foot orthoses in the management of AKP as an alternative or adjunct to multimodal physiotherapy. The primary aim of this thesis was to investigate the clinical efficacy of foot orthoses in AKP, utilising high-quality research methodologies. The two systematic reviews conducted have identified a significant gap in the literature regarding evidence from randomised clinical trials (RCTs) for foot orthoses in AKP and other lower limb overuse conditions. While the best evidence for AKP management was for multimodal physiotherapy, there was insufficient evidence to support or refute the use of foot orthoses in the treatment of lower limb overuse conditions, including AKP. Meta-analysis provided evidence to support the use of foot orthoses in the prevention of the first incidence of lower limb overuse conditions. An interesting finding was evidence from pooled and individual study data of no difference between custom and prefabricated foot orthoses in both treatment and prevention of lower limb overuse conditions, inferring that either type of orthosis may be utilised. Both systematic reviews highlighted substantial methodological flaws of the included studies, and recommended that future studies include larger participant numbers, longer participant follow-up, more consistent use of reliable and valid outcome measures and reporting of outcome data, and utilisation of the CONSORT guidelines in the design and reporting of RCTs. A 12-month prospective RCT investigated the short- and long-term clinical efficacy of prefabricated foot orthoses in the treatment of 179 participants with AKP. Foot orthoses were more effective than flat shoe inserts in the short term, implying that their contoured form has some therapeutic effect. Foot orthoses were not significantly different to multimodal physiotherapy over 12 months, nor was there any benefit in adding foot orthoses to physiotherapy. Considering that all groups experienced clinically meaningful long-term improvements in pain and function, clinicians may prescribe foot orthoses for AKP to hasten recovery. Findings of post-hoc analyses to develop a clinical prediction rule indicate that those of older age and shorter height, who have a lower severity of AKP and a more mobile midfoot, are more than twice as likely to experience a successful outcome with foot orthoses. As a secondary aim, this thesis has provided a more comprehensive profile of AKP as a condition. Baseline data from the RCT participants confirms previous reports of higher rates of AKP in females, and a tendency towards bilaterality and chronicity. This AKP sample did not differ from asymptomatic individuals in terms of body mass index, physical activity level, general and mental health, and foot posture, although they tended to have a more mobile foot under load. These characteristics tend to be homogenous across a number of published RCTs, indicating that the findings of the RCT described above are likely to be generalisable to the broader population with AKP. An additional finding in this group was that those with AKP of long duration, higher pain levels, lower functional levels, and an overall lower score on a specific measure of AKP have a poorer prognosis over 12 months, irrespective of their age, gender or morphometry. These findings suggest that, in order to improve prognosis and the chance of a successful outcome, the primary goals of intervention should be to reduce the severity and duration of AKP, through the use of early intervention with foot orthoses, multimodal physiotherapy, or a combination of the two.

Σκοπός της παρούσας διπλωματικής εργασίας είναι η ταξινόμηση κλινικών περιπτώσεων κοιλιακών αλγών και συγκεκριμένα περιπτώσεων σκωληκοειδίτιδας σε παιδιά ηλικίας μέχρι 14 ετών μέσω ενός εργαλείου που υλοποιούμε. Βασικός λόγος για τη κατασκευή αυτού του εργαλείου αποτέλεσε η δυσκολία στη πρόβλεψη της ασθένειας από τους ειδικούς (κατά μέσο όρο γίνονται 20% - 30% αχρείαστες εγχειρήσεις), η συχνή σύγχυσή της με άλλες περιπτώσεις κοιλιακών αλγών ενώ το ποσοστό θνησιμότητας στα παιδιά με σκωληκοειδίτιδα ποικίλλει από 0,1% - 1%. Βασισμένοι σε ένα σύνολο δεδομένων από τη Παιδοχειρουργική Κλινική του Πανεπιστημιακού Νοσοκομείου της Αλεξανδρούπολης, διεξάγουμε αναζήτηση των καλύτερων παραμέτρων για τη κατασκευή μοντέλων ταξινομητών βασισμένων στις τρεις παρακάτω τεχνικές Υπολογιστικής Νοημοσύνης: α) τα Τεχνητά Νευρωνικά Δίκτυα, β) τις Μηχανές Διανυσμάτων Υποστήριξης και γ) τα Τυχαία Δάση. Χρησιμοποιώντας ένα σύνολο 14 κλινικών και εργαστηριακών παραγόντων, υλοποιούμε μοντέλα ταξινομητών. Η βασική ιδέα για την υλοποίηση τους είναι η αντιμετώπιση των παρακάτω προβλημάτων: : α) έχει το παιδί σκωληκοειδίτιδα ή όχι; β) Αν έχει σκωληκοειδίτιδα, ποιος τρόπος αντιμετώπισής της ενδείκνυται: χειρουργική επέμβαση ή συντηρητική αγωγή; Μετά την εύρεση των βέλτιστων μοντέλων από κάθε μία από τις μεθόδους Υπολογιστικής Νοημοσύνης που χρησιμοποιήθηκαν, υλοποιήθηκε ένα εργαλείο εύχρηστης διεπαφής χρήστη στο προγραμματιστικό περιβάλλον της Matlab 2012a το οποίο ευελπιστούμε ότι θα υποβοηθήσει τους ειδικούς στη λήψη απόφασης για τη πορεία ενός νεαρού ασθενούς που εισέρχεται στο νοσοκομείο παραπονούμενος για σκωληκοειδίτιδα. Το εργαλείο αυτό ελέγχθηκε με καινούργια πραγματικά κλινικά δεδομένα από το Καραμανδάνειο Νοσοκομείο Παίδων Πατρών και η απόδοσή του ήταν ενθαρρυντική. / The purpose of this paper is the classification of clinical cases of abdominal pain and, to be more precise, the prediction of cases with acute appendicitis at children aged up to 14 years old through a tool that we implement. The main reasons for the construction of this tool are: a) the difficulty in the prediction of the appendicitis since the 20%-30% of the operations made from the experts for this disease are gratuitous, b) the frequent confusion that there is with other diseases that cause abdominal pain and c) the mortality rate at children with appendicitis varies from 0,1% to 1%. Based on a data set from the Department of the Child Surgery of the Hospital of the University of Alexandroupolis, we conduct a search of the best parameters for the construction of model classifiers based on the three following techniques of the Computational Intelligence: a) the Artificial Neural Networks, b) the Support Vector Machines and c) the Random Forests. The basic idea for the implementation of these models is, based on a sum of 14 clinical and laboratory factors, facing the following questions: a) if a child has appendicitis or not?, b) and if it does have appendicitis, which way should we follow to cure it: operational surgery or medication? After finding these best models, we implement a tool which is actually a Graphical User Interface of Matlab 2012a which we hope that will assist the experts in making the correct decision about a young patient that goes to the hospital complaining for appendicitis. This tool was tested on new real clinical data of patients of the Child Hospital of Patras and its performance was found really encouraging.

Objectives: Cardiovascular disease is the leading cause of mortality and morbidity in the developed world. Surgery can improve prognosis and relieve symptoms. Risk prediction models are increasingly being used to inform clinicians and patients about the risks of surgery, to facilitate clinical decision making and for the risk-adjustment of surgical outcome data. The importance of risk prediction models in cardiovascular surgery has been highlighted by the publication of cardiovascular surgery outcome data and the need for risk-adjustment. The overall objective of this thesis is to advance risk prediction modelling in cardiovascular surgery with a focus on the development of models for elective AAA repair and assessment of models for cardiac surgery. Methods: Three large clinical databases (two elective AAA repair and one cardiac surgery) were utilised. Each database was cleaned prior to analysis. Logistic regression was used to develop both regional and national risk prediction models for mortality following elective AAA repair. A regional model to identify the risk of developing renal failure following elective AAA repair was also developed. The performance of a widely used cardiac surgery risk prediction model (the logistic EuroSCORE) over time was evaluated using a national cardiac database. In addition an updated model version (EuroSCORE II) was validated and both models’ performance in emergency cardiac surgery was evaluated. Results: Regional risk models for mortality following elective AAA repair (VGNW model) and a model to predict post-operative renal failure were developed. Validation of the model for mortality using a national dataset demonstrated good performance compared to other available risk models. To improve generalisability a national model (the BAR score) with better discriminatory ability was developed. In a prospective validation of both models using regional data, the BAR score demonstrated excellent discrimination overall and good discrimination in procedural sub-groups. The EuroSCORE was found to have lost calibration over time due to a fall in observed mortality despite an increase in the predicted mortality of patients undergoing cardiac surgery. The EuroSCORE II demonstrated good performance for contemporary cardiac surgery. Both EuroSCORE models demonstrated inadequate performance for emergency cardiac surgery. Conclusions: Risk prediction models play an important role in cardiovascular surgery. Two accurate risk prediction models for mortality following elective AAA repair have been developed and can be used to risk-adjust surgical outcomes and facilitate clinical decision making. As surgical practice changes over time risk prediction models may lose accuracy which has implications for their application. Cardiac risk models may not be sufficiently accurate for high-risk patient groups such as those undergoing emergency surgery and specific emergency models may be required. Continuing research into new risk factors and model outcomes is needed and risk prediction models may play an increasing role in clinical decision making in the future.

Background: Coronary artery disease is a common cause of morbidity and mortality in the UK. Interventional revascularisation procedures for addressing the disease include percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG), which respectively seek to open up or bypass blocked arteries to restore blood flow to heart muscle. Rates at which these procedures are carried out have changed in recent years, as have clinical indications for referral. PCI is delivered by interventional cardiologists, while CABG is carried out by cardiothoracic surgeons, necessitating multi-disciplinary decision making. There is both within- and cross-speciality debate as to the optimal treatment strategy in some case types. Evaluation of the care provided is of clinical and political importance, and requires information about how post-procedure event rates per operator and hospital compare with those expected given the composition of patient populations. Methods: Two UK-wide audit databases of PCI and CABG procedures were used to explore a range of clinical outcome questions. The patient populations contained within each database were compared to see how they differed, and also how each had changed in recent years. In CABG patients, comparative effectiveness of two different surgical techniques (single vs bilateral mammary artery grafting) was assessed with respect to both short-term and long-term mortality outcomes. In PCI patients, a risk model to predict 30-day mortality was developed for use in clinical appraisal. Results: In both patient populations there had been changes to the relative frequencies of many characteristics over time. In the CABG population, multivariable analysis showed that patients undergoing single mammary artery grafting had lower odds of all-cause mortality within 30 days of procedure than those receiving bilateral mammary artery grafting, but had worse overall survival in the long term. In the PCI population, the developed risk model demonstrated good calibration and discrimination at predicting 30-day all-cause mortality. Discussion: The studies described above demonstrate that large-scale routinely collected data can be used to gain insights into clinical care quality and delivery. These resources are under-utilised at present; correcting this requires an understanding of the limitations of the data and how the information contained therein relates to actual clinical care.