Medical Test Results Research Articles

HRV-based Stress Level Assessment Using Very Short Recordings

The increased stress level of an individual often influences the medical test results. Heart rate variability (HRV) can be used to characterize stress level. Parameters in the time domain are preferred, as they make the assessment possible from relatively short (3 - 5 minute-long) recordings. Electrocardiographic signal (ECG) in Einthoven I lead and photoplethysmographic signal (PPG) at the fingertip were recorded in parallel. This paper analyzes the differences between the lengths of successive heart cycles (NN); the ratio of these differences exceeding 50 ms (pNN50) is considered to be a good measure of stress. The parameter triplet pNNtri has been defined dividing the differences of successive NN intervals into three categories: pNN0_20 (0 – 20 ms), pNN20_50 (20 – 50 ms) and pNN50 (greater than 50 ms). pNNtri characterizes the actual stress level significantly better (especially for senior persons) than pNN50 alone. NN intervals determined from PPG differ from those determined from ECG recorded in parallel.

The Effect of Medical Test to Belief Updating and Willingness to Pay for Health Insurance Premium: Evidences from Laboratory Experiment

Purpose: The objective of this study is to analyze the effect of the results of medical tests on three health indicators, i.e. blood pressure, cholesterol level, and blood glucose level, for belief updating and willingness to pay for health insurance. Specifically, this study examined whether individuals update their belief on their health status after being informed the results of their medical tests. This study also investigated whether there is a significant difference between the willingness to pay for the individuals who were informed about the results of their medical tests and of individuals who were not informed about the results of their medical tests. Approach: This study utilizes laboratory experiments. There are two groups in the experiments: the treatment group and the control group. The individuals in the treatment group receive information on the results of the medical tests which cover blood pressure, glucose level and cholesterol level tests. The individuals in the control group do not receive any information. We compare the willingness to pay between the treatment group and the control group. Results: There are significant differences in the value of willingness to pay for health insurance premium based on prior belief (individuals’ belief prior to the medical tests) and on posterior belief (individuals’ belief after the medical tests) between control group and treatment group. Belief updating occurs when there is a difference between prior belief and posterior belief due the presence of an event. Value: This work contributes to the better understanding about the individual decision making on health insurance purchase. Conclusion: The medical tests on blood pressure, cholesterol level, and glucose level significantly affect the willingness to pay for health insurance premium. There are significant changes in individual’s posterior belief due to the information provided by the medical tests. An individual’s willingness to pay for health insurance premium may change due to a change in his or her health status belief.

Feature extraction through parallel Probabilistic Principal Component Analysis for heart disease diagnosis

Automatic diagnosis of human diseases are mostly achieved through decision support systems. The performance of these systems is mainly dependent on the selection of the most relevant features. This becomes harder when the dataset contains missing values for the different features. Probabilistic Principal Component Analysis (PPCA) has reputation to deal with the problem of missing values of attributes. This research presents a methodology which uses the results of medical tests as input, extracts a reduced dimensional feature subset and provides diagnosis of heart disease. The proposed methodology extracts high impact features in new projection by using Probabilistic Principal Component Analysis (PPCA). PPCA extracts projection vectors which contribute in highest covariance and these projection vectors are used to reduce feature dimension. The selection of projection vectors is done through Parallel Analysis (PA). The feature subset with the reduced dimension is provided to radial basis function (RBF) kernel based Support Vector Machines (SVM). The RBF based SVM serves the purpose of classification into two categories i.e., Heart Patient (HP) and Normal Subject (NS). The proposed methodology is evaluated through accuracy, specificity and sensitivity over the three datasets of UCI i.e., Cleveland, Switzerland and Hungarian. The statistical results achieved through the proposed technique are presented in comparison to the existing research showing its impact. The proposed technique achieved an accuracy of 82.18%, 85.82% and 91.30% for Cleveland, Hungarian and Switzerland dataset respectively.

Psychosis and psoriasis, the skin talks the truth

IntroductionIt is well known about relation between skin and mind, not only due to their mutual origin, but also by their illness expression parallelism. We report a case to show that reciprocity.Personal antecedentsWoman, 42-year-old, single. She only suffers from a skin disease; mild psoriasis guttata placed in both elbows and knees. She treated it with local treatment (cortisone cream) during seasonal prutius and the lesions did not grow or expand. She was hospitalized due to psychotic symptoms (paranoid delusions with her colleagues) and started antipsychotics treatment (risperidone 12 mg per day and olanzapine 10 mg per night). By the same time, she suffered a psoriasis crisis. Her psoriatic plaques increased their sizes and her chest and both thighs were affected too. She complained about grave pruritus. All her medical test results were normal. After that, the patient improved her psychotics’ symptoms, but she started with agoraphobic signs and seclusion at home. Psoriasis were even worse than before and she needed metrotexate to treat it. Being introduced to escitalopram 15 mg per day, anxiety and depression symptoms disappeared and her grave psoriasis became the mild one that she knew.ConclusionSchizophrenia was associated with a greater variety of autoimmune diseases than was anticipated. Studies found evidence for a shared genetic etiology between schizophrenia and psoriasis. Despite that, we think that the study of psychopathology can amplify our understanding about the etiopathogenesis of psoriasis and associated mental disorders.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Computer-Aided Medical Diagnosis Using Bayesian Classifier - Decision Support System for Medical Diagnosis

This study employs a Bayesian framework to construct a Web-based decision support system for medical diagnosis. The purpose is to help users (patients and physicians) with issues pertinent to medical diagnosis decisions and to detect diseases with highest probability through the Bayesian framework. Users could perform a more accurate diagnosis with the prior/conditional probabilities obtained from selected data sets and compute the posterior probability using the Bayes theorem. The proposed system identifies diseases by analyzing symptoms or by analyzing medical test results. Currently the system detects different types of diseases that people suffer in their day-to-day lives (general diseases) with an average detection accuracy of 92.56%. System also detects complex diseases (e.g.: heart disease - 83.67%, breast cancer - 80.98%, liver disorders - 79.43%, lung cancer - 71.00%, primary tumor - 78.02%, etc.) based on the analysis of the medical test results. The proposed system enhances the quality, accuracy and efficiency of decisions in medical diagnosis since the use of Bayesian theorem allows this system to offer more accurate platform than the conventional systems. Other than that this web-based system provides value-added services in conjunction with CAD system, such as; e-Chat & e-Channeling. More importantly, the targeted user group will be able to access the system as a software element freely and quickly. In this way the goal of this study – which is to provide a web-based medical diagnosis system is effectively achieved. KEYWORDS: Bayesian framework, medical decision support systems, computer-aided medical diagnosis, probability distributions, diseases

Computer-Aided Medical Diagnosis Using Bayesian Classifier - Decision Support System for Medical Diagnosis

This study employs a Bayesian framework to construct a Web-based decision support system for medical diagnosis. The purpose is to help users (patients and physicians) with issues pertinent to medical diagnosis decisions and to detect diseases with highest probability through the Bayesian framework. Users could perform a more accurate diagnosis with the prior/conditional probabilities obtained from selected data sets and compute the posterior probability using the Bayes theorem. The proposed system identifies diseases by analyzing symptoms or by analyzing medical test results. Currently the system detects different types of diseases that people suffer in their day-to-day lives (general diseases) with an average detection accuracy of 92.56%. System also detects complex diseases (e.g.: heart disease - 83.67%, breast cancer - 80.98%, liver disorders - 79.43%, lung cancer - 71.00%, primary tumor - 78.02%, etc.) based on the analysis of the medical test results. The proposed system enhances the quality, accuracy and efficiency of decisions in medical diagnosis since the use of Bayesian theorem allows this system to offer more accurate platform than the conventional systems. Other than that this web-based system provides value-added services in conjunction with CAD system, such as; e-Chat & e-Channeling. More importantly, the targeted user group will be able to access the system as a software element freely and quickly. In this way the goal of this study – which is to provide a web-based medical diagnosis system is effectively achieved. KEYWORDS: Bayesian framework, medical decision support systems, computer-aided medical diagnosis, probability distributions, diseases

PP59. SERVICE EVALUATION OF INFORMATION PROVISION TO PATIENTS WITH TUMOURS OF THE CENTRAL NERVOUS SYSTEM IN NINEWELLS HOSPITAL, DUNDEE

BACKGROUND: A recent report from the Brain Tumour Charity (BTC) found that 52% of patients with brain tumours felt the NHS did not give brain tumour patients the attention they required and 29% were dissatisfied with how health professionals addressed their condition. Poor information provision was one reason for low satisfaction. The 2014 NCPES report found that 25% of patients felt that side effects of treatment were not explained satisfactorily. METHODS: Service evaluation of Ninewells Hospital, Dundee was performed, between September 2015 and February 2016 at the CNS cancer outpatient clinic. The EORTC QLQ-INFO25 questionnaire was used to evaluate information provision to patients. Domains assessed included information relating to disease; medical tests; treatment; and other services. QLQ-INFO25 uses a 1–4 Likert scale with 1 representing the lowest level of information and 4 the highest. Scores were linearly converted to a 0–100 scale for the purposes of analysis. Patients were asked an additional eight ‘open’ questions to better allow patients to communicate their opinions and ideas relating to their care in a qualitative manner. RESULTS: Twenty-five patients returned questionnaires (eight patients left at least one question unanswered). Mean scores are reported for each question ±SD. The highest scores were for information relating to medical test results (87.3 ± 19.65), and to procedures of medical tests (84.85 ± 22.36). Lowest scores were for information received about causes of disease (36.84 ± 33.13) and about available rehabilitation services (43.33 ± 44.72). Other areas with low scores included information received about the effects of treatment on sexual activity (50.00 ± 36.60) as well as information about professional psychological support (48.48 ± 39.48). The overall score across all domains was 78.26 ± 23.80. 80% reported receiving written information at some point during their care. Responses to additional questions were largely positive and comments about staff complementary. Patients reported few difficulties getting to appointments. Three patients reported that the single thing done “less well during care” was the time to receive a scan/diagnosis. When asked what they would spend additional funding on, if available, 20% of patients said research into diagnosis and treatment. The remaining responses were variable, suggesting heterogeneity in CNS cancer patients’ priorities. 44% patients stated that nothing could be improved about their care. Possible improvements suggested included quicker scans, and for care to take place in a more local setting. CONCLUSIONS: It is unsurprising that levels of information provision are highest with regards to information received about medical tests and treatment, as most patients receive written information on these topics. The cause of CNS tumours is not completely understood, and so it is unsurprising that not all patients received this information. Information about other services may not always be addressed by the Ninewells hospital care team, as these services may be provided by other teams. These data will be used to implement changes to the CNS tumour service within Ninewells Hospital - particularly regarding psychological, social and sexual advice as well as other services - in order to improve information provision to patients in these highlighted domains.

The use of mobile technology in waiting rooms to leverage women's empowerment: A conceptual context.

This article focuses on a conceptual framework that can be applied to the use of mobile technology in the waiting room with the goal of empowering women recently diagnosed with abnormal Pap test results. It further describes trends which indicate a need for improved and timely information dissemination. Genecology practice outpatients report a predominant feeling of worry on receipt of abnormal medical test results, along with a clearly expressed wish for additional information. This research suggests that there is room for improvement in existing processes through use of mobile technology with carefully vetted materials which indicate a doctor is interested in the patient's well-being.

18F-FDG PET/CT for identifying the potential causes and extent of secondary hemophagocytic lymphohistiocytosis

We aimed to evaluate the value of 18F-FDG positron emission tomography/computed tomography (PET/CT) for identifying the possible causes of secondary hemophagocytic lymphohistiocytosis (HLH). Forty-five cases (17 female, 28 male; age, 17-79 years) with secondary HLH were included. The standard of reference for diagnosis in all patients was a combination of histology, clinical results (medical history, physical examination, and laboratory test results), and follow-up imaging for at least 12 months. All cases underwent 18F-FDG PET/CT to identify the possible trigger in HLH. Of 45 secondary HLH cases 10 (22.2%) were associated with infection, seven (15.6%) with rheumatic disease, and 28 (62.2%) with lymphoma. PET/CT images of 22 secondary HLH cases (48.9%) showed true positive results. PET/CT images demonstrated obvious tracer uptake in five of 10 secondary HLH cases with infection, one of three cases with lupus, two of two cases with rheumatoid arthritis, one of two cases with adult-onset Still disease, and 13 of 28 cases with lymphoma. PET/CT is helpful for identifying the possible trigger (infection or malignant disease) and extent of secondary HLH. However, PET/CT alone is not sufficient to make a correct differential diagnosis.

“We’ll call you when the results are in”: Preferences for how medical test results are delivered

ObjectiveWhether healthy or sick, adults undergo frequent medical testing; however, no guidelines currently exist as to how patients are informed of their medical test results. This short report provides an initial look at how healthcare professionals deliver medical test results and patient preferences regarding these procedures. MethodsWe specifically focus on two options for delivery of results: (1) open-ended timing, in which patients are contacted without warning when test results become available; or (2) closed-ended timing, in which patients are provided with a specific day and time when they will learn their test results. Participants who underwent a recent medical test indicated which delivery method their healthcare professional provided and their preferred method. ResultsFindings demonstrate a large discrepancy between actual and preferred timing, stemming from a general trend towards providing open-ended timing, whereas patient preferences were evenly split between the two options. ConclusionThis study provides a first step in understanding the merits of two options for delivering medical test results to patients and suggests an opportunity to improve patient care. Practice implicationsThe findings from this study provide first steps toward the development of guidelines for delivering test results in ways that maximize the quality of patient care.

Participation of Pharmacists in Emergency Care at Outpatient Clinics with Multiple Beds.

A major difference in medical flow between acute and nonacute medical care is the urgency of diagnosis and treatment. In the acute medical setting, diagnosis and treatment sometimes must be done almost simultaneously. Learning clinical management in the acute-care setting can be the basis of drug therapy in other clinical settings. When infusion is performed in emergency medicine, stabilization of blood pH is achieved through kidney and lung functions. At the same time, the oxygen transport capacity is monitored using blood gas analysis. One medical intervention can lead to multiple diagnostic and treatment processes in the emergency medical field. Most pharmacists rarely have the opportunity to learn about the reasoning process in which different body functions are linked together such as heart, lung, and kidney functions when performing infusions in emergency medicine before starting to work in the clinical setting. Learning from emergency medicine can be applied to drug therapy in other clinical settings as it teaches how to link different body functions and understand the relationships between those functions and the results of medical tests. These are considered to be necessary reasoning skills to understand patients' conditions in various clinical situations, including management in intensive care and the treatment of chronic disease. Knowledge of emergency medicine can be the foundation of drug therapy in other clinical settings, for example, the meanings of vital signs.

Predicting Medical Test Results and Intra-Operative Findings in Chronic Pain Patients Using the On-Line “Pain Validity Test”

Previous reports indicated The Pain Validity Test (PVT) can predict the presence of abnormalities on the correct medical testing, with 94% accuracy, and the absence of abnormalities on the correct medical testing with 85% accuracy, in patients with chronic back, neck or limb pain. However, 40%-71% of chronic pain patients are misdiagnosed, primarily because physicians use the wrong medical tests, or use tests, such as the MRI, which have a false negative rate as high as 78%. Rather than rely on inaccurate medical testing which is typically used, we conducted research to see if the Pain Validity Test could predict a more reliable and irrefutable indication of pathology, i.e. intra-operative findings. Prior to surgery, the Pain Validity Test (PVT) correctly predicted which patients had abnormal results on the correct medical tests with 94% accuracy, (r = 0.554; p < .0001). Of the original 149 patient studied in the original report, 74 patients had surgery. In the 71 patients with abnormal medical testing, the Pain Validity Test correctly predicted that 69 patients would have abnormal testing (97.1 %). Of the 74 patients with intra-operative pathology, the Pain Validity Test predicted 69 would have pathology (93.2%). Of the 69 patients predicted to have abnormal medical testing, 69 of the 69 had moderate or severe intra-operative pathology (100%), so there were no false positives. Two of the remaining 5 patients in whom the Pain Validity Test predicted no pathology, did have abnormal medical testing, and intra-operatively did have pathology. Three of the remaining 5 patients in whom the Pain Validity Test predicted no abnormal medical testing did not have abnormal testing, but intra-operatively, were found to have moderate pathology. Therefore, The Pain Validity Test can predict who will have a) abnormal medical testing with 97.1% accuracy (69/71) and b) regardless of pre-operative testing, will predict who will have intra-operative pathology if surgery is indicated with 93% accuracy (69/74).

Faktor-Faktor yang Berhubungan dengan Putus Berobat Pada Penderita TB Paru BTA Positif (+ ) di Wilayah Kerja Puskesmas Harapan Raya

Putus berobat adalah pasien yang tidak berobat 2 bulan berturut-turut atau lebih sebelum masa pengobatannya selesai. Angka putus berobat di Puskesmas Harapan Raya diperkirakan mencapai 40%. Akibat putus berobat adalah pasien bisa kebal terhadap obat (MDR=Multi Drugs Resisten). Penelitian ini dilakukan pada bulan Mei sampai Juni 2015. Penelitian ini bertujuan untuk melihat apakah umur, jenis kelamin, tidak ada PMO dan kunjungan keyankes merupakan faktor –faktor yang berhubungan dengan putus berobat pada penderita TB Paru BTA +. Jenis penelitian ini bersifat kuantitatif observasional dengan desain kasus kontrol dimana sampel diambil dengan cara menghitung mundur jumlah kasus dan kontrol berdasarkan data TB 01 dengan jumlah sampel 120 sampel terdiri dari 60 sampel kasus dan 60 sampel kontrol yang dilaksanakan di wilayah kerja Puskesmas Harapan Raya. Alat ukur yang digunakan adalah Data TB 01. Analisis data untuk uji bivariat dengan uji chisquare. Hasil penelitian yaitu ada hubungan antara putus berobat dengan umur diperoleh Pvalue 0,011 (OR= 3,500), tidak ada hubungan putus berobat dengan jenis kelamin diperoleh Pvalue 0,180 (OR= 1,807), ada hubungan putus berobat dengan tidak ada PMO diperoleh Pvalue 0,004 (OR= 3,778) dan ada hubungan putus berobat dengan kunjungan keyankes diperoleh Pvalue 0,001 (OR= 6,057). Sebagai kesimpulan dari penelitian ini dapat dikatakan bahwa antara umur, ada tidaknya PMO dan kunjungan keyankes merupakan faktor resiko putus berobat dan dari hasil uji chi-square jenis kelamin merupakan bukan faktor resiko terjadinya putus berobat pada penderita TB Paru BTA +. Saran bagi petugas kesehatan Puskesmas agar lebih menekankan bagi penderita TB Paru yang berusia produktif agar melakukan pengobatan hingga tuntas, memiliki PMO, memberi dorongan agar pengobatannya termotivasi dari diri sendiri

Natural Frequencies Do Not Foster Public Understanding of Medical Test Results.

Major organizations recommend presenting medical test results in terms of natural frequencies, rather than single-event probabilities. The evidence, however, is that natural frequency presentations benefit at most one-fifth of samples of health service users and patients. Only one study reported a substantial benefit of these presentations. Here, we replicate that study, testing online survey respondents. Study 1 attributed the previously reported benefit of natural frequencies to a scoring artifact. Study 2 showed that natural frequencies may elicit evaluations that conflict with the normatively correct one, potentially hindering informed decision making. Ironically, these evaluations occurred less often when respondents reasoned about single-event probabilities. These results suggest caution in promoting natural frequencies as the best way to communicate medical test data to health service users and patients.

Implementation of Cloud based Electronic Health Record (EHR) for Indian Healthcare Needs

Background/Objectives: EHR means the digital version of the patients medical report, in store the data in real time, it contains medication and treatment history which includes the broader view of patients care and it also contains patients medical history, diagnosis, medications, treatment plans, immunization data, allergies, radiology images, laboratory and test results. Methods/Statistical Analysis: The main intention of EHR is to have access to evidence based tools that health providers can make use to make decision and disease diagnosis about the patients care delivery. The current population of India (2014) is 1.27 billion. About 72.2% of the population lives in some 638,000 villages and the rest 27.8% in about 5,480 towns and urban agglomerations. Findings: In our proposed work we develop Electronic Health Records (EHR) to integrate with the health care providers all over India and to implement it with the cloud infrastructure. The main challenges that are addressed in this works are, handling heterogeneous data, data storage, use of data analytics tool for decision making, data privacy and the data security. Application/Improvements: This can be used to integrate the healthcare management system. Once implemented it provides remote medication, vaccination management, disease diagnosis, remote diagnosis and remote real time monitoring and personal health record.

Normal Reference Values for Doppler Echocardiography: Influences of Ageing, Gender and Ethnicity.

Normal Reference Values for Doppler Echocardiography: Influences of Ageing, Gender and Ethnicity.

자기조직화지도 신경망을 활용한 의료 진단검사 결과 패턴인식 모델

의학 및 생물학계에서 질병의 조기 선별이나 진단을 위해 인체에서 발생하는 각종 검체에 대해 다양한 진단검사가 시행되고 있고, 진단검사 결과 데이터는 질환을 표지하는 정보를 가지고 있기에 정확한 분석과 해석이 수행되어야 한다. 의료기관에서 수행하는 다양한 유형의 의료 진단검사로부터 발생하는 대용량 데이터를 최적의 분석 방법을 활용하여 정보 및 지식화 함으로써 이를 기준으로 양질의 의료서비스를 제공할 수 있는 기반을 구축할 필요가 있고 최근 이러한 노력이 수행되고 있다. 본 연구는 의료 진단검사 결과 데이터에 존재하는 검사결과 패턴들을 추출하고 분류하여, 의료진의 신속․정확한 의사결정과 종합적인 통찰력 향상을 지원할 수 있는 의료 진단검사 결과 패턴인식 모델을 제안한다. 제안 모델의 1단계에서는 자기조직화지도 신경망을 활용하여 의료 검사 데이터에 존재하는 유의한 진단검사 결과 패턴들을 추출한다. 최적의 진단검사 결과 패턴만을 추출하기 위해, 본 연구에서 제안한 모델에서는 Davies-Bouldin 지수를 산출하여 최적의 패턴 수를 결정하고 이를 반영하여 자기조직화지도 신경망을 사용하여 패턴을 추출한다. 제안 모델의 2단계에서는 신규 수진자의 진단검사 결과 데이터가 발생하면 1단계에서 추출했던 최적의 진단검사 결과 패턴들과의 내적 값을 산출하여 유사도 수준을 규명하여 신규 수진자의 진단검사 결과 패턴으로 분류한다. 본 연구에서 제안한 패턴인식 모델을 국내에서 다양한 의료 진단검사를 수행하는 의료기관에서 수행한 89종의 혈액 진단검사 데이터 집합에 적용함으로써 실무 적용의 타당성을 검증하였다. 제안 모델의 적용을 통해, 우선적으로 수진자의 성별과 연령대별로 존재하는 89종 혈액 검사결과 패턴들을 추출하였다. 이를 통해, 성별과 연령대별로 유의하게 존재하는 89종 혈액 검사의 중요한 특징과 경향 및 수진자 개별로 존재하는 특징 및 경향이 무엇인지 쉽게 확인할 수 있었다. 또한, 추출한 진단검사 결과 패턴들을 기준으로 신규 수진자의 혈액 검사 데이터를 패턴 매칭함으로써, 신규 수진자의 진단검사 결과 패턴을 분류하였다. 이와 같은 결과로부터, 본 연구에서 제안한 진단검사 결과 패턴인식 모델이 의료기관에서 발생하는 대용량 데이터의 분석 및 가공을 통해 의료기관의 의료 정보 및 지식 관리 실무에 효과적으로 활용될 수 있음을 확인할 수 있었다. 본 연구는 Davies-Bouldin 지수와 자기조직화지도 신경망의 논리적인 연계 활용과 자기조직화 신경망 기반의 지식 추출 및 지식 활용 과정을 구체적으로 제시하는 패턴인식 모델을 검증하였다는 점에서 학술적 의의가 있다.

Patient Preferences for Receiving Reports of Test Results.

The general public's preferences for modes of communication (other than in-person communication) for medical test results were investigated. We hypothesized that patients would prefer a variety of methods to receive common tests results (blood cholesterol and colonoscopy) compared with genetics test results. This study was a cross-sectional survey. A total of 409 participants responded to the survey. Among these participants, ≥50% reported that they were comfortable receiving results for a blood cholesterol test or colonoscopy via 4 of the 7 non-in-person communication methods (password-protected website, personal voicemail, personal E-mail, and letter were preferred over home voicemail, fax, and mobile phone text message). In comparison, >50% of participants were comfortable with only 1 non-in-person communication method for non-HIV sexually transmitted infections (STIs) and none for genetic tests. Patients were least comfortable receiving any information via fax, regardless of test type. There were statistical differences among comfort levels for blood cholesterol and colonoscopy tests and both STIs and genetic testing for personal voicemail, personal E-mail, mobile phone text message, and password-protected website, but there were no differences between STIs and genetic testing. No correlation was found between "familiarity" with test and "comfort" of receiving information about specific test. Participants demonstrated preferences in how they received test results by non-in-person communication methods, preferring personal E-mail and password-protected websites, but did not prefer fax. Importantly, participants also demonstrated that preference was dependent on test type.

Doctor, what does my positive test mean? From Bayesian textbook tasks to personalized risk communication.

Most of the research on Bayesian reasoning aims to answer theoretical questions about the extent to which people are able to update their beliefs according to Bayes' Theorem, about the evolutionary nature of Bayesian inference, or about the role of cognitive abilities in Bayesian inference. Few studies aim to answer practical, mainly health-related questions, such as, “What does it mean to have a positive test in a context of cancer screening?” or “What is the best way to communicate a medical test result so a patient will understand it?”. This type of research aims to translate empirical findings into effective ways of providing risk information. In addition, the applied research often adopts the paradigms and methods of the theoretically-motivated research. But sometimes it works the other way around, and the theoretical research borrows the importance of the practical question in the medical context. The study of Bayesian reasoning is relevant to risk communication in that, to be as useful as possible, applied research should employ specifically tailored methods and contexts specific to the recipients of the risk information. In this paper, we concentrate on the communication of the result of medical tests and outline the epidemiological and test parameters that affect the predictive power of a test—whether it is correct or not. Building on this, we draw up recommendations for better practice to convey the results of medical tests that could inform health policy makers (What are the drawbacks of mass screenings?), be used by health practitioners and, in turn, help patients to make better and more informed decisions.

FDG PET and Split-Bolus Multi-Detector Row CT Fusion Imaging in Oncologic Patients: Preliminary Results.

To assess the incremental value of split-bolus multidetector computed tomography (CT) combined with fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET) for follow-up of oncologic patients. The institutional ethics committee approved the use of this protocol. Thirty-eight oncologic patients who underwent FDG PET/unenhanced multidetector CT and split-bolus multidetector CT for restaging were investigated retrospectively. The split-bolus CT protocol included imaging during the hepatic arterial and portal venous phases in one scan. Software was used for fusion of the independently acquired FDG PET and split-bolus CT data, and fused datasets were compared with FDG PET/unenhanced CT data. The standard of reference for diagnosis of lesions in all patients was a combination of histologic results (if available), clinical results (medical history, physical examination, and laboratory test results), and the results of follow-up imaging (conventional CT, magnetic resonance imaging, and/or ultrasonography) for at least 6 months. Descriptive statistics were used. Fifty-nine true-positive lesions were identified with fused FDG PET/split-bolus CT; 41 were concordant and detected with both split-bolus CT and PET/unenhanced CT, 16 with split-bolus CT only, and two with PET/unenhanced CT. Two different false-positive lesions were identified with PET/unenhanced CT and PET/split-bolus CT. Furthermore, in 20 of 38 (53%) patients, FDG PET/split-bolus CT allowed detection of important additional findings (n = 40) not detected at FDG PET/unenhanced CT. Both the tumor-related findings (n = 13, 32.5%) and the non-tumor-related findings (n = 27, 67.5%) were important to the clinical treatment of these patients. Fused FDG PET/split-bolus multidetector CT provides additional information compared with FDG PET/unenhanced multidetector CT in oncologic patients.