Taxiarchis Botsis

Current status and future perspectives in telecare for elderly people suffering from chronic diseases

Summary We reviewed the literature on home telecare for elderly patients suffering from chronic diseases. Articles published between 1990 and 2007 were identified via the PubMed database. The literature search yielded 485 papers. After reviewing the title and abstract from each, 54 were selected for closer examination. They were published in 37 different journals. The number of papers increased from one in 1997 to 14 in 2006. The diseases in which home telecare had been used were diabetes (14 studies), heart failure (13 studies), cognitive impairment (dementia and/or Alzheimers disease, 10 studies), chronic obstructive pulmonary disease (5 studies), chronic wounds (4 studies) and mobility disabilities (4 studies). Patients were generally satisfied with home telecare, but they preferred a combination of home telecare with conventional health-care delivery. Health-care professionals were positive about telecare. Users felt that on many occasions telecare led to a reduction in costs due to time savings and avoidance of travelling. Even though there were important benefits from home telecare, there are organizational, ethical, legal, design, usability and other matters that need to be resolved before widespread implementation can occur.

Home telecare technologies for the elderly.

There are many home telecare technologies which have been developed specifically for chronic diseases and there are some more generic technologies that could be used as well. For home telecare, the equipment must be certified, the operational routines must be reformed, the infrastructure must be in place, the market must be prepared, the health authorities must be convinced that the system will work and the cost-effectiveness must be evaluated. Organizational and societal changes, such as cost reduction policies and an aging population, are the main driving forces for the development of home telecare, especially for elderly patients. At the moment there is no holistic model for scientific evaluation from different perspectives (e.g. clinical, legal, technical). We suggest that more research on home telecare and its effects needs to be conducted, in order to provide evidence for optimizing the use of this promising technique.

Vaccine adverse event text mining system for extracting features from vaccine safety reports

OBJECTIVE To develop and evaluate a text mining system for extracting key clinical features from vaccine adverse event reporting system (VAERS) narratives to aid in the automated review of adverse event reports. DESIGN Based upon clinical significance to VAERS reviewing physicians, we defined the primary (diagnosis and cause of death) and secondary features (eg, symptoms) for extraction. We built a novel vaccine adverse event text mining (VaeTM) system based on a semantic text mining strategy. The performance of VaeTM was evaluated using a total of 300 VAERS reports in three sequential evaluations of 100 reports each. Moreover, we evaluated the VaeTM contribution to case classification; an information retrieval-based approach was used for the identification of anaphylaxis cases in a set of reports and was compared with two other methods: a dedicated text classifier and an online tool. MEASUREMENTS The performance metrics of VaeTM were text mining metrics: recall, precision and F-measure. We also conducted a qualitative difference analysis and calculated sensitivity and specificity for classification of anaphylaxis cases based on the above three approaches. RESULTS VaeTM performed best in extracting diagnosis, second level diagnosis, drug, vaccine, and lot number features (lenient F-measure in the third evaluation: 0.897, 0.817, 0.858, 0.874, and 0.914, respectively). In terms of case classification, high sensitivity was achieved (83.1%); this was equal and better compared to the text classifier (83.1%) and the online tool (40.7%), respectively. CONCLUSION Our VaeTM implementation of a semantic text mining strategy shows promise in providing accurate and efficient extraction of key features from VAERS narratives.

Molecular classification of nonsmall cell lung cancer using a 4-protein quantitative assay

The importance of definitive histological subclassification has increased as drug trials have shown benefit associated with histology in nonsmall‐cell lung cancer (NSCLC). The acuity of this problem is further exacerbated by the use of minimally invasive cytology samples. Here we describe the development and validation of a 4‐protein classifier that differentiates primary lung adenocarcinomas (AC) from squamous cell carcinomas (SCC).

Modeling prognostic Factors in Resectable pancreatic Adenocarcinomas

Background The accurate prognosis for patients with resectable pancreatic adenocarcinomas requires the incorporation of more factors than those included in AJCC TNM system. Methods We identified 218 patients diagnosed with stage I and II pancreatic adenocarcinoma at NewYork-Presbyterian Hospital/Columbia University Medical Center (1999 to 2009). Tumor and clinical characteristics were retrieved and associations with survival were assessed by univariate Cox analysis. A multivariable model was constructed and a prognostic score was calculated; the prognostic strength of our model was assessed with the concordance index. Results Our cohort had a median age of 67 years and consisted of 49% men; the median follow-up time was 14.3 months and the 5-year survival 3.6%. Age, tumor differentiation and size, alkaline phosphatase, albumin and CA 19–9 were the independent factors of the final multivariable model; patients were thus classified into low (n = 14, median survival = 53.7 months), intermediate (n = 124, median survival = 19.7 months) and high risk groups (n = 80, median survival = 12.3 months). The prognostic classification of our model remained significant after adjusting for adjuvant chemotherapy and the concordance index was 0.73 compared to 0.59 of the TNM system. Conclusion Our prognostic model was accurate in stratifying patients by risk and could be incorporated into clinical decisions.

Developing a multivariable prognostic model for pancreatic endocrine tumors using the clinical data warehouse resources of a single institution

OBJECTIVE: Current staging systems are not accurate for classifying pancreatic endocrine tumors (PETs) by risk. Here, we developed a prognostic model for PETs and compared it to the WHO classification system. METHODS: We identified 98 patients diagnosed with PET at NewYork-Presbyterian Hospital/Columbia University Medical Center (1999 to 2009). Tumor and clinical characteristics were retrieved and associations with survival were assessed by univariate Cox analysis. A multivariable model was constructed and a risk score was calculated; the prognostic strength of our model was assessed with the concordance index. RESULTS: Our cohort had median age of 60 years and consisted of 61.2% women; median follow-up time was 10.4 months (range: 0.1-99.6) with a 5-year survival of 61.5%. The majority of PETs were non-functional and no difference was observed between functional and non-functional tumors with respect to WHO stage, age, pathologic characteristics or survival. Distant metastases, aspartate aminotransferase-AST and surgical resection (HR=3.39, 95% CI: 1.38-8.35, p=0.008, HR=3.73, 95% CI: 1.20-11.57, p=0.023 and HR=0.20, 95% CI: 0.08-0.51, p<0.001 respectively) were the strongest predictors in the univariate analysis. Age, perineural and/or lymphovascular invasion, distant metastases and AST were the independent prognostic factors in the final multivariable model; a risk score was calculated and classified patients into low (n=40), intermediate (n=48) and high risk (n=10) groups. The concordance index of our model was 0.93 compared to 0.72 for the WHO system. CONCLUSION: Our prognostic model was highly accurate in stratifying patients by risk; novel approaches as such could thus be incorporated into clinical decisions.

Proof of concept for the role of glycemic control in the early detection of infections in diabetics

The relationship of infections and glycemic control in diabetes has been previously investigated but no solid findings have been described. Meanwhile, the detection of any infection at the early stages of disease progression, i.e. during the incubation period, is critical. In order to study this topic, we used the infection evidence and the daily glycemic control data of 248 type-2 diabetics who participated in a large telemedicine study. The results showed that morning blood glucose was significantly elevated and that diabetics performed the measurements at a later time when infected. A simple model for predicting the occurrence of infection based on the glycemic control variables showed good performance (sensitivity: 56%, specificity: 92%). A set of variables that synthesize a diabetic’s profile could be included in a dedicated model and facilitate the early detection of infections; other aspects, such as continuous self-monitoring and personalized medical records, should be examined in this direction.

Comment on Internet use for health-related purposes in Greece.

To the Editor: he authors of a recent paper in Telemedicine and e-Health by Halkias et al., “Internet use for health-related purposes among Greek consumers” (Vol. 14, No. 3, pp. 255–260), stated that their purpose was “to survey the extent of Internet use for health-related purposes among a representative sample of Greek consumers.” A representative sample is expected to have approximately the same distribution of characteristics as the population from which it was drawn. As declared by the authors, the population in this study is Greek consumers. Consequently, a sample of all ages, social classes, levels of education, and so on from the Greek population should be expected. However, the sample in this study included mainly young people: “More than 87% were 34 years or younger,” and “more than half...were under the age of 25.” Even if the age distribution issue is skipped, there is the gender distribution one: “female respondents outnumbered males ones at a ratio of almost 4-to-1.” Gender appears to be significant in a study by Pandey et al., who suggested that Internet use for health information is greater among women with higher levels of income.1 The authors mention that the sample was taken from “students of the Hellenic American Union and the Hellenic American University in Athens, Greece.” These two institutions do not at all represent the Greek university/college-level undergraduate and graduate education; the majority of Greek youth studies in public universities and schools. Also, the authors state that these institutions are “nonprofit.” Nevertheless, it should be mentioned that the students have to pay a quite respectable amount of tuition and other fees; the cost for a Master of Science program is more than 12,000 Euros and for the undergraduate level it is 465 Euros per course.2 So, only students of upper or middle social classes could afford such studies. At the same time, the majority of young Greeks (regardless their income) pay nothing for tuition, books, or additional material. Last but not least, the term “consumer” does not include healthy subjects only but also people with minor/major disabilities, chronic diseases, vulnerable populations, and so forth. Baker et al. found that poor health status was related to high rates of Internet use for health purposes.3 This parameter is not discussed throughout the paper as well, even though it is essential to evaluate the users’ needs before studying their initiative to seek health-related information. It seems that the aforementioned issues limit this study to the evaluation of Internet use for health-related purposes among a nonrepresentative sample of Greek consumers, which consists of a small number of students in a private institution in Greece. The numerous methodological limitations of this study and the bias they introduce could mislead the reader. The Andreassen et al. study4 that contains data from an extensive report for Greek consumers by Chronaki et al.5 could be recommended as a reliable source for this interesting and important topic. Comment on Internet Use for Health-Related Purposes in Greece

Point-of-care devices for healthy consumers - a feasibility study.

Point of care (POC) devices are small, portable instruments that perform diagnostic testing at the site of patient care, e.g. at the bedside. They may be useful in telemedicine because they have the potential to provide a rapid assessment of health status for a non-expert user. We are interested in the possible value of POC devices for longterm personal health monitoring of subjects at home. Internationally recognized organizations control the quality of POC devices and validate them before their introduction into service. For example, the Food and Drug Administration in the USA reviews medical devices and decides to approve or reject them, based partly on clinical trial data submitted by the manufacturers. We have investigated users’ attitudes towards the use of certain POC devices and their perceptions about the usability of the equipment.

Implementation of a Computerized System in an Oncology Unit

Information management is essential for health professionals in order to maintain a level of productivity for health care services management. This is significant when treating cancer patients. The main target of this study was to employ computers to enhance the daily practice of Oncology Unit (Sotiria Hospital, Athens, Greece). Accordingly, a computerized system was developed consisting of three modules: the EPR, the Image Archive, and the Lab Module. The EPR Module is a database application that stores clinical results, physician orders, and several administrative data. The Image Archive Module is used mainly for the reduction of images volume and the Lab Module stores information about the patient blood samples. These two modules interoperate through EPR Module under strict data security policies. Key physicians, biologists, and secretary personnel are involved in data entry and information management, while the system administrator is responsible for the system functioning. Improved health care, user satisfaction, and cost savings were the most important benefits gained with this system. The need of similar systems in oncology is crucial and could involve additional applications, such as quality of life (QoL) systems.