Overuse, Overdose, Overdiagnosis… Overreaction?

When x-rays were first discovered, the harmful effects of radiation had to be manifest in the early users before they were known. Today, radiation protection and safety have been established and the effects of radiation, as well as its risks, are known. Even so, medical radiation, in particular the growth in the use of computed tomography (CT), has resulted in soaring radiation doses received by the population in general. Inappropriate use has resulted in overuse, overdose and, perhaps, overdiagnosis, especially when used in screening. In the quest to control and curb the use of procedures involving radiation, however, we must be careful not to provoke a pandemic of irrational fear of radiation. Overreaction to the overuse and overdose of radiation might deter patients from life-saving procedures

Structured reporting: if, why, when, how—and at what expense? Results of a focus group meeting of radiology professionals from eight countries

Purpose: To determine why, despite growing evidence that radiologists and referring physicians prefer structured reporting (SR) to free text (FT) reporting, SR has not been widely adopted in most radiology departments. Methods: A focus group was formed consisting of 11 radiology professionals from eight countries. Eight topics were submitted for discussion. The meeting was videotaped, transcribed, and analyzed according to the principles of qualitative healthcare research. Results: Perceived advantages of SR were facilitation of research, easy comparison, discouragement of ambiguous reports, embedded links to images, highlighting important findings, not having to dictate text nobody will read, and automatic translation of teleradiology reports. Being compelled to report within a rigid frame was judged unacceptable. Personal convictions appeared to have high emotional value. It was felt that other healthcare stakeholders would impose SR without regard to what radiologists thought of it. If the industry were to provide ready-made templates for selected examinations, most radiologists would use them. Conclusion: If radiologists can be convinced of the advantages of SR and the risks associated with failing to participate actively in its implementation, they will take a positive stand. The industry should propose technology allowing SR without compromising accuracy, completeness, workflows, and cost-benefit balance

Discerning Tumor Status from Unstructured MRI Reports—Completeness of Information in Existing Reports and Utility of Automated Natural Language Processing

Information in electronic medical records is often in an unstructured free-text format. This format presents challenges for expedient data retrieval and may fail to convey important findings. Natural language processing (NLP) is an emerging technique for rapid and efficient clinical data retrieval. While proven in disease detection, the utility of NLP in discerning disease progression from free-text reports is untested. We aimed to (1) assess whether unstructured radiology reports contained sufficient information for tumor status classification; (2) develop an NLP-based data extraction tool to determine tumor status from unstructured reports; and (3) compare NLP and human tumor status classification outcomes. Consecutive follow-up brain tumor magnetic resonance imaging reports (2000–­2007) from a tertiary center were manually annotated using consensus guidelines on tumor status. Reports were randomized to NLP training (70%) or testing (30%) groups. The NLP tool utilized a support vector machines model with statistical and rule-based outcomes. Most reports had sufficient information for tumor status classification, although 0.8% did not describe status despite reference to prior examinations. Tumor size was unreported in 68.7% of documents, while 50.3% lacked data on change magnitude when there was detectable progression or regression. Using retrospective human classification as the gold standard, NLP achieved 80.6% sensitivity and 91.6% specificity for tumor status determination (mean positive predictive value, 82.4%; negative predictive value, 92.0%). In conclusion, most reports contained sufficient information for tumor status determination, though variable features were used to describe status. NLP demonstrated good accuracy for tumor status classification and may have novel application for automated disease status classification from electronic databases

A Meta-Analysis of Probiotic Efficacy for Gastrointestinal Diseases

Background: Meta-analyses on the effects of probiotics on specific gastrointestinal diseases have generally shown positive effects on disease prevention and treatment; however, the relative efficacy of probiotic use for treatment and prevention across different gastrointestinal diseases, with differing etiology and mechanisms of action, has not been addressed. Methods/Principal Findings: We included randomized controlled trials in humans that used a specified probiotic in the treatment or prevention of Pouchitis, Infectious diarrhea, Irritable Bowel Syndrome, Helicobacter pylori, Clostridium difficile Disease, Antibiotic Associated Diarrhea, Traveler’s Diarrhea, or Necrotizing Enterocolitis. Random effects models were used to evaluate efficacy as pooled relative risks across the eight diseases as well as across probiotic species, single vs. multiple species, patient ages, dosages, and length of treatment. Probiotics had a positive significant effect across all eight gastrointestinal diseases with a relative risk of 0.58 (95 % (CI) 0.51–0.65). Six of the eight diseases: Pouchitis, Infectious diarrhea, Irritable Bowel Syndrome, Helicobacter pylori, Clostridium difficile Disease, and Antibiotic Associated Diarrhea, showed positive significant effects. Traveler’s Diarrhea and Necrotizing Enterocolitis did not show significant effects of probiotcs. Of the 11 species and species mixtures, all showed positive significant effects except for Lactobacillus acidophilus, Lactobacillus plantarum, and Bifidobacterium infantis. Across all diseases and probiotic species, positive significant effects of probiotics were observed for all age groups, single vs. multiple species, and treatment lengths

Reconstruction of the Core and Extended Regulons of Global Transcription Factors

The processes underlying the evolution of regulatory networks are unclear. To address this question, we used a comparative genomics approach that takes advantage of the large number of sequenced bacterial genomes to predict conserved and variable members of transcriptional regulatory networks across phylogenetically related organisms. Specifically, we developed a computational method to predict the conserved regulons of transcription factors across α-proteobacteria. We focused on the CRP/FNR super-family of transcription factors because it contains several well-characterized members, such as FNR, FixK, and DNR. While FNR, FixK, and DNR are each proposed to regulate different aspects of anaerobic metabolism, they are predicted to recognize very similar DNA target sequences, and they occur in various combinations among individual α-proteobacterial species. In this study, the composition of the respective FNR, FixK, or DNR conserved regulons across 87 α-proteobacterial species was predicted by comparing the phylogenetic profiles of the regulators with the profiles of putative target genes. The utility of our predictions was evaluated by experimentally characterizing the FnrL regulon (a FNR-type regulator) in the α-proteobacterium Rhodobacter sphaeroides. Our results show that this approach correctly predicted many regulon members, provided new insights into the biological functions of the respective regulons for these regulators, and suggested models for the evolution of the corresponding transcriptional networks. Our findings also predict that, at least for the FNR-type regulators, there is a core set of target genes conserved across many species. In addition, the members of the so-called extended regulons for the FNR-type regulators vary even among closely related species, possibly reflecting species-specific adaptation to environmental and other factors. The comparative genomics approach we developed is readily applicable to other regulatory networks

Conceptual Approach for the Design of Radiology Reporting Interfaces: The Talking Template

Within the coming decade, traditional dictation supported by human transcription for radiology reports will be replaced by one or more computerized methods. This paper discusses the cognitive and process efficiency problems arising from currently available technology including speech recognition and menu-driven interfaces. A specific concept for interaction with the reporting interface is proposed. This is called the „talking template” and departs from other designs by providing for all interactions to be mediated through audible prompts and microphone controls. The radiologist can recapture efficiency and cognitive focus by dictating while viewing images without the „look away” problem inherent in other interfaces