Computerized history-taking improves data quality for clinical decision-making-Comparison of EHR and computer-acquired history data in patients with chest pain.

Patients' medical histories are the salient dataset for diagnosis. Prior work shows consistently, however, that medical history-taking by physicians generally is incomplete and not accurate. Such findings suggest that methods to improve the completeness and accuracy of medical history data could have clinical value. We address this issue with expert system software to enable automated history-taking by computers interacting directly with patients, i.e. computerized history-taking (CHT). Here we compare the completeness and accuracy of medical history data collected and recorded by physicians in electronic health records (EHR) with data collected by CHT for patients presenting to an emergency room with acute chest pain. Physician history-taking and CHT occurred at the same ED visit for all patients. CHT almost always preceded examination by a physician. Data fields analyzed were relevant to the differential diagnosis of chest pain and comprised information obtainable only by interviewing patients. Measures of data quality were completeness and consistency of negative and positive findings in EHR as compared with CHT datasets. Data significant for the differential of chest pain was missing randomly in all EHRs across all data items analyzed so that the dimensionality of EHR data was limited. CHT files were near complete for all data elements reviewed. Separate from the incompleteness of EHR data, there were frequent factual inconsistencies between EHR and CHT data across all data elements. EHR data did not contain representations of symptoms that were consistent with those reported by patients during CHT. Trial registration: This study is registered at https://www.clinicaltrials.gov (unique identifier: NCT03439449).

Radiation-Induced Chromosomal Breaks may be DNA Repair Fragile Sites with Larger-scale Correlations to Eight Double-Strand-Break Related Data Sets over the Human Genome.

In this work, we compared the genomic distribution of common radiation-induced chromosomal breaks to eight different data sets covering the whole human genome. Sites with a high probability of chromatid breakage after exposure to low and high ionization density radiations were often located inside common and rare fragile sites, indicating that they may be a new and more local type of DNA repair-related fragility. Breaks in specific chromosome bands after acute exposure to oil and benzene also showed strong correlation with these sites and fragile sites. In addition, close correlation was found with cytologically detected chiasma and MLH1 immunofluorescence sites and with the HapMap recombination density distributions. Also, of interest, copy number changes occurred predominantly at radiation-induced breaks and fragile sites, at least for breast cancers with poor prognosis, and they decreased weakly but significantly in regions with increasing recombination and CpG density. An increased CpG density is linked to regions of high gene density to secure high-fidelity reproduction and survival. To minimize cancer induction, cancer-related genes are often located in regions of decreased recombination density and/or higher-than-average CpG density. It is compelling that all these data sets were influenced by the cells' handling of double-strand breaks and, more generally, DNA damage on its genome. In fact, the DNA repair genes systematically avoid regions with a high recombination density, as they need to be intact to accurately handle repairable DNA lesions.