Do coder characteristics influence validity of ICD-10 hospital discharge data?

<p>Abstract</p> <p>Background</p> <p>Administrative data are widely used to study health systems and make important health policy decisions. Yet little is known about the influence of coder characteristics on administrative data validity in these studies. Our goal was to describe the relationship between several measures of validity in coded hospital discharge data and 1) coders' volume of coding (≥13,000 vs. <13,000 records), 2) coders' employment status (full- vs. part-time), and 3) hospital type.</p> <p>Methods</p> <p>This descriptive study examined 6 indicators of face validity in ICD-10 coded discharge records from 4 hospitals in Calgary, Canada between April 2002 and March 2007. Specifically, mean number of coded diagnoses, procedures, complications, Z-codes, and codes ending in 8 or 9 were compared by coding volume and employment status, as well as hospital type. The mean number of diagnoses was also compared across coder characteristics for 6 major conditions of varying complexity. Next, kappa statistics were computed to assess agreement between discharge data and linked chart data reabstracted by nursing chart reviewers. Kappas were compared across coder characteristics.</p> <p>Results</p> <p>422,618 discharge records were coded by 59 coders during the study period. The mean number of diagnoses per record decreased from 5.2 in 2002/2003 to 3.9 in 2006/2007, while the number of records coded annually increased from 69,613 to 102,842. Coders at the tertiary hospital coded the most diagnoses (5.0 compared with 3.9 and 3.8 at other sites). There was no variation by coder or site characteristics for any other face validity indicator. The mean number of diagnoses increased from 1.5 to 7.9 with increasing complexity of the major diagnosis, but did not vary with coder characteristics. Agreement (kappa) between coded data and chart review did not show any consistent pattern with respect to coder characteristics.</p> <p>Conclusions</p> <p>This large study suggests that coder characteristics do not influence the validity of hospital discharge data. Other jurisdictions might benefit from implementing similar employment programs to ours, e.g.: a requirement for a 2-year college training program, a single management structure across sites, and rotation of coders between sites. Limitations include few coder characteristics available for study due to privacy concerns.</p

Anticancer Gene Transfer for Cancer Gene Therapy

Gene therapy vectors are among the treatments currently used to treat malignant tumors. Gene therapy vectors use a specific therapeutic transgene that causes death in cancer cells. In early attempts at gene therapy, therapeutic transgenes were driven by non-specific vectors which induced toxicity to normal cells in addition to the cancer cells. Recently, novel cancer specific viral vectors have been developed that target cancer cells leaving normal cells unharmed. Here we review such cancer specific gene therapy systems currently used in the treatment of cancer and discuss the major challenges and future directions in this field

Assessment of the quality and variability of health information on chronic pain websites using the DISCERN instrument

<p>Abstract</p> <p>Background</p> <p>The Internet is used increasingly by providers as a tool for disseminating pain-related health information and by patients as a resource about health conditions and treatment options. However, health information on the Internet remains unregulated and varies in quality, accuracy and readability. The objective of this study was to determine the quality of pain websites, and explain variability in quality and readability between pain websites.</p> <p>Methods</p> <p>Five key terms (pain, chronic pain, back pain, arthritis, and fibromyalgia) were entered into the Google, Yahoo and MSN search engines. Websites were assessed using the DISCERN instrument as a quality index. Grade level readability ratings were assessed using the Flesch-Kincaid Readability Algorithm. Univariate (using alpha = 0.20) and multivariable regression (using alpha = 0.05) analyses were used to explain the variability in DISCERN scores and grade level readability using potential for commercial gain, health related seals of approval, language(s) and multimedia features as independent variables.</p> <p>Results</p> <p>A total of 300 websites were assessed, 21 excluded in accordance with the exclusion criteria and 110 duplicate websites, leaving 161 unique sites. About 6.8% (11/161 websites) of the websites offered patients' commercial products for their pain condition, 36.0% (58/161 websites) had a health related seal of approval, 75.8% (122/161 websites) presented information in English only and 40.4% (65/161 websites) offered an interactive multimedia experience. In assessing the quality of the unique websites, of a maximum score of 80, the overall average DISCERN Score was 55.9 (13.6) and readability (grade level) of 10.9 (3.9). The multivariable regressions demonstrated that website seals of approval (<it>P </it>= 0.015) and potential for commercial gain (<it>P </it>= 0.189) were contributing factors to higher DISCERN scores, while seals of approval (<it>P </it>= 0.168) and interactive multimedia (<it>P </it>= 0.244) contributed to lower grade level readability, as indicated by estimates of the beta coefficients.</p> <p>Conclusion</p> <p>The overall quality of pain websites is moderate, with some shortcomings. Websites that scored high using the DISCERN questionnaire contained health related seals of approval and provided commercial solutions for pain related conditions while those with low readability levels offered interactive multimedia options and have been endorsed by health seals.</p

Experimental Infection of Mice with Avian Paramyxovirus Serotypes 1 to 9

The nine serotypes of avian paramyxoviruses (APMVs) are frequently isolated from domestic and wild birds worldwide. APMV-1, also called Newcastle disease virus, was shown to be attenuated in non-avian species and is being developed as a potential vector for human vaccines. In the present study, we extended this evaluation to the other eight serotypes by evaluating infection in BALB/c mice. Mice were inoculated intranasally with a prototype strain of each of the nine serotypes and monitored for clinical disease, gross pathology, histopathology, virus replication and viral antigen distribution, and seroconversion. On the basis of multiple criteria, each of the APMV serotypes except serotype 5 was found to replicate in mice. Five of the serotypes produced clinical disease and significant weight loss in the following order of severity: 1, 2>6, 9>7. However, disease was short-lived. The other serotypes produced no evident clinical disease. Replication of all of the APMVs except APMV-5 in the nasal turbinates and lungs was confirmed by the recovery of infectious virus and by substantial expression of viral antigen in the epithelial lining detected by immunohistochemistry. Trace levels of infectious APMV-4 and -9 were detected in the brain of some animals; otherwise, no virus was detected in the brain, small intestine, kidney, or spleen. Histologically, infection with the APMVs resulted in lung lesions consistent with broncho-interstitial pneumonia of varying severity that were completely resolved at 14 days post infection. All of the mice infected with the APMVs except APMV-5 produced serotype-specific HI serum antibodies, confirming a lack of replication of APMV-5. Taken together, these results demonstrate that all APMV serotypes except APMV-5 are capable of replicating in mice with minimal disease and pathology

EIFiso4G augments the synthesis of specific plant proteins involved in normal chloroplast function

Copyright © 2019 American Society of Plant Biologists. All rights reserved. The plant-specific translation initiation complex eIFiso4F is encoded by three genes in Arabidopsis (Arabidopsis thaliana)-genes encoding the cap binding protein eIFiso4E (eifiso4e) and two isoforms of the large subunit scaffolding protein eIFiso4G (i4g1 and i4g2). To quantitate phenotypic changes, a phenomics platform was used to grow wild-type and mutant plants (i4g1, i4g2, i4e, i4g1 × i4g2, and i4g1 × i4g2 × i4e [i4f]) under various light conditions. Mutants lacking both eIFiso4G isoforms showed the most obvious phenotypic differences from the wild type. Two-dimensional differential gel electrophoresis and mass spectrometry were used to identify changes in protein levels in plants lacking eIFiso4G. Four of the proteins identified as measurably decreased and validated by immunoblot analysis were two light harvesting complex binding proteins 1 and 3, Rubisco activase, and carbonic anhydrase. The observed decreased levels for these proteins were not the direct result of decreased transcription or protein instability. Chlorophyll fluorescence induction experiments indicated altered quinone reduction kinetics for the double and triple mutant plants with significant differences observed for absorbance, trapping, and electron transport. Transmission electron microscopy analysis of the chloroplasts in mutant plants showed impaired grana stacking and increased accumulation of starch granules consistent with some chloroplast proteins being decreased. Rescue of the i4g1 × i4g2 plant growth phenotype and increased expression of the validated proteins to wild-type levels was obtained by overexpression of eIFiso4G1. These data suggest a direct and specialized role for eIFiso4G in the synthesis of a subset of plant proteins

Towards Predictive Computational Models of Oncolytic Virus Therapy: Basis for Experimental Validation and Model Selection

Oncolytic viruses are viruses that specifically infect cancer cells and kill them, while leaving healthy cells largely intact. Their ability to spread through the tumor makes them an attractive therapy approach. While promising results have been observed in clinical trials, solid success remains elusive since we lack understanding of the basic principles that govern the dynamical interactions between the virus and the cancer. In this respect, computational models can help experimental research at optimizing treatment regimes. Although preliminary mathematical work has been performed, this suffers from the fact that individual models are largely arbitrary and based on biologically uncertain assumptions. Here, we present a general framework to study the dynamics of oncolytic viruses that is independent of uncertain and arbitrary mathematical formulations. We find two categories of dynamics, depending on the assumptions about spatial constraints that govern that spread of the virus from cell to cell. If infected cells are mixed among uninfected cells, there exists a viral replication rate threshold beyond which tumor control is the only outcome. On the other hand, if infected cells are clustered together (e.g. in a solid tumor), then we observe more complicated dynamics in which the outcome of therapy might go either way, depending on the initial number of cells and viruses. We fit our models to previously published experimental data and discuss aspects of model validation, selection, and experimental design. This framework can be used as a basis for model selection and validation in the context of future, more detailed experimental studies. It can further serve as the basis for future, more complex models that take into account other clinically relevant factors such as immune responses

Investigation of Indazole Unbinding Pathways in CYP2E1 by Molecular Dynamics Simulations

Human microsomal cytochrome P450 2E1 (CYP2E1) can oxidize not only low molecular weight xenobiotic compounds such as ethanol, but also many endogenous fatty acids. The crystal structure of CYP2E1 in complex with indazole reveals that the active site is deeply buried into the protein center. Thus, the unbinding pathways and associated unbinding mechanisms remain elusive. In this study, random acceleration molecular dynamics simulations combined with steered molecular dynamics and potential of mean force calculations were performed to identify the possible unbinding pathways in CYP2E1. The results show that channel 2c and 2a are most likely the unbinding channels of CYP2E1. The former channel is located between helices G and I and the B-C loop, and the latter resides between the region formed by the F-G loop, the B-C loop and the β1 sheet. Phe298 and Phe478 act as the gate keeper during indazole unbinding along channel 2c and 2a, respectively. Previous site-directed mutagenesis experiments also supported these findings

Single Assay for Simultaneous Detection and Differential Identification of Human and Avian Influenza Virus Types, Subtypes, and Emergent Variants

For more than four decades the cause of most type A influenza virus infections of humans has been attributed to only two viral subtypes, A/H1N1 or A/H3N2. In contrast, avian and other vertebrate species are a reservoir of type A influenza virus genome diversity, hosting strains representing at least 120 of 144 combinations of 16 viral hemagglutinin and 9 viral neuraminidase subtypes. Viral genome segment reassortments and mutations emerging within this reservoir may spawn new influenza virus strains as imminent epidemic or pandemic threats to human health and poultry production. Traditional methods to detect and differentiate influenza virus subtypes are either time-consuming and labor-intensive (culture-based) or remarkably insensitive (antibody-based). Molecular diagnostic assays based upon reverse transcriptase-polymerase chain reaction (RT-PCR) have short assay cycle time, and high analytical sensitivity and specificity. However, none of these diagnostic tests determine viral gene nucleotide sequences to distinguish strains and variants of a detected pathogen from one specimen to the next. Decision-quality, strain- and variant-specific pathogen gene sequence information may be critical for public health, infection control, surveillance, epidemiology, or medical/veterinary treatment planning. The Resequencing Pathogen Microarray (RPM-Flu) is a robust, highly multiplexed and target gene sequencing-based alternative to both traditional culture- or biomarker-based diagnostic tests. RPM-Flu is a single, simultaneous differential diagnostic assay for all subtype combinations of type A influenza viruses and for 30 other viral and bacterial pathogens that may cause influenza-like illness. These other pathogen targets of RPM-Flu may co-infect and compound the morbidity and/or mortality of patients with influenza. The informative specificity of a single RPM-Flu test represents specimen-specific viral gene sequences as determinants of virus type, A/HN subtype, virulence, host-range, and resistance to antiviral agents