35 research outputs found
Coupling computer-interpretable guidelines with a drug-database through a web-based system – The PRESGUID project
BACKGROUND: Clinical Practice Guidelines (CPGs) available today are not extensively used due to lack of proper integration into clinical settings, knowledge-related information resources, and lack of decision support at the point of care in a particular clinical context. OBJECTIVE: The PRESGUID project (PREScription and GUIDelines) aims to improve the assistance provided by guidelines. The project proposes an online service enabling physicians to consult computerized CPGs linked to drug databases for easier integration into the healthcare process. METHODS: Computable CPGs are structured as decision trees and coded in XML format. Recommendations related to drug classes are tagged with ATC codes. We use a mapping module to enhance computerized guidelines coupling with a drug database, which contains detailed information about each usable specific medication. In this way, therapeutic recommendations are backed up with current and up-to-date information from the database. RESULTS: Two authoritative CPGs, originally diffused as static textual documents, have been implemented to validate the computerization process and to illustrate the usefulness of the resulting automated CPGs and their coupling with a drug database. We discuss the advantages of this approach for practitioners and the implications for both guideline developers and drug database providers. Other CPGs will be implemented and evaluated in real conditions by clinicians working in different health institutions
Measuring diversity in medical reports based on categorized attributes and international classification systems
<p>Abstract</p> <p>Background</p> <p>Narrative medical reports do not use standardized terminology and often bring insufficient information for statistical processing and medical decision making. Objectives of the paper are to propose a method for measuring diversity in medical reports written in any language, to compare diversities in narrative and structured medical reports and to map attributes and terms to selected classification systems.</p> <p>Methods</p> <p>A new method based on a general concept of f-diversity is proposed for measuring diversity of medical reports in any language. The method is based on categorized attributes recorded in narrative or structured medical reports and on international classification systems. Values of categories are expressed by terms. Using SNOMED CT and ICD 10 we are mapping attributes and terms to predefined codes. We use f-diversities of Gini-Simpson and Number of Categories types to compare diversities of narrative and structured medical reports. The comparison is based on attributes selected from the Minimal Data Model for Cardiology (MDMC).</p> <p>Results</p> <p>We compared diversities of 110 Czech narrative medical reports and 1119 Czech structured medical reports. Selected categorized attributes of MDMC had mostly different numbers of categories and used different terms in narrative and structured reports. We found more than 60% of MDMC attributes in SNOMED CT. We showed that attributes in narrative medical reports had greater diversity than the same attributes in structured medical reports. Further, we replaced each value of category (term) used for attributes in narrative medical reports by the closest term and the category used in MDMC for structured medical reports. We found that relative Gini-Simpson diversities in structured medical reports were significantly smaller than those in narrative medical reports except the "Allergy" attribute.</p> <p>Conclusions</p> <p>Terminology in narrative medical reports is not standardized. Therefore it is nearly impossible to map values of attributes (terms) to codes of known classification systems. A high diversity in narrative medical reports terminology leads to more difficult computer processing than in structured medical reports and some information may be lost during this process. Setting a standardized terminology would help healthcare providers to have complete and easily accessible information about patients that would result in better healthcare.</p
Enhanced mass spectrometry-based proteomics can be used to distinguish differences in protein compositions of acellular emphysematous versus normal lungs.
Residual detergent detection method for nondestructive cytocompatibility evaluation of decellularized whole lung scaffolds.
The development of reliable tissue engineering methods using decellularized cadaveric or donor lungs could potentially provide a new source of lung tissue. The vast majority of current lung decellularization protocols are detergent based and incompletely removed residual detergents may have a deleterious impact on subsequent scaffold recellularization. Detergent removal and quality control measures that rigorously and reliably confirm removal, ideally utilizing nondestructive methods, are thus critical for generating optimal acellular scaffolds suitable for potential clinical translation. Using a modified and optimized version of a methylene blue-based detergent assay, we developed a straightforward, noninvasive method for easily and reliably detecting two of the most commonly utilized anionic detergents, sodium deoxycholate (SDC) and sodium dodecyl sulfate (SDS), in lung decellularization effluents. In parallel studies, we sought to determine the threshold of detergent concentration that was cytotoxic using four different representative human cell types utilized in the study of lung recellularization: human bronchial epithelial cells, human pulmonary vascular endothelial cells (CBF12), human lung fibroblasts, and human mesenchymal stem cells. Notably, different cells have varying thresholds for either SDC or SDS-based detergent-induced cytotoxicity. These studies demonstrate the importance of reliably removing residual detergents and argue that multiple cell lines should be tested in cytocompatibility-based assessments of acellular scaffolds. The detergent detection assay presented here is a useful nondestructive tool for assessing detergent removal in potential decellularization schemes or for use as a potential endpoint in future clinical schemes, generating acellular lungs using anionic detergent-based decellularization protocols