High bacterial load in asymptomatic diabetic patients with neurotrophic ulcers retards wound healing after application of Dermagraft

Diabetic neuropathic foot ulcers are a major healthcare burden. These chronic wounds always have a bacterial load, and although normal flora is not harmful, increased tissue burden may impede healing before clinical signs of infection are evident. In this study, chronic noninfected diabetic neuropathic foot ulcers (those with adequate blood supply and pressure offloading) were assessed for bacterial burden immediately before the application of a skin substitute. Eight patients with diabetic neuropathic foot ulcers greater than 1 cm2 and free of necrotic tissue had 3-mm tissue biopsies taken from the ulcer base for quantitative bacteriology. Five of the eight patients (75%) had greater or equal to 10(5) colony forming units/gram organisms present despite the absence of clinical signs of infection. Wound healing rates were linked to bacterial load as determined from quantitative biopsy--no growth was associated with a wound healing rate of 0.2 cm per week, 10(5) to 10(6) colony forming units/gram was associated with a healing rate of 0.15 cm per week, and greater than 10(6) colony forming units/gram was associated with 0.05 cm/per week healing rate. High bacterial burden impeded healing both before and after the application of the skin substitute. The authors will change their clinical practice to assess all diabetic neuropathic foot ulcers using quantitative skin biopsies before applying skin substitutes. All patients will be treated with combination antibiotics and repeat biopsies obtained with decreased bacterial burden (< 10(6) colony forming units/gram) prior to using any bioengineered skin substitute or growth factor treatment.

Screening evaluation of an ionized nanocrystalline silver dressing in chronic wound care

The successful topical treatment of chronic wounds requires adequate debridement, bacterial balance, and moisture balance. An ionized nanocrystalline silver dressing was evaluated through an uncontrolled, prospective study of a case series of 29 patients with a variety of chronic nonhealing wounds. The four arms of the study included nine patients with foot ulcers, six patients with venous stasis ulcers, two patients with pressure ulcers, and 12 patients with miscellaneous wounds. All wounds were assessed for the usual signs of clinical infection, with most of these parameters being measured and recorded. Microbiologically, bacterial load was determined via quantitative biopsies and semi-quantitative swabs. In general, the results showed a marked clinical improvement for the majority of wounds treated with the dressing. Among improved parameters included decreased exudate and decreased purulence. The quantitative bacterial biopsies did not show any decrease in organism numbers, although the semi-quantitative swabs indicated a decrease in the wound surface bacterial loading. This was indicative of the dressing's ability to reduce surface bacteria and achieve an element of bacterial balance in the superficial dermal compartment. The proposed mechanism of action for this ionized nanocrystalline based dressing is through bacterial and moisture balance within the superficial wound space compartment.

Evaluating UMLS strings for natural language processing

The National Library of Medicine's Unified Medical Language System (UMLS) is a rich source of knowledge in the biomedical domain. The UMLS is used for research and development in a range of different applications, including natural language processing (NLP). In this paper we investigate the nature of the strings found in the UMLS Metathesaurus and evaluate them for their usefulness in NLP. We begin by identifying a number of properties that might allow us to predict the likelihood of a given string being found or not found in a corpus. We use a statistical model to test these predictors against our corpus, which is derived from the MEDLINE database. For one set of properties the model correctly predicted 77% of the strings that do not belong to the corpus, and 85% of the strings that do belong to the corpus. For another set of properties the model correctly predicted 96% of the strings that do not belong to the corpus and 29% of the strings that do belong to the corpus.

The diabetic neuropathic ulcer: an overview

The leading cause of amputation in patients with diabetes is the nonhealing foot wound and its complications. The effects of peripheral neuropathy, peripheral vascular disease, and infection often combine to facilitate ulcer development that can lead to gangrene and amputation. In many instances, foot ulcers and amputation can be prevented. The literature over the past 5 years has included information on the infrared thermometry in the diagnosis of infection and acute Charcot change. Pressure downloading has been facilitated by computerized foot scanning systems and the use of prefabricated pneumatic walkers as an alternative to the contact cast. Local wound care is enforced by repeated sharp debridement. Nonhealing ulcers can benefit from biologicals: platelet-derived growth factors and a human dermal replacement containing viable fibroblasts. The most successful outcomes are achieved when interdisciplinary teams are formed to provide coordinated care. The goal of this article is to provide healthcare professionals with an overview of the risks of neuropathic foot injury and to offer strategies for prevention, protection, and reduction of recurrences of the diabetic foot ulcer.

Analysis of biomedical text for chemical names: a comparison of three methods

At the National Library of Medicine (NLM), a variety of biomedical vocabularies are found in data pertinent to its mission. In addition to standard medical terminology, there are specialized vocabularies including that of chemical nomenclature. Normal language tools including the lexically based ones used by the Unified Medical Language System (UMLS) to manipulate and normalize text do not work well on chemical nomenclature. In order to improve NLM's capabilities in chemical text processing, two approaches to the problem of recognizing chemical nomenclature were explored. The first approach was a lexical one and consisted of analyzing text for the presence of a fixed set of chemical segments. The approach was extended with general chemical patterns and also with terms from NLM's indexing vocabulary, MeSH, and the NLM SPECIALIST lexicon. The second approach applied Bayesian classification to n-grams of text via two different methods. The single lexical method and two statistical methods were tested against data from the 1999 UMLS Metathesaurus. One of the statistical methods had an overall classification accuracy of 97%.

Terminology issues in user access to Web-based medical information

We conducted a study of user queries to the National Library of Medicine Web site over a three month period. Our purpose was to study the nature and scope of these queries in order to understand how to improve users' access to the information they are seeking on our site. The results show that the queries are primarily medical in content (94%), with only a small percentage (5.5%) relating to library services, and with a very small percentage (.5%) not being medically relevant at all. We characterize the data set, and conclude with a discussion of our plans to develop a UMLS-based terminology server to assist NLM Web users.

Discovering the modifiers in a terminology data set

We recently conducted a study of a subset of the data collected in the NLM/AHCPR Large Scale Vocabulary Test (LSVT). We studied those 11,387 terms in the LSVT data that were narrower in meaning than the UMLS concepts mapped to. We hypothesized that when one term is narrower in meaning than another, the first and second terms are likely to differ primarily by modification. We compared three lexical processing methods of increasing sophistication and measured the ability of each of these methods to correctly identify the modifiers in the data set. The results indicate that when using the most powerful of the methods, 63% of the term pairs were found to differ only by premodification, by postmodification or by both, 31% share some lexical material, and the remaining 6% have no lexical items in common. The implications of the study are discussed.

Evaluating lexical variant generation to improve information retrieval

Techniques for managing lexical variation constitute an integral part of information retrieval systems. We report on a series of experiments aimed at evaluating LVG, a lexical variant management tool which addresses the particular problems involved in matching health related vocabularies to concepts in the Unified Medical Language System (UMLS) Metathesaurus. Experiments conducted on data from the Large Scale Vocabulary Test indicate the effectiveness of this approach to managing biomedical information.

The UMLS Knowledge Source Server: a versatile Internet-based research tool

The National Library of Medicine's Unified Medical Language System (UMLS) project regularly distributes a set of Knowledge Sources to the research community. In 1995 the UMLS data were made available for the first time through the Internet-based UMLS Knowledge Source Server. The server can be accessed through three different client interfaces. The World Wide Web interface allows users to browse and explore the data and to see how those data are organized in the UMLS. The command-line interface is best suited for batch processing, and the application programming interface allows developers at remote sites to embed calls in their application programs to the Knowledge Source Server.

Lexical methods for managing variation in biomedical terminologies

Access to biomedical terminologies is hampered by the high degree of variability inherent in natural language terms and in the terminologies themselves. The lexicon, lexical programs, databases, and indexes included with the 1994 release of the UMLS Knowledge Sources are designed to help users manage this variability. We describe these resources and illustrate their flexibility and usefulness in providing enhanced access to data in the UMLS Metathesaurus.

UMLS knowledge for biomedical language processing

This paper describes efforts to provide access to the free text in biomedical databases. The focus of the effort is the development of SPECIALIST, an experimental natural language processing system for the biomedical domain. The system includes a broad coverage parser supported by a large lexicon, modules that provide access to the extensive Unified Medical Language System (UMLS) Knowledge Sources, and a retrieval module that permits experiments in information retrieval. The UMLS Metathesaurus and Semantic Network provide a rich source of biomedical concepts and their interrelationships. Investigations have been conducted to determine the type of information required to effect a map between the language of queries and the language of relevant documents. Mappings are never straightforward and often involve multiple inferences.