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Complete patient health information that is available where and when it is needed is essential to providers and patients and improves healthcare quality and patient safety. VA and DoD have built on their previous experience in patient data exchange to establish data standards and terminology services to enable real-time bi-directional computable (i.e., encoded) data exchange and achieve semantic interoperability in compliance with recommended national standards and the eGov initiative. The project uses RxNorm, UMLS, and SNOMED CT terminology standards to mediate codified pharmacy and allergy data with greater than 92 and 60 percent success rates respectively. Implementation of the project has been well received by users and is being expanded to multiple joint care sites. Stable and mature standards, mediation strategies, and a close relationship between healthcare institutions and Standards Development Organizations are recommended to achieve and maintain semantic interoperability in a clinical setting. [ABSTRACT FROM AUTHOR]

The circadian clock represents a critical regulatory network, which allows plants to anticipate environmental changes as inputs and promote plant survival by regulating various physiological outputs. Here, we examine the function of the clock-regulated transcription factor, CYCLING DOF FACTOR 6 (CDF6), during cold stress in Arabidopsis thaliana . We found that the clock gates CDF6 transcript accumulation in the vasculature during cold stress. CDF6 mis-expression results in an altered flowering phenotype during both ambient and cold stress. A genome-wide transcriptome analysis links CDF6 to genes associated with flowering and seed germination during cold and ambient temperatures, respectively. Analysis of key floral regulators indicates that CDF6 alters flowering during cold stress by repressing photoperiodic flowering components, FLOWERING LOCUS T ( FT ), CONSTANS ( CO ), and BROTHER OF FT (BFT) . Gene ontology enrichment further suggests that CDF6 regulates circadian and developmental-associated genes. These results provide insights into how the clock-controlled CDF6 modulates plant development during moderate cold stress., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Blair, Goralogia, Lincoln, Imaizumi and Nagel.)

The informatics community has a long-standing vision of freely flowing and highly re-usable patient-specific clinical data that improves care quality and safety. We sought to evaluate the extent to which a standards-based mapping approach is sufficient to support semantic interoperability. We simulated large-scale clinical data transmission and measured semantic success between VA and DoD systems via one-way testing (OWT) and round-trip testing (RTT). Simulations were accomplished via SQL queries and production standards-based maps for medications, allergens, document titles, vitals and payers. Success rates for mapping local codes to national standards varied from 62.5% for DoD document titles and medications, to 100% for VA and DoD vital signs. Successful, one-way testing was considerably lower, ranging from 8.52% to 62.7%. Round-trip success rates were lower still, ranging from 1.7% to 76.3%. We present an error framework, lessons learned, and proposed mitigating steps to enhance standards-based semantic interoperability., (©2019 AMIA - All rights reserved.)

Interoperability among medication classification systems is known to be limited. We investigated the mapping of the Established Pharmacologic Classes (EPCs) to SNOMED CT. We compared lexical and instance-based methods to an expert-reviewed reference standard to evaluate contributions of these methods. Of the 543 EPCs, 284 had an equivalent SNOMED CT class, 205 were more specific, and 54 could not be mapped. Precision, recall, and F1 score were 0.416, 0.620, and 0.498 for lexical mapping and 0.616, 0.504, and 0.554 for instance-based mapping. Each automatic method has strengths, weaknesses, and unique contributions in mapping between medication classification systems. In our experience, it was beneficial to consider the mapping provided by both automated methods for identifying potential matches, gaps, inconsistencies, and opportunities for quality improvement between classifications. However, manual review by subject matter experts is still needed to select the most relevant mappings.

Dentists have a significant role to identify and intervene in domestic abuse, violence, and neglect of the vulnerable. Over 75% of abuse victims have injuries to the head, face, mouth, and neck and so dentists are often first responders. However, under recognition and under reporting of domestic abuse and violence is a particular problem among health care providers, including dentists. Forensic odontologists are well suited to lead the training of their clinical colleagues in the various cultural determinants to abuse, including etiology, symptoms, physical signs of abuse, as well as appropriate reporting. In addition to leading their colleagues, forensic odontologists play an essential role as part of multidisciplinary teams that investigate conflict situations, serious crimes, exploitation of disadvantaged populations, and other serious violence and abuse. Whether in conflict zones or within private families, early detection and intervention is important to prevent establishment of abusive social and family patterns that perpetuate a "cycle of violence". This is especially true in young children, the most vulnerable population of all. To support this theory of early and effective intervention, this paper comprehensively reviews the most recent evidence concerning the etiology, detection, and prevention of violence and abuse., (Copyright 2010 Elsevier Ireland Ltd. All rights reserved.)

The Health Level 7 (HL7) Clinical Document Architecture, Release 2 (CDA R2) standardizes the structure and semantics of clinical documents in order to permit interchange. We have applied this standard to generate a platform independent CDA model and write a toolset that permits model specialization, generation of XML implementation artifacts, and provides an interface for clinical data managers. The resulting work was tested using US Department of Veterans Affairs Operative Note templates.

Background: Two candidate terminologies to support entry of general medical data are SNOMED CT and MEDCIN. We compare the ability of SNOMED CT and MEDCIN to represent concepts and interface terms from a VA general medical examination template., Methods: We parsed the VA general medical evaluation template and mapped the resulting expressions into SNOMED CT and MEDCIN. Internists conducted double independent reviews on 864 expressions. Exact concept level matches were used to evaluate reference coverage. Exact term level matches were required for interface terms., Results: Sensitivity of SNOMED CT as a reference terminology was 83% vs. 25% for MEDCIN (p<0.001). The sensitivity of SNOMED CT as an interface terminology was 53% vs. 7% for MEDCIN (P< 0.001)., Discussion: The content coverage of SNOMED CT as a reference terminology and as an interface terminology outperformed MEDCIN. We did not evaluate other aspects of interface terminologies such as richness of clinical linkages.

Under a congressional mandate, VA and DoD have built a framework to exchange standardized, codified patient drug allergy information through a mediation terminology. Initially, the Unified Medical Language System (UMLS) was deemed to be the most appropriate translator. After both agency files were mapped to UMLS, DoD could understand 45 percent of VA's mapped terms and VA could understand 26 percent of DoD's mapped terms. A significant portion of the non-mediated information was brand names in DoD with generic counterparts in VA. Recently, a Consolidated Health Informatics (CHI) group designated RxNorm as the standard for trade name allergies. An analysis was conducted to estimate mediation improvement using RxNorm. Both agency files were re-mapped to RxNorm. By utilizing the RxNorm defined relationships between brand names and generics and between variants of therapeutic moieties , DoD will understand 74 percent of VA terms and VA will understand 58 percent of DoD terms.

Drug information sources use category labels to assist in navigating and organizing information. Some category labels describe drugs from multiple perspectives (e.g., both structure and function). The National Drug File - Reference Terminology (NDF RT) is a drug information source that augments a "legacy" categorization system with a formal reference model specifying Chemical Structure, Cellular or Sub-Cellular Mechanism of Action, Organ- or System-Level Physiological Effect, and Therapeutic Intent categories. We examined drug category names from three sources to better understand their information content and evaluate NDF RT's semantic coverage. On average, category names contain more than 1.5 attributes. NDF RT's reference model covers more than 76% of the information identified in drug category labels. A new NDF RT reference axis of drug formulations could improve NDF RT's coverage to 85%. The distinction between Physiological Effect and Therapeutic Intent, prompted many questions among category reviewers, suggesting that further clarification of these reference concepts is required. Careful review of existing categorization schemes may guide structured terminology and ontology development efforts toward greater fidelity to deployed information sources.

The Veterans Administration (VA) has adopted an ambitious program to standardize its clinical terminology to comply with industry-wide standards. The VA is using commercially available tools and in-house software to create a high-quality reference terminology system. The terminology will be used by current and future applications with no planned disruption to operational systems. The first large customer of the group is the national VA Health Data Repository (HDR). Unique enterprise identifiers are assigned to each standard term, and a rich network of semantic relationships makes the resulting data not only recognizable, but highly computable and reusable in a variety of applications, including decision support and data sharing with partners such as the Department of Defense (DoD). This paper describes the specific methods and approaches that the VA has employed to develop and implement this innovative program in existing information system. The goal is to share with others our experience with key issues that face our industry as we move toward an electronic health record for every individual.

The Veterans Health Affairs (VHA) branch of the Department of Veterans Affairs has undertaken an Enterprise Reference Terminology (ERT). VHA, arguably the largest integrated healthcare provider in the United States, has completely computerized virtually all clinical transactions, including physician orders and documentation. The VA is now integrating its clinical records across hundreds of sites of care by means of a Health Data Repository (HDR) project. ERT has been designed to provide a terminology development environment, terminology services, and maintenance services for the clinical and business content in HDR and other VHA applications. Drug, laboratory observations, and clinical document title files have been developed, and the ERT will encompass all HDR domains by 2008. Commercial tools are used to host the VHA's ERT terminology development and server environments. We will select and adopt both open-source and licensable terminology systems to provide ERT content, as well as reuse existing VA-specific terminology content.

Background: Content coverage studies provide valuable information to potential users of terminologies. We detail the VA National Drug File Reference Terminology's (NDF-RT) ability to represent dictated medication list phrases from the Mayo Clinic. NDF-RT is a description logic-based resource created to support clinical operations at one of the largest healthcare providers in the US., Methods: Medication list phrases were extracted from dictated patient notes from the Mayo Clinic. Algorithmic mappings to NDF-RT using the SmartAccess Vocabulary Server (SAVS) were presented to two non-VA physicians. The physicians used a terminology browser to determine the accuracy of the algorithmic mapping and the content coverage of NDF-RT., Results: The 509 extracted documents on 300 patients contained 847 medication concepts in medication lists. NDF-RT covered 97.8% of concepts. Of the 18 phrases that NDF-RT did not represent, 10 were for OTC's and food supplements, 5 were for prescription medications, and 3 were missing synonyms. The SAVS engine properly mapped 773 of 810 phrases with an overall sensitivity (precision) was 95.4% and positive predictive value (recall) of 99.9%., Conclusions: This study demonstrates that NDF-RT has more general utility than its initial design parameters dictated

Veterans Health Administration (VHA) is now evaluating use of SNOMED-CT. This paper reports the first phase of this evaluation, which examines the coverage of SNOMED-CT for problem list entries. Clinician expressions in VA problem lists are quite diverse compared to the content of the current VA terminology Lexicon. We selected a random set of 5054 narratives that were previously "unresolved" against the Lexicon. These narratives were mapped to SNOMED-CT using two automated tools. Experts reviewed a subset of the tools' matched, partly matched, and un-matched narratives. The automated tools produced exact or partial matches for over 90% of the 5054 unresolved narratives. SNOMED-CT has promise as a coding system for clinical problems. In subsequent studies, VA will examine the coverage of SNOMED for other clinical domains, such as drugs, allergies, and physician orders.

Clinically useful controlled vocabularies should represent healthcare concepts completely and with high reliability. Anticipating and pre-coordinating all possible expressions (e.g. 'fracture of the left femur' and 'fracture of the right femur') is not feasible. Variation in practice styles, requirements for the granularity of content, the exponential growth of terminology size, and increased cost of maintaining pre-coordinated terminologies lead us to conclude that no enumerated terminology can ever be truly comprehensive. Compositional terminologies are one potential solution to the problem of content completeness, but carry a risk of generating expressions whose equivalency cannot be easily determined. In order for post-coordinated expressions to be comparable, a sufficiently detailed formal mechanism for information representation is necessary. Comparable data for post-coordinated expressions requires normalization of both the contents and the semantics of the contents of the terminology with the information captured in post-coordinated expressions. In addition, comparable data requires a storage and messaging paradigm robust enough to faithfully represent the information contained within arbitrarily complex compositional expressions. We present a formalism for storing, and sending messages containing compositional expressions using a large-scale reference terminology. It is our intent that this formalism be used to algorithmically determine whether or not messages contain comparable data. In addition, we advocate transmitting the upward transitive closure of subsumption of all concepts, to improve comparability of data and to decrease reliance on locally stored versions of the underlying reference terminology.

This study assessed the effects of forensic odontologists' training and experience upon the accuracy of their dental radiographic identifications. Forty participating odontologists with various levels of training and experience completed a Web-based survey of their qualifications and then completed nine Web-based radiographic identification cases. They made their identifications using the American Board of Forensic Odontology Categories and Terminology for Body Identification. The results indicate that odontologists with high levels of training and experience performed significantly more accurately than those with lower levels. We conclude that high levels of training and experience in forensic odontology should be developed, maintained, and required of dentists who participate in a forensic team dealing with challenging identification cases.

The Veterans Health Administration of the U.S. Department of Veterans Affairs has a long, successful, and interesting history of using information technology to meet its mission. Each medical center is computerized to a degree that surprises the uninitiated. For example, medical documentation and ordering are computerized at every facility. A sophisticated national infrastructure has been developed to replicate, support, and evolve single-center successes. With advances in inter-facility networking, data sharing, and specialized central support and technical tools, VistA is becoming a single, highly scalable national health information system (HIS) solution. In this paper, we present an historical overview of VistA's development, describe its current functionality, and discuss its emergence as a national-scale hospital information system.

The importance of data representation in healthcare has been of concern for centuries. In the last fifty years there has been an increasing awareness of the need for formal representations of terminological systems. We propose that terminological system development should be consensus driven and the product of iterative open refinement in order to practically serve the needs of the healthcare community. The system of development and maintenance of such a system must involve recruitment of the best and the brightest in the medical community to take responsibility for insuring the accuracy and completeness of such an effort. We suggest a method for algorithmically building a starting point for such a reference terminology. Further we suggest a distributed authoring environment that would allow domain experts to contribute regardless of their location or language. Open intellectual contribution is the necessary ingredient for a consensus based international health reference terminology.

This paper evaluates the reliability and validity of eight published dental age estimation methods for adults that may aid in victim identification. Age was calculated on 20 Caucasian teeth of known age according to the methods of Kvaal (for in situ and extracted teeth), Solheim (for in situ and sectioned teeth), Lamendin (for extracted teeth), Johanson (for sectioned teeth) and Bang (for extracted and sectioned teeth) by one independent observer. For each method, mean age error and standard error were assessed as the measures of accuracy and precision. In addition, method simplicity, requirements for tooth preparation and the equipment necessary were assessed and recommendations given for forensic use in various situations. Methods for sectioned teeth gave more reliable results when compared to methods for intact teeth.

The National Drug File Reference Terminology contains a novel reference hierarchy to describe physiologic effects (PE) of drugs. The PE reference hierarchy contains 1697 concepts arranged into two broad categories; organ specific and generalized systemic effects. This investigation evaluated the appropriateness of the PE concepts for classifying a random selection of commonly prescribed medications. Ten physician reviewers classified the physiologic effects of ten drugs and rated the accuracy of the selected term. Inter reviewer agreement, overall confidence, and concept frequencies were assessed and were correlated with the complexity of the drug's known physiologic effects. In general, agreement between reviewers was fair to moderate (kappa 0.08-0.49). The physiologic effects modeled became more disperse with drugs having and inducing multiple physiologic processes. Complete modeling of all physiologic effects was limited by reviewers focusing on different physiologic processes. The reviewers were generally comfortable with the accuracy of the concepts selected. Overall, the PE reference hierarchy was useful for physician reviewers classifying the physiologic effects of drugs. Ongoing evolution of the PE reference hierarchy as it evolves should take into account the experiences of our reviewers.

Student records flow through medical school offices at a rapid rate. Much of this data is often tracked on paper, spread across multiple departments. The Medical Student Informatics Group at the University of Utah School of Medicine identified offices and organizations documenting student information. We assessed departmental needs, identified records, and researched database software available within the private sector and academic community. Although a host of database applications exist, few publications discuss database models for storage and retrieval of student records. We developed and deployed an Internet based application to meet current requirements, and allow for future expandability. During a test period, users were polled regarding utility, security, stability, ease of use, data accuracy, and potential project expansion. Feedback demonstrated widespread approval, and considerable interest in additional feature development. This experience suggests that many medical schools would benefit from centralized database management of student records.

The Large Scale Vocabulary Test (LSVT) was designed to evaluate how well the Metathesaurus plus planned additions to Meta covered the documentation needs of clinicians. Our consortium collected 10,538 clinical narratives from patient problem lists recorded at 65 Veterans Hospitals, internal medicine ambulatory care practices, diagnostic history and physical examination data elements from Iliad, and nursing shift notes and emergency transport patient records. The results showed 94% of submitted terms resulted in acceptable matches. 49% of submitted terms were judged to be synonymous with the match terms, 35% were judged to be more specific (usually due to modifiers), 2%, were less specific, and 6% had an associative relationship. In 8% of cases either no match was found by the LSVT interface or all proposed matches were rejected by the raters. The LSVT content was quite suitable for coding our narratives. Necessary improvements for an electronic record would include the ability to compose modifiers together with root concepts.

To better understand how VA clinicians use medical vocabulary in every day practice, we set out to characterize terms generated in the Problem List module of the VA's DHCP system that were not mapped to terms in the controlled-vocabulary lexicon of DHCP. When entered terms fail to match those in the lexicon, a note is sent to a central repository. When our study started, the volume in that repository had reached 16,783 terms. We wished to characterize the potential reasons why these terms failed to match terms in the lexicon. After examining two small samples of randomly selected terms, we used group consensus to develop a set of rating criteria and a rating form. To be sure that the results of multiple reviewers could be confidently compared, we analyzed the inter-rater agreement of our rating process. Two rates used this form to rate the same 400 terms. We found that modifiers and numeric data were common and consistent reasons for failure to match, while others such as use of synonyms and absence of the concept from the lexicon were common but less consistently selected.

This paper describes a prototype for research to evaluate the impact of diagnostic decision support systems on the behavior of physicians. Several indices that can be used to quantify the magnitude of impact are proposed. A large medical diagnostic knowledge base in internal medicine (the Iliad knowledge base) was used in this evaluation. The impact on behavior when different inference models are run against this knowledge base is evaluated for two different case domains and physician's specialties.

Computerized reminder systems have been shown to be effective in improving physician compliance with preventive services guidelines. Very little has been published about the use of computerized reminders for preventive care in diabetes. We implemented a computer-generated reminder system for diabetes care guidelines in a randomized controlled study in the outpatient clinics of 35 internal medicine residents at the University of Utah and Salt Lake Veterans Affairs Hospitals. After a six month study period, compliance with the recommended care significantly improved in both the intervention group that received patient-specific reminders about the guidelines (38.0% at baseline, 54.9% at follow-up) and the control group that received a nonspecific report (34.6% at baseline, 51.0% at follow-up). There was no significant difference between the two groups. Both clinic sites showed similar improvement over baseline levels of compliance. Residents who completed encounter forms used by the system showed a significantly greater improvement in compliance than those who did not complete encounter forms (19.7% vs. 7.6%, p = 0.006). The improvements in guideline compliance were seen in all areas of diabetes preventive care studied, and significant improvements were seen with recommended items from the medical history, physical exam, laboratory testing, referrals, and patient education. The use of encounter forms by the providers significantly improved documented compliance with the guidelines in almost all categories of preventive care. These results suggest that computerized reminder systems improve compliance with recommended care more by facilitating the documentation of clinical findings and the ordering of recommended procedures than by providing the clinician with patient-specific information about guideline compliance status. Further study is needed to understand the implications of these findings to the development of future computerized reminder systems for chronic diseases such as diabetes.

Diabetes mellitus is a chronic condition with several late complications that can be delayed or avoided through proper preventive health care. Although practice guidelines have been established to improve the preventive care in diabetics, dissemination of these guidelines among physicians and educational programs have been only moderately successful in changing physicians' practice patterns. Previous efforts, however, did not utilize computer-generated reminders. We developed a system of computer-generated reminders for diabetic preventive care. We completed an implementation of the system in the outpatient clinics of internal medicine residents at our institution. This paper describes the development and implementation of this system. Our results showed that the system flagged an average of 13 items that deviated from diabetes guideline compliance, out of a possible 21 items per patient. The residents completed encounter forms used by the system for 37% of patients seen during a six month period. Physician users exhibited positive attitudes toward the use of guidelines which they judged improved quality at no additional cost of care. However, the complexity and length of the guideline encounter forms and the additional time demands proved to be significant obstacles to current routine use. Our experience will help to improve the system so that it is more usable and acceptable to physicians, especially in the future as health care increasingly makes use of electronic medical record systems.

This study evaluates inter-author variability in knowledge base construction. Seven board-certified internists independently profiled "acute perinephric abscess", using as reference material a set of 109 peer-reviewed articles. Each participant created a list of findings associated with the disease, estimated the predictive value and sensitivity of each finding, and assessed the pertinence of each article for making each judgment. Agreement in finding selection was significantly different from chance: seven, six, and five participants selected the same finding 78.6, 9.8, and 1.6 times more often than predicted by chance. Findings with the highest sensitivity were most likely to be included by all participants. The selection of supporting evidence from the medical literature was significantly related to each physician's agreement with the majority. The study shows that, with appropriate guidance, physicians can reproducibly extract information from the medical literature, and thus established a foundation for multi-author knowledge base construction.

Medical informatics could facilitate more effective analysis and use of clinical knowledge by means of expert systems. To be most effective, such systems should be constructed in a manner which is consistent with physicians' cognitive processes. Our past five years' work with a system called Iliad indicates that it provides effective medical training and education. The current research extends our previous work by using a wider array of training and test cases. We also evaluated whether training on specific cases could generalize to improved testing performance on related cases, which featured similar complaints and pathophysiologic mechanisms, but different final diagnoses. In their junior internal medicine clerkship, students (n = 100) completed 1300 Iliad training cases covering 48 diagnoses. The findings indicated improved problem solving on the specifically trained cases as well as the generalization cases. We discuss a possible training model for expert systems such as Iliad.

Iliad is a diagnostic expert system for internal medicine. Iliad's "best information" mode is used to determine the most cost-effective findings to pursue next at any stage of a work-up. The "best information" algorithm combines an information content calculation together with a cost factor. The calculations then provide a rank-ordering of the alternative patient findings according to cost-effectiveness. The authors evaluated five information content models under two different strategies. The first, the single-frame strategy, considers findings only within the context of each individual disease frame. The second, the across-frame strategy, considers the information that a single finding could provide across several diseases. The study found that (1) a version of Shannon's information model performed the best under both strategies---this finding confirms the result of a previous independent study, (2) the across-frame strategy was preferred over the single-frame strategy.

Iliad is a computerized, expert system for internal medical diagnosis. The system is designed to teach diagnostic skills by means of simulated patient case presentations. We report the results of a controlled trial in which junior students were randomly assigned to received Iliad training on one of two different simulated case mixes. Each group was subsequently tested in both their "trained" and "untrained" case domain. The testing consisted of computerized, simulated patient cases for which no training feedback was provided. Outcome variables were designed to measure the students' performance on these test cases. The results indicate that students made fewer diagnostic errors and more conclusively confirmed their diagnostic hypotheses when they were tested in their trained domain. We conclude that expert systems such as Iliad can effectively teach diagnostic skills by supplementing trainees' actual case experience with computerized simulations.

Iliad is a diagnostic expert system consisting of an "inference engine" (collection of rules and procedures for making decisions) and a "knowledge base" (collection of medical facts). Iliad's internal medicine knowledge base recognizes 5000 medical findings and covers 1150 diagnostic conditions in 10 subspecialty fields. We used Iliad's simulator mode to train diagnostic skills in junior-year medical students. The results corroborate previous findings documenting Iliad's teaching efficacy. Recent developments in cognitive psychology provide a framework for explaining Iliad's training effects.

Iliad is a diagnostic expert system for internal medicine. One important feature that Iliad offers is the ability to analyze a particular patient case and to determine the most cost-effective method for pursuing the work-up. Iliad's current "best information" algorithm has not been previously validated and compared to other potential algorithms. Therefore, this paper presents a comparison of four new algorithms to the current algorithm. The basis for this comparison was eighteen "vignette" cases derived from real patient cases from the University of Utah Medical Center. The results indicated that the current algorithm can be significantly improved. More promising algorithms are suggested for future investigation.

To assess rib cage muscle fatigue and its relationship to diaphragmatic fatigue, we recorded the electromyogram (EMG) of the parasternal intercostals (PS), sternocleidomastoid (SM), and platysma with fine wire electrodes and the EMG of the diaphragm (DI) with an esophageal electrode. Six normal subjects were studied during inspiratory resistive breathing. Two different breathing patterns were imposed: mainly diaphragmatic or mainly rib cage breathing. The development of fatigue was assessed by analysis of the high-to-low (H/L) ratio of the EMG. To determine the appropriate frequency bands for the PS and SM, we established their EMG power spectrum by Fourier analysis. The mean and SD for the centroid frequency was 312 +/- 16 Hz for PS and 244 +/- 48 Hz for SM. When breathing with the diaphragmatic patterns, all subjects showed a fall in H/L of the DI and none had a fall in H/L of the PS or SM. During rib cage emphasis, four out of five subjects showed a fall in H/L of the PS and five out of six showed a fall in H/L of the SM. Four subjects showed no fall in H/L of the DI; the other two subjects were unable to inhibit diaphragm activity to a substantial degree and did show a fall in H/L of the DI. Activity of the platysma was minimal or absent during diaphragmatic emphasis but was usually strong during rib cage breathing. We conclude that fatigue of either the diaphragm or the parasternal and sternocleidomastoid can occur independently according to the recruitment pattern of inspiratory muscles.(ABSTRACT TRUNCATED AT 250 WORDS)

We describe an elderly patient with an unusual presentation of hereditary hemorrhagic telangiectasia (Rendu-Osler-Weber disease) involving the lung. He had recurrent "pneumonia" caused by massive hemorrhage from endobronchial telangiectases. When stable, he was normoxic, had no evidence of right-to-left shunting, and had mild pulmonary arterial hypertension. His pulmonary telangiectases may be isolated to the bronchial circulation. We report hemodynamic data and show the first photographs of endobronchial telangiectases.