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Biomedical subjects

C A Knirsch

Publications and source records attributed to C A Knirsch.

8 recordsLinked to original sources

Clinical efficacy of intravenous followed by oral azithromycin monotherapy in hospitalized patients with community-acquired pneumonia. The Azithromycin Intravenous Clinical Trials Group.

The purpose of this study was to evaluate intravenous (i.v.) azithromycin followed by oral azithromycin as a monotherapeutic regimen for community-acquired pneumonia (CAP). Two trials of i.v. azithromycin used as initial monotherapy in hospitalized CAP patients are summarized. Clinical efficacy is reported from an open-label randomized trial of azithromycin compared to cefuroxime with or without erythromycin. Bacteriologic and clinical efficacy results are also presented from a noncomparative trial of i.v. azithromycin that was designed to give additional clinical experience with a larger number of pathogens. Azithromycin was administered to 414 patients: 202 and 212 in the comparative and noncomparative trials, respectively. The comparator regimen was used as treatment for 201 patients; 105 were treated with cefuroxime alone and 96 were given cefuroxime plus erythromycin. In the comparative trial, clinical outcome data were available for 268 evaluable patients with confirmed CAP at the 10- to 14-day visit, with 106 (77%) of the azithromycin patients cured or improved and 97 (74%) of the comparator patients cured or improved. Mean i.v. treatment duration and mean total treatment duration (i.v. and oral) for the clinically evaluable patients were significantly (P < 0.05) shorter for the azithromycin group (3.6 days for the i.v. group and 8.6 days for the i.v. and oral group) than for the evaluable patients given cefuroxime plus erythromycin (4.0 days for the i.v. group and 10.3 days for the i.v. and oral group). The present comparative study demonstrates that initial therapy with i.v. azithromycin for hospitalized patients with CAP is associated with fewer side effects and is equal in efficacy to a 1993 American Thoracic Society-suggested regimen of cefuroxime plus erythromycin when the erythromycin is deemed necessary by clinicians.

Administration, Oral↗

A health information network for managing innercity tuberculosis: bridging clinical care, public health, and home care.

The purpose of this study was to use a health information network and innovative technology to coordinate tuberculosis care. An innercity medical center, a local health department, and a home care nurse service in northern Manhattan were used. The organizations were linked with computer networks. An automated decision support system with a natural language processor was used to detect tuberculosis cases and report them to the health department, and to select patients for respiratory isolation. Educational materials were placed on the World Wide Web and a Web-based kiosk. Home care nurses were outfitted with wireless pen-based computers, and data were relayed to the medical center. Automated tuberculosis case reporting resulted in time savings but not improved accuracy. Automated rules resulted in significant improvements in respiratory isolation. Kiosk educational materials were well-used. Wireless computing led to better access to information for both nurses and physicians, but not to reduction of workload. The key success element was recognition of critical priorities. It is concluded that innovative technology can facilitate the coordination of clinical care, public health, and home care.

Academic Medical Centers↗

Respiratory isolation of tuberculosis patients using clinical guidelines and an automated clinical decision support system.

OBJECTIVE: To evaluate a clinical guideline and an automated computer protocol for detection and respiratory isolation of tuberculosis (TB) patients. DESIGN: An automated computer protocol was tested on a retrospective cohort of adult culture-positive TB patients admitted from 1992 to 1993 to Columbia-Presbyterian Medical Center and evaluated prospectively from July 1995 until July 1996. SETTING: A large teaching hospital in New York City. PATIENTS: 171 adult patients admitted from 1992 to 1993 and 43 patients admitted between July 1995 and July 1996. INTERVENTIONS: The 1990 Centers for Disease Control and Prevention guidelines for preventing transmission of TB were adapted to formulate clinical guidelines to ensure early isolation of TB patients at Columbia-Presbyterian Medical Center. RESULTS: Implementation of a clinical respiratory isolation protocol resulted in a significant improvement in TB patient isolation rates, from 45 (51%) of 88 in 1992 to 62 (75%) of 83 in 1993 (P<.001). In testing automated protocols, the theoretical improvement would have identified an additional 27 patients not isolated by clinicians, making the overall isolation rate 134 (78%) of 171. For the prospective evaluation, 30 (70%) of 43 TB patients were isolated by clinicians adhering to the clinical protocol. Four additional patients were identified by the automated TB protocol, making the combined isolation rate 34 (79%) of 43. CONCLUSIONS: A clinical policy to isolate TB patients and suspected human immunodeficiency virus-infected patients with cough, fever, or radiographic abnormalities improved isolation of culture-documented TB patients from 1992 to 1993. Automated computer protocols were successful in identifying additional potentially infectious patients that clinicians failed to place on respiratory isolation. Clinical and automated protocols combined resulted in better isolation rates than a clinical protocol alone.

AIDS-Related Opportunistic Infections↗

Nonadherence in tuberculosis treatment: predictors and consequences in New York City.

BACKGROUND: Poor adherence to antituberculosis treatment is the most important obstacle to tuberculosis control. PURPOSE: To identify and analyze predictors and consequences of nonadherence to antituberculosis treatment. PATIENTS AND METHODS: Retrospective study of a citywide cohort of 184 patients with tuberculosis in New York City, newly diagnosed by culture in April 1991-before the strengthening of its control program-and followed up through 1994. Follow-up information was collected through the New York City tuberculosis registry. Nonadherence was defined as treatment default for at least 2 months. RESULTS: Eighty-eight of the 184 (48%) patients were nonadherent. Greater nonadherence was noted among blacks (unadjusted relative risk [RR] 3.0, 95% confidence interval [CI] 1.1 to 8.6, compared with whites), injection drug users (RR 1.5, 95% CI 1.1 to 2.0), homeless (RR 1.4, 95% CI 1.0 to 1.8), alcoholics (RR 1.4, 95% CI 1.0 to 1.9), and HIV-infected patients (RR 1.4, 95% CI 1.1 to 1.9); also, census-derived estimates of household income were lower among nonadherent patients (P = 0.018). In multivariate analysis, only injection drug use and homelessness predicted nonadherence, yet 46 (39%) of 117 patients who were neither homeless nor drug users were nonadherent. Nonadherent patients took longer to convert to negative culture (254 versus 64 days, P < 0.001), were more likely to acquire drug resistance (RR 5.6, 95% CI 0.7 to 44.2), required longer treatment regimens (560 versus 324 days, P < 0.0001), and were less likely to complete treatment (RR 0.5, 95% CI 0.4 to 0.7). There was no association between treatment adherence and all-cause mortality. CONCLUSIONS: In the absence of public health intervention, half the patients defaulted treatment for 2 months or longer. Although common among the homeless and injection drug users, the problem occurred frequently and unpredictably in other patients. Nonadherence may contribute to the spread of tuberculosis and the emergence of drug resistance, and may increase the cost of treatment. These data lend support to directly observed therapy in tuberculosis.

AIDS-Related Opportunistic Infections↗

The role of diabetes mellitus in the higher prevalence of tuberculosis among Hispanics.

OBJECTIVES: This research studied the relative contribution of diabetes mellitus to the increased prevalence of tuberculosis in Hispanics. METHODS: A case-control study was conducted involving all 5290 discharges from civilian hospitals in California during 1991 who had a diagnosis of tuberculosis, and 37,366 control subjects who had a primary discharge diagnosis of deep venous thrombosis, pulmonary embolism, or acute appendicitis. Risk of tuberculosis was estimated as the odds ratio (OR) across race/ethnicity, with adjustment for other factors. RESULTS: Diabetes mellitus was found to be an independent risk factor for tuberculosis. The association of diabetes and tuberculosis was higher among Hispanics (adjusted OR [ORadj] = 2.95: 95% confidence interval [CI] = 2.61, 3.33) than among non-Hispanic Whites (ORadj = 1.31: 95% CI = 1.19. 1.45): among non-Hispanic Blacks, diabetes was not found to be associated with tuberculosis (ORadj = 0.93: 95% CI = 0.78, 1.09). Among Hispanics aged 25 to 54, the estimated risk of tuberculosis attributable to diabetes (25.2%) was equivalent to that attributable to HIV infection (25.5%). CONCLUSIONS: Diabetes mellitus remains a significant risk factor for tuberculosis in the United States. The association is especially notable in middle-aged Hispanics.

Adult↗

Identification of suspected tuberculosis patients based on natural language processing of chest radiograph reports.

Identification of eligible patients from electronically available patient data is a key difficulty in computerizing clinical practice guidelines because a large amount of the relevant data is stored as free text. We have been using MedLEE (Medical Language Extraction and Encoding System), a natural language processing system, to encode the clinical information in all chest radiograph and mammogram reports. This paper describes a retrospective study to determine if MedLEE can identify patients at risk for having tuberculosis (TB) based on their admission chest radiographs. Reports of 171 adult inpatients with culture-positive TB during 1992 and 1993 were manually coded (by a TB specialist) using seven terms suggestive of TB, and were also encoded by MedLEE. Using manual coding as the gold standard, MedLEE agreed on the classification of 152/171 (88.9%) reports--129/142 (90.8%) suspicious for TB and 23/29 (79.3%) not suspicious for TB; and 1072/1197 (89.6%) terms indicative of TB. Analysis showed that most of the discrepancies were caused by MedLEE not finding the location of the infiltrate. By ignoring the location of the infiltrate, the agreement became 157/171 (91.8%) reports and 946/1026 (92.2%) terms. Thus, natural language processing offers a practical alternative for using free-text reports to determine patient eligibility for computerized clinical practice guidelines.

Adult↗

Automated tuberculosis detection.

OBJECTIVE: To measure the accuracy of automated tuberculosis case detection. SETTING: An inner-city medical center. INTERVENTION: An electronic medical record and a clinical event monitor with a natural language processor were used to detect tuberculosis cases according to Centers for Disease Control criteria. MEASUREMENT: Cases identified by the automated system were compared to the local health department's tuberculosis registry, and positive predictive value and sensitivity were calculated. RESULTS: The best automated rule was based on tuberculosis cultures; it had a sensitivity of .89 (95% CI.75-.96) and a positive predictive value of .96 (.89-.99). All other rules had a positive predictive value less than .20. A rule based on chest radiographs had a sensitivity of .41 (.26-.57) and a positive predictive value of .03 (.02-.05), and rule the represented the overall Centers for Disease Control criteria had a sensitivity of .91 (.78-.97) and a positive predictive value of .15 (.12-.18). The culture-based rule was the most useful rule for automated case reporting to the health department, and the chest radiograph-based rule was the most useful rule for improving tuberculosis respiratory isolation compliance. CONCLUSIONS: Automated tuberculosis case detection is feasible and useful, although the predictive value of most of the clinical rules was low. The usefulness of an individual rule depends on the context in which it is used. The major challenge facing automated detection is the availability and accuracy of electronic clinical data.

Diagnosis, Computer-Assisted↗