Literature DB >> 10979058

Evaluation of clinical parameters to predict Mycobacterium tuberculosis in inpatients.

J P Wisnivesky1, J Kaplan, C Henschke, T G McGinn, R G Crystal.   

Abstract

BACKGROUND: Respiratory isolation has been recommended for all patients with suspected tuberculosis (TB) to avoid transmission to other patients and health care personnel. In implementing these guidelines, patients with and without TB are frequently isolated, significantly increasing hospital costs. The objective of this study was to derive a clinical rule to predict the need for respiratory isolation of patients with suspected TB.
METHODS: To identify potential predictors of the need for isolation, 56 inpatients with sputum cultures positive for TB were retrospectively compared with 56 controls who were isolated on admission to the hospital based on clinically suspected TB but whose sputum cultures tested negative for TB. Variables analyzed included TB risk factors, clinical symptoms, and findings from physical examination and chest radiography.
RESULTS: Multivariate analysis revealed that the following factors were significantly associated with a culture positive for TB: presence of TB risk factors or symptoms (odds ratio [OR], 7.9 [95% confidence interval (CI), 4.4-24.2]), a positive purified protein derivative tuberculin test result (OR, 13.2 [95% CI, 4.4-40.7]), high temperature (OR, 2.8 [95% CI, 1.1-8.3]), and upper-lobe disease on chest radiograph (OR, 14.6 [95% CI, 3.7-57.5]). Shortness of breath (OR, 0.2 [95% CI, 0.12-0.53]) and crackles noted during the physical examination (OR, 0.29 [95% CI, 0.15-0.57]) were negative predictors of TB. A scoring system was developed using these variables. A patient's total score of 1 or higher indicated the need for respiratory isolation, accurately predicting a culture positive for TB (98% sensitivity [95% CI, 95%-100%]; 46% specificity [95% CI, 33%-59%]).
CONCLUSION: Among inpatients with suspected active pulmonary TB, a prediction rule based on clinical and chest radiographic findings accurately identified patients requiring respiratory isolation.

Entities:  

Mesh:

Year:  2000        PMID: 10979058     DOI: 10.1001/archinte.160.16.2471

Source DB:  PubMed          Journal:  Arch Intern Med        ISSN: 0003-9926


  19 in total

1.  Performance assessment of two commercial amplification assays for direct detection of Mycobacterium tuberculosis complex from respiratory and extrapulmonary specimens.

Authors:  Claudio Piersimoni; Claudio Scarparo; Paola Piccoli; Alessandra Rigon; Giuliana Ruggiero; Domenico Nista; Stefano Bornigia
Journal:  J Clin Microbiol       Date:  2002-11       Impact factor: 5.948

2.  Performance of a commercial nucleic acid amplification test with extrapulmonary specimens for the diagnosis of tuberculosis.

Authors:  C Piersimoni; S Bornigia; G Gherardi
Journal:  Eur J Clin Microbiol Infect Dis       Date:  2011-06-24       Impact factor: 3.267

3.  Development of two artificial neural network models to support the diagnosis of pulmonary tuberculosis in hospitalized patients in Rio de Janeiro, Brazil.

Authors:  Fábio S Aguiar; Rodrigo C Torres; João V F Pinto; Afrânio L Kritski; José M Seixas; Fernanda C Q Mello
Journal:  Med Biol Eng Comput       Date:  2016-03-25       Impact factor: 2.602

Review 4.  Validity of clinical prediction rules for isolating inpatients with suspected tuberculosis. A systematic review.

Authors:  Juan P Wisnivesky; Denise Serebrisky; Carlton Moore; Henry S Sacks; Michael C Iannuzzi; Thomas McGinn
Journal:  J Gen Intern Med       Date:  2005-10       Impact factor: 5.128

5.  Clinical and radiographic factors do not accurately diagnose smear-negative tuberculosis in HIV-infected inpatients in Uganda: a cross-sectional study.

Authors:  J Lucian Davis; William Worodria; Harriet Kisembo; John Z Metcalfe; Adithya Cattamanchi; Michael Kawooya; Rachel Kyeyune; Saskia den Boon; Krista Powell; Richard Okello; Samuel Yoo; Laurence Huang
Journal:  PLoS One       Date:  2010-03-26       Impact factor: 3.240

6.  Predictive factors for tuberculosis in patients with a TB-PCR-negative bronchial aspirate.

Authors:  C H Kim; J K Lim; S Y Lee; D I Won; S I Cha; J Y Park; W K Lee; J Lee
Journal:  Infection       Date:  2013-01-03       Impact factor: 3.553

7.  Classification and regression tree (CART) model to predict pulmonary tuberculosis in hospitalized patients.

Authors:  Fabio S Aguiar; Luciana L Almeida; Antonio Ruffino-Netto; Afranio Lineu Kritski; Fernanda Cq Mello; Guilherme L Werneck
Journal:  BMC Pulm Med       Date:  2012-08-07       Impact factor: 3.317

8.  Validation of a clinical-radiographic score to assess the probability of pulmonary tuberculosis in suspect patients with negative sputum smears.

Authors:  Alonso Soto; Lely Solari; Javier Díaz; Alberto Mantilla; Francine Matthys; Patrick van der Stuyft
Journal:  PLoS One       Date:  2011-04-05       Impact factor: 3.240

9.  Predicting smear negative pulmonary tuberculosis with classification trees and logistic regression: a cross-sectional study.

Authors:  Fernanda Carvalho de Queiroz Mello; Luiz Gustavo do Valle Bastos; Sérgio Luiz Machado Soares; Valéria M C Rezende; Marcus Barreto Conde; Richard E Chaisson; Afrânio Lineu Kritski; Antonio Ruffino-Netto; Guilherme Loureiro Werneck
Journal:  BMC Public Health       Date:  2006-02-23       Impact factor: 3.295

10.  Development of a simple reliable radiographic scoring system to aid the diagnosis of pulmonary tuberculosis.

Authors:  Lancelot M Pinto; Keertan Dheda; Grant Theron; Brian Allwood; Gregory Calligaro; Richard van Zyl-Smit; Jonathan Peter; Kevin Schwartzman; Dick Menzies; Eric Bateman; Madhukar Pai; Rodney Dawson
Journal:  PLoS One       Date:  2013-01-18       Impact factor: 3.240

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