Literature DB >> 18218573

Predictors for identifying the most infectious pulmonary tuberculosis patient.

Chuan-Sheng Wang1, Huang-Chi Chen, Inn-Wen Chong, Jhi-Jhu Hwang, Ming-Shyan Huang.   

Abstract

BACKGROUND/
PURPOSE: Clinicians need to decide whether to begin isolation and empiric therapy for patients suspected of having infectious tuberculosis (TB). This study aimed to identify the demographic, clinical and radiographic characteristics of acid-fast bacilli (AFB) smear-positive patients and to create a smear-positive TB prediction rule, which clinicians may use to predict risk.
METHODS: This was a retrospective study involving 105 patients with AFB smear-positive TB and 52 patients with AFB smear-negative TB at Kaohsiung Municipal Hsiao-Kang Hospital in southern Taiwan from August 1, 2003 to July 31, 2006. All of the patients had at least one sputum culture that was positive for Mycobacterium tuberculosis. Demographic, clinical and radiographic data of patients with AFB smear-positive TB were compared to those of patients with AFB smear-negative TB.
RESULTS: On univariate analysis, young age (p = 0.033), alcoholism (p = 0.036), weight loss (p = 0.003), fever (p = 0.018), consolidation (p = 0.001), infiltration (p = 0.012), cavitary pattern (p = 0.005), right upper lung field (p < 0.001) and left upper lung field (p = 0.001) lesions on chest radiographs were found to be predictive of smear-positive TB patients. In contrast, end-stage renal disease (p = 0.035) and normal chest radiograph (p = 0.006) were predictive of smear-negative TB patients. On multivariate analysis, age less than 65 years (p = 0.004), fever (p = 0.004), right upper lung field (p = 0.044), left upper lung field (p = 0.041), consolidation (p = 0.018) and cavitary (p = 0.049) lesions on chest radiograph were independently associated with an increased risk of an AFB positive smear finding. The smear-positive TB prediction model was created based on the results of the multivariate analysis that had an area of 0.788 under the receiver operating characteristic curve.
CONCLUSION: The smear-positive TB prediction model may help clinicians decide if a patient with pending sputum smear results should first be placed in isolation and empiric anti-tuberculous therapy started.

Entities:  

Mesh:

Year:  2008        PMID: 18218573     DOI: 10.1016/S0929-6646(08)60003-0

Source DB:  PubMed          Journal:  J Formos Med Assoc        ISSN: 0929-6646            Impact factor:   3.282


  9 in total

1.  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

2.  Alcohol use and clinical manifestations of tuberculosis.

Authors:  Christina T Fiske; Carol D Hamilton; Jason E Stout
Journal:  J Infect       Date:  2008-10-09       Impact factor: 6.072

3.  Alcohol use and clinical manifestations of tuberculosis.

Authors:  Christina T Fiske; Carol D Hamilton; Jason E Stout
Journal:  J Infect       Date:  2009-05       Impact factor: 6.072

4.  Predictors of pulmonary involvement in patients with extra-pulmonary tuberculosis.

Authors:  Malak M El-Hazmi; Fawzia E Al-Otaibi
Journal:  J Family Community Med       Date:  2012-05

5.  Culture-independent detection and characterisation of Mycobacterium tuberculosis and M. africanum in sputum samples using shotgun metagenomics on a benchtop sequencer.

Authors:  Emma L Doughty; Martin J Sergeant; Ifedayo Adetifa; Martin Antonio; Mark J Pallen
Journal:  PeerJ       Date:  2014-09-23       Impact factor: 2.984

6.  TST positivity in household contacts of tuberculosis patients: a case-contact study in Malawi.

Authors:  Jonas Hector; Suzanne T Anderson; Gertrude Banda; Mercy Kamdolozi; Laura F Jefferys; Doris Shani; Natalie J Garton; Agnes Mwale; Annie Jobe; Geraint R Davies; Derek J Sloan
Journal:  BMC Infect Dis       Date:  2017-04-11       Impact factor: 3.090

7.  Predictors of Initial Smear-Negative Active Pulmonary Tuberculosis with Acute Early Stage Lung Injury by High-Resolution Computed Tomography and Clinical Manifestations: An Auxiliary Model in Critical Patients.

Authors:  Jun-Jun Yeh
Journal:  Sci Rep       Date:  2019-03-14       Impact factor: 4.379

Review 8.  Risk factors for infectiousness of patients with tuberculosis: a systematic review and meta-analysis.

Authors:  Y A Melsew; T N Doan; M Gambhir; A C Cheng; E McBryde; J M Trauer
Journal:  Epidemiol Infect       Date:  2018-01-17       Impact factor: 4.434

Review 9.  Indications to Hospital Admission and Isolation of Children With Possible or Defined Tuberculosis: Systematic Review and Proposed Recommendations for Pediatric Patients Living in Developed Countries. [Corrected].

Authors:  Andrea Lo Vecchio; Marialuisa Bocchino; Laura Lancella; Clara Gabiano; Silvia Garazzino; Riccardo Scotto; Irene Raffaldi; Luca Rosario Assante; Alberto Villani; Susanna Esposito; Alfredo Guarino
Journal:  Medicine (Baltimore)       Date:  2015-12       Impact factor: 1.817

  9 in total

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