Publications by authors named "Geric C"

Background: Pulmonary TB (PTB) predominantly affects individuals of working age. We sought to characterise the occupations of people newly diagnosed with PTB in Karachi, Pakistan, by type and physical intensity.

Design/methods: We did a secondary analysis of data from a study evaluating the diagnostic accuracy of artificial intelligence-based chest X-ray (CXR) analysis software, where individuals had been evaluated for active PTB using sputum cultures and had provided information on occupation.

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Objectives: Computer-aided detection (CAD) software packages quantify tuberculosis (TB)-compatible chest X-ray (CXR) abnormality as continuous scores. In practice, a threshold value is selected for binary CXR classification. We assessed the diagnostic accuracy of an alternative approach to applying CAD for TB triage: incorporating CAD scores in multivariable modeling.

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Article Synopsis
  • Computer-aided detection (CAD) may serve as a beneficial screening tool for tuberculosis (TB), especially in communities affected by HIV, but limited data exist on its effectiveness in such settings.
  • A systematic review of 1,748 articles published between January 2012 and February 2023 identified only 5 studies that met rigorous criteria for evaluating CAD against established TB testing standards, revealing a pooled sensitivity of 0.87 and specificity of 0.74.
  • Despite its potential as a cost-effective screening tool, the review highlights significant methodological concerns, indicating a need for caution in applying these findings more broadly due to biases and limited study quality.
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We provide an overview of the latest evidence on computer-aided detection (CAD) software for automated interpretation of chest radiographs (CXRs) for TB detection. CAD is a useful tool that can assist in rapid and consistent CXR interpretation for TB. CAD can achieve high sensitivity TB detection among people seeking care with symptoms of TB and in population-based screening, has accuracy on-par with human readers.

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Objectives: We applied computer-aided detection (CAD) software for chest X-ray (CXR) analysis to determine if diabetes affects the radiographic presentation of tuberculosis.

Methods: From March 2017-July 2018, we consecutively enrolled adults being evaluated for pulmonary tuberculosis in Karachi, Pakistan. Participants had same-day CXR, two sputum mycobacterial cultures, and random blood glucose measurement.

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We assessed the COVID-19 pandemic's impact on treatment of latent tuberculosis, and of active tuberculosis, at 3 centers in Montreal and Toronto, using data from 10 833 patients (8685 with latent tuberculosis infection, 2148 with active tuberculosis). Observation periods prior to declarations of COVID-19 public health emergencies ranged from 219 to 744 weeks, and after declarations, from 28 to 33 weeks. In the latter period, reductions in latent tuberculosis infection treatment initiation rates ranged from 30% to 66%.

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Background: Automated radiologic analysis using computer-aided detection software (CAD) could facilitate chest X-ray (CXR) use in tuberculosis diagnosis. There is little to no evidence on the accuracy of commercially available deep learning-based CAD in different populations, including patients with smear-negative tuberculosis and people living with human immunodeficiency virus (HIV, PLWH).

Methods: We collected CXRs and individual patient data (IPD) from studies evaluating CAD in patients self-referring for tuberculosis symptoms with culture or nucleic acid amplification testing as the reference.

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Members of the family of surface adhesins of oral streptococci, including P1 of Streptococcus mutans, contain two highly conserved repeat domains, one rich in alanine (A region) and the other rich in proline (P region). To assess the contribution of the P region to the biological properties of P1, an internal deletion in spaP was engineered. In addition, the P region was subcloned and expressed as a fusion partner with the maltose binding protein of Escherichia coli and liberated by digestion with factor Xa.

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