Dataset Information

Screening strategies for tuberculosis prevalence surveys: the value of chest radiography and symptoms.

ABSTRACT: We conducted a tuberculosis (TB) prevalence survey and evaluated the screening methods used in our survey, to assess if screening in TB prevalence surveys could be simplified, and to assess the accuracy of screening algorithms that may be applicable for active case finding.All participants with a positive screen on either a symptom questionnaire, chest radiography (CXR) and/or sputum smear microscopy submitted sputum for culture. HIV status was obtained from prevalent cases. We estimated the accuracy of modified screening strategies with bacteriologically confirmed TB as the gold standard, and compared these with other survey reports. We also assessed whether sequential rather than parallel application of symptom, CXR and HIV screening would substantially reduce the number of participants requiring CXR and/or sputum culture.Presence of any abnormality on CXR had 94% (95%CI 88-98) sensitivity (92% in HIV-infected and 100% in HIV-uninfected) and 73% (95%CI 68-77) specificity. Symptom screening combinations had significantly lower sensitivity than CXR except for 'any TB symptom' which had 90% (95%CI 84-95) sensitivity (96% in HIV-infected and 82% in HIV-uninfected) and 32% (95%CI 30-34) specificity. Smear microscopy did not yield additional suspects, thus the combined symptom/CXR screen applied in the survey had 100% (95%CI 97-100) sensitivity. Specificity was 65% (95%CI 61-68). Sequential application of first a symptom screen for 'any symptom', followed by CXR-evaluation and different suspect criteria depending on HIV status would result in the largest reduction of the need for CXR and sputum culture, approximately 36%, but would underestimate prevalence by 11%.CXR screening alone had higher accuracy compared to symptom screening alone. Combined CXR and symptom screening had the highest sensitivity and remains important for suspect identification in TB prevalence surveys in settings where bacteriological sputum examination of all participants is not feasible.

SUBMITTER: van't Hoog AH

PROVIDER: S-EPMC3391193 | biostudies-other | 2012

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Screening strategies for tuberculosis prevalence surveys: the value of chest radiography and symptoms.

van't Hoog Anna H AH Meme Helen K HK Laserson Kayla F KF Agaya Janet A JA Muchiri Benson G BG Githui Willie A WA Odeny Lazarus O LO Marston Barbara J BJ Borgdorff Martien W MW

PloS one 20120706 7

<h4>Background</h4>We conducted a tuberculosis (TB) prevalence survey and evaluated the screening methods used in our survey, to assess if screening in TB prevalence surveys could be simplified, and to assess the accuracy of screening algorithms that may be applicable for active case finding.<h4>Methods</h4>All participants with a positive screen on either a symptom questionnaire, chest radiography (CXR) and/or sputum smear microscopy submitted sputum for culture. HIV status was obtained from pr ...[more]

PMID: 22792158

Similar Datasets

Project description:To assess the frequency and spectrum of abnormalities on routine screening chest radiographs in the pre-employment evaluation of health care workers with positive tuberculin skin test (TST) results.The institutional review board approved this HIPAA-compliant retrospective study and waived the need for written informed patient consent. Chest radiographic reports of all 2586 asymptomatic individuals with positive TST results who underwent pre-employment evaluation between January 1, 2003, and December 31, 2007, were evaluated to determine the frequency of detection of evidence of active tuberculosis (TB) or latent TB infection (LTBI) and the spectrum of imaging findings. All chest radiographs interpreted as positive were reviewed by an experienced board-certified radiologist. If there was a discrepancy between the two readings, a second experienced radiologist served as an independent and final arbiter. Any follow-up chest radiographs or computed tomographic images that had been acquired by employee health services or by the employee's private physician as a result of a suspected abnormality detected at initial screening were also evaluated.Of the 159 (6.1%) chest radiographic examinations that yielded abnormal results, there were no findings that were consistent with active TB. There were 92 cases of calcified granulomas, calcified lymph nodes, or both; 25 cases of apical pleural thickening; 16 cases of fibrous scarring; and 31 cases of noncalcified nodules. All cases of fibrous scarring involved an area smaller than 2 cm(2). All noncalcified nodules were 4 mm in diameter or smaller, with the exception of one primary lung malignancy and one necrotizing granuloma (negative for acid-fast bacilli) that grew Mycobacterium kansasii on culture.Universal chest radiography in a large pre-employment TB screening program was of low yield in the detection of active TB or increased LTBI reactivation risk, and it provided no assistance in deciding which individuals to prioritize for LTBI treatment.

Project description:Background Radiologists are proficient in differentiating between chest radiographs with and without symptoms of pneumonia but have found it more challenging to differentiate coronavirus disease 2019 (COVID-19) pneumonia from non-COVID-19 pneumonia on chest radiographs. Purpose To develop an artificial intelligence algorithm to differentiate COVID-19 pneumonia from other causes of abnormalities at chest radiography. Materials and Methods In this retrospective study, a deep neural network, CV19-Net, was trained, validated, and tested on chest radiographs in patients with and without COVID-19 pneumonia. For the chest radiographs positive for COVID-19, patients with reverse transcription polymerase chain reaction results positive for severe acute respiratory syndrome coronavirus 2 with findings positive for pneumonia between February 1, 2020, and May 30, 2020, were included. For the non-COVID-19 chest radiographs, patients with pneumonia who underwent chest radiography between October 1, 2019, and December 31, 2019, were included. Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were calculated to characterize diagnostic performance. To benchmark the performance of CV19-Net, a randomly sampled test data set composed of 500 chest radiographs in 500 patients was evaluated by the CV19-Net and three experienced thoracic radiologists. Results A total of 2060 patients (5806 chest radiographs; mean age, 62 years ± 16 [standard deviation]; 1059 men) with COVID-19 pneumonia and 3148 patients (5300 chest radiographs; mean age, 64 years ± 18; 1578 men) with non-COVID-19 pneumonia were included and split into training and validation and test data sets. For the test set, CV19-Net achieved an AUC of 0.92 (95% CI: 0.91, 0.93). This corresponded to a sensitivity of 88% (95% CI: 87, 89) and a specificity of 79% (95% CI: 77, 80) by using a high-sensitivity operating threshold, or a sensitivity of 78% (95% CI: 77, 79) and a specificity of 89% (95% CI: 88, 90) by using a high-specificity operating threshold. For the 500 sampled chest radiographs, CV19-Net achieved an AUC of 0.94 (95% CI: 0.93, 0.96) compared with an AUC of 0.85 (95% CI: 0.81, 0.88) achieved by radiologists. Conclusion CV19-Net was able to differentiate coronavirus disease 2019-related pneumonia from other types of pneumonia, with performance exceeding that of experienced thoracic radiologists. © RSNA, 2021 Online supplemental material is available for this article.

Dataset Information

Screening strategies for tuberculosis prevalence surveys: the value of chest radiography and symptoms.

Publications

Screening strategies for tuberculosis prevalence surveys: the value of chest radiography and symptoms.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets