Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 2 de 2
Filtrar
Mais filtros

Base de dados
Ano de publicação
Tipo de documento
País de afiliação
Intervalo de ano de publicação
1.
BMC Infect Dis ; 23(1): 148, 2023 Mar 10.
Artigo em Inglês | MEDLINE | ID: mdl-36899314

RESUMO

BACKGROUND: Diagnostics for pulmonary tuberculosis (PTB) are usually inaccurate, expensive, or complicated. The breathomics-based method may be an attractive option for fast and noninvasive PTB detection. METHOD: Exhaled breath samples were collected from 518 PTB patients and 887 controls and tested on the real-time high-pressure photon ionization time-of-flight mass spectrometer. Machine learning algorithms were employed for breathomics analysis and PTB detection mode, whose performance was evaluated in 430 blinded clinical patients. RESULTS: The breathomics-based PTB detection model achieved an accuracy of 92.6%, a sensitivity of 91.7%, a specificity of 93.0%, and an AUC of 0.975 in the blinded test set (n = 430). Age, sex, and anti-tuberculosis treatment does not significantly impact PTB detection performance. In distinguishing PTB from other pulmonary diseases (n = 182), the VOC modes also achieve good performance with an accuracy of 91.2%, a sensitivity of 91.7%, a specificity of 88.0%, and an AUC of 0.961. CONCLUSIONS: The simple and noninvasive breathomics-based PTB detection method was demonstrated with high sensitivity and specificity, potentially valuable for clinical PTB screening and diagnosis.


Assuntos
Pneumopatias , Tuberculose Pulmonar , Humanos , Estudos Transversais , Tuberculose Pulmonar/diagnóstico , Algoritmos , Aprendizado de Máquina
2.
J Clin Transl Hepatol ; 11(2): 425-432, 2023 Apr 28.
Artigo em Inglês | MEDLINE | ID: mdl-36643044

RESUMO

Background and Aims: Anti-tuberculosis (anti-TB) drug-induced liver injury (AT-DILI) is the most common side effect in patients who received anti-TB therapy. AT-DILI management includes monitoring liver function until symptoms arise in patients without high-risk factors for liver damage. The present study aimed to investigate the effect of liver function test (LFT) abnormal identification on the risk of DILI, including liver failure and anti-TB drug resistance in patients without high-risk factors. Methods: A total of 399 patients without high-risk factors for liver damage at baseline and who experienced LFT abnormal during the 6 months of first-line anti-TB treatment were enrolled. The Roussel Uclaf Causal Relationship Assessment Method (RUCAM, 2016) was applied in suspected DILI. The correlations between the time of LFT abnormal identification and DILI, liver failure, and anti-TB drug resistance were analyzed by smooth curve fitting and multivariable logistic regression models. Results: Among all study patients, 131 met the criteria for DILI with a mean RUCAM causality score of 8.86±0.63. 26/131 and 105/131 were in the probable grading and highly probable grading, respectively. The time of abnormal LFT identification was an independent predictor of DILI, liver failure, and anti-TB drug resistance in the crude model and after adjusting for other risk patient factors. The time of abnormal LFT identification was positively correlated with DILI, liver failure, and anti-TB drug resistance. The late identification group (>8 weeks) had the highest risk of DILI, followed by liver failure compared with the other two groups. Conclusions: The time to identification of LFT was positively correlated with DILI, liver failure, and anti-TB drug resistance. The risk of DILI and liver failure was significantly increased in the late identification group with abnormal LFT identified after 8 weeks compared with 4 and 8 weeks. Early monitoring of LFT is recommended for patients without the high-risk factor of DILI after anti-TB treatment is initiated.

SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA