Concordance between of TBMAS and CMG in identifying non-adherents.

Figshare2015-12-02 更新2026-04-29 收录

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https://figshare.com/articles/dataset/_Concordance_between_of_TBMAS_and_CMG_in_identifying_non_adherents_/196168 数据链接链接失效反馈

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Concordance between of TBMAS and CMG in identifying non-adherents.

创建时间：

2015-12-02

Provision of guideline-based care for drug-resistant tuberculosis in South Africa: Level of concordance between prescribing practices and guidelines

结核病治疗依从性

指南实施评估

TitleProvision of guideline-based care for drug-resistant tuberculosis in South Africa: Level of concordance between prescribing practices and guidelines.ObjectiveWe examined the influence of individu

Figshare2018-11-05 更新70

Rate ratio of the selected variables of each dimension for the tuberculosis treatment non-adherence according to the Poisson multivariable regression model.

结核病治疗依从性

风险因素流行病学

Rate ratio of the selected variables of each dimension for the tuberculosis treatment non-adherence according to the Poisson multivariable regression model.

NIAID Data Ecosystem20

Selection of latent classes model in a cohort of PLHIV taking ART who defaulted on TB treatment, Recife/ PE, Brazil.

结核病治疗依从性

HIV合并感染

Selection of latent classes model in a cohort of PLHIV taking ART who defaulted on TB treatment, Recife/ PE, Brazil.

Figshare2024-03-13 更新10

Association of factors with time to loss from DR-TB treatment—2009–2013 (n = 373*).

结核病治疗依从性

患者失访风险

* 79 patients who died while on treatment were excluded from this analysis#statistically significant^ Sensitivity analysis-Multivariate analysis including Culture conversion status at 4 months of trea

Figshare2015-12-03 更新40

Factors associated with non-completion of latent tuberculosis infection treatment.

结核病治疗依从性

接触者追踪

590 contacts (close and frequent contacts) to whom treatment had been prescribed; contacts were detected through contact tracing of sputum smear-positive pulmonary tuberculosis cases. Barcelona 2008–2

Figshare2019-04-15 更新10

Concordance between of TBMAS and CMG in identifying non-adherents.

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